case study tasks

The Ultimate Guide to Qualitative Research - Part 1: The Basics

• Introduction and overview
• What is qualitative research?
• What is qualitative data?
• Examples of qualitative data
• Qualitative vs. quantitative research
• Mixed methods
• Qualitative research preparation
• Theoretical perspective
• Theoretical framework
• Literature reviews

Research question

• Conceptual framework
• Conceptual vs. theoretical framework

Data collection

• Qualitative research methods
• Focus groups
• Observational research

What is a case study?

Applications for case study research, what is a good case study, process of case study design, benefits and limitations of case studies.

• Ethnographical research
• Ethical considerations
• Confidentiality and privacy
• Power dynamics
• Reflexivity

Case studies

Case studies are essential to qualitative research , offering a lens through which researchers can investigate complex phenomena within their real-life contexts. This chapter explores the concept, purpose, applications, examples, and types of case studies and provides guidance on how to conduct case study research effectively.

Whereas quantitative methods look at phenomena at scale, case study research looks at a concept or phenomenon in considerable detail. While analyzing a single case can help understand one perspective regarding the object of research inquiry, analyzing multiple cases can help obtain a more holistic sense of the topic or issue. Let's provide a basic definition of a case study, then explore its characteristics and role in the qualitative research process.

Definition of a case study

A case study in qualitative research is a strategy of inquiry that involves an in-depth investigation of a phenomenon within its real-world context. It provides researchers with the opportunity to acquire an in-depth understanding of intricate details that might not be as apparent or accessible through other methods of research. The specific case or cases being studied can be a single person, group, or organization – demarcating what constitutes a relevant case worth studying depends on the researcher and their research question .

Among qualitative research methods , a case study relies on multiple sources of evidence, such as documents, artifacts, interviews , or observations , to present a complete and nuanced understanding of the phenomenon under investigation. The objective is to illuminate the readers' understanding of the phenomenon beyond its abstract statistical or theoretical explanations.

Characteristics of case studies

Case studies typically possess a number of distinct characteristics that set them apart from other research methods. These characteristics include a focus on holistic description and explanation, flexibility in the design and data collection methods, reliance on multiple sources of evidence, and emphasis on the context in which the phenomenon occurs.

Furthermore, case studies can often involve a longitudinal examination of the case, meaning they study the case over a period of time. These characteristics allow case studies to yield comprehensive, in-depth, and richly contextualized insights about the phenomenon of interest.

The role of case studies in research

Case studies hold a unique position in the broader landscape of research methods aimed at theory development. They are instrumental when the primary research interest is to gain an intensive, detailed understanding of a phenomenon in its real-life context.

In addition, case studies can serve different purposes within research - they can be used for exploratory, descriptive, or explanatory purposes, depending on the research question and objectives. This flexibility and depth make case studies a valuable tool in the toolkit of qualitative researchers.

Remember, a well-conducted case study can offer a rich, insightful contribution to both academic and practical knowledge through theory development or theory verification, thus enhancing our understanding of complex phenomena in their real-world contexts.

What is the purpose of a case study?

Case study research aims for a more comprehensive understanding of phenomena, requiring various research methods to gather information for qualitative analysis . Ultimately, a case study can allow the researcher to gain insight into a particular object of inquiry and develop a theoretical framework relevant to the research inquiry.

Why use case studies in qualitative research?

Using case studies as a research strategy depends mainly on the nature of the research question and the researcher's access to the data.

Conducting case study research provides a level of detail and contextual richness that other research methods might not offer. They are beneficial when there's a need to understand complex social phenomena within their natural contexts.

The explanatory, exploratory, and descriptive roles of case studies

Case studies can take on various roles depending on the research objectives. They can be exploratory when the research aims to discover new phenomena or define new research questions; they are descriptive when the objective is to depict a phenomenon within its context in a detailed manner; and they can be explanatory if the goal is to understand specific relationships within the studied context. Thus, the versatility of case studies allows researchers to approach their topic from different angles, offering multiple ways to uncover and interpret the data .

The impact of case studies on knowledge development

Case studies play a significant role in knowledge development across various disciplines. Analysis of cases provides an avenue for researchers to explore phenomena within their context based on the collected data.

This can result in the production of rich, practical insights that can be instrumental in both theory-building and practice. Case studies allow researchers to delve into the intricacies and complexities of real-life situations, uncovering insights that might otherwise remain hidden.

Types of case studies

In qualitative research , a case study is not a one-size-fits-all approach. Depending on the nature of the research question and the specific objectives of the study, researchers might choose to use different types of case studies. These types differ in their focus, methodology, and the level of detail they provide about the phenomenon under investigation.

Understanding these types is crucial for selecting the most appropriate approach for your research project and effectively achieving your research goals. Let's briefly look at the main types of case studies.

Exploratory case studies

Exploratory case studies are typically conducted to develop a theory or framework around an understudied phenomenon. They can also serve as a precursor to a larger-scale research project. Exploratory case studies are useful when a researcher wants to identify the key issues or questions which can spur more extensive study or be used to develop propositions for further research. These case studies are characterized by flexibility, allowing researchers to explore various aspects of a phenomenon as they emerge, which can also form the foundation for subsequent studies.

Descriptive case studies

Descriptive case studies aim to provide a complete and accurate representation of a phenomenon or event within its context. These case studies are often based on an established theoretical framework, which guides how data is collected and analyzed. The researcher is concerned with describing the phenomenon in detail, as it occurs naturally, without trying to influence or manipulate it.

Explanatory case studies

Explanatory case studies are focused on explanation - they seek to clarify how or why certain phenomena occur. Often used in complex, real-life situations, they can be particularly valuable in clarifying causal relationships among concepts and understanding the interplay between different factors within a specific context.

Intrinsic, instrumental, and collective case studies

These three categories of case studies focus on the nature and purpose of the study. An intrinsic case study is conducted when a researcher has an inherent interest in the case itself. Instrumental case studies are employed when the case is used to provide insight into a particular issue or phenomenon. A collective case study, on the other hand, involves studying multiple cases simultaneously to investigate some general phenomena.

Each type of case study serves a different purpose and has its own strengths and challenges. The selection of the type should be guided by the research question and objectives, as well as the context and constraints of the research.

The flexibility, depth, and contextual richness offered by case studies make this approach an excellent research method for various fields of study. They enable researchers to investigate real-world phenomena within their specific contexts, capturing nuances that other research methods might miss. Across numerous fields, case studies provide valuable insights into complex issues.

Critical information systems research

Case studies provide a detailed understanding of the role and impact of information systems in different contexts. They offer a platform to explore how information systems are designed, implemented, and used and how they interact with various social, economic, and political factors. Case studies in this field often focus on examining the intricate relationship between technology, organizational processes, and user behavior, helping to uncover insights that can inform better system design and implementation.

Health research

Health research is another field where case studies are highly valuable. They offer a way to explore patient experiences, healthcare delivery processes, and the impact of various interventions in a real-world context.

Case studies can provide a deep understanding of a patient's journey, giving insights into the intricacies of disease progression, treatment effects, and the psychosocial aspects of health and illness.

Asthma research studies

Specifically within medical research, studies on asthma often employ case studies to explore the individual and environmental factors that influence asthma development, management, and outcomes. A case study can provide rich, detailed data about individual patients' experiences, from the triggers and symptoms they experience to the effectiveness of various management strategies. This can be crucial for developing patient-centered asthma care approaches.

Other fields

Apart from the fields mentioned, case studies are also extensively used in business and management research, education research, and political sciences, among many others. They provide an opportunity to delve into the intricacies of real-world situations, allowing for a comprehensive understanding of various phenomena.

Case studies, with their depth and contextual focus, offer unique insights across these varied fields. They allow researchers to illuminate the complexities of real-life situations, contributing to both theory and practice.

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Understanding the key elements of case study design is crucial for conducting rigorous and impactful case study research. A well-structured design guides the researcher through the process, ensuring that the study is methodologically sound and its findings are reliable and valid. The main elements of case study design include the research question , propositions, units of analysis, and the logic linking the data to the propositions.

The research question is the foundation of any research study. A good research question guides the direction of the study and informs the selection of the case, the methods of collecting data, and the analysis techniques. A well-formulated research question in case study research is typically clear, focused, and complex enough to merit further detailed examination of the relevant case(s).

Propositions

Propositions, though not necessary in every case study, provide a direction by stating what we might expect to find in the data collected. They guide how data is collected and analyzed by helping researchers focus on specific aspects of the case. They are particularly important in explanatory case studies, which seek to understand the relationships among concepts within the studied phenomenon.

Units of analysis

The unit of analysis refers to the case, or the main entity or entities that are being analyzed in the study. In case study research, the unit of analysis can be an individual, a group, an organization, a decision, an event, or even a time period. It's crucial to clearly define the unit of analysis, as it shapes the qualitative data analysis process by allowing the researcher to analyze a particular case and synthesize analysis across multiple case studies to draw conclusions.

Argumentation

This refers to the inferential model that allows researchers to draw conclusions from the data. The researcher needs to ensure that there is a clear link between the data, the propositions (if any), and the conclusions drawn. This argumentation is what enables the researcher to make valid and credible inferences about the phenomenon under study.

Understanding and carefully considering these elements in the design phase of a case study can significantly enhance the quality of the research. It can help ensure that the study is methodologically sound and its findings contribute meaningful insights about the case.

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Conducting a case study involves several steps, from defining the research question and selecting the case to collecting and analyzing data . This section outlines these key stages, providing a practical guide on how to conduct case study research.

Defining the research question

The first step in case study research is defining a clear, focused research question. This question should guide the entire research process, from case selection to analysis. It's crucial to ensure that the research question is suitable for a case study approach. Typically, such questions are exploratory or descriptive in nature and focus on understanding a phenomenon within its real-life context.

Selecting and defining the case

The selection of the case should be based on the research question and the objectives of the study. It involves choosing a unique example or a set of examples that provide rich, in-depth data about the phenomenon under investigation. After selecting the case, it's crucial to define it clearly, setting the boundaries of the case, including the time period and the specific context.

Previous research can help guide the case study design. When considering a case study, an example of a case could be taken from previous case study research and used to define cases in a new research inquiry. Considering recently published examples can help understand how to select and define cases effectively.

Developing a detailed case study protocol

A case study protocol outlines the procedures and general rules to be followed during the case study. This includes the data collection methods to be used, the sources of data, and the procedures for analysis. Having a detailed case study protocol ensures consistency and reliability in the study.

The protocol should also consider how to work with the people involved in the research context to grant the research team access to collecting data. As mentioned in previous sections of this guide, establishing rapport is an essential component of qualitative research as it shapes the overall potential for collecting and analyzing data.

Collecting data

Gathering data in case study research often involves multiple sources of evidence, including documents, archival records, interviews, observations, and physical artifacts. This allows for a comprehensive understanding of the case. The process for gathering data should be systematic and carefully documented to ensure the reliability and validity of the study.

Analyzing and interpreting data

The next step is analyzing the data. This involves organizing the data , categorizing it into themes or patterns , and interpreting these patterns to answer the research question. The analysis might also involve comparing the findings with prior research or theoretical propositions.

Writing the case study report

The final step is writing the case study report . This should provide a detailed description of the case, the data, the analysis process, and the findings. The report should be clear, organized, and carefully written to ensure that the reader can understand the case and the conclusions drawn from it.

Each of these steps is crucial in ensuring that the case study research is rigorous, reliable, and provides valuable insights about the case.

The type, depth, and quality of data in your study can significantly influence the validity and utility of the study. In case study research, data is usually collected from multiple sources to provide a comprehensive and nuanced understanding of the case. This section will outline the various methods of collecting data used in case study research and discuss considerations for ensuring the quality of the data.

Interviews are a common method of gathering data in case study research. They can provide rich, in-depth data about the perspectives, experiences, and interpretations of the individuals involved in the case. Interviews can be structured , semi-structured , or unstructured , depending on the research question and the degree of flexibility needed.

Observations

Observations involve the researcher observing the case in its natural setting, providing first-hand information about the case and its context. Observations can provide data that might not be revealed in interviews or documents, such as non-verbal cues or contextual information.

Documents and artifacts

Documents and archival records provide a valuable source of data in case study research. They can include reports, letters, memos, meeting minutes, email correspondence, and various public and private documents related to the case.

These records can provide historical context, corroborate evidence from other sources, and offer insights into the case that might not be apparent from interviews or observations.

Physical artifacts refer to any physical evidence related to the case, such as tools, products, or physical environments. These artifacts can provide tangible insights into the case, complementing the data gathered from other sources.

Ensuring the quality of data collection

Determining the quality of data in case study research requires careful planning and execution. It's crucial to ensure that the data is reliable, accurate, and relevant to the research question. This involves selecting appropriate methods of collecting data, properly training interviewers or observers, and systematically recording and storing the data. It also includes considering ethical issues related to collecting and handling data, such as obtaining informed consent and ensuring the privacy and confidentiality of the participants.

Data analysis

Analyzing case study research involves making sense of the rich, detailed data to answer the research question. This process can be challenging due to the volume and complexity of case study data. However, a systematic and rigorous approach to analysis can ensure that the findings are credible and meaningful. This section outlines the main steps and considerations in analyzing data in case study research.

Organizing the data

The first step in the analysis is organizing the data. This involves sorting the data into manageable sections, often according to the data source or the theme. This step can also involve transcribing interviews, digitizing physical artifacts, or organizing observational data.

Categorizing and coding the data

Once the data is organized, the next step is to categorize or code the data. This involves identifying common themes, patterns, or concepts in the data and assigning codes to relevant data segments. Coding can be done manually or with the help of software tools, and in either case, qualitative analysis software can greatly facilitate the entire coding process. Coding helps to reduce the data to a set of themes or categories that can be more easily analyzed.

Identifying patterns and themes

After coding the data, the researcher looks for patterns or themes in the coded data. This involves comparing and contrasting the codes and looking for relationships or patterns among them. The identified patterns and themes should help answer the research question.

Interpreting the data

Once patterns and themes have been identified, the next step is to interpret these findings. This involves explaining what the patterns or themes mean in the context of the research question and the case. This interpretation should be grounded in the data, but it can also involve drawing on theoretical concepts or prior research.

Verification of the data

The last step in the analysis is verification. This involves checking the accuracy and consistency of the analysis process and confirming that the findings are supported by the data. This can involve re-checking the original data, checking the consistency of codes, or seeking feedback from research participants or peers.

Like any research method , case study research has its strengths and limitations. Researchers must be aware of these, as they can influence the design, conduct, and interpretation of the study.

Understanding the strengths and limitations of case study research can also guide researchers in deciding whether this approach is suitable for their research question . This section outlines some of the key strengths and limitations of case study research.

Benefits include the following:

• Rich, detailed data: One of the main strengths of case study research is that it can generate rich, detailed data about the case. This can provide a deep understanding of the case and its context, which can be valuable in exploring complex phenomena.
• Flexibility: Case study research is flexible in terms of design , data collection , and analysis . A sufficient degree of flexibility allows the researcher to adapt the study according to the case and the emerging findings.
• Real-world context: Case study research involves studying the case in its real-world context, which can provide valuable insights into the interplay between the case and its context.
• Multiple sources of evidence: Case study research often involves collecting data from multiple sources , which can enhance the robustness and validity of the findings.

On the other hand, researchers should consider the following limitations:

• Generalizability: A common criticism of case study research is that its findings might not be generalizable to other cases due to the specificity and uniqueness of each case.
• Time and resource intensive: Case study research can be time and resource intensive due to the depth of the investigation and the amount of collected data.
• Complexity of analysis: The rich, detailed data generated in case study research can make analyzing the data challenging.
• Subjectivity: Given the nature of case study research, there may be a higher degree of subjectivity in interpreting the data , so researchers need to reflect on this and transparently convey to audiences how the research was conducted.

Being aware of these strengths and limitations can help researchers design and conduct case study research effectively and interpret and report the findings appropriately.

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Organizing Your Social Sciences Research Assignments

• Annotated Bibliography
• Analyzing a Scholarly Journal Article
• Group Presentations
• Dealing with Nervousness
• Using Visual Aids
• Grading Someone Else's Paper
• Types of Structured Group Activities
• Group Project Survival Skills
• Leading a Class Discussion
• Multiple Book Review Essay
• Reviewing Collected Works
• Writing a Case Analysis Paper
• Writing a Case Study
• About Informed Consent
• Writing Field Notes
• Writing a Policy Memo
• Writing a Reflective Paper
• Writing a Research Proposal
• Generative AI and Writing
• Acknowledgments

Definition and Introduction

Case analysis is a problem-based teaching and learning method that involves critically analyzing complex scenarios within an organizational setting for the purpose of placing the student in a “real world” situation and applying reflection and critical thinking skills to contemplate appropriate solutions, decisions, or recommended courses of action. It is considered a more effective teaching technique than in-class role playing or simulation activities. The analytical process is often guided by questions provided by the instructor that ask students to contemplate relationships between the facts and critical incidents described in the case.

Cases generally include both descriptive and statistical elements and rely on students applying abductive reasoning to develop and argue for preferred or best outcomes [i.e., case scenarios rarely have a single correct or perfect answer based on the evidence provided]. Rather than emphasizing theories or concepts, case analysis assignments emphasize building a bridge of relevancy between abstract thinking and practical application and, by so doing, teaches the value of both within a specific area of professional practice.

Given this, the purpose of a case analysis paper is to present a structured and logically organized format for analyzing the case situation. It can be assigned to students individually or as a small group assignment and it may include an in-class presentation component. Case analysis is predominately taught in economics and business-related courses, but it is also a method of teaching and learning found in other applied social sciences disciplines, such as, social work, public relations, education, journalism, and public administration.

Ellet, William. The Case Study Handbook: A Student's Guide . Revised Edition. Boston, MA: Harvard Business School Publishing, 2018; Christoph Rasche and Achim Seisreiner. Guidelines for Business Case Analysis . University of Potsdam; Writing a Case Analysis . Writing Center, Baruch College; Volpe, Guglielmo. "Case Teaching in Economics: History, Practice and Evidence." Cogent Economics and Finance 3 (December 2015). doi:https://doi.org/10.1080/23322039.2015.1120977.

How to Approach Writing a Case Analysis Paper

The organization and structure of a case analysis paper can vary depending on the organizational setting, the situation, and how your professor wants you to approach the assignment. Nevertheless, preparing to write a case analysis paper involves several important steps. As Hawes notes, a case analysis assignment “...is useful in developing the ability to get to the heart of a problem, analyze it thoroughly, and to indicate the appropriate solution as well as how it should be implemented” [p.48]. This statement encapsulates how you should approach preparing to write a case analysis paper.

Before you begin to write your paper, consider the following analytical procedures:

• Review the case to get an overview of the situation . A case can be only a few pages in length, however, it is most often very lengthy and contains a significant amount of detailed background information and statistics, with multilayered descriptions of the scenario, the roles and behaviors of various stakeholder groups, and situational events. Therefore, a quick reading of the case will help you gain an overall sense of the situation and illuminate the types of issues and problems that you will need to address in your paper. If your professor has provided questions intended to help frame your analysis, use them to guide your initial reading of the case.
• Read the case thoroughly . After gaining a general overview of the case, carefully read the content again with the purpose of understanding key circumstances, events, and behaviors among stakeholder groups. Look for information or data that appears contradictory, extraneous, or misleading. At this point, you should be taking notes as you read because this will help you develop a general outline of your paper. The aim is to obtain a complete understanding of the situation so that you can begin contemplating tentative answers to any questions your professor has provided or, if they have not provided, developing answers to your own questions about the case scenario and its connection to the course readings,lectures, and class discussions.
• Determine key stakeholder groups, issues, and events and the relationships they all have to each other . As you analyze the content, pay particular attention to identifying individuals, groups, or organizations described in the case and identify evidence of any problems or issues of concern that impact the situation in a negative way. Other things to look for include identifying any assumptions being made by or about each stakeholder, potential biased explanations or actions, explicit demands or ultimatums , and the underlying concerns that motivate these behaviors among stakeholders. The goal at this stage is to develop a comprehensive understanding of the situational and behavioral dynamics of the case and the explicit and implicit consequences of each of these actions.
• Identify the core problems . The next step in most case analysis assignments is to discern what the core [i.e., most damaging, detrimental, injurious] problems are within the organizational setting and to determine their implications. The purpose at this stage of preparing to write your analysis paper is to distinguish between the symptoms of core problems and the core problems themselves and to decide which of these must be addressed immediately and which problems do not appear critical but may escalate over time. Identify evidence from the case to support your decisions by determining what information or data is essential to addressing the core problems and what information is not relevant or is misleading.
• Explore alternative solutions . As noted, case analysis scenarios rarely have only one correct answer. Therefore, it is important to keep in mind that the process of analyzing the case and diagnosing core problems, while based on evidence, is a subjective process open to various avenues of interpretation. This means that you must consider alternative solutions or courses of action by critically examining strengths and weaknesses, risk factors, and the differences between short and long-term solutions. For each possible solution or course of action, consider the consequences they may have related to their implementation and how these recommendations might lead to new problems. Also, consider thinking about your recommended solutions or courses of action in relation to issues of fairness, equity, and inclusion.
• Decide on a final set of recommendations . The last stage in preparing to write a case analysis paper is to assert an opinion or viewpoint about the recommendations needed to help resolve the core problems as you see them and to make a persuasive argument for supporting this point of view. Prepare a clear rationale for your recommendations based on examining each element of your analysis. Anticipate possible obstacles that could derail their implementation. Consider any counter-arguments that could be made concerning the validity of your recommended actions. Finally, describe a set of criteria and measurable indicators that could be applied to evaluating the effectiveness of your implementation plan.

Use these steps as the framework for writing your paper. Remember that the more detailed you are in taking notes as you critically examine each element of the case, the more information you will have to draw from when you begin to write. This will save you time.

NOTE : If the process of preparing to write a case analysis paper is assigned as a student group project, consider having each member of the group analyze a specific element of the case, including drafting answers to the corresponding questions used by your professor to frame the analysis. This will help make the analytical process more efficient and ensure that the distribution of work is equitable. This can also facilitate who is responsible for drafting each part of the final case analysis paper and, if applicable, the in-class presentation.

Framework for Case Analysis . College of Management. University of Massachusetts; Hawes, Jon M. "Teaching is Not Telling: The Case Method as a Form of Interactive Learning." Journal for Advancement of Marketing Education 5 (Winter 2004): 47-54; Rasche, Christoph and Achim Seisreiner. Guidelines for Business Case Analysis . University of Potsdam; Writing a Case Study Analysis . University of Arizona Global Campus Writing Center; Van Ness, Raymond K. A Guide to Case Analysis . School of Business. State University of New York, Albany; Writing a Case Analysis . Business School, University of New South Wales.

Structure and Writing Style

A case analysis paper should be detailed, concise, persuasive, clearly written, and professional in tone and in the use of language . As with other forms of college-level academic writing, declarative statements that convey information, provide a fact, or offer an explanation or any recommended courses of action should be based on evidence. If allowed by your professor, any external sources used to support your analysis, such as course readings, should be properly cited under a list of references. The organization and structure of case analysis papers can vary depending on your professor’s preferred format, but its structure generally follows the steps used for analyzing the case.

Introduction

The introduction should provide a succinct but thorough descriptive overview of the main facts, issues, and core problems of the case . The introduction should also include a brief summary of the most relevant details about the situation and organizational setting. This includes defining the theoretical framework or conceptual model on which any questions were used to frame your analysis.

Following the rules of most college-level research papers, the introduction should then inform the reader how the paper will be organized. This includes describing the major sections of the paper and the order in which they will be presented. Unless you are told to do so by your professor, you do not need to preview your final recommendations in the introduction. U nlike most college-level research papers , the introduction does not include a statement about the significance of your findings because a case analysis assignment does not involve contributing new knowledge about a research problem.

Background Analysis

Background analysis can vary depending on any guiding questions provided by your professor and the underlying concept or theory that the case is based upon. In general, however, this section of your paper should focus on:

• Providing an overarching analysis of problems identified from the case scenario, including identifying events that stakeholders find challenging or troublesome,
• Identifying assumptions made by each stakeholder and any apparent biases they may exhibit,
• Describing any demands or claims made by or forced upon key stakeholders, and
• Highlighting any issues of concern or complaints expressed by stakeholders in response to those demands or claims.

These aspects of the case are often in the form of behavioral responses expressed by individuals or groups within the organizational setting. However, note that problems in a case situation can also be reflected in data [or the lack thereof] and in the decision-making, operational, cultural, or institutional structure of the organization. Additionally, demands or claims can be either internal and external to the organization [e.g., a case analysis involving a president considering arms sales to Saudi Arabia could include managing internal demands from White House advisors as well as demands from members of Congress].

Throughout this section, present all relevant evidence from the case that supports your analysis. Do not simply claim there is a problem, an assumption, a demand, or a concern; tell the reader what part of the case informed how you identified these background elements.

Identification of Problems

In most case analysis assignments, there are problems, and then there are problems . Each problem can reflect a multitude of underlying symptoms that are detrimental to the interests of the organization. The purpose of identifying problems is to teach students how to differentiate between problems that vary in severity, impact, and relative importance. Given this, problems can be described in three general forms: those that must be addressed immediately, those that should be addressed but the impact is not severe, and those that do not require immediate attention and can be set aside for the time being.

All of the problems you identify from the case should be identified in this section of your paper, with a description based on evidence explaining the problem variances. If the assignment asks you to conduct research to further support your assessment of the problems, include this in your explanation. Remember to cite those sources in a list of references. Use specific evidence from the case and apply appropriate concepts, theories, and models discussed in class or in relevant course readings to highlight and explain the key problems [or problem] that you believe must be solved immediately and describe the underlying symptoms and why they are so critical.

Alternative Solutions

This section is where you provide specific, realistic, and evidence-based solutions to the problems you have identified and make recommendations about how to alleviate the underlying symptomatic conditions impacting the organizational setting. For each solution, you must explain why it was chosen and provide clear evidence to support your reasoning. This can include, for example, course readings and class discussions as well as research resources, such as, books, journal articles, research reports, or government documents. In some cases, your professor may encourage you to include personal, anecdotal experiences as evidence to support why you chose a particular solution or set of solutions. Using anecdotal evidence helps promote reflective thinking about the process of determining what qualifies as a core problem and relevant solution .

Throughout this part of the paper, keep in mind the entire array of problems that must be addressed and describe in detail the solutions that might be implemented to resolve these problems.

Recommended Courses of Action

In some case analysis assignments, your professor may ask you to combine the alternative solutions section with your recommended courses of action. However, it is important to know the difference between the two. A solution refers to the answer to a problem. A course of action refers to a procedure or deliberate sequence of activities adopted to proactively confront a situation, often in the context of accomplishing a goal. In this context, proposed courses of action are based on your analysis of alternative solutions. Your description and justification for pursuing each course of action should represent the overall plan for implementing your recommendations.

For each course of action, you need to explain the rationale for your recommendation in a way that confronts challenges, explains risks, and anticipates any counter-arguments from stakeholders. Do this by considering the strengths and weaknesses of each course of action framed in relation to how the action is expected to resolve the core problems presented, the possible ways the action may affect remaining problems, and how the recommended action will be perceived by each stakeholder.

In addition, you should describe the criteria needed to measure how well the implementation of these actions is working and explain which individuals or groups are responsible for ensuring your recommendations are successful. In addition, always consider the law of unintended consequences. Outline difficulties that may arise in implementing each course of action and describe how implementing the proposed courses of action [either individually or collectively] may lead to new problems [both large and small].

Throughout this section, you must consider the costs and benefits of recommending your courses of action in relation to uncertainties or missing information and the negative consequences of success.

The conclusion should be brief and introspective. Unlike a research paper, the conclusion in a case analysis paper does not include a summary of key findings and their significance, a statement about how the study contributed to existing knowledge, or indicate opportunities for future research.

Begin by synthesizing the core problems presented in the case and the relevance of your recommended solutions. This can include an explanation of what you have learned about the case in the context of your answers to the questions provided by your professor. The conclusion is also where you link what you learned from analyzing the case with the course readings or class discussions. This can further demonstrate your understanding of the relationships between the practical case situation and the theoretical and abstract content of assigned readings and other course content.

Problems to Avoid

The literature on case analysis assignments often includes examples of difficulties students have with applying methods of critical analysis and effectively reporting the results of their assessment of the situation. A common reason cited by scholars is that the application of this type of teaching and learning method is limited to applied fields of social and behavioral sciences and, as a result, writing a case analysis paper can be unfamiliar to most students entering college.

After you have drafted your paper, proofread the narrative flow and revise any of these common errors:

• Unnecessary detail in the background section . The background section should highlight the essential elements of the case based on your analysis. Focus on summarizing the facts and highlighting the key factors that become relevant in the other sections of the paper by eliminating any unnecessary information.
• Analysis relies too much on opinion . Your analysis is interpretive, but the narrative must be connected clearly to evidence from the case and any models and theories discussed in class or in course readings. Any positions or arguments you make should be supported by evidence.
• Analysis does not focus on the most important elements of the case . Your paper should provide a thorough overview of the case. However, the analysis should focus on providing evidence about what you identify are the key events, stakeholders, issues, and problems. Emphasize what you identify as the most critical aspects of the case to be developed throughout your analysis. Be thorough but succinct.
• Writing is too descriptive . A paper with too much descriptive information detracts from your analysis of the complexities of the case situation. Questions about what happened, where, when, and by whom should only be included as essential information leading to your examination of questions related to why, how, and for what purpose.
• Inadequate definition of a core problem and associated symptoms . A common error found in case analysis papers is recommending a solution or course of action without adequately defining or demonstrating that you understand the problem. Make sure you have clearly described the problem and its impact and scope within the organizational setting. Ensure that you have adequately described the root causes w hen describing the symptoms of the problem.
• Recommendations lack specificity . Identify any use of vague statements and indeterminate terminology, such as, “A particular experience” or “a large increase to the budget.” These statements cannot be measured and, as a result, there is no way to evaluate their successful implementation. Provide specific data and use direct language in describing recommended actions.
• Unrealistic, exaggerated, or unattainable recommendations . Review your recommendations to ensure that they are based on the situational facts of the case. Your recommended solutions and courses of action must be based on realistic assumptions and fit within the constraints of the situation. Also note that the case scenario has already happened, therefore, any speculation or arguments about what could have occurred if the circumstances were different should be revised or eliminated.

Bee, Lian Song et al. "Business Students' Perspectives on Case Method Coaching for Problem-Based Learning: Impacts on Student Engagement and Learning Performance in Higher Education." Education & Training 64 (2022): 416-432; The Case Analysis . Fred Meijer Center for Writing and Michigan Authors. Grand Valley State University; Georgallis, Panikos and Kayleigh Bruijn. "Sustainability Teaching using Case-Based Debates." Journal of International Education in Business 15 (2022): 147-163; Hawes, Jon M. "Teaching is Not Telling: The Case Method as a Form of Interactive Learning." Journal for Advancement of Marketing Education 5 (Winter 2004): 47-54; Georgallis, Panikos, and Kayleigh Bruijn. "Sustainability Teaching Using Case-based Debates." Journal of International Education in Business 15 (2022): 147-163; .Dean,  Kathy Lund and Charles J. Fornaciari. "How to Create and Use Experiential Case-Based Exercises in a Management Classroom." Journal of Management Education 26 (October 2002): 586-603; Klebba, Joanne M. and Janet G. Hamilton. "Structured Case Analysis: Developing Critical Thinking Skills in a Marketing Case Course." Journal of Marketing Education 29 (August 2007): 132-137, 139; Klein, Norman. "The Case Discussion Method Revisited: Some Questions about Student Skills." Exchange: The Organizational Behavior Teaching Journal 6 (November 1981): 30-32; Mukherjee, Arup. "Effective Use of In-Class Mini Case Analysis for Discovery Learning in an Undergraduate MIS Course." The Journal of Computer Information Systems 40 (Spring 2000): 15-23; Pessoa, Silviaet al. "Scaffolding the Case Analysis in an Organizational Behavior Course: Making Analytical Language Explicit." Journal of Management Education 46 (2022): 226-251: Ramsey, V. J. and L. D. Dodge. "Case Analysis: A Structured Approach." Exchange: The Organizational Behavior Teaching Journal 6 (November 1981): 27-29; Schweitzer, Karen. "How to Write and Format a Business Case Study." ThoughtCo. https://www.thoughtco.com/how-to-write-and-format-a-business-case-study-466324 (accessed December 5, 2022); Reddy, C. D. "Teaching Research Methodology: Everything's a Case." Electronic Journal of Business Research Methods 18 (December 2020): 178-188; Volpe, Guglielmo. "Case Teaching in Economics: History, Practice and Evidence." Cogent Economics and Finance 3 (December 2015). doi:https://doi.org/10.1080/23322039.2015.1120977.

Writing Tip

Ca se Study and Case Analysis Are Not the Same!

Confusion often exists between what it means to write a paper that uses a case study research design and writing a paper that analyzes a case; they are two different types of approaches to learning in the social and behavioral sciences. Professors as well as educational researchers contribute to this confusion because they often use the term "case study" when describing the subject of analysis for a case analysis paper. But you are not studying a case for the purpose of generating a comprehensive, multi-faceted understanding of a research problem. R ather, you are critically analyzing a specific scenario to argue logically for recommended solutions and courses of action that lead to optimal outcomes applicable to professional practice.

To avoid any confusion, here are twelve characteristics that delineate the differences between writing a paper using the case study research method and writing a case analysis paper:

• Case study is a method of in-depth research and rigorous inquiry ; case analysis is a reliable method of teaching and learning . A case study is a modality of research that investigates a phenomenon for the purpose of creating new knowledge, solving a problem, or testing a hypothesis using empirical evidence derived from the case being studied. Often, the results are used to generalize about a larger population or within a wider context. The writing adheres to the traditional standards of a scholarly research study. A case analysis is a pedagogical tool used to teach students how to reflect and think critically about a practical, real-life problem in an organizational setting.
• The researcher is responsible for identifying the case to study; a case analysis is assigned by your professor . As the researcher, you choose the case study to investigate in support of obtaining new knowledge and understanding about the research problem. The case in a case analysis assignment is almost always provided, and sometimes written, by your professor and either given to every student in class to analyze individually or to a small group of students, or students select a case to analyze from a predetermined list.
• A case study is indeterminate and boundless; a case analysis is predetermined and confined . A case study can be almost anything [see item 9 below] as long as it relates directly to examining the research problem. This relationship is the only limit to what a researcher can choose as the subject of their case study. The content of a case analysis is determined by your professor and its parameters are well-defined and limited to elucidating insights of practical value applied to practice.
• Case study is fact-based and describes actual events or situations; case analysis can be entirely fictional or adapted from an actual situation . The entire content of a case study must be grounded in reality to be a valid subject of investigation in an empirical research study. A case analysis only needs to set the stage for critically examining a situation in practice and, therefore, can be entirely fictional or adapted, all or in-part, from an actual situation.
• Research using a case study method must adhere to principles of intellectual honesty and academic integrity; a case analysis scenario can include misleading or false information . A case study paper must report research objectively and factually to ensure that any findings are understood to be logically correct and trustworthy. A case analysis scenario may include misleading or false information intended to deliberately distract from the central issues of the case. The purpose is to teach students how to sort through conflicting or useless information in order to come up with the preferred solution. Any use of misleading or false information in academic research is considered unethical.
• Case study is linked to a research problem; case analysis is linked to a practical situation or scenario . In the social sciences, the subject of an investigation is most often framed as a problem that must be researched in order to generate new knowledge leading to a solution. Case analysis narratives are grounded in real life scenarios for the purpose of examining the realities of decision-making behavior and processes within organizational settings. A case analysis assignments include a problem or set of problems to be analyzed. However, the goal is centered around the act of identifying and evaluating courses of action leading to best possible outcomes.
• The purpose of a case study is to create new knowledge through research; the purpose of a case analysis is to teach new understanding . Case studies are a choice of methodological design intended to create new knowledge about resolving a research problem. A case analysis is a mode of teaching and learning intended to create new understanding and an awareness of uncertainty applied to practice through acts of critical thinking and reflection.
• A case study seeks to identify the best possible solution to a research problem; case analysis can have an indeterminate set of solutions or outcomes . Your role in studying a case is to discover the most logical, evidence-based ways to address a research problem. A case analysis assignment rarely has a single correct answer because one of the goals is to force students to confront the real life dynamics of uncertainly, ambiguity, and missing or conflicting information within professional practice. Under these conditions, a perfect outcome or solution almost never exists.
• Case study is unbounded and relies on gathering external information; case analysis is a self-contained subject of analysis . The scope of a case study chosen as a method of research is bounded. However, the researcher is free to gather whatever information and data is necessary to investigate its relevance to understanding the research problem. For a case analysis assignment, your professor will often ask you to examine solutions or recommended courses of action based solely on facts and information from the case.
• Case study can be a person, place, object, issue, event, condition, or phenomenon; a case analysis is a carefully constructed synopsis of events, situations, and behaviors . The research problem dictates the type of case being studied and, therefore, the design can encompass almost anything tangible as long as it fulfills the objective of generating new knowledge and understanding. A case analysis is in the form of a narrative containing descriptions of facts, situations, processes, rules, and behaviors within a particular setting and under a specific set of circumstances.
• Case study can represent an open-ended subject of inquiry; a case analysis is a narrative about something that has happened in the past . A case study is not restricted by time and can encompass an event or issue with no temporal limit or end. For example, the current war in Ukraine can be used as a case study of how medical personnel help civilians during a large military conflict, even though circumstances around this event are still evolving. A case analysis can be used to elicit critical thinking about current or future situations in practice, but the case itself is a narrative about something finite and that has taken place in the past.
• Multiple case studies can be used in a research study; case analysis involves examining a single scenario . Case study research can use two or more cases to examine a problem, often for the purpose of conducting a comparative investigation intended to discover hidden relationships, document emerging trends, or determine variations among different examples. A case analysis assignment typically describes a stand-alone, self-contained situation and any comparisons among cases are conducted during in-class discussions and/or student presentations.

The Case Analysis . Fred Meijer Center for Writing and Michigan Authors. Grand Valley State University; Mills, Albert J. , Gabrielle Durepos, and Eiden Wiebe, editors. Encyclopedia of Case Study Research . Thousand Oaks, CA: SAGE Publications, 2010; Ramsey, V. J. and L. D. Dodge. "Case Analysis: A Structured Approach." Exchange: The Organizational Behavior Teaching Journal 6 (November 1981): 27-29; Yin, Robert K. Case Study Research and Applications: Design and Methods . 6th edition. Thousand Oaks, CA: Sage, 2017; Crowe, Sarah et al. “The Case Study Approach.” BMC Medical Research Methodology 11 (2011):  doi: 10.1186/1471-2288-11-100; Yin, Robert K. Case Study Research: Design and Methods . 4th edition. Thousand Oaks, CA: Sage Publishing; 1994.

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Do Your Students Know How to Analyze a Case—Really?

Explore more.

• Case Teaching
• Student Engagement

J ust as actors, athletes, and musicians spend thousands of hours practicing their craft, business students benefit from practicing their critical-thinking and decision-making skills. Students, however, often have limited exposure to real-world problem-solving scenarios; they need more opportunities to practice tackling tough business problems and deciding on—and executing—the best solutions.

To ensure students have ample opportunity to develop these critical-thinking and decision-making skills, we believe business faculty should shift from teaching mostly principles and ideas to mostly applications and practices. And in doing so, they should emphasize the case method, which simulates real-world management challenges and opportunities for students.

To help educators facilitate this shift and help students get the most out of case-based learning, we have developed a framework for analyzing cases. We call it PACADI (Problem, Alternatives, Criteria, Analysis, Decision, Implementation); it can improve learning outcomes by helping students better solve and analyze business problems, make decisions, and develop and implement strategy. Here, we’ll explain why we developed this framework, how it works, and what makes it an effective learning tool.

The Case for Cases: Helping Students Think Critically

Business students must develop critical-thinking and analytical skills, which are essential to their ability to make good decisions in functional areas such as marketing, finance, operations, and information technology, as well as to understand the relationships among these functions. For example, the decisions a marketing manager must make include strategic planning (segments, products, and channels); execution (digital messaging, media, branding, budgets, and pricing); and operations (integrated communications and technologies), as well as how to implement decisions across functional areas.

Faculty can use many types of cases to help students develop these skills. These include the prototypical “paper cases”; live cases , which feature guest lecturers such as entrepreneurs or corporate leaders and on-site visits; and multimedia cases , which immerse students into real situations. Most cases feature an explicit or implicit decision that a protagonist—whether it is an individual, a group, or an organization—must make.

For students new to learning by the case method—and even for those with case experience—some common issues can emerge; these issues can sometimes be a barrier for educators looking to ensure the best possible outcomes in their case classrooms. Unsure of how to dig into case analysis on their own, students may turn to the internet or rely on former students for “answers” to assigned cases. Or, when assigned to provide answers to assignment questions in teams, students might take a divide-and-conquer approach but not take the time to regroup and provide answers that are consistent with one other.

To help address these issues, which we commonly experienced in our classes, we wanted to provide our students with a more structured approach for how they analyze cases—and to really think about making decisions from the protagonists’ point of view. We developed the PACADI framework to address this need.

PACADI: A Six-Step Decision-Making Approach

The PACADI framework is a six-step decision-making approach that can be used in lieu of traditional end-of-case questions. It offers a structured, integrated, and iterative process that requires students to analyze case information, apply business concepts to derive valuable insights, and develop recommendations based on these insights.

Prior to beginning a PACADI assessment, which we’ll outline here, students should first prepare a two-paragraph summary—a situation analysis—that highlights the key case facts. Then, we task students with providing a five-page PACADI case analysis (excluding appendices) based on the following six steps.

Step 1: Problem definition. What is the major challenge, problem, opportunity, or decision that has to be made? If there is more than one problem, choose the most important one. Often when solving the key problem, other issues will surface and be addressed. The problem statement may be framed as a question; for example, How can brand X improve market share among millennials in Canada? Usually the problem statement has to be re-written several times during the analysis of a case as students peel back the layers of symptoms or causation.

Step 2: Alternatives. Identify in detail the strategic alternatives to address the problem; three to five options generally work best. Alternatives should be mutually exclusive, realistic, creative, and feasible given the constraints of the situation. Doing nothing or delaying the decision to a later date are not considered acceptable alternatives.

Step 3: Criteria. What are the key decision criteria that will guide decision-making? In a marketing course, for example, these may include relevant marketing criteria such as segmentation, positioning, advertising and sales, distribution, and pricing. Financial criteria useful in evaluating the alternatives should be included—for example, income statement variables, customer lifetime value, payback, etc. Students must discuss their rationale for selecting the decision criteria and the weights and importance for each factor.

Step 4: Analysis. Provide an in-depth analysis of each alternative based on the criteria chosen in step three. Decision tables using criteria as columns and alternatives as rows can be helpful. The pros and cons of the various choices as well as the short- and long-term implications of each may be evaluated. Best, worst, and most likely scenarios can also be insightful.

Step 5: Decision. Students propose their solution to the problem. This decision is justified based on an in-depth analysis. Explain why the recommendation made is the best fit for the criteria.

Step 6: Implementation plan. Sound business decisions may fail due to poor execution. To enhance the likeliness of a successful project outcome, students describe the key steps (activities) to implement the recommendation, timetable, projected costs, expected competitive reaction, success metrics, and risks in the plan.

“Students note that using the PACADI framework yields ‘aha moments’—they learned something surprising in the case that led them to think differently about the problem and their proposed solution.”

PACADI’s Benefits: Meaningfully and Thoughtfully Applying Business Concepts

The PACADI framework covers all of the major elements of business decision-making, including implementation, which is often overlooked. By stepping through the whole framework, students apply relevant business concepts and solve management problems via a systematic, comprehensive approach; they’re far less likely to surface piecemeal responses.

As students explore each part of the framework, they may realize that they need to make changes to a previous step. For instance, when working on implementation, students may realize that the alternative they selected cannot be executed or will not be profitable, and thus need to rethink their decision. Or, they may discover that the criteria need to be revised since the list of decision factors they identified is incomplete (for example, the factors may explain key marketing concerns but fail to address relevant financial considerations) or is unrealistic (for example, they suggest a 25 percent increase in revenues without proposing an increased promotional budget).

In addition, the PACADI framework can be used alongside quantitative assignments, in-class exercises, and business and management simulations. The structured, multi-step decision framework encourages careful and sequential analysis to solve business problems. Incorporating PACADI as an overarching decision-making method across different projects will ultimately help students achieve desired learning outcomes. As a practical “beyond-the-classroom” tool, the PACADI framework is not a contrived course assignment; it reflects the decision-making approach that managers, executives, and entrepreneurs exercise daily. Case analysis introduces students to the real-world process of making business decisions quickly and correctly, often with limited information. This framework supplies an organized and disciplined process that students can readily defend in writing and in class discussions.

PACADI in Action: An Example

Here’s an example of how students used the PACADI framework for a recent case analysis on CVS, a large North American drugstore chain.

The CVS Prescription for Customer Value*

PACADI Stage

Summary Response

How should CVS Health evolve from the “drugstore of your neighborhood” to the “drugstore of your future”?

Alternatives

A1. Kaizen (continuous improvement)

A2. Product development

A3. Market development

A4. Personalization (micro-targeting)

Criteria (include weights)

C1. Customer value: service, quality, image, and price (40%)

C2. Customer obsession (20%)

C3. Growth through related businesses (20%)

C4. Customer retention and customer lifetime value (20%)

Each alternative was analyzed by each criterion using a Customer Value Assessment Tool

Alternative 4 (A4): Personalization was selected. This is operationalized via: segmentation—move toward segment-of-1 marketing; geodemographics and lifestyle emphasis; predictive data analysis; relationship marketing; people, principles, and supply chain management; and exceptional customer service.

Implementation

Partner with leading medical school

Curbside pick-up

Pet pharmacy

E-newsletter for customers and employees

Employee incentive program

CVS beauty days

Expand to Latin America and Caribbean

Healthier/happier corner

Holiday toy drives/community outreach

*Source: A. Weinstein, Y. Rodriguez, K. Sims, R. Vergara, “The CVS Prescription for Superior Customer Value—A Case Study,” Back to the Future: Revisiting the Foundations of Marketing from Society for Marketing Advances, West Palm Beach, FL (November 2, 2018).

Results of Using the PACADI Framework

When faculty members at our respective institutions at Nova Southeastern University (NSU) and the University of North Carolina Wilmington have used the PACADI framework, our classes have been more structured and engaging. Students vigorously debate each element of their decision and note that this framework yields an “aha moment”—they learned something surprising in the case that led them to think differently about the problem and their proposed solution.

These lively discussions enhance individual and collective learning. As one external metric of this improvement, we have observed a 2.5 percent increase in student case grade performance at NSU since this framework was introduced.

Tips to Get Started

The PACADI approach works well in in-person, online, and hybrid courses. This is particularly important as more universities have moved to remote learning options. Because students have varied educational and cultural backgrounds, work experience, and familiarity with case analysis, we recommend that faculty members have students work on their first case using this new framework in small teams (two or three students). Additional analyses should then be solo efforts.

To use PACADI effectively in your classroom, we suggest the following:

Advise your students that your course will stress critical thinking and decision-making skills, not just course concepts and theory.

Use a varied mix of case studies. As marketing professors, we often address consumer and business markets; goods, services, and digital commerce; domestic and global business; and small and large companies in a single MBA course.

As a starting point, provide a short explanation (about 20 to 30 minutes) of the PACADI framework with a focus on the conceptual elements. You can deliver this face to face or through videoconferencing.

Give students an opportunity to practice the case analysis methodology via an ungraded sample case study. Designate groups of five to seven students to discuss the case and the six steps in breakout sessions (in class or via Zoom).

Ensure case analyses are weighted heavily as a grading component. We suggest 30–50 percent of the overall course grade.

Once cases are graded, debrief with the class on what they did right and areas needing improvement (30- to 40-minute in-person or Zoom session).

Encourage faculty teams that teach common courses to build appropriate instructional materials, grading rubrics, videos, sample cases, and teaching notes.

When selecting case studies, we have found that the best ones for PACADI analyses are about 15 pages long and revolve around a focal management decision. This length provides adequate depth yet is not protracted. Some of our tested and favorite marketing cases include Brand W , Hubspot , Kraft Foods Canada , TRSB(A) , and Whiskey & Cheddar .

Art Weinstein , Ph.D., is a professor of marketing at Nova Southeastern University, Fort Lauderdale, Florida. He has published more than 80 scholarly articles and papers and eight books on customer-focused marketing strategy. His latest book is Superior Customer Value—Finding and Keeping Customers in the Now Economy . Dr. Weinstein has consulted for many leading technology and service companies.

Herbert V. Brotspies , D.B.A., is an adjunct professor of marketing at Nova Southeastern University. He has over 30 years’ experience as a vice president in marketing, strategic planning, and acquisitions for Fortune 50 consumer products companies working in the United States and internationally. His research interests include return on marketing investment, consumer behavior, business-to-business strategy, and strategic planning.

John T. Gironda , Ph.D., is an assistant professor of marketing at the University of North Carolina Wilmington. His research has been published in Industrial Marketing Management, Psychology & Marketing , and Journal of Marketing Management . He has also presented at major marketing conferences including the American Marketing Association, Academy of Marketing Science, and Society for Marketing Advances.

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Writing the Case Study

How should i approach it.

Investigating and writing up a report will require the completion of specific stages. You will need to timetable sufficient time to complete each stage, but also be aware that some stages are revisited while you are analysing the case and writing the report. Thinking and writing becomes a cyclical process.

Stages essential for analysing and writing a case study report may include:

1. Define the task

Your first step is to read the case and all the instructions for the assignment.

Use the checklist as a guide. You can print out this checklist to record your definition of the task. You may find it helpful to compare and discuss your understanding of the task with other students or colleagues. Try to visualise all the elements of the problem by using mind-maps to chart the main issues on a large piece of paper.

Checklist for defining the task

2. consider which theories and analysis tools may apply to the situation.

Your course notes, text books and readings should indicate the appropriate methodology for your case study analysis

Identify the problems

In your initial analysis you should identify the problems (issues/risks etc.) inherent in the case. Read to uncover the organisation's history of success and failure in relation to the case, the communication processes that are occurring, and relevant current strengths and weaknesses of the organisation or its activities that relate to the case.

A useful technique here is to create a mind-map of the situation, the processes and problems or issues. Use the mind-map to separate the problem elements and to note the most important and their relationships.

In your notes, document the causes and consequences of the problems highlighted in the case and also your preliminary ideas for solutions. Be prepared to discover more problems and solutions as you continue your analysis of the case!

Apply analysis tools

There are many tools available for analysis in the management and engineering fields but you need to evaluate which tools would best apply to your assessment of the issues/problems / risks etc. If you are unsure about which tool to use, read the rationale and purpose of each tool and discuss the options with your colleagues and course facilitator.

Document your results and ideas

It is important to create a complete set of notes that will be useful to refer to when writing up the case study report. For this reason record your findings and your own thoughts on the case. Also clearly document any testing, calculations or specifications that relate to your investigation of solutions as well.

3. Make recommendations and form conclusions

Make recommendations.

Recommendations are a clear statement (in text and/or table format) of what action should be taken to minimise, solve or remove the problems being investigated. Recommendations usually require a detailed action plan for implementation of a solution or a range of solutions depending on future events/scenarios.

According to Jarvis (2002), "for each part of your solution ask: 

• Will it work - why - what could possibly go wrong?
• Who will do it, are they capable, who else might be, who might be block?
• When- timing-sequence?
• How and how much –cost it out- where are the pay offs/savings?"

Form conclusions

Conclusions are drawn from your analysis and assessment of the situation. You usually consider must and desirable objectives. Also consider the limitations of your recommendations based on your testing of solutions and original assumptions that had to be made in the case.

4. Write the report

This section provides some advice on the process of writing up your report.

Plan the report 

Before you begin to write the report, it is essential to have a plan of its structure. You can begin to plan the report while you are investigating the case.

Fist, prepare an outline (in list or mind-map format) of the main headings and subheadings you will have in the report. Then add notes and ideas to the outline which remind you of what you want to achieve in each section and subsection. Use the outline to help you consider what information to include, where it should go and in what sequence. Be prepared to change your outline as your ideas develop. Finally, the outline headings and subheadings can be converted into the contents page of your report. 

Schedule your writing time

Prepare a schedule for writing and editing the sections of the report. Allow some extra time just in case you find some sections difficult to write. Begin by writing the sections you feel most confident about. Preliminary sections (executive summary, introduction) and supplementary sections (conclusions, reference list and appendices) are usually prepared last. Some writers like to begin with their conclusions (where the writer's thoughts are at that moment) or the methodology (it's easier to write about your own work). 

Analyse your audience 

In writing a case study report in your course, the report is often intended for an imaginary person so you need to make sure that your language and style suites that person. For example, a report for senior management will be different in content and style and language to a technical report. A report to a community group would also be different again in content, style and language. Audience definition helps you decide what to include in the report based on what readers need to know to perform their jobs better or what the readers need to know to increase their knowledge about your subject. These notes on audience analysis are adapted from Huckin and Olsen (p1991)

*After: Huckin & Olsen ,1991.1.

• Who will read the report? Think about all the uses of the report and where and when it would be read. Reports written within an organisation may be read by different people and different departments; for example, technical and design specialists, supervisors, senior managers, lawyers, marketing and finance specialists.
• What are the readers' needs and goals? Each department or unit in an organisation has its own needs and goals. Understanding the different perspectives can help you decide how to communicate persuasively to these groups. For example while design engineers may prefer to develop new or alternative design to show progress in their field, the marketing specialist may prefer that the organisation imitate a known successful design to save time.
• How do I make communication clear for managers? Communication must be accessible and useful to busy managers as they will primarily seek important generalisations. This has implications for the report's structure, the amount of orientation or background information provided and the level of technical language used. An executive summary, introductions to new sections and concluding summaries for major sections should be included in the report.
• What might be the readers' preferences or objections to the report? You may need to address the significance and benefits/limitations of your recommendations from a number of readers' perspectives in the report. You may also need to consider compromises as a way to acknowledge potential conflicts or criticisms of your recommendations or solutions.

Prepare a draft report 

Writers rarely produce a perfect piece of text in their first attempt so a number of drafts are usually produced. Careful planning and editing will ensure a consistent professional standard in the report. You will need to do the following:

• Revise the task often 

Do this by keeping both the reader's needs and the report's objectives in mind as you gather information, take notes and write sections of the report.

• Be selective 

Do this by taking clear notes, which include the information gathered and your thoughts about the usefulness and the implications of this information. Review your notes to decide what is essential information to include in the report.

• Create a logical structure 

Use your contents page outline to decide where information will go. Within each section, plan the subheadings and then decide on the sequence of information within these.

Check that your writing flows and that your ideas are supported and plausible. If you are not sure what to look for, here are links to advice and activities on report organisation, cohesion and evidence.

Ensure that all your figures and tables communicate a clear message. Show a colleague your visuals to check how they will be interpreted or 'read'.

• Edit, edit, edit

For first drafts, a word processor's spell checker and grammar checker can be useful however, do not rely solely on these tools in your final edit as they are not perfect. Errors will be overlooked or even created by these programs! The best ways to edit are to read a printed copy and where possible get a colleague to read and give feedback.

Here is a report checklist that you can print out: CHECKLIST

5. Prepare the reference list

The reference list is a list of all the sources you refer to in the report. If you do not reference sources of information, your assignment could be failed. As you read and take notes remember to collect the following information so that you can easily and quickly assemble your reference list.

 Further advice on the conventions for formatting reference lists and 'in text' references can be found in the Academic Skills toolkit .

6. Prepare cover/title page

Check your course requirements on the content and layout of the title page. As a general rule include the following:

• Institution the authors are affiliated with: eg UNSW School of Safety Science
• Title of the report

Eg "BHP Billiton Risk Assessment: Strategic Political Risks to BHP's Operations In Angola". 

• Author/s names (+ student numbers)
• Course name and code
• Date document was submitted

7. Final edit

At this stage it is best if you can leave the report for a day or so before conducting a final proof-read. This assists you to approach your report as a 'reader' rather than as the 'writer' so you will more easily see errors. You should expect to spend a couple of hours on this task.

• Reread the assignment guidelines so the task is fresh in your mind. Read the whole report to check that there is a logical structure to the whole report.
• Check each section of the report (including your executive summary, introduction and conclusion) for content and structure. Note changes to make in the sequence of sections.
• Note (highlight) changes you wish to make within sections (delete, simplify, expand, reorganise). In particular look closely at transition sections, figures and tables, sentences, referencing conventions and document formatting.
• Read through the report and make changes as required.

Here are some editing activities for you to try!

How is a case study organised?

Engineering & science

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Blog Graphic Design

15+ Professional Case Study Examples [Design Tips + Templates]

By Alice Corner , Jan 12, 2023

Have you ever bought something — within the last 10 years or so — without reading its reviews or without a recommendation or prior experience of using it?

If the answer is no — or at least, rarely — you get my point.

Positive reviews matter for selling to regular customers, and for B2B or SaaS businesses, detailed case studies are important too.

Wondering how to craft a compelling case study ? No worries—I’ve got you covered with 15 marketing case study templates , helpful tips, and examples to ensure your case study converts effectively.

Click to jump ahead:

• What is a Case Study?

Business Case Study Examples

Simple case study examples.

• Marketing Case Study Examples

Sales Case Study Examples

• Case Study FAQs

What is a case study?

A case study is an in-depth, detailed analysis of a specific real-world situation. For example, a case study can be about an individual, group, event, organization, or phenomenon. The purpose of a case study is to understand its complexities and gain insights into a particular instance or situation.

In the context of a business, however, case studies take customer success stories and explore how they use your product to help them achieve their business goals.

As well as being valuable marketing tools , case studies are a good way to evaluate your product as it allows you to objectively examine how others are using it.

It’s also a good way to interview your customers about why they work with you.

Related: What is a Case Study? [+6 Types of Case Studies]

Marketing Case Study Template

A marketing case study showcases how your product or services helped potential clients achieve their business goals. You can also create case studies of internal, successful marketing projects. A marketing case study typically includes:

• Company background and history
• The challenge
• How you helped
• Specific actions taken
• Visuals or Data
• Client testimonials

Here’s an example of a marketing case study template:

Whether you’re a B2B or B2C company, business case studies can be a powerful resource to help with your sales, marketing, and even internal departmental awareness.

Business and business management case studies should encompass strategic insights alongside anecdotal and qualitative findings, like in the business case study examples below.

Conduct a B2B case study by researching the company holistically

When it comes to writing a case study, make sure you approach the company holistically and analyze everything from their social media to their sales.

Think about every avenue your product or service has been of use to your case study company, and ask them about the impact this has had on their wider company goals.

In business case study examples like the one above, we can see that the company has been thought about holistically simply by the use of icons.

By combining social media icons with icons that show in-person communication we know that this is a well-researched and thorough case study.

This case study report example could also be used within an annual or end-of-year report.

Highlight the key takeaway from your marketing case study

To create a compelling case study, identify the key takeaways from your research. Use catchy language to sum up this information in a sentence, and present this sentence at the top of your page.

This is “at a glance” information and it allows people to gain a top-level understanding of the content immediately. 

You can use a large, bold, contrasting font to help this information stand out from the page and provide interest.

Learn  how to choose fonts  effectively with our Venngage guide and once you’ve done that.

Upload your fonts and  brand colors  to Venngage using the  My Brand Kit  tool and see them automatically applied to your designs.

The heading is the ideal place to put the most impactful information, as this is the first thing that people will read.

In this example, the stat of “Increase[d] lead quality by 90%” is used as the header. It makes customers want to read more to find out how exactly lead quality was increased by such a massive amount.

If you’re conducting an in-person interview, you could highlight a direct quote or insight provided by your interview subject.

Pick out a catchy sentence or phrase, or the key piece of information your interview subject provided and use that as a way to draw a potential customer in.

Use charts to visualize data in your business case studies

Charts are an excellent way to visualize data and to bring statistics and information to life. Charts make information easier to understand and to illustrate trends or patterns.

Making charts is even easier with Venngage.

In this consulting case study example, we can see that a chart has been used to demonstrate the difference in lead value within the Lead Elves case study.

Adding a chart here helps break up the information and add visual value to the case study. 

Using charts in your case study can also be useful if you’re creating a project management case study.

You could use a Gantt chart or a project timeline to show how you have managed the project successfully.

Use direct quotes to build trust in your marketing case study

To add an extra layer of authenticity you can include a direct quote from your customer within your case study.

According to research from Nielsen , 92% of people will trust a recommendation from a peer and 70% trust recommendations even if they’re from somebody they don’t know.

So if you have a customer or client who can’t stop singing your praises, make sure you get a direct quote from them and include it in your case study.

You can either lift part of the conversation or interview, or you can specifically request a quote. Make sure to ask for permission before using the quote.

This design uses a bright contrasting speech bubble to show that it includes a direct quote, and helps the quote stand out from the rest of the text.

This will help draw the customer’s attention directly to the quote, in turn influencing them to use your product or service.

Less is often more, and this is especially true when it comes to creating designs. Whilst you want to create a professional-looking, well-written and design case study – there’s no need to overcomplicate things.

These simple case study examples show that smart clean designs and informative content can be an effective way to showcase your successes.

Use colors and fonts to create a professional-looking case study

Business case studies shouldn’t be boring. In fact, they should be beautifully and professionally designed.

This means the normal rules of design apply. Use fonts, colors, and icons to create an interesting and visually appealing case study.

In this case study example, we can see how multiple fonts have been used to help differentiate between the headers and content, as well as complementary colors and eye-catching icons.

Marketing case study examples

Marketing case studies are incredibly useful for showing your marketing successes. Every successful marketing campaign relies on influencing a consumer’s behavior, and a great case study can be a great way to spotlight your biggest wins.

In the marketing case study examples below, a variety of designs and techniques to create impactful and effective case studies.

Show off impressive results with a bold marketing case study

Case studies are meant to show off your successes, so make sure you feature your positive results prominently. Using bold and bright colors as well as contrasting shapes, large bold fonts, and simple icons is a great way to highlight your wins.

In well-written case study examples like the one below, the big wins are highlighted on the second page with a bright orange color and are highlighted in circles.

Making the important data stand out is especially important when attracting a prospective customer with marketing case studies.

Use a simple but clear layout in your case study

Using a simple layout in your case study can be incredibly effective, like in the example of a case study below.

Keeping a clean white background, and using slim lines to help separate the sections is an easy way to format your case study.

Making the information clear helps draw attention to the important results, and it helps improve the  accessibility of the design .

Business case study examples like this would sit nicely within a larger report, with a consistent layout throughout.

Use visuals and icons to create an engaging and branded business case study

Nobody wants to read pages and pages of text — and that’s why Venngage wants to help you communicate your ideas visually.

Using icons, graphics, photos, or patterns helps create a much more engaging design. 

With this Blue Cap case study icons, colors, and impactful pattern designs have been used to create an engaging design that catches your eye.

Use a monochromatic color palette to create a professional and clean case study

Let your research shine by using a monochromatic and minimalistic color palette.

By sticking to one color, and leaving lots of blank space you can ensure your design doesn’t distract a potential customer from your case study content.

In this case study on Polygon Media, the design is simple and professional, and the layout allows the prospective customer to follow the flow of information.

The gradient effect on the left-hand column helps break up the white background and adds an interesting visual effect.

Did you know you can generate an accessible color palette with Venngage? Try our free accessible color palette generator today and create a case study that delivers and looks pleasant to the eye:

Add long term goals in your case study

When creating a case study it’s a great idea to look at both the short term and the long term goals of the company to gain the best understanding possible of the insights they provide.

Short-term goals will be what the company or person hopes to achieve in the next few months, and long-term goals are what the company hopes to achieve in the next few years.

Check out this modern pattern design example of a case study below:

In this case study example, the short and long-term goals are clearly distinguished by light blue boxes and placed side by side so that they are easy to compare.

Use a strong introductory paragraph to outline the overall strategy and goals before outlining the specific short-term and long-term goals to help with clarity.

This strategy can also be handy when creating a consulting case study.

Use data to make concrete points about your sales and successes

When conducting any sort of research stats, facts, and figures are like gold dust (aka, really valuable).

Being able to quantify your findings is important to help understand the information fully. Saying sales increased 10% is much more effective than saying sales increased.

While sales dashboards generally tend it make it all about the numbers and charts, in sales case study examples, like this one, the key data and findings can be presented with icons. This contributes to the potential customer’s better understanding of the report.

They can clearly comprehend the information and it shows that the case study has been well researched.

Use emotive, persuasive, or action based language in your marketing case study

Create a compelling case study by using emotive, persuasive and action-based language when customizing your case study template.

In this well-written case study example, we can see that phrases such as “Results that Speak Volumes” and “Drive Sales” have been used.

Using persuasive language like you would in a blog post. It helps inspire potential customers to take action now.

Keep your potential customers in mind when creating a customer case study for marketing

82% of marketers use case studies in their marketing  because it’s such an effective tool to help quickly gain customers’ trust and to showcase the potential of your product.

Why are case studies such an important tool in content marketing?

By writing a case study you’re telling potential customers that they can trust you because you’re showing them that other people do.

Not only that, but if you have a SaaS product, business case studies are a great way to show how other people are effectively using your product in their company.

In this case study, Network is demonstrating how their product has been used by Vortex Co. with great success; instantly showing other potential customers that their tool works and is worth using.

Related: 10+ Case Study Infographic Templates That Convert

Case studies are particularly effective as a sales technique.

A sales case study is like an extended customer testimonial, not only sharing opinions of your product – but showcasing the results you helped your customer achieve.

Make impactful statistics pop in your sales case study

Writing a case study doesn’t mean using text as the only medium for sharing results.

You should use icons to highlight areas of your research that are particularly interesting or relevant, like in this example of a case study:

Icons are a great way to help summarize information quickly and can act as visual cues to help draw the customer’s attention to certain areas of the page.

In some of the business case study examples above, icons are used to represent the impressive areas of growth and are presented in a way that grabs your attention.

Use high contrast shapes and colors to draw attention to key information in your sales case study

Help the key information stand out within your case study by using high contrast shapes and colors.

Use a complementary or contrasting color, or use a shape such as a rectangle or a circle for maximum impact.

This design has used dark blue rectangles to help separate the information and make it easier to read.

Coupled with icons and strong statistics, this information stands out on the page and is easily digestible and retainable for a potential customer.

Case Study Examples Summary

Once you have created your case study, it’s best practice to update your examples on a regular basis to include up-to-date statistics, data, and information.

You should update your business case study examples often if you are sharing them on your website .

It’s also important that your case study sits within your brand guidelines – find out how Venngage’s My Brand Kit tool can help you create consistently branded case study templates.

Case studies are important marketing tools – but they shouldn’t be the only tool in your toolbox. Content marketing is also a valuable way to earn consumer trust.

Case Study FAQ

Why should you write a case study.

Case studies are an effective marketing technique to engage potential customers and help build trust.

By producing case studies featuring your current clients or customers, you are showcasing how your tool or product can be used. You’re also showing that other people endorse your product.

In addition to being a good way to gather positive testimonials from existing customers , business case studies are good educational resources and can be shared amongst your company or team, and used as a reference for future projects.

How should you write a case study?

To create a great case study, you should think strategically. The first step, before starting your case study research, is to think about what you aim to learn or what you aim to prove.

You might be aiming to learn how a company makes sales or develops a new product. If this is the case, base your questions around this.

You can learn more about writing a case study  from our extensive guide.

Related: How to Present a Case Study like a Pro (With Examples)

Some good questions you could ask would be:

• Why do you use our tool or service?
• How often do you use our tool or service?
• What does the process of using our product look like to you?
• If our product didn’t exist, what would you be doing instead?
• What is the number one benefit you’ve found from using our tool?

You might also enjoy:

• 12 Essential Consulting Templates For Marketing, Planning and Branding
• Best Marketing Strategies for Consultants and Freelancers in 2019 [Study + Infographic]

Case studies

Case studies allow you to apply what you are learning to a real-world example, or ‘case’. The case could be either an actual or hypothetical situation, person, business or organisation.

Case studies usually ask you to:

• describe the case
• identify key issues of the case
• analyse the case using relevant theory or concepts
• make recommendations for the case.

General tips for case studies

Analyse the task carefully.

Case studies vary between disciplines, so read the assignment instructions and marking rubric carefully to understand what is expected.

Some case study assignments will ask you to answer very specific questions related to the case. For other case studies, you will decide on the content by interpreting the case information and connecting it with what you have been learning.

Read the case information thoroughly

Read the case information multiple times. You can use a range of reading strategies, including:

• skimming to get an idea of the case study scenario
• scanning to find specific information relevant to the assignment
• reading in detail to develop an in-depth understanding of the case.

While reading, keep the task in mind and ask yourself relevant questions, such as:

• How does this case relate to what I have been learning in class?
• What issues are evident in the case?
• What are the causes of these issues?
• What are some possible solutions to these issues?

Highlight any important information and make notes with your answers to these questions.

Connect the case, theory or concepts, and your analysis

Use a mind map or table to help you make connections between the case and theory or concepts. Draw on what you remember from classes and prescribed readings, and then conduct further research to help you analyse the case.

Use a mind map or table to help you plan the structure and content of your writing.

Example mindmap - Nursing

Example table for note-taking - Cybersecurity

This table shows how the student has analysed case evidence to identify problems in the case. The student has then researched relevant theory and made recommendations to solve the problems.

Writing a case study

Case studies are commonly written in a report  or essay format. Regardless of the format, all case studies should include three elements:

• facts from the case
• theory or concepts from literature (e.g. books, journals)
• your analysis.

This paragraph includes:

• case evidence (about Darren's drinking and smoking)
• theory (about the effect of alcohol and smoking and pain) and in-text citations (Chiang et al., 2016; Miyoshi, 2007)
• analysis (the implications for Darren's nursing care after the operation) 

Darren’s potential for pain is also influenced by lifestyle factors including excessive drinking and long-term smoking. [Case evidence] Darren identifies as a social drinker and consumes two beers each day after work and up to ten beers per day on weekends. [Theory] Frequent consumption of alcohol at high levels can increase a postoperative patient’s need for pain-relieving opioid medications, due to stimulating neuropathic pain delivered through both peripheral nervous system and central nervous system (CNS) pathways (Miyoshi, 2007, p. 208). [Case evidence] In addition to his high alcohol consumption, Darren is a current smoker and has smoked 30 cigarettes per day for the past 20 years. [Theory] Chiang et al. (2016) found that patients who smoke metabolise analgesic medications faster than non-smokers, as nicotine stimulates the CNS and produces analgesia in low quantities, resulting in smokers having a lower pain tolerance or hyperalgesia. [Analysis] Therefore, Darren’s alcohol use and smoking status mean that he is likely to experience higher levels of pain and require higher amounts of analgesia following his operation. 

Paragraph adapted and used with student permission

• case evidence (about access to Green Coin Company's network)
• theory (about attacks on passwords and Windows XP) and in-text citations (CVE 2014; Kapersky 2007; Windows 2017)
• analysis (the consequences of an attack on the company)

A major ICT weakness in Green Coin Company is that [Case evidence] employees access the network through a Windows XP frontend with a password authentication system. Passwords can be an effective way to authenticate into the system, provided that the password is strong and that the user keeps it secret. [Theory] However, a common attack vector on passwords is a trial-and-error approach where the attacker tries passwords repeatedly until they guess correctly and gain access to the network (Kapersky 2019). On a system with good security controls, the account will be locked out for a specified period after several wrong guesses, and an admin will be alerted that the account has been locked out (Windows 2017). However, Windows XP has a vulnerability that can bypass the lockout system, giving an attacker the ability to guess the password as many times as needed without being detected by the system (CVE 2014). [Analysis] If the attacker compromises an account that has access to the database, they will be able to add fake sales records, shipping requests and bullion transactions, thus compromising the integrity of the overall database. 

For more complete example case studies with further annotations, see the Word and PDF documents below.

Example case studies

• Example case study - Nursing [Word - 68KB]
• Example case study - Nursing [PDF - 170KB]
• Example case study - Cybersecurity [Word - 61KB]
• Example case study - Cybersecurity [PDF - 168KB]

Pathfinder link

Still have questions? Do you want to talk to an expert? Peer Learning Advisors or Academic Skills and Language Advisors  are available.

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Assessment by Case Studies and Scenarios

Case studies depict real-life situations in which problems need to be solved. Scenario-based teaching may be similar to case studies, or may be oriented toward developing communication or teamwork skills. Both case studies and scenarios are commonly used methods of problem-based learning. Typically, using these methods, teachers aim to develop student reasoning, problem-solving and decision-making skills. Case studies differ from role plays in that in the former, learning takes place largely through discussion and analysis, whereas in the latter, students assume a character or role and "act out" what that character would do in the scenario (The Teaching Gateway page Assessing with Role Plays and Simulations contains more information on using role plays for assessments.) Like role plays and simulations, case studies and scenarios aim for authenticity:  allowing students to get a sense of the situations they might face in the real world upon graduation. Students can see how their learning and skills can be applied in a real-world situation, without the pressure of being actually involved in that situation with the associated constraints on research, discussion and reflection time.

Case studies and scenarios are particularly useful when they present situations are complex and solutions are uncertain. Ideally, their complexity requires group members to draw from and share their experiences, work together, and learn by doing to understand and help solve the case-study problem.

You can present a single case to several groups in a class and require each group to offer its solutions, or you can give a different case to each group or individual.

Case studies' effectiveness comes from their abiliity to:

• engage students in research and reflective discussion
• encourage clinical and professional reasoning in a safe environment
• encourage higher-order thinking
• facilitate creative problem solving and the application of different problem-solving theories without risk to third parties or projects
• allow students to develop realistic solutions to complex problems
• develop students' ability to identify and distinguish between critical and extraneous factors
• enable students to apply previously acquired skills
• allow students to learn from one another
• provide an effective simulated learning environment
• encourage practical reasoning
• allow you to assess individuals or teams.

You can use case studies to bridge the gap between teacher-centred lectures and pure problem-based learning. They leave room for you to guide students directly, while the scenarios themselves suggest how students should operate, and provide parameters for their work.

Although some students have reported greater satisfaction with simulations as learning tools than with case studies (Maamari & El-Nakla, 2023), case studies generally require less up-front preparation time, and can be less intimidating for students.

To make case studies an effective form of assessment, instructors and tutors need to be familiar with their use in both teaching and assessment. This applies whether teachers are developing the case studies for their courses themselves or using those developed by others.

Case studies reach their highest effectiveness as a teaching and assessment tool when they are authentic; ensuring that case studies accurately reflect the circumstances in which a student will eventually be practising professionally can require a considerable amount of research, as well as the potential involvement of industry professionals.

Students may need scaffolding as they learn how to problem-solve in the context of case studies; using case studies as low-stakes, formative assessments can prepare them for summative assessment by case study at the end of the course.

Learning outcomes, course outlines, and marking rubrics need to be entirely clear about how case studies will be used in the course and how students will be expected to demonstrate their learning through thee way they analyse and problem-solve in the context of case studies.

Assessment preparation

Typically, the product assessed after case study or scenario work is a verbal presentation or a written submission. Decide who will take part in the assessment: the tutor, an industry specialist, a panel, peer groups or students themselves by self-evaluation? Choose whether to give a class or group mark or to assess individual performance; and whether to assess the product yourself or have it assessed by peers.

Assessment strategies

You can assess students’ interaction with other members of a group by asking open-ended questions, and setting tasks that require teamwork and sharing resources.

Assess the process of analysis

Case studies allow you to assess a student’s demonstration of deeper understanding and cognitive skills as they address the case.  These skills include, for example:

• identification of a problem
• hypotheses generation
• construction of an enquiry plan
• interpretation of findings
• investigation of results collected for evidence to refine a hypothesis and construction of a management plan.

During the problem-solving process, you can also observe and evaluate:

• quality of research
• structural issues in written material
• organisation of arguments
• feasibility of solutions presented
• intra-group dynamics
• evidence of consideration of all case factors
• multiple resolutions of the same scenario issue.

Use a variety of questions in case analysis

The Questioning page discusses in detail various ways to use questions in teaching . If your students are using the Harvard Business School case study method for their analysis, use a range of question types to enable the class to move through the stages of analysis:

• clarification/information seeking ( What? )
• analysis/diagnosis ( Why? )
• conclusion/recommendation ( What now? )
• implementation ( How? ) and
• application/reflection ( So what? What does it mean to you?)

Use technology

Learning-management systems such as Moodle can help you track contributions to case discussions . You can assess students' interactions with other members of a group by viewing their responses to open-ended questions or observing their teamwork and sharing of resources as part of the discussion.  You can incorporate the use of various tools in these systems, or others such as Survey Monkey, into students' assessment of their peers, or of their group members' contribution to exploring and presenting case studies. You can also set this peer assessment up so that it takes place anonymously.

Assessing by Case Studies: UNSW examples

These videos show examples of how UNSW faculty have implemented case studies in their own courses.

• Boston University. Using Case Studies to Teach
• Columbia University. Case Method Teaching and Learning
• Science Education Resource Center, Carleton College. Starting Point: What is Investigative Case-Based Learning?

Maamari, B. E., & El-Nakla, D. (2023). From case studies to experiential learning. Is simulation an effective tool for student assessment? Arab Economic and Business Journal, 15(1), Article 2. https://doi.org/10.38039/2214-4625.1023

Merret, C. (2020). Using case studies and build projects as authentic assessments in cornerstone courses. International Journal of Mechanical Engineering Education , 50 (1), 20-50. https://doi.org/10.1177/0306419020913286

Porzecanski, A. L., Bravo, A., Groom, M. J., Dávalos, L. M., Bynum, N., Abraham, B. J., Cigliano, J. A., Griffiths, C., Stokes, D. L., Cawthorn, M., Fernandez, D. S., Freeman,  L., Leslie, T., Theodose, T., Vogler, D., & Sterling, E. J. (2021). Using case studies to improve the critical thinking skills of undergraduate conservation biology students. Case Studies in the Environment , 5 (1), 1536396. https://doi.org/10.1525/cse.2021.1536396

• Teaching for learning
• Assessment Toolkit
• Digital Assessment at UNSW
• Designing Assessment
• Selecting Assessment Methods
• Selecting Assessment Technologies
• Oral Assessment
• Capstone Project
• Case Studies & Scenarios
• Oral Presentations
• Role Play & Simulation
• Grading & Giving Feedback
• Reviewing Assessment Quality
• Spotlight on Assessment
• Assessment Development Framework
• Teaching Settings

Events & news

How To Write Case Study Assignment – 7 Easy Steps

Students want to know, “how to write case study assignment easily. One of the most important qualities you’ll need in college is the ability to write a case study analysis. When you are given the task of writing a case study report, you may feel overwhelmed because it necessitates critical thinking skills.

You must analyze a business dilemma, explore possible solutions, and suggest the most appropriate approach using supporting data in a case study report. Writing a case study assignment is similar to writing a thesis paper .

When you have to write a case report, there are a few things you can keep in mind. You’re supposed to solve a dilemma that may not be easy.

A case study is a situation in a specific professional sense that students must analyze and react to.

Influenced by basic questions raised about the situation In certain situations, the situation or case study includes a variety of concerns or problems that must be addressed in the workplace.

You can also get Case study assignment help online from our professional experts. They will provide you A+ quality assignment solution at an affordable price.

What is a case study?

Table of Contents

A case study is a detailed examination of a particular individual, group, organization, or event. It is a research method that involves analyzing a specific example in depth and detail to understand its unique characteristics and to draw conclusions about broader phenomena.

Case studies can be qualitative, quantitative, or mixed methods in nature, and they can involve a variety of data collection techniques, such as interviews, surveys, observations, and document analysis.

Case studies are commonly used in academic research, business, and other fields to gain insights into complex phenomena that cannot be fully understood through statistical analyses or experiments. They are often used to illustrate a particular theory or concept, to provide a detailed description of a particular situation or event, or to identify best practices in a particular field or industry.

What are the different types of case studies?

The aim of a case study is to provide comprehensive reports on an incident, an organization, a location, an individual, or much more.

Certain kinds of case studies are typical, but the type of case depends on the subject. The most popular fields for case studies are as follows.

• Analysis of the illustrative case
• Case studies from the past
• Case studies that address a specific issue
• Case Study for Investigative Purposes
• Case Study in Context
• Case Study of a Critical Situation

What is the difference between a research paper And A case study?

Although research papers address a certain issue to the reader, case studies go even deeper. Guidelines on case studies recommend that students pay attention to specifics and examine topics in detail, using various analysis techniques. Case studies often investigate specific events for an individual or a group of individuals and include many narrations.

There are a variety of case study subjects to choose from

The first challenge when writing a case study is deciding on the right case study subjects.

In most cases, students are given the option of choosing their subject.

Instructors allow students to express their understanding of the subject as well as the whole course in this way. If you’re having trouble coming up with case study solutions, start with this list of classic topics:

• An individual
• A group of people
• It’s an occasion
• Organization

Some Other Case Study Subject

• What are some of the ways that people are abusing drugs at work?
• In difficult times, how can workers stay engaged?
• Images vs. real humans
• What is the best way to manage your promotional budget?
• How can social media advertising assist in attracting customers?
• Is it necessary for a small company to have a website?
• How should small consumers be considered for higher profits?
• The lost experience of retirement workers.
• Social media’s effect on today’s market.

Best Ways To Writing An Answer Of A Case Study Assignment

Before giving steps to answer a case study assignment, check below, quick guidance may seem too simplistic, but most students seem to disregard it, which is a huge mistake.

• Be realistic about the case study’s objectives
• Choose an engaging angle for your case study
• Make Your Case Study Relevant to ALL Potential Clients
• In your case study, stick to the traditional narrative arc
• In your case study, use data to illustrate key points
• portray your company as a supporting character
• Allow your customers to tell their own stories

How To Write Case Study Assignment – Easy Ways

Let’s know How To Write Case Study Assignment with a step-by-step guide.

Step 1:- Take the time to read through the Case Study and the Questions

• Read the situation and the issues that go with it carefully.
• Highlight the case’s key points and any problems you can recognize.
• Describe the case study’s intent.
• Define your study area.
• Without going through specifics, summarise the case study’s problems and results.
• Read the questions carefully and consider what they require of you.
• Reread the case, this time connecting the details that are important to some of the questions you’ve been asking.

Step 2:- Determine the Case Study’s Problems

Case studies identify a condition in a specific particular area. They also entail a large group of people in a difficult situation.

They will also characterize a scenario that is difficult to contend with, either because of how it is handled or because of its difficulty.

Analyzing the situation and identifying the challenges described in the case that may be troublesome is a vital part of the response.

Step 3:- Connect the dots between theory and application

To sum up the key difficulties. Identify alternatives to the big challenges. Briefly identify and assess the benefits and drawbacks of any possible option.

Determine what was done correctly and what was not using the knowledge of current codes of conduct, hypotheses, and other technical documentation and behaviors.

Step 4:- Make a strategy for responding.

At the end of the day, the score is all that counts. Determine the case study format that is necessary and follow it diligently. It’s a good idea to use the questions you’ve been given as headings and answer each part in turn, so you don’t miss any of the set questions.

Step 5:- Begin composing your answer to the case study

1. write an introduction for a case study assignment.

Your intro must always make it clear to your viewer what subject and method you would use to address it in your assignment.

You must provide the context when writing a case study introduction. Begin by posing a question or using a quote from someone you spoke with.

Not only should you describe the research issue and its importance in your presentation, but you should also explain why it is important.

However, you can also talk about why this case is being written and how it applies to the issue.

2. Paragraphs of the Body

This is where you start talking about the case study. Provide one viable approach to the problem, clarify the rationale for the suggested solution, back it up with evidence, and provide important theoretical principles in addition to the research findings.

You must determine the number of paragraphs needed for each question based on how many you have been given and how much debate is involved in addressing each one.

3. Final Remarks

To summarise, a case study is one of the better ways to understand what happened to an individual, a community, or a circumstance in reality.

It gives you an in-depth look at real-world issues that corporations, healthcare, and criminal justice can face.

This perspective allows one to see those circumstances in a new way.

This is due to the fact that we see scenarios that we would not normally see if we were not there.

Step 6:- Proofread and edit

When you’ve completed writing your case report, you’ll need to proofread and edit it.

Check that you’ve answered all of the questions and that your answers are supported by applicable literature.

Correct some grammatical or spelling errors, as well as punctuation errors.

Keep a close watch on how the thoughts flow and transition.

Step 7:- Submit your work

Can you’re paper show why you would do so if you were an expert in this situation?

Be sure that all of the sources are properly referenced.

Examine the proof and see if it is valid, useful, and trustworthy. Recheck the formatting. If that’s the case, it’s good to go.

case study example

This is a great example of a case study.

How to cite a case study?

Citing a case study can depend on the citation style you are using. In general, the following information should be included:

• Author(s) of the case study
• Title of the case study
• Title of the book or journal the case study is published in
• Date of publication
• Page numbers (if applicable)
• URL (if the case study is available online)

Here are some examples of how to cite a case study in different citation styles:

Author(s) Last name, First initial. (Year). Title of case study. In Editor(s) First initial. Last name (Ed.), Title of book (pp. page numbers). Publisher.

Smith, J. D. (2015). A case study of marketing strategies for a new product. In K. Jones (Ed.), Marketing in the 21st Century (pp. 50-60). ABC Publishing.

Author(s) Last name, First name. “Title of Case Study.” Title of Book or Journal, edited by Editor(s) First name Last name, Publisher, Year, pp. page numbers.

Jones, Mary. “The Impact of Social Media on Small Business: A Case Study.” Journal of Small Business Management, vol. 30, no. 2, Wiley-Blackwell, 2017, pp. 34-45.

Case study assignment writing service

Many students feel stuck while writing their case study assignments. A case study seems to be very complicated as it includes the study of a particular scenario that holds various perceptions.

Hence, it is tough for them to figure out “how to write a case study assignment.” Well, the answer to that question lies in this article. Still, many students struggle to do the work. In that case, they seek case study assignment help. But many organizations provide case study assignment writing services to needy students.

You need to analyze and examine all the service providers. Students can get help from the best case study assignment writers and get good grades.

Click to Ask Expert 

Writing a case study necessitates a thorough investigation and enough time for analysis. If you’re having trouble writing a good case report, you can next contact an online writing service.

Calltutors.com’s Cheap Assignment Help expert writers will assist you in finishing your case study project on time and according to your specifications.

What are the 3 methods of the case study?

There are three main types of case studies. These methods are such as; intrinsic, instrumental and collective.

How many pages should a case study be?

The length of a case study typically depends on the purpose of the study and the guidelines provided by the organization or instructor requesting the study. However, a typical case study can range from 2-5 pages for shorter assignments to 10-20 pages for more comprehensive case studies.

Are case studies hard to write?

The difficulty of writing a case study can vary depending on the complexity of the subject matter, the amount of research required, and the skill level of the writer.

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Writing A Case Study

Case Study Examples

Brilliant Case Study Examples and Templates For Your Help

15 min read

People also read

A Complete Case Study Writing Guide With Examples

Simple Case Study Format for Students to Follow

Understand the Types of Case Study Here

It’s no surprise that writing a case study is one of the most challenging academic tasks for students. You’re definitely not alone here!

Most people don't realize that there are specific guidelines to follow when writing a case study. If you don't know where to start, it's easy to get overwhelmed and give up before you even begin.

Don't worry! Let us help you out!

We've collected over 25 free case study examples with solutions just for you. These samples with solutions will help you win over your panel and score high marks on your case studies.

So, what are you waiting for? Let's dive in and learn the secrets to writing a successful case study.

• 1. An Overview of Case Studies
• 2. Case Study Examples for Students
• 3. Business Case Study Examples
• 4. Medical Case Study Examples
• 5. Psychology Case Study Examples 
• 6. Sales Case Study Examples
• 7. Interview Case Study Examples
• 8. Marketing Case Study Examples
• 9. Tips to Write a Good Case Study

An Overview of Case Studies

A case study is a research method used to study a particular individual, group, or situation in depth. It involves analyzing and interpreting data from a variety of sources to gain insight into the subject being studied. 

Case studies are often used in psychology, business, and education to explore complicated problems and find solutions. They usually have detailed descriptions of the subject, background info, and an analysis of the main issues.

The goal of a case study is to provide a comprehensive understanding of the subject. Typically, case studies can be divided into three parts, challenges, solutions, and results. 

Here is a case study sample PDF so you can have a clearer understanding of what a case study actually is:

Case Study Sample PDF

How to Write a Case Study Examples

Learn how to write a case study with the help of our comprehensive case study guide.

Case Study Examples for Students

Quite often, students are asked to present case studies in their academic journeys. The reason instructors assign case studies is for students to sharpen their critical analysis skills, understand how companies make profits, etc.

Below are some case study examples in research, suitable for students:

Case Study Example in Software Engineering

Qualitative Research Case Study Sample

Software Quality Assurance Case Study

Social Work Case Study Example

Ethical Case Study

Case Study Example PDF

These examples can guide you on how to structure and format your own case studies.

Struggling with formatting your case study? Check this case study format guide and perfect your document’s structure today.

Business Case Study Examples

A business case study examines a business’s specific challenge or goal and how it should be solved. Business case studies usually focus on several details related to the initial challenge and proposed solution. 

To help you out, here are some samples so you can create case studies that are related to businesses: 

Here are some more business case study examples:

Business Case Studies PDF

Business Case Studies Example

Typically, a business case study discovers one of your customer's stories and how you solved a problem for them. It allows your prospects to see how your solutions address their needs. 

Medical Case Study Examples

Medical case studies are an essential part of medical education. They help students to understand how to diagnose and treat patients. 

Here are some medical case study examples to help you.

Medical Case Study Example

Nursing Case Study Example

Want to understand the various types of case studies? Check out our types of case study blog to select the perfect type.

Psychology Case Study Examples 

Case studies are a great way of investigating individuals with psychological abnormalities. This is why it is a very common assignment in psychology courses. 

By examining all the aspects of your subject’s life, you discover the possible causes of exhibiting such behavior. 

For your help, here are some interesting psychology case study examples:

Psychology Case Study Example

Mental Health Case Study Example

Sales Case Study Examples

Case studies are important tools for sales teams’ performance improvement. By examining sales successes, teams can gain insights into effective strategies and create action plans to employ similar tactics.

By researching case studies of successful sales campaigns, sales teams can more accurately identify challenges and develop solutions.

Sales Case Study Example

Interview Case Study Examples

Interview case studies provide businesses with invaluable information. This data allows them to make informed decisions related to certain markets or subjects.

Interview Case Study Example

Marketing Case Study Examples

Marketing case studies are real-life stories that showcase how a business solves a problem. They typically discuss how a business achieves a goal using a specific marketing strategy or tactic.

They typically describe a challenge faced by a business, the solution implemented, and the results achieved.

This is a short sample marketing case study for you to get an idea of what an actual marketing case study looks like.

 Here are some more popular marketing studies that show how companies use case studies as a means of marketing and promotion:

“Chevrolet Discover the Unexpected” by Carol H. Williams

This case study explores Chevrolet's “ DTU Journalism Fellows ” program. The case study uses the initials “DTU” to generate interest and encourage readers to learn more. 

Multiple types of media, such as images and videos, are used to explain the challenges faced. The case study concludes with an overview of the achievements that were met.

Key points from the case study include:

• Using a well-known brand name in the title can create interest.
• Combining different media types, such as headings, images, and videos, can help engage readers and make the content more memorable.
• Providing a summary of the key achievements at the end of the case study can help readers better understand the project's impact.

“The Met” by Fantasy

“ The Met ” by Fantasy is a fictional redesign of the Metropolitan Museum of Art in New York City, created by the design studio Fantasy. The case study clearly and simply showcases the museum's website redesign.

The Met emphasizes the website’s features and interface by showcasing each section of the interface individually, allowing the readers to concentrate on the significant elements.

For those who prefer text, each feature includes an objective description. The case study also includes a “Contact Us” call-to-action at the bottom of the page, inviting visitors to contact the company.

Key points from this “The Met” include:

• Keeping the case study simple and clean can help readers focus on the most important aspects.
• Presenting the features and solutions with a visual showcase can be more effective than writing a lot of text.
• Including a clear call-to-action at the end of the case study can encourage visitors to contact the company for more information.

“Better Experiences for All” by Herman Miller

Herman Miller's minimalist approach to furniture design translates to their case study, “ Better Experiences for All ”, for a Dubai hospital. The page features a captivating video with closed-captioning and expandable text for accessibility.

The case study presents a wealth of information in a concise format, enabling users to grasp the complexities of the strategy with ease. It concludes with a client testimonial and a list of furniture items purchased from the brand.

Key points from the “Better Experiences” include:

• Make sure your case study is user-friendly by including accessibility features like closed captioning and expandable text.
• Include a list of products that were used in the project to guide potential customers.

“NetApp” by Evisort 

Evisort's case study on “ NetApp ” stands out for its informative and compelling approach. The study begins with a client-centric overview of NetApp, strategically directing attention to the client rather than the company or team involved.

The case study incorporates client quotes and explores NetApp’s challenges during COVID-19. Evisort showcases its value as a client partner by showing how its services supported NetApp through difficult times. 

• Provide an overview of the company in the client’s words, and put focus on the customer. 
• Highlight how your services can help clients during challenging times.
• Make your case study accessible by providing it in various formats.

“Red Sox Season Campaign,” by CTP Boston

The “ Red Sox Season Campaign ” showcases a perfect blend of different media, such as video, text, and images. Upon visiting the page, the video plays automatically, there are videos of Red Sox players, their images, and print ads that can be enlarged with a click.

The page features an intuitive design and invites viewers to appreciate CTP's well-rounded campaign for Boston's beloved baseball team. There’s also a CTA that prompts viewers to learn how CTP can create a similar campaign for their brand.

Some key points to take away from the “Red Sox Season Campaign”: 

• Including a variety of media such as video, images, and text can make your case study more engaging and compelling.
• Include a call-to-action at the end of your study that encourages viewers to take the next step towards becoming a customer or prospect.

“Airbnb + Zendesk” by Zendesk

The case study by Zendesk, titled “ Airbnb + Zendesk : Building a powerful solution together,” showcases a true partnership between Airbnb and Zendesk. 

The article begins with an intriguing opening statement, “Halfway around the globe is a place to stay with your name on it. At least for a weekend,” and uses stunning images of beautiful Airbnb locations to captivate readers.

Instead of solely highlighting Zendesk's product, the case study is crafted to tell a good story and highlight Airbnb's service in detail. This strategy makes the case study more authentic and relatable.

Some key points to take away from this case study are:

• Use client's offerings' images rather than just screenshots of your own product or service.
• To begin the case study, it is recommended to include a distinct CTA. For instance, Zendesk presents two alternatives, namely to initiate a trial or seek a solution.

“Influencer Marketing” by Trend and WarbyParker

The case study "Influencer Marketing" by Trend and Warby Parker highlights the potential of influencer content marketing, even when working with a limited budget. 

The “Wearing Warby” campaign involved influencers wearing Warby Parker glasses during their daily activities, providing a glimpse of the brand's products in use. 

This strategy enhanced the brand's relatability with influencers' followers. While not detailing specific tactics, the case study effectively illustrates the impact of third-person case studies in showcasing campaign results.

Key points to take away from this case study are:

• Influencer marketing can be effective even with a limited budget.
• Showcasing products being used in everyday life can make a brand more approachable and relatable.
• Third-person case studies can be useful in highlighting the success of a campaign.

Marketing Case Study Example

Marketing Case Study Template

Now that you have read multiple case study examples, hop on to our tips.

Tips to Write a Good Case Study

Here are some note-worthy tips to craft a winning case study 

• Define the purpose of the case study This will help you to focus on the most important aspects of the case. The case study objective helps to ensure that your finished product is concise and to the point.
• Choose a real-life example. One of the best ways to write a successful case study is to choose a real-life example. This will give your readers a chance to see how the concepts apply in a real-world setting.
• Keep it brief. This means that you should only include information that is directly relevant to your topic and avoid adding unnecessary details.
• Use strong evidence. To make your case study convincing, you will need to use strong evidence. This can include statistics, data from research studies, or quotes from experts in the field.
• Edit and proofread your work. Before you submit your case study, be sure to edit and proofread your work carefully. This will help to ensure that there are no errors and that your paper is clear and concise.

There you go!

We’re sure that now you have secrets to writing a great case study at your fingertips! This blog teaches the key guidelines of various case studies with samples. So grab your pen and start crafting a winning case study right away!

Having said that, we do understand that some of you might be having a hard time writing compelling case studies.

But worry not! Our expert case study writing service is here to take all your case-writing blues away! 

With 100% thorough research guaranteed, our online essay service can craft an amazing case study within 24 hours! 

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Dr. Barbara is a highly experienced writer and author who holds a Ph.D. degree in public health from an Ivy League school. She has worked in the medical field for many years, conducting extensive research on various health topics. Her writing has been featured in several top-tier publications.

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Case Study Analysis: Examples + How-to Guide & Writing Tips

A case study analysis is a typical assignment in business management courses. The task aims to show high school and college students how to analyze a current situation, determine what problems exist, and develop the best possible strategy to achieve the desired outcome.

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Many students feel anxious about writing case analyses because being told to analyze a case study and provide a solution can seem like a big task. That is especially so when working with real-life scenarios. However, you can rest assured writing a case analysis paper is easier than you think. Just keep reading this article and you will find case study examples for students and the advice provided by Custom-writing experts!

• 👣 Main Steps
• 🕵 Preparing the Case

🔬 Analyzing the Case

• 📑 Format & Structure
• 🙅 Things to Avoid
• 🏁 Conclusion

🔗 References

👣 writing a case study analysis: main steps.

Business management is built on case analysis. Every single economic result shows that the methods and instruments employed were either well-timed and expedient, in the event of success, or not, in case of failure. These two options indicate whether the strategy is efficient (and should be followed) or requires corrections (or complete change). Such an approach to the case study will make your writing piece more proficient and valuable for the reader. The following steps will direct your plan for writing a case study analysis.

Step 1: Preliminary work

• Make notes and highlight the numbers and ideas that could be quoted.
• Single out as many problems as you can, and briefly mark their underlying issues. Then make a note of those responsible. In the report, you will use two to five of the problems, so you will have a selection to choose from.
• Outline a possible solution to each of the problems you found. Course readings and outside research shall be used here. Highlight your best and worst solution for further reference.

Step 2: Drafting the Case

• Provide a general description of the situation and its history.
• Name all the problems you are going to discuss.
• Specify the theory used for the analysis.
• Present the assumptions that emerged during the analysis, if any.
• Describe the detected problems in more detail.
• Indicate their link to, and effect on, the general situation.
• Explain why the problems emerged and persist.
• List realistic and feasible solutions to the problems you outlined, in the order of importance.
• Specify your predicted results of such changes.
• Support your choice with reliable evidence (i.e., textbook readings, the experience of famous companies, and other external research).
• Define the strategies required to fulfill your proposed solution.
• Indicate the responsible people and the realistic terms for its implementation.
• Recommend the issues for further analysis and supervision.

Step 3: Finalizing the Case

Like any other piece of writing, a case analysis requires post-editing. Carefully read it through, looking for inconsistencies and gaps in meaning. Your purpose is to make it look complete, precise, and convincing.

🕵 Preparing a Case for Analysis

Your professor might give you various case study examples from which to choose, or they may just assign you a particular case study. To conduct a thorough data analysis, you must first read the case study. This might appear to be obvious. However, you’d be surprised at how many students don’t take adequate time to complete this part.

Read the case study very thoroughly, preferably several times. Highlight, underline, flag key information, and make notes to refer to later when you are writing your analysis report.

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If you don’t have a complete knowledge of the case study your professor has assigned, you won’t conduct a proper analysis of it. Even if you make use of a business case study template or refer to a sample analysis, it won’t help if you aren’t intimately familiar with your case study.

You will also have to conduct research. When it comes to research, you will need to do the following:

• Gather hard, quantitative data (e.g. 67% of the staff participated in the meeting).
• Design research tools , such as questionnaires and surveys (this will aid in gathering data).
• Determine and suggest the best specific, workable solutions.

It would be best if you also learned how to analyze a case study. Once you have read through the case study, you need to determine the focus of your analysis. You can do this by doing the following:

Compare your chosen solutions to the solutions offered by the experts who analyzed the case study you were given or to online assignments for students who were dealing with a similar task. The experts’ solutions will probably be more advanced than yours simply because these people are more experienced. However, don’t let this discourage you; the whole point of doing this analysis is to learn. Use the opportunity to learn from others’ valuable experience, and your results will be better next time.

If you are still in doubt, the University of South Carolina offers a great guide on forming a case study analysis.

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📑 Case Analysis Format & Structure

When you are learning how to write a case study analysis, it is important to get the format of your analysis right. Understanding the case study format is vital for both the professor and the student. The person planning and handing out such an assignment should ensure that the student doesn’t have to use any external sources .

In turn, students have to remember that a well-written case analysis provides all the data, making it unnecessary for the reader to go elsewhere for information.

Regardless of whether you use a case study template, you will need to follow a clear and concise format when writing your analysis report. There are some possible case study frameworks available. Still, a case study should contain eight sections laid out in the following format:

• Describe the purpose of the current case study;
• Provide a summary of the company;
• Briefly introduce the problems and issues found in the case study
• Discuss the theory you will be using in the analysis;
• Present the key points of the study and present any assumptions made during the analysis.
• Present each problem you have singled out;
• Justify your inclusion of each problem by providing supporting evidence from the case study and by discussing relevant theory and what you have learned from your course content;
• Divide the section (and following sections) into subsections, one for each of your selected problems.
• Present a summary of each problem you have identified;
• Present plausible solutions for each of the problems, keeping in mind that each problem will likely have more than one possible solution;
• Provide the pros and cons of each solution in a way that is practical.
• Conclusion . This is a summary of your findings and discussion.
• Decide which solution best fits each of the issues you identified;
• Explain why you chose this solution and how it will effectively solve the problem;
• Be persuasive when you write this section so that you can drive your point home;
• Be sure to bring together theory and what you have learned throughout your course to support your recommendations.
• Provide an explanation of what must be done, who should take action, and when the solution should be carried out;
• Where relevant, you should provide an estimate of the cost in implementing the solution, including both the financial investment and the cost in terms of time.
• References. While you generally do not need to refer to many external sources when writing a case study analysis, you might use a few. When you do, you will need to properly reference these sources, which is most often done in one of the main citation styles, including APA, MLA, or Harvard. There is plenty of help when citing references, and you can follow these APA guidelines , these MLA guidelines , or these Harvard guidelines .
• Appendices. This is the section you include after your case study analysis if you used any original data in the report. These data, presented as charts, graphs, and tables, are included here because to present them in the main body of the analysis would be disruptive to the reader. The University of Southern California provides a great description of appendices and when to make use of them.

When you’ve finished your first draft, be sure to proofread it. Look not only for potential grammar and spelling errors but also for discrepancies or holes in your argument.

You should also know what you need to avoid when writing your analysis.

Get an originally-written paper according to your instructions!

🙅 Things to Avoid in Case Analysis

Whenever you deal with a case study, remember that there are some pitfalls to avoid! Beware of the following mistakes:

• Excessive use of colloquial language . Even though it is a study of an actual case, it should sound formal.
• Lack of statistical data . Give all the important data, both in percentages and in numbers.
• Excessive details. State only the most significant facts, rather than drowning the reader in every fact you find.
• Inconsistency in the methods you have used . In a case study, theory plays a relatively small part, so you must develop a specific case study research methodology.
• Trivial means of research . It is critical that you design your own case study research method in whatever form best suits your analysis, such as questionnaires and surveys.

It is useful to see a few examples of case analysis papers. After all, a sample case study report can provide you with some context so you can see how to approach each aspect of your paper.

👀 Case Study Examples for Students

It might be easier to understand how a case study analysis works if you have an example to look at. Fortunately, examples of case studies are easy to come by. Take a look at this video for a sample case study analysis for the Coca-Cola Company.

If you want another example, then take a look at the one below!

Business Case Analysis: Example

CRM’s primary focus is customers and customer perception of the brand or the company. The focus may shift depending on customers’ needs. The main points that Center Parcs should consider are an increase in customer satisfaction and its market share. Both of these points will enhance customer perception of the product as a product of value. Increased customer satisfaction will indicate that the company provides quality services, and increased market share can reduce the number of switching (or leaving) customers, thus fostering customer loyalty.

Case Study Topics

• Equifax case study: the importance of cybersecurity measures . 
• Study a case illustrating ethical issues of medical research.  
• Examine the case describing the complications connected with nursing and residential care.  
• Analyze the competitive strategy of Delta Airlines . 
• Present a case study of an ethical dilemma showing the conflict between the spirit and the letter of the law.  
• Explore the aspects of Starbucks’ marketing strategyin a case study.  
• Research a case of community-based clinic organization and development.  
• Customer service of United Airlines: a case study . 
• Analyze a specific schizophrenia case and provide your recommendations.  
• Provide a case study of a patient with hyperglycemia.  
• Examine the growth strategy of United Healthcare. 
• Present a case study demonstrating ethical issues in business .  
• Study a case of the 5% shareholding rule application and its impact on the company.  
• Case study of post-traumatic stress disorder . 
• Analyze a case examining the issues of cross-cultural management .  
• Write a case study exploring the ethical issues the finance manager of a long-term care facility can face and the possible reaction to them.  
• Write a case study analyzing the aspects of a new president of a firm election. 
• Discuss the specifics of supply chain management in the case of Tehindo company. 
• Study a case of a life crisis in a family and the ways to cope with it.  
• Case study of Tea Leaves and More: supply chain issues .   
• Explore the case of ketogenic diet implementation among sportspeople.  
• Analyze the case of Webster Jewelry shop and suggest some changes.  
• Examine the unique aspects of Tea and More brand management .  
• Adidas case study: an ethical dilemma .  
• Research the challenges of Brazos Valley Food Bank and suggest possible solutions.  
• Describe the case of dark web monitoring for business.  
• Study a case of permissive parenting style .  
• Case study of Starbucks employees . 
• Analyze a case of workplace discrimination and suggest a strategy to avoid it.  
• Examine a case of the consumer decision-making process and define the factors that influence it.  
• Present a case study of Netflix illustrating the crucial role of management innovation for company development.  
• Discuss a case describing a workplace ethical issue and propose ways to resolve it.  
• Case study of the 2008 financial crisis: Graham’s value investing principles in the modern economic climate. 
• Write a case study analyzing the harmful consequences of communication issues in a virtual team .  
• Analyze a case that highlights the importance of a proper functional currency choice. 
• Examine the case of Hitachi Power Systems management.  
• Present a case study of medication research in a healthcare facility.  
• Study the case of Fiji Water and the challenges the brand faces.  
• Research a social problem case and suggest a solution.  
• Analyze a case that reveals the connection between alcohol use and borderline personality disorder .  
• Transglobal Airline case study: break-even analysis.   
• Examine the case of Chiquita Brands International from the moral and business ethics points of view.  
• Present a case study of applying for Social Security benefits. 
• Study the case of a mass hacker attack on Microsoft clients and suggest possible ways to prevent future attacks.  
• Case study of leadership effectiveness . 
• Analyze a case presenting a clinical moral dilemma and propose ways to resolve it. 
• Describe the case of Cowbell Brewing Company and discuss the strategy that made them successful.  
• Write a case study of WeWork company and analyze the strengths and weaknesses of its strategy.  
• Case study of medical ethical decision-making. 
• Study the case of The Georges hotel and suggest ways to overcome its managerial issues.  

🏁 Concluding Remarks

Writing a case study analysis can seem incredibly overwhelming, especially if you have never done it before. Just remember, you can do it provided you follow a plan, keep to the format described here, and study at least one case analysis example.

If you still need help analyzing a case study, your professor is always available to answer your questions and point you in the right direction. You can also get help with any aspect of the project from a custom writing company. Just tackle the research and hand over the writing, write a rough draft and have it checked by a professional, or completely hand the project off to an expert writer.

Regardless of the path you choose, you will turn in something of which you can be proud!

✏️ Case Study Analysis FAQ

Students (especially those who study business) often need to write a case study analysis. It is a kind of report that describes a business case. It includes multiple aspects, for example, the problems that exist, possible solutions, forecasts, etc.

There should be 3 main points covered in a case study analysis:

• The challenge(s) description,
• Possible solutions,
• Outcomes (real and/or foreseen).

Firstly, study some examples available online and in the library. Case study analysis should be a well-structured paper with all the integral components in place. Thus, you might want to use a template and/or an outline to start correctly.

A case study analysis is a popular task for business students. They typically hand it in the format of a paper with several integral components:

• Description of the problem
• Possible ways out
• Results and/or forecasts

Students sometimes tell about the outcome of their research within an oral presentation.

• Case Study: Academia
• Windows of vulnerability: a case study analysis (IEEE)
• A (Very) Brief Refresher on the Case Study Method: SAGE
• The case study approach: Medical Research Methodology
• Strengths and Limitations of Case Studies: Stanford University
• A Sample APA Paper: Radford University
• How to Write a Case Study APA Style: Seattle PI
• The Case Analysis: GVSU
• How to Outline: Purdue OWL
• Incorporating Interview Data: UW-Madison Writing Center
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If you are a student, you might need to learn how to write a literature review at some point. But don’t think it’s the same as the book review or other types of academic writing you had to do in high school! A literature review is a close examination of...

So, have you been recently assigned a research project? Or, even worse, is it already due soon? The following research paper hacks will help you do it in record time. In the article, you’ll see ten things you can do to conduct a study and compose a piece like a...

Eating a delicacy, watching a good movie, and proving a point to an audience are the three things that make life seem better. Today, you’ll deal with the last one. You’re about to become a professional at public speaking and attention grabbing. Here, you can learn how to write a...

What is a library research paper? It’s nothing more than an academic writing project that summarizes the information on a specific topic taken from primary and secondary sources. There are numerous library research examples you can find online. But to complete this assignment, you should simply follow these essential steps:...

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Henry Gustav Molaison: The Curious Case of Patient H.M. 

Erin Heaning

Clinical Safety Strategist at Bristol Myers Squibb

Psychology Graduate, Princeton University

Erin Heaning, a holder of a BA (Hons) in Psychology from Princeton University, has experienced as a research assistant at the Princeton Baby Lab.

Learn about our Editorial Process

Saul Mcleod, PhD

Editor-in-Chief for Simply Psychology

BSc (Hons) Psychology, MRes, PhD, University of Manchester

Saul Mcleod, PhD., is a qualified psychology teacher with over 18 years of experience in further and higher education. He has been published in peer-reviewed journals, including the Journal of Clinical Psychology.

Olivia Guy-Evans, MSc

Associate Editor for Simply Psychology

BSc (Hons) Psychology, MSc Psychology of Education

Olivia Guy-Evans is a writer and associate editor for Simply Psychology. She has previously worked in healthcare and educational sectors.

On This Page:

Henry Gustav Molaison, known as Patient H.M., is a landmark case study in psychology. After a surgery to alleviate severe epilepsy, which removed large portions of his hippocampus , he was left with anterograde amnesia , unable to form new explicit memories , thus offering crucial insights into the role of the hippocampus in memory formation.

• Henry Gustav Molaison (often referred to as H.M.) is a famous case of anterograde and retrograde amnesia in psychology.
• H. M. underwent brain surgery to remove his hippocampus and amygdala to control his seizures. As a result of his surgery, H.M.’s seizures decreased, but he could no longer form new memories or remember the prior 11 years of his life.
• He lost his ability to form many types of new memories (anterograde amnesia), such as new facts or faces, and the surgery also caused retrograde amnesia as he was able to recall childhood events but lost the ability to recall experiences a few years before his surgery.
• The case of H.M. and his life-long participation in studies gave researchers valuable insight into how memory functions and is organized in the brain. He is considered one of the most studied medical and psychological history cases.

Who is H.M.?

Henry Gustav Molaison, or “H.M” as he is commonly referred to by psychology and neuroscience textbooks, lost his memory on an operating table in 1953.

For years before his neurosurgery, H.M. suffered from epileptic seizures believed to be caused by a bicycle accident that occurred in his childhood. The seizures started out as minor at age ten, but they developed in severity when H.M. was a teenager.

Continuing to worsen in severity throughout his young adulthood, H.M. was eventually too disabled to work. Throughout this period, treatments continued to turn out unsuccessful, and epilepsy proved a major handicap and strain on H.M.’s quality of life.

And so, at age 27, H.M. agreed to undergo a radical surgery that would involve removing a part of his brain called the hippocampus — the region believed to be the source of his epileptic seizures (Squire, 2009).

For epilepsy patients, brain resection surgery refers to removing small portions of brain tissue responsible for causing seizures. Although resection is still a surgical procedure used today to treat epilepsy, the use of lasers and detailed brain scans help ensure valuable brain regions are not impacted.

In 1953, H.M.’s neurosurgeon did not have these tools, nor was he or the rest of the scientific or medical community fully aware of the true function of the hippocampus and its specific role in memory. In one regard, the surgery was successful, as H.M. did, in fact, experience fewer seizures.

However, family and doctors soon noticed he also suffered from severe amnesia, which persisted well past when he should have recovered. In addition to struggling to remember the years leading up to his surgery, H.M. also had gaps in his memory of the 11 years prior.

Furthermore, he lacked the ability to form new memories — causing him to perpetually live an existence of moment-to-moment forgetfulness for decades to come.

In one famous quote, he famously and somberly described his state as “like waking from a dream…. every day is alone in itself” (Squire et al., 2009).

H.M. soon became a major case study of interest for psychologists and neuroscientists who studied his memory deficits and cognitive abilities to better understand the hippocampus and its function.

When H.M. died on December 2, 2008, at the age of 82, he left behind a lifelong legacy of scientific contribution.

Surgical Procedure

Neurosurgeon William Beecher Scoville performed H.M.’s surgery in Hartford, Connecticut, in August 1953 when H.M. was 27 years old.

During the procedure, Scoville removed parts of H.M.’s temporal lobe which refers to the portion of the brain that sits behind both ears and is associated with auditory and memory processing.

More specifically, the surgery involved what was called a “partial medial temporal lobe resection” (Scoville & Milner, 1957). In this resection, Scoville removed 8 cm of brain tissue from the hippocampus — a seahorse-shaped structure located deep in the temporal lobe .

Bilateral resection of the anterior temporal lobe in patient HM.

Further research conducted after this removal showed Scoville also probably destroyed the brain structures known as the “uncus” (theorized to play a role in the sense of smell and forming new memories) and the “amygdala” (theorized to play a crucial role in controlling our emotional responses such as fear and sadness).

As previously mentioned, the removal surgery partially reduced H.M.’s seizures; however, he also lost the ability to form new memories.

At the time, Scoville’s experimental procedure had previously only been performed on patients with psychosis, so H.M. was the first epileptic patient and showed no sign of mental illness. In the original case study of H.M., which is discussed in further detail below, nine of Scoville’s patients from this experimental surgery were described.

However, because these patients had disorders such as schizophrenia, their symptoms were not removed after surgery.

In this regard, H.M. was the only patient with “clean” amnesia along with no other apparent mental problems.

H.M’s Amnesia

H.M.’s apparent amnesia after waking from surgery presented in multiple forms. For starters, H.M. suffered from retrograde amnesia for the 11-year period prior to his surgery.

Retrograde describes amnesia, where you can’t recall memories that were formed before the event that caused the amnesia. Important to note, current research theorizes that H.M.’s retrograde amnesia was not actually caused by the loss of his hippocampus, but rather from a combination of antiepileptic drugs and frequent seizures prior to his surgery (Shrader 2012).

In contrast, H.M.’s inability to form new memories after his operation, known as anterograde amnesia, was the result of the loss of the hippocampus.

This meant that H.M. could not learn new words, facts, or faces after his surgery, and he would even forget who he was talking to the moment he walked away.

However, H.M. could perform tasks, and he could even perform those tasks easier after practice. This important finding represented a major scientific discovery when it comes to memory and the hippocampus. The memory that H.M. was missing in his life included the recall of facts, life events, and other experiences.

This type of long-term memory is referred to as “explicit” or “ declarative ” memories and they require conscious thinking.

In contrast, H.M.’s ability to improve in tasks after practice (even if he didn’t recall that practice) showed his “implicit” or “ procedural ” memory remained intact (Scoville & Milner, 1957). This type of long-term memory is unconscious, and examples include riding a bike, brushing your teeth, or typing on a keyboard.

Most importantly, after removing his hippocampus, H.M. lost his explicit memory but not his implicit memory — establishing that implicit memory must be controlled by some other area of the brain and not the hippocampus.

After the severity of the side effects of H.M.’s operation became clear, H.M. was referred to neurosurgeon Dr. Wilder Penfield and neuropsychologist Dr. Brenda Milner of Montreal Neurological Institute (MNI) for further testing.

As discussed, H.M. was not the only patient who underwent this experimental surgery, but he was the only non-psychotic patient with such a degree of memory impairment. As a result, he became a major study and interest for Milner and the rest of the scientific community.

Since Penfield and Milner had already been conducting memory experiments on other patients at the time, they quickly realized H.M.’s “dense amnesia, intact intelligence, and precise neurosurgical lesions made him a perfect experimental subject” (Shrader 2012).

Milner continued to conduct cognitive testing on H.M. for the next fifty years, primarily at the Massachusetts Institute of Technology (MIT). Her longitudinal case study of H.M.’s amnesia quickly became a sensation and is still one of the most widely-cited psychology studies.

In publishing her work, she protected Henry’s identity by first referring to him as the patient H.M. (Shrader 2012).

In the famous “star tracing task,” Milner tested if H.M.’s procedural memory was affected by the removal of the hippocampus during surgery.

In this task, H.M. had to trace an outline of a star, but he could only trace the star based on the mirrored reflection. H.M. then repeated this task once a day over a period of multiple days.

Over the course of these multiple days, Milner observed that H.M. performed the test faster and with fewer errors after continued practice. Although each time he performed the task, he had no memory of having participated in the task before, his performance improved immensely (Shrader 2012).

As this task showed, H.M. had lost his declarative/explicit memory, but his unconscious procedural/implicit memory remained intact.

Given the damage to his hippocampus in surgery, researchers concluded from tasks such as these that the hippocampus must play a role in declarative but not procedural memory.

Therefore, procedural memory must be localized somewhere else in the brain and not in the hippocampus.

H.M’s Legacy

Milner’s and hundreds of other researchers’ work with H.M. established fundamental principles about how memory functions and is organized in the brain.

Without the contribution of H.M. in volunteering the study of his mind to science, our knowledge today regarding the separation of memory function in the brain would certainly not be as strong.

Until H.M.’s watershed surgery, it was not known that the hippocampus was essential for making memories and that if we lost this valuable part of our brain, we would be forced to live only in the moment-to-moment constraints of our short-term memory .

Once this was realized, the findings regarding H.M. were widely publicized so that this operation to remove the hippocampus would never be done again (Shrader 2012).

H.M.’s case study represents a historical time period for neuroscience in which most brain research and findings were the result of brain dissections, lesioning certain sections, and seeing how different experimental procedures impacted different patients.

Therefore, it is paramount we recognize the contribution of patients like H.M., who underwent these dangerous operations in the mid-twentieth century and then went on to allow researchers to study them for the rest of their lives.

Even after his death, H.M. donated his brain to science. Researchers then took his unique brain, froze it, and then in a 53-hour procedure, sliced it into 2,401 slices which were then individually photographed and digitized as a three-dimensional map.

Through this map, H.M.’s brain could be preserved for posterity (Wb et al., 2014). As neuroscience researcher Suzanne Corkin once said it best, “H.M. was a pleasant, engaging, docile man with a keen sense of humor, who knew he had a poor memory but accepted his fate.

There was a man behind the data. Henry often told me that he hoped that research into his condition would help others live better lives. He would have been proud to know how much his tragedy has benefitted science and medicine” (Corkin, 2014).

Corkin, S. (2014). Permanent present tense: The man with no memory and what he taught the world. Penguin Books.

Hardt, O., Einarsson, E. Ö., & Nader, K. (2010). A bridge over troubled water: Reconsolidation as a link between cognitive and neuroscientific memory research traditions. Annual Review of Psychology, 61, 141–167.

Scoville, W. B., & Milner, B. (1957). Loss of recent memory after bilateral hippocampal lesions . Journal of neurology, neurosurgery, and psychiatry, 20 (1), 11.

Shrader, J. (2012, January). HM, the man with no memory | Psychology Today. Retrieved from, https://www.psychologytoday.com/us/blog/trouble-in-mind/201201/hm-the-man-no-memory

Squire, L. R. (2009). The legacy of patient H. M. for neuroscience . Neuron, 61 , 6–9.

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21 UX case studies to learn from in 2024

UX case studies are the heart of your design portfolio. They offer a peek into your design process, showcasing how you tackle challenges, your methods, and your results. For recruiters, these case studies serve as a metric for evaluating your skills, problem-solving abilities, and talent.

If you’re considering creating your own UX case study in 2024 but don’t know where to start, you’re in the right place. This article aims to inspire you with 21 carefully hand-picked UX case study examples, each offering valuable lessons.

But before we dive into these examples, let’s address a question that might be lingering: Is a UX case study truly worth the effort?

Is it worth creating a UX case study?

The short answer is yes.

Remember how in math class, showing your workings was even more important than getting the correct answer? UX case studies are like that for designers. They are more than just showcasing the final product (the polished website or app); they detail the steps taken to get there (the research, user testing, and design iterations). By showing your design process, you give potential employers or clients a peek into your thought process and problem-solving skills.

A well-laid-out case study has many benefits, including the following:

Building credibility

As case studies provide evidence of your expertise and past successes, they can build credibility and trust with potential employers or clients.

Educational value

By showing your design process, you provide valuable insights and learnings for other designers and stakeholders.

Differentiation

A compelling case study can leave a lasting impression on potential recruiters and clients, helping you stand out.

Iterative improvement

A case study is like a roadmap of each project, detailing the highs, lows, failures, and successes. This information allows you to identify areas for improvement, learn from mistakes, and refine your approach in subsequent projects.

Now that you know why a stand-out case study is so important, let’s look at 21 examples to help you get creative. The case studies will fall under five categories:

• Language learning app
• Learning app
• Travel agency app
• Intelly healthcare app
• Cox Automotive
• Swiftwash laundry
• Wayfaro trip planner
• New York Times app redesign
• Disney+ app redesign
• Fitbit redesign
• Ryanair app redesign
• Forbes app redesign
• Enhancing virtual teaching with Google Meet
• Airbnb’s global check-in tool
• Spotify home shortcuts
• AI-powered spatial banking for Apple Vision Pro
• Sage Express

In this section, we’ll explore case studies that take us through the complete design journey of creating a digital product from scratch.

1. Language learning app

If you’re a designer looking to get your foot in the door, this is one case study you need to check out. It’s so well detailed that it helped this designer land their first role as a UX designer:

Created by Christina Sa, this case study tackles the all-too-common struggle of learning a new language through a mobile app. It takes us through the process of designing a nontraditional learning app that focuses on building a habit by teaching the Korean language using Korean media such as K-pop, K-drama, and K-webtoon.

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Key takeaway

This case study shows how a structured design process, user-centered approach, and effective communication can help you stand out. The creator meticulously laid out their design process from the exploratory research phase to the final prototype, even detailing how the case study changed their view on the importance of a design process.

If you’re searching for a comprehensive case study that details every step of the design process, look no further. This one is for you:

This impressive case study by Finna Wang explores the creation of a fan-focused responsive platform for Jambb, an already existing social platform. The creator starts by identifying the problem and then defines the project scope before diving into the design process.

This case study shows us the importance of an iterative problem-solving approach. It identifies a problem (pre-problem statement), creates a solution, tests the solution, and then revises the problem statement based on the new findings.

3. Learning app

If you need a highly visual case study that takes you through every step of the design process in an engaging way, this one is for you:

This case study walks us through the design of a platform where users can find experts to explain complex topics to them in a simple and friendly manner. It starts by defining the scope of work, then progresses through research, user journeys, information architecture, user flow, initial design, and user testing, before presenting the final solution.

This case study demonstrates effective ways to keep readers engaged while taking them through the steps of a design process. By incorporating illustrations and data visualization, the designer communicates complex information in an engaging manner, without boring the readers.

If you’re in search of a case study that details the design process but is also visually appealing, you should give this one a look:

This case study by Orbix Studio takes us through the process of designing GiveHub, a fundraising app that helps users set up campaigns for causes they’re passionate about. It starts with an overview of the design process, then moves on to identifying the challenges and proposing solutions, before showing us how the solutions are brought to life.

This case study illustrates how a visually engaging design and clear organization can make your presentation easy to grasp.

5. Travel agency app

This case study is quite popular on Behance, and it’s easy to see why:

The case study takes us through the process of creating a travel app that lets users compare travel packages from various travel agencies or groups. The creators set out a clear problem statement, propose a solution, and then show us the step-by-step implementation process. The incorporation of data visualization tools makes this case study easy to digest.

This is another case study that shows the importance of using a clearly defined design process. Going by its popularity on Behance, you can tell that the step-by-step process breakdown was well worth the effort.

6. Intelly healthcare app

If you’re looking for a UX case study that explores the design journey for both mobile and desktop versions of an app, this is one you should check out:

This case study explores the process of creating Intelly, an app that transforms patient care with telemedicine, prescription management, and real-time tracking. The case study begins with a clear design goal, followed by a layout of existing problems and design opportunities. The final design is a mobile app for patients and a desktop app for doctors.

This case study highlights the importance of proactive problem-solving and creative thinking in the design process. The creators laid out some key problems, identified design opportunities in them, and effectively leveraged them to create an app.

7. Cox Automotive

If you prefer a results-oriented case study, you’ll love this one:

This case study delves into how Cox Automotive’s Manheim division, used LogRocket to optimize their customers’ digital experience for remote car auctions. It starts by highlighting the three key outcomes before giving us an executive summary of the case study. The rest of the case study takes us through the process of achieving the highlighted outcomes.

A key takeaway from this case study is the significance of using user data and feedback to enhance the digital experience continuously. Cox Automotive used LogRocket to identify and address user-reported issues, gain insights into customer behaviors, and make data-driven decisions to optimize their product.

These case studies are more focused on the visual aspects of the design process, teaching us a thing or two about presentation and delivery.

If you love a case study that scores high on aesthetics with vivid colors, cool illustrations, and fun animations, you need to check this one out:

This case study takes us on a visual journey of creating Rebank, a digital product aimed at revolutionizing the baking industry. It starts with the research process, moves on to branding and style, and then takes us through the different screens, explaining what each one offers.

This case study illustrates the value of thinking outside the box. Breaking away from the conventional design style of financial products makes it a stand-out case study.

9. Swiftwash Laundry

If you’re looking for a case study that prioritizes aesthetics and visual appeal, you should check this one out:

This case study by Orbix Studio gives us a peek into how they created Swiftwash, a laundry service app. It takes us through the steps involved in creating an intuitive, user-friendly, and visually appealing interface.

If there’s one thing to take away from this case study, it’s the value of presenting information in a straightforward manner. Besides being easy on the eye, this case study is also easy to digest. The creators lay out the problem and detail the steps taken to achieve a solution, in an easy-to-follow way, while maintaining a high visual appeal.

10. Wayfaro trip planner

If you’re looking for a concise case study with clean visuals, you should definitely check this one out:

This Behance case study takes us through the design of Wayfaro, a trip planner app that allows users to plan their itineraries for upcoming journeys. The creators dive straight into the visual design process, showing us aspects such as branding and user flow, and explaining the various features on each screen.

This case study shows us the power of an attractive presentation. Not only is the mobile app design visually appealing, but the design process is presented in a sleek and stylish manner.

App redesign

These case studies delve into the redesign of existing apps, offering valuable insights into presentation techniques and problem-solving approaches.

11. New York Times app redesign

If you’re looking for an app redesign case study that’s impactful yet concise, this one is for you:

This study details the creation of “Timely,” a design feature to address issues with the NYT app such as irrelevant content, low usage, and undesirable coverage. It takes us through the process of identifying the problem, understanding audience needs, creating wireframes, and prototyping.

This case study shows us that you don’t always need to overhaul the existing app when redesigning. It suggests a solution that fits into the current information setup, adding custom graphics to the mobile app. Starting with a simple problem statement, it proposes a solution to address the app’s issues without changing what customers already enjoy.

12. Disney+ app redesign

If you’re looking for an engaging case study that’s light on information, you should check out this one:

This case study by Andre Carioca dives right into giving the user interface a little facelift to make it more fun and engaging. By employing compelling storytelling and appealing visuals, the creator crafts a narrative that’s a delight to read.

Given how popular this case study is on Behance, you can tell that the designer did something right. It shows how injecting a little playfulness can elevate your case study and make it more delightful.

13. Fitbit redesign

If you want an in-depth case study that doesn’t bore you to sleep, this one is for you:

This case study by Stacey Wang takes us through the process of redesigning Fitbit, a wearable fitness tracker. The creator starts by understanding personas and what users expect from a fitness tracker.

Next was the development of use cases and personas. Through a series of guerrilla tests, they were able to identify user pain points. The redesign was centered around addressing these pain points.

This case study highlights the importance of clear organization and strong visual communication. The creator goes in-depth into the intricacies of redesigning the Fitbit app, highlighting every step, without boring the readers.

14. Ryanair app redesign

If you’re bored of the usual static case studies and need something more interactive, this app redesign is what you’re looking for:

This case study takes us through the process of giving the Ryanair app a fresh look. Besides the clean aesthetics and straightforward presentation, the incorporation of playful language and interactive elements makes this case study captivating.

This case study shows how adding a bit of interactivity to your presentation can elevate your work.

15. Forbes app redesign

This case study starts by explaining why the redesign was needed and dives deep into analyzing the current app. The creator then takes us through the research and ideation phases and shares their proposed solution. After testing the solution, they made iterations based on the results.

When it comes to redesigning an existing product, it’s a good idea to make a strong case for why the redesign was needed in the first place.

UX research

These case studies are centered around UX research, highlighting key research insights to enhance your design process.

16. Enhancing virtual teaching with Google Meet

This case study by Amanda Rosenburg, Head of User Experience Research, Google Classroom shows us how listening to user feedback can help make our products more useful and inclusive to users.

To improve the virtual teaching experience on Google Meet, the team spent a lot of time getting feedback from teachers. They then incorporated this feedback into the product design, resulting in new functionality like attendance taking, hand raising, waiting rooms, and polls. Not only did these new features improve the user experience for teachers and students, but they also created a better user experience for all Google Meet users.

When there isn’t room for extensive user research and you need to make quick improvements to the user experience, it’s best to go straight to your users for feedback.

17. Airbnb’s global check-in tool

This case study by Vibha Bamba, Design Lead on Airbnb’s Host Success team, shows us how observing user behaviors inspired the creation of a global check-in tool:

By observing interactions between guests and hosts, the Airbnb team discovered a design opportunity. This led to the creation of visual check-in guides for Airbnb guests, which they can access both offline and online.

There’s a lot to be learned from observing user behavior. Don’t limit yourself to insights obtained from periodic research. Instead, observe how people interact with your product in their daily lives. The insights obtained from such observations can help unlock ingenious design opportunities.

18. Spotify Home Shortcuts

This case study by Nhi Ngo, a Senior User Researcher at Spotify shows us the importance of a human perspective in a data-driven world:

When the Spotify team set out to develop and launch the ML-powered Shortcuts feature on the home tab, they hit a brick wall with the naming. A/B tests came back inconclusive. In the end, they had to go with the product designer’s suggestion of giving the feature a name that would create a more human and personal experience for users.

This led to the creation of a humanistic product feature that evoked joy in Spotify’s users and led to the incorporation of more time-based features in the model, making the content more time-sensitive for users.

Although data-driven research is powerful, it doesn’t hold all the answers. So in your quest to uncover answers through research, never lose sight of the all-important human perspective.

Artificial intelligence

The following case studies are centered around the design of AI-powered products.

19. AI-powered spatial banking for Apple Vision Pro

If you want to be wowed by a futuristic case study that merges artificial intelligence with spatial banking, you should check this out:

In this revolutionary case study, UXDA designers offer a sneak peek into the future with a banking experience powered by AI. They unveil their vision of AI-powered spatial banking on the visionOS platform, showcasing its features and their AI use cases.

This case study shows us the importance of pushing boundaries to create innovative experiences that cater to user needs and preferences.

20. Sage Express

If what you need is an AI case study that isn’t information-dense, this one is for you:

This case study by Arounda takes us through the design of Sage Express, an AI-powered data discovery tool that automatically extracts patterns, tendencies, and insights from data. It outlines the challenge, proposes a solution, and details the journey of bringing the proposed solution to life. But it doesn’t stop there: it also shows the actual results of the design using tangible metrics.

This case study underscores the importance of showing your outcomes in tangible form. You’ve worked hard on a project, but what were the actual results?

If you’re looking for a clean and well-structured AI case study, this will be helpful:

This case study takes us through the process of creating Delfi, an AI-driven banking financial report system. It details the entire design process from onboarding to prototype creation.

If there’s one thing to learn from this case study, it’s how a well-structured presentation can simplify complex information. Although the case study is heavy on financial data, the organized layout not only enhances visual appeal but also aids comprehension.

This article has shown you 21 powerful case study examples across various niches, each providing valuable insights into the design process. These case studies demonstrate the importance of showcasing the design journey, not just the final polished product.

When creating your own case study, remember to walk your users through the design process, the challenges you faced, and your solutions. This gives potential recruiters and clients a glimpse of your creativity and problem-solving skills.

And finally, don’t forget to add that human touch. Let your personality shine through and don’t be afraid to inject a little playfulness and storytelling where appropriate. By doing so, you can craft a case study that leaves a lasting impression on your audience.

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Understanding CronJobs to Automate Tasks for Efficiency

CronJobs are automated tasks that run on Operating Systems like Unix, including Linux and MacOS. These commands or scripts can be scheduled to be executed at specific times, dates, or intervals. This automated nature allows you to command your computer to perform certain actions at specified times without you having to manually do them each time.

This application allows you to automate and schedule system maintenance, data management, web applications, and more. In addition to this, CronJobs comes with a range of benefits like allowing you to schedule tasks regardless of how simple or complex they are and giving you the flexibility to handle different circumstances appropriately. This versatile method gives you granular levels of control over scheduling so that you can get as precise as you want.

Jump to Section

How Cron Jobs Work?

In order to better understand CronJobs, we should take a look at their inner workings and how they operate. So here’s a breakdown.

The Cron Daemon

At the center of CronJobs is a program known as the Cron Daemon. It acts as the task scheduler and runs all the time while constantly checking for tasks it has to execute, and once the current date and time match the schedule in a crontab file, the cron daemon triggers the execution of the command. It does all this by silently running in the background, making sure that tasks are completed without any disruptions.

Crontab files

The role of crontab files is similar to that of an instruction manual. This is because crontab files tell the cron daemon which commands to execute and when. It contains important information like schedule info and details regarding which tasks to run.

Crontab Syntax

Within the crontab files lies the crontab syntax. This defines the structure of crontab files, as they are used to schedule tasks, or CronJobs to automatically run on Unix-based systems. To learn how to create a proper crontab syntax, you need to learn how to use the 4 main concepts of it. This includes the five fields, special characters, keywords, and commands.

What we meant by five fields is that each line in a crontab file is made up of five fields which are separated by spaces. The importance of these fields is that they are what define the schedule for the cronjob. They respectively specify the minute, hour, date, month, and day of the week respectively. For a better idea take a look at the snippet below.

“minute hour dayofmonth month dayofweek ”

Crontab syntaxes also use special characters to translate how often a cronjob should run. The most commonly used ones are as follows.

“ * “ : The asterisks represent every value in that specific field. So if you put an “ * “ in the hour field, it will translate to every hour. For example, if you wanted to schedule a task to execute in the first 10 minutes of every hour you can use the following.

10 * * * * command

“ , “ : The comma in any field implies that two values are entered into the same field. So if you were to put “ 3,14 “ in the day of the month field, the task will execute on these particular dates.

“ – “ : The hyphen is less cryptic as it refers to a range of values as usual. If a hyphen was added in the day of the week field to show as “ 1-5 “ ,it means the cronjob will run between the 1st and 5th day of the week. As a more complex example, if you wanted a cronjob to execute every first three hours of every weekday, you could use 0 0-3 * * 1-5 command The last part of the line that follows the five fields in crontab syntax is the actual command that you want to schedule.

Here are some examples of commands you could use within crontab tasks

“/usr/bin/rsync” : Used for file synchronization between locations. “/usr/bin/tar -czf” : Creates a compressed archive file (tar.gz) for backups. “/usr/bin/rm -rf” : Deletes files or directories

Advantages of CronJobs

By utilizing CronJobs, you’ll be able to capitalize on its automation capabilities to get rid of time-consuming menial tasks like manual backups and focus on more important tasks. This would not only free up your time but also your server resources. Although this is the most apparent advantage of CronJobs, you’ll be delighted to find out that there’s more.

While CronJobs allows you to handle tasks without human intervention, it also takes human error out of the equation. Meaning, that all the granular scheduling control you’ll have will ensure that tasks will execute at predefined times, saving you from the consequences of forgetfulness and tardiness.

On top of all of this, CronJobs can also be scaled to accommodate larger numbers of automated tasks as there is no compromise to be made in terms of performance. This makes CronJobs very suitable for complex systems with recurring processes.

Real-world applications of CronJobs

The simple yet effective concept of CronJobs can be applied to multiple instances in different fields owing to their scheduling and execution capabilities. This includes system maintenance, website maintenance, content management, and more. Let’s discuss some of them.

In system maintenance, CronJobs can be used to automatically compress old logs at set intervals instead of having to manually manage them. This will have your system running smoothly with ample disk space. Another way in which CronJobs can be used to manage your system is by automating security updates. Using a script that uses the package manager’s capability to look for updates and initiate updates you’ll be able to detect whether an update is available. This script of course should be set up to run periodically through CronJobs. While this would download the update, it wouldn’t necessarily install it until it gets the say-so from you.

A popular application of CronJobs is for the purpose of website maintenance. In this context, CronJobs is used mostly for data backup purposes. They can be scheduled to undertake data backups during certain times of the day or even more frequently if necessary. Cron jobs are also used to clean up the system by removing old or unnecessary data like outdated cache data to keep the database and system optimized. CronJobs can also be used to automate tasks like processing visitor statistics, sending out email notifications or reminders, software, and security updates, and calling APIs at regular intervals if your website relies on the data from them.

Cron jobs are also widely adopted for content management tasks. While similar to website maintenance, CronJobs are used in content management for database maintenance and data backup, they are also used for tasks like scheduling and automatically posting new content at peak traffic hours to maximize engagement. You can leverage its automated capabilities to send promotional emails and newsletters, update descriptions like average ratings, monitor server loads and regenerate the XML file for an RSS feed which will make sure that your web content stays up to date.

The automated scheduling and execution capabilities of CronJobs are also applied in areas such as healthcare management, financial services, Education and LMS, Travel and hospitality, Supply chain management, and more, proving Cronjob’s versatility and wide adaptability.

Why do some think CronJobs are complex?

Although CronJobs are a relatively simpler solution to manage your systems and execute tasks simultaneously, it does come with their fair share of complexities. Let’s discuss some of them.

One of the common complexities in CronJobs is that the cron expressions (syntax) can be somewhat cryptic and error-prone. This can be solved using tools that generate cron expression if manual entry comes as a challenge.

If you experience issues with your CronJobs and don’t execute properly, troubleshooting might be a difficult process. This is because you need to check the logs to see if the cron daemon even registered the job and recheck if the cronjob itself works without errors.

As CronJobs can be leveraged as a backdoor to your system, if CronJobs is improperly secured it could have major implications. This means unauthorized users gain access to edit the crontab file, they could execute tasks that might be harmful to your operations.

When the number of CronJobs increases, managing their interactions and dependencies can potentially be complex. This complexity might go up if multiple applications rely on CronJobs.

Integrating CronJobs with HostStage Hosting Solutions

HostStage.net offers a variety of hosting plans that support the use of cron jobs, enabling the automatic execution of scheduled tasks. For users with basic needs, such as website backups or content updates, HostStage’s shared hosting plans provide an accessible cPanel interface. This allows for straightforward setup of cron jobs without needing to directly edit crontab files. It’s an ideal solution for those new to web hosting, offering a simple way to automate essential tasks.

For more advanced users, HostStage’s VPS and dedicated server options offer greater control and resource allocation, making them suitable for more complex and resource-intensive automation. These plans allow for full command line access, giving users the flexibility to configure detailed cron jobs tailored to specific requirements. Whether you’re managing large-scale data processes or frequent operational tasks, HostStage adapts to fit a wide range of technical demands.

Overall, CronJobs can prove to be an effective method for scheduling and automatically executing tasks on a server. By doing so, they make your workflows and processes much simpler, handling complex time-consuming tasks and reducing your responsibilities. It undertakes timely executions by constantly running in the background, vigilantly scanning the crontab and your systems, and scanning for triggers.

Although it does come with its complexities, by understanding the stakes and being aware of them beforehand, you’ll be able to overcome them to take full advantage of your CronJobs.

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• Open access
• Published: 01 May 2024

A critical assessment of using ChatGPT for extracting structured data from clinical notes

• Jingwei Huang   ORCID: orcid.org/0000-0003-2155-6107 1 ,
• Donghan M. Yang 1 ,
• Ruichen Rong 1 ,
• Kuroush Nezafati   ORCID: orcid.org/0000-0002-6785-7362 1 ,
• Colin Treager 1 ,
• Zhikai Chi   ORCID: orcid.org/0000-0002-3601-3351 2 ,
• Shidan Wang   ORCID: orcid.org/0000-0002-0001-3261 1 ,
• Xian Cheng 1 ,
• Yujia Guo 1 ,
• Laura J. Klesse 3 ,
• Guanghua Xiao 1 ,
• Eric D. Peterson 4 ,
• Xiaowei Zhan 1 &
• Yang Xie   ORCID: orcid.org/0000-0001-9456-1762 1  

npj Digital Medicine volume  7 , Article number:  106 ( 2024 ) Cite this article

38 Altmetric

Metrics details

• Non-small-cell lung cancer

Existing natural language processing (NLP) methods to convert free-text clinical notes into structured data often require problem-specific annotations and model training. This study aims to evaluate ChatGPT’s capacity to extract information from free-text medical notes efficiently and comprehensively. We developed a large language model (LLM)-based workflow, utilizing systems engineering methodology and spiral “prompt engineering” process, leveraging OpenAI’s API for batch querying ChatGPT. We evaluated the effectiveness of this method using a dataset of more than 1000 lung cancer pathology reports and a dataset of 191 pediatric osteosarcoma pathology reports, comparing the ChatGPT-3.5 (gpt-3.5-turbo-16k) outputs with expert-curated structured data. ChatGPT-3.5 demonstrated the ability to extract pathological classifications with an overall accuracy of 89%, in lung cancer dataset, outperforming the performance of two traditional NLP methods. The performance is influenced by the design of the instructive prompt. Our case analysis shows that most misclassifications were due to the lack of highly specialized pathology terminology, and erroneous interpretation of TNM staging rules. Reproducibility shows the relatively stable performance of ChatGPT-3.5 over time. In pediatric osteosarcoma dataset, ChatGPT-3.5 accurately classified both grades and margin status with accuracy of 98.6% and 100% respectively. Our study shows the feasibility of using ChatGPT to process large volumes of clinical notes for structured information extraction without requiring extensive task-specific human annotation and model training. The results underscore the potential role of LLMs in transforming unstructured healthcare data into structured formats, thereby supporting research and aiding clinical decision-making.

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Introduction.

Large Language Models (LLMs) 1 , 2 , 3 , 4 , 5 , 6 , such as Generative Pre-trained Transformer (GPT) models represented by ChatGPT, are being utilized for diverse applications across various sectors. In the healthcare industry, early applications of LLMs are being used to facilitate patient-clinician communication 7 , 8 . To date, few studies have examined the potential of LLMs in reading and interpreting clinical notes, turning unstructured texts into structured, analyzable data.

Traditionally, the automated extraction of structured data elements from medical notes has relied on medical natural language processing (NLP) using rule-based or machine-learning approaches or a combination of both 9 , 10 . Machine learning methods 11 , 12 , 13 , 14 , particularly deep learning, typically employ neural networks and the first generation of transformer-based large language models (e.g., BERT). Medical domain knowledge needs to be integrated into model designs to enhance performance. However, a significant obstacle to developing these traditional medical NLP algorithms is the limited existence of human-annotated datasets and the costs associated with new human annotation 15 . Despite meticulous ground-truth labeling, the relatively small corpus sizes often result in models with poor generalizability or make evaluations of generalizability impossible. For decades, conventional artificial intelligence (AI) systems (symbolic and neural networks) have suffered from a lack of general knowledge and commonsense reasoning. LLMs, like GPT, offer a promising alternative, potentially using commonsense reasoning and broad general knowledge to facilitate language processing.

ChatGPT is the application interface of the GPT model family. This study explores an approach to using ChatGPT to extract structured data elements from unstructured clinical notes. In this study, we selected lung cancer pathology reports as the corpus for extracting detailed diagnosis information for lung cancer. To accomplish this, we developed and improved a prompt engineering process. We then evaluated the effectiveness of this method by comparing the ChatGPT output with expert-curated structured data and used case studies to provide insights into how ChatGPT read and interpreted notes and why it made mistakes in some cases.

Data and endpoints

The primary objective of this study was to develop an algorithm and assess the capabilities of ChatGPT in processing and interpreting a large volume of free-text clinical notes. To evaluate this, we utilized unstructured lung cancer pathology notes, which provide diagnostic information essential for developing treatment plans and play vital roles in clinical and translational research. We accessed a total of 1026 lung cancer pathology reports from two web portals: the Cancer Digital Slide Archive (CDSA data) ( https://cancer.digitalslidearchive.org/ ) and The Cancer Genome Atlas (TCGA data) ( https://cBioPortal.org ). These platforms serve as public data repositories for de-identified patient information, facilitating cancer research. The CDSA dataset was utilized as the “training” data for prompt development, while the TCGA dataset, after removing the overlapping cases with CDSA, served as the test data for evaluating the ChatGPT model performance.

From all the downloaded 99 pathology reports from CDSA for the training data, we excluded 21 invalid reports due to near-empty content, poor scanning quality, or missing report forms. Seventy-eight valid pathology reports were included as the training data to optimize the prompt. To evaluate the model performance, 1024 pathology reports were downloaded from cBioPortal. Among them, 97 overlapped with the training data and were excluded from the evaluation. We further excluded 153 invalid reports due to near-empty content, poor scanning quality, or missing report forms. The invalid reports were preserved to evaluate ChatGPT’s handling of irregular inputs separately, and were not included in the testing data for accuracy performance assessment. As a result, 774 valid pathology reports were included as the testing data for performance evaluation. These valid reports still contain typos, missing words, random characters, incomplete contents, and other quality issues challenging human reading. The corresponding numbers of reports used at each step of the process are detailed in Fig. 1 .

Exclusions are accounted for due to reasons such as empty reports, poor scanning quality, and other factors, including reports of stage IV or unknown conditions.

The specific task of this study was to identify tumor staging and histology types which are important for clinical care and research from pathology reports. The TNM staging system 16 , outlining the primary tumor features (T), regional lymph node involvement (N), and distant metastases (M), is commonly used to define the disease extent, assign prognosis, and guide lung cancer treatment. The American Joint Committee on Cancer (AJCC) has periodically released various editions 16 of TNM classification/staging for lung cancers based on recommendations from extensive database analyses. Following the AJCC guideline, individual pathologic T, N, and M stage components can be summarized into an overall pathologic staging score of Stage I, II, III, or IV. For this project, we instructed ChatGPT to use the AJCC 7 th edition Cancer Staging Manual 17 as the reference for staging lung cancer cases. As the lung cancer cases in our dataset are predominantly non-metastatic, the pathologic metastasis (pM) stage was not extracted. The data elements we chose to extract and evaluate for this study are pathologic primary tumor (pT) and pathologic lymph node (pN) stage components, overall pathologic tumor stage, and histology type.

Overall Performance

Using the training data in the CDSA dataset ( n  = 78), we experimented and improved prompts iteratively, and the final prompt is presented in Fig. 2 . The overall performance of the ChatGPT (gpt-3.5-turbo-16k model) is evaluated in the TCGA dataset ( n  = 774), and the results are summarized in Table 1 . The accuracy of primary tumor features (pT), regional lymph node involvement (pN), overall tumor stage, and histological diagnosis are 0.87, 0.91, 0.76, and 0.99, respectively. The average accuracy of all attributes is 0.89. The coverage rates for pT, pN, overall stage and histological diagnosis are 0.97, 0.94, 0.94 and 0.96, respectively. Further details of the accuracy evaluation, F1, Kappa, recall, and precision for each attribute are summarized as confusion matrices in Fig. 3 .

Final prompt for information extraction and estimation from pathology reports.

For meaningful evaluation, the cases with uncertain values, such as “Not Available”, “Not Specified”, “Cannot be determined”, “Unknown”, et al. in reference and prediction have been removed. a Primary tumor features (pT), b regional lymph node involvement (pN), c overall tumor stage, and d histological diagnosis.

Inference and Interpretation

To understand how ChatGPT reads and makes inferences from pathology reports, we demonstrated a case study using a typical pathology report in this cohort (TCGA-98-A53A) in Fig. 4a . The left panel shows part of the original pathology report, and the right panel shows the ChatGPT output with estimated pT, pN, overall stage, and histology diagnosis. For each estimate, ChatGPT gives the confidence level and the corresponding evidence it used for the estimation. In this case, ChatGPT correctly extracted information related to tumor size, tumor features, lymph node involvement, and histology information and used the AJCC staging guidelines to estimate tumor stage correctly. In addition, the confidence level, evidence interpretation, and case summary align well with the report and pathologists’ evaluations. For example, the evidence for the pT category was described as “The pathology report states that the tumor is > 3 cm and < 5 cm in greatest dimension, surrounded by lung or visceral pleura.” The evidence for tumor stage was described as “Based on the estimated pT category (T2a) and pN category (N0), the tumor stage is determined to be Stage IB according to AJCC7 criteria.” It shows that ChatGPT extracted relevant information from the note and correctly inferred the pT category based on the AJCC guideline (Supplementary Fig. 1 ) and the extracted information.

a TCGA-98-A53A. An example of a scanned pathological report (left panel) and ChatGPT output and interpretation (right panel). All estimations and support evidence are consistent with the pathologist’s evaluations. b The GPT model correctly inferred pT as T2a based on the tumor’s size and involvement according to AJCC guidelines.

In another more complex case, TCGA-50-6590 (Fig. 4b ), ChatGPT correctly inferred pT as T2a based on both the tumor’s size and location according to AJCC guidelines. Case TCGA-44-2656 demonstrates a more challenging scenario (Supplementary Fig. 2 ), where the report only contains some factual data without specifying pT, pN, and tumor stage. However, ChatGPT was able to infer the correct classifications based on the reported facts and provide proper supporting evidence.

Error analysis

To understand the types and potential reasons for misclassifications, we performed a detailed error analysis by looking into individual attributes and cases where ChatGPT made mistakes, the results of which are summarized below.

Primary tumor feature (pT) classification

In total, 768 cases with valid reports and reference values in the testing data were used to evaluate the classification performance of pT. Among them, 15 cases were reported with unknown or empty output by ChatGPT, making the coverage rate 0.97. For the remaining 753 cases, 12.6% of pT was misclassified. Among these misclassification cases, the majority were T1 misclassified as T2 (67 out of 753 or 8.9%) or T3 misclassified as T2 (12 out of 753, or 1.6%).

In most cases, ChatGPT extracted the correct tumor size information but used an incorrect rule to distinguish pT categories. For example, in the case TCGA-22-4609 (Fig. 5a ), ChatGPT stated, “Based on the tumor size of 2.0 cm, it falls within the range of T2 category according to AJCC 7th edition for lung carcinoma staging manual.” However, according to the AJCC 7 th edition staging guidelines for lung cancer, if the tumor is more than 2 cm but less than 3 cm in greatest dimension and does not invade nearby structures, pT should be classified as T1b. Therefore, ChatGPT correctly extracted the maximum tumor dimension of 2 cm but incorrectly interpreted this as meeting the criteria for classification as T2. Similarly, for case TCGA-85-A4JB, ChatGPT incorrectly claimed, “Based on the tumor size of 10 cm, the estimated pT category is T2 according to AJCC 7th edition for lung carcinoma staging manual.” According to the AJCC 7 th edition staging guidelines, a tumor more than 7 cm in greatest dimension should be classified as T3.

a TCGA-22-4609 illustrates a typical case where the GPT model uses a false rule, which is incorrect by AJCC guideline. b Case TCGA-39-5028 shows a complex case where there exist two tumors and the GPT model only capture one of them. c Case TCGA-39-5016 reveals a case where the GPT model made a mistake for getting confused with domain terminology.

Another challenging situation arose when multiple tumor nodules were identified within the lung. In the case of TCGA-39-5028 (Fig. 5b ), two separate tumor nodules were identified: one in the right upper lobe measuring 2.1 cm in greatest dimension and one in the right lower lobe measuring 6.6 cm in greatest dimension. According to the AJCC 7 th edition guidelines, the presence of separate tumor nodules in a different ipsilateral lobe results in a classification of T4. However, ChatGPT classified this case as T2a, stating, “The pathology report states the tumor’s greatest diameter as 2.1 cm”. This classification would be appropriated if the right upper lobe nodule were a single isolated tumor. However, ChatGPT failed to consider the presence of the second, larger nodule in the right lower lobe when determining the pT classification.

Regional lymph node involvement (pN)

The classification performance of pN was evaluated using 753 cases with valid reports and reference values in the testing data. Among them, 27 cases were reported with unknown or empty output by ChatGPT, making the coverage rate 0.94. For the remaining 726 cases, 8.5% of pN was misclassified. Most of these misclassification cases were N1 misclassified as N2 (32 cases). The AJCC 7th edition staging guidelines use the anatomic locations of positive lymph nodes to determine N1 vs. N2. However, most of the misclassification cases were caused by ChatGPT interpreting the number of positive nodes rather than the locations of the positive nodes. One such example is the case TCGA-85-6798. The report states, “Lymph nodes: 2/16 positive for metastasis (Hilar 2/16)”. Positive hilar lymph nodes correspond to N1 classification according to AJCC 7th edition guidelines. However, ChatGPT misclassifies this case as N2, stating, “The pathology report states that 2 out of 16 lymph nodes are positive for metastasis. Based on this information, the pN category can be estimated as N2 according to AJCC 7th edition for lung carcinoma staging manual.” This interpretation is incorrect, as the number of positive lymph nodes is not part of the criteria used to determine pN status according to AJCC 7th edition guidelines. The model misinterpreted pN2 predictions in 22 cases due to similar false assertions.

In some cases, the ChatGPT model made classification mistakes by misunderstanding the locations’ terminology. Figure 5c shows a case (TCGA-39-5016) where the ChatGPT model recognized that “6/9 peribronchial lymph nodes involved, “ corresponding with classification as N1, but ChatGPT misclassified this case as N2. By AJCC 7th edition guidelines, N2 is defined as “Metastasis in ipsilateral mediastinal and/or subcarinal lymph node(s)”. The ChatGPT model did not fully understand that terminology and made misclassifications.

Pathology tumor stage

The overall tumor stage classification performance was evaluated using 744 cases with valid reports and reference values as stage I, II and III in the testing data. Among them, 18 cases were reported as unknown or empty output by ChatGPT making the coverage rate as 0.94. For the remaining 726 cases, 23.6% of the overall stage was misclassified. Since the overall stage depends on individual pT and pN stages, the mistakes could come from misclassification of pT or pN (error propagation) or applying incorrect inference rules to determine the overall stage from pT and pN (incorrect rules). Looking into the 56 cases where ChatGPT misclassified stage II as stage III, 22 cases were due to error propagation, and 34 were due to incorrect rules. Figure 6a shows an example of error propagation (TCGA-MP-A4TK). ChatGPT misclassified the pT stage from T2a to T3, and then this mistake led to the incorrect classification of stage IIA to stage IIIA. Figure 6b illustrates a case (TCGA-49-4505) where ChatGPT made correct estimation of pT and pN but made false prediction about tumor stage by using a false rule. Among the 34 cases affected by incorrect rules, ChatGPT mistakenly inferred tumor stage as stage III for 26 cases where pT is T3 and pN is N0, respectively. For example, for case TCGA-55-7994, ChatGPT provided the evidence as “Based on the estimated pT category (T3) and pN category (N0), the tumor stage is determined to be Stage IIIA according to AJCC7 criteria”. According to AJCC7, tumors with T3 and N0 should be classified as stage IIB. Similarly, error analysis for other tumor stages shows that misclassifications come from both error propagation and applying false rules.

a Case TCGA-MP-A4TK: An example of typical errors GPT made in the experiments, i.e. GPT took false rule and further led to faulty propagation. b Case TCGA-49-4505: The GPT model made false estimation of Stage IIIA with a false rule, although it made correct inference with T2b and N1.

Histological diagnosis

The classification performance of histology diagnosis was evaluated using 762 cases with valid reports and reference values in the testing data. Among them, 17 cases were reported as either unknown or empty output by ChatGPT, making the coverage rate 0.96. For the remaining 745 cases, 6 ( < 1%) of histology types were misclassified. Among the mistakes that ChatGPT made for histology diagnosis, ChatGPT misclassified 3 of them as “other” type and 3 cases of actual “other” type (neither adenocarcinomas nor squamous cell carcinomas) as 2 adenocarcinomas and 1 squamous cell carcinoma. In TCGA-22-5485, two tumors exist: one squamous cell carcinoma and another adenocarcinoma, which should be classified as the ‘other’ type. However, ChatGPT only identified and extracted information for one tumor. In the case TCGA-33-AASB, which is the “other” type of histology, ChatGPT captured the key information and gave it as evidence: “The pathology report states the histologic diagnosis as infiltrating poorly differentiated non-small cell carcinoma with both squamous and glandular features”. However, it mistakenly estimated this case as “adenocarcinoma”. In another case (TCGA-86-8668) of adenocarcinoma, ChatGPT again captured key information and stated as evidence, “The pathology report states the histologic diagnosis as Bronchiolo-alveolar carcinoma, mucinous” but could not tell it is a subtype of adenocarcinoma. Both cases reveal that ChatGPT still has limitations in the specific domain knowledge in lung cancer pathology and the capability of correcting understanding its terminology.

Analyzing irregularities

The initial model evaluation and prompt-response review uncovered irregular scenarios: the original pathology reports may be blank, poorly scanned, or simply missing report forms. We reviewed how ChatGPT responded to these anomalies. First, when a report was blank, the prompt contained only the instruction part. ChatGPT failed to recognize this situation in most cases and inappropriately generated a fabricated case. Our experiments showed that, with the temperature set at 0 for blank reports, ChatGPT converged to a consistent, hallucinated response. Second, for nearly blank reports with a few random characters and poorly scanned reports, ChatGPT consistently converged to the same response with increased variance as noise increased. In some cases, ChatGPT responded appropriately to all required attributes but with unknown values for missing information. Last, among the 15 missing report forms in a small dataset, ChatGPT responded “unknown” as expected in only 5 cases, with the remaining 10 still converging to the hallucinated response.

Reproducibility evaluation

Since ChatGPT models (even with the same version) evolve over time, it is important to evaluate the stability and reproducibility of ChatGPT. For this purpose, we conducted experiments with the same model (“gpt-3.5-turbo-0301”), the same data, prompt, and settings (e.g., temperature = 0) twice in early April and the middle of May of 2023. The rate of equivalence between ChatGPT estimations in April and May on key attributes of interest (pT, pN, tumor stage, and histological diagnosis) is 0.913. The mean absolute error between certainty degrees in the two experiments is 0.051. Considering the evolutionary nature of ChatGPT models, we regard an output difference to a certain extent as reasonable and the overall ChatGPT 3.5 model as stable.

Comparison with other NLP methods

In order to have a clear perspective on how ChatGPT’s performance stands relative to established methods, we conducted a comparative analysis of the results generated by ChatGPT with two established methods: a keyword search algorithm and a deep learning-based Named Entity Recognition (NER) method.

Data selection and annotation

Since the keyword search and NER methods do not support zero-shot learning and require human annotations on the entity level, we carefully annotated our dataset for these traditional NLP methods. We used the same training and testing datasets as in the prompt engineering for ChatGPT. The training dataset underwent meticulous annotation by experienced medical professionals, adhering to the AJCC7 standards. This annotation process involved identifying and highlighting all relevant entities and text spans related to stage, histology, pN, and pT attributes. The detailed annotation process for the 78 cases required a few weeks of full-time work from medical professionals.

Keyword search algorithm using wordpiece tokenizer

For the keyword search algorithm, we employed the WordPiece tokenizer to segment words into subwords. We compiled an annotated entity dictionary from the training dataset. To assess the performance of this method, we calculated span similarities between the extracted spans in the validation and testing datasets and the entries in the dictionary.

Named Entity Recognition (NER) classification algorithm

For the NER classification algorithm, we designed a multi-label span classification model. This model utilized the pre-trained Bio_ClinicalBERT as its backbone. To adapt it for multi-label classification, we introduced an additional linear layer. The model underwent fine-tuning for 1000 epochs using the stochastic gradient descent (SGD) optimizer. The model exhibiting the highest overall F1 score on the validation dataset was selected as the final model for further evaluation in the testing dataset.

Performance evaluation

We evaluated the performance of both the keyword search and NER methods on the testing dataset. We summarized the predicted entities/spans and their corresponding labels. In cases where multiple related entities were identified for a specific category, we selected the most severe entities as the final prediction. Moreover, we inferred the stage information for corpora lacking explicit staging information by aggregating details from pN, pT, and diagnosis, aligning with the AJCC7 protocol. The overall predictions for stage, diagnosis, pN, and pT were compared against the ground truth table to gauge the accuracy and effectiveness of our methods. The results (Supplementary Table S1 ) show that the ChatGPT outperforms WordPiece tokenizer and NER Classifier. The average accuracy for ChatGPT, WordPiece tokenizer, and NER Classifier are 0.89, 0.51, and 0.76, respectively.

Prompt engineering process and results

Prompt design is a heuristic search process with many elements to consider, thus having a significantly large design space. We conducted many experiments to explore better prompts. Here, we share a few typical prompts and the performance of these prompts in the training data set to demonstrate our prompt engineering process.

Output format

The most straightforward prompt without special design would be: “read the pathology report and answer what are pT, pN, tumor stage, and histological diagnosis”. However, this simple prompt would make ChatGPT produce unstructured answers varying in format, terminology, and granularity across the large number of pathology reports. For example, ChatGPT may output pT as “T2” or “pT2NOMx”, and it outputs histological diagnosis as “Multifocal invasive moderately differentiated non-keratinizing squamous cell carcinoma”. The free-text answers will require a significant human workload to clean and process the output from ChatGPT. To solve this problem, we used a multiple choice answer format to force ChatGPT to pick standardized values for some attributes. For example, for pT, ChatGPT could only provide the following outputs: “T0, Tis, T1, T1a, T1b, T2, T2a, T2b, T3, T4, TX, Unknown”. For the histologic diagnosis, ChatGPT could provide output in one of these categories: Lung Adenocarcinoma, Lung Squamous Cell Carcinoma, Other, Unknown. In addition, we added the instruction, “Please make sure to output the whole set of answers together as a single JSON file, and don’t output anything beyond the required JSON file,” to emphasize the requirement for the output format. These requests in the prompt make the downstream analysis of ChatGPT output much more efficient. In order to know the certainty degree of ChatGPT’s estimate and the evidence, we asked ChatGPT to provide the following 4 outputs for each attribute/variable: extracted value as stated in the pathology report, estimated value based on AJCC 7th edition for lung carcinoma staging manual, the certainty degree of the estimation, and the supporting evidence for the estimation. The classification accuracy of this prompt with multiple choice output format (prompt v1) in our training data could achieve 0.854.

Evidence-based inference

One of the major concerns for LLM is that the results from the model are not supported by any evidence, especially when there is not enough information for specific questions. In order to reduce this problem, we emphasize the use of evidence for inference in the prompt by adding this instruction to ChatGPT: “Please ensure to make valid inferences for attribute estimation based on evidence. If there is no available evidence provided to make an estimation, please answer the value as “Unknown.” In addition, we asked ChatGPT to “Include “comment” as the last key of the JSON file.” After adding these two instructions (prompt v2), the performance of the classification in the training data increased to 0.865.

Chain of thought prompting by asking intermediate questions

Although tumor size is not a primary interest for diagnosis and clinical research, it plays a critical role in classifying the pT stage. We hypothesize that if ChatGPT pays closer attention to tumor size, it will have better classification performance. Therefore, we added an instruction in the prompt (prompt v3) to ask ChatGPT to estimate: “tumor size max_dimension: [<the greatest dimension of tumor in Centimeters (cm)>, ‘Unknown’]” as one of the attributes. After this modification, the performance of the classification in the training data increased to 0.90.

Providing examples

Providing examples is an effective way for humans to learn, and it should have similar effects for ChatGPT. We provided a specific example to infer the overall stage based on pT and pN by adding this instruction: “Please estimate the tumor stage category based on your estimated pT category and pN category and use AJCC7 criteria. For example, if pT is estimated as T2a and pN as N0, without information showing distant metastasis, then by AJCC7 criteria, the tumor stage is “Stage IB”.” After this modification (prompt v4), the performance of the classification in the training data increased to 0.936.

Although we can further refine and improve prompts, we decided to use prompt v4 as the final model and apply it to the testing data and get the final classification accuracy of 0.89 in the testing data.

ChatGPT-4 performance

LLM evolves rapidly and OpenAI just released the newest GPT-4 Turbo model (GPT-4-1106-preview) in November 2023. To compare this new model with GPT-3.5-Turbo, we applied this newest GPT model GPT-4-1106 to analyze all the lung cancer pathology notes in the testing data. The classification result and the comparison with the GPT-3.5-Turbo-16k are summarized in Supplementary Table 1 . The results show that GPT-4-turbo performs better in almost every aspect; overall, the GPT-4-turbo model increases performance by over 5%. However, GPT-4-Turbo is much more expensive than GPT-3.5-Turbo. The performance of GPT-3.5-Turbo-16k is still comparable and acceptable. As such, this study mainly focuses on assessing GPT-3.5-Turbo-16k, but highlights the fast development and promise of using LLM to extract structured data from clinical notes.

Analyzing osteosarcoma data

To demonstrate the broader application of this method beyond lung cancer, we collected and analyzed clinical notes from pediatric osteosarcoma patients. Osteosarcoma, the most common type of bone cancer in children and adolescents, has seen no substantial improvement in patient outcomes for the past few decades 18 . Histology grades and margin status are among the most important prognostic factors for osteosarcoma. We collected pathology reports from 191 osteosarcoma cases (approved by UTSW IRB #STU 012018-061). Out of these, 148 cases had histology grade information, and 81 had margin status information; these cases were used to evaluate the performance of the GPT-3.5-Turbo-16K model and our prompt engineering strategy. Final diagnoses on grade and margin were manually reviewed and curated by human experts, and these diagnoses were used to assess ChatGPT’s performance. All notes were de-identified prior to analysis. We applied the same prompt engineering strategy to extract grade and margin information from these osteosarcoma pathology reports. This analysis was conducted on our institution’s private Azure OpenAI platform, using the GPT-3.5-Turbo-16K model (version 0613), the same model used for lung cancer cases. ChatGPT accurately classified both grades (with a 98.6% accuracy rate) and margin status (100% accuracy), as shown in Supplementary Fig. 3 . In addition, Supplementary Fig. 4 details a specific case, illustrating how ChatGPT identifies grades and margin status from osteosarcoma pathology reports.

Since ChatGPT’s release in November 2022, it has spurred many potential innovative applications in healthcare 19 , 20 , 21 , 22 , 23 . To our knowledge, this is among the first reports of an end-to-end data science workflow for prompt engineering, using, and rigorously evaluating ChatGPT in its capacity of batch-processing information extraction tasks on large-scale clinical report data.

The main obstacle to developing traditional medical NLP algorithms is the limited availability of annotated data and the costs for new human annotations. To overcome these hurdles, particularly in integrating problem-specific information and domain knowledge with LLMs’ task-agnostic general knowledge, Augmented Language Models (ALMs) 24 , which incorporate reasoning and external tools for interaction with the environment, are emerging. Research shows that in-context learning (most influentially, few-shot prompting) can complement LLMs with task-specific knowledge to perform downstream tasks effectively 24 , 25 . In-context learning is an approach of training through instruction or light tutorial with a few examples (so called few-shot prompting; well instruction without any example is called 0-shot prompting) rather than fine-tuning or computing-intensive training, which adjusts model weights. This approach has become a dominant method for using LLMs in real-world problem-solving 24 , 25 , 26 . The advent of ALMs promises to revolutionize almost every aspect of human society, including the medical and healthcare domains, altering how we live, work, and communicate. Our study shows the feasibility of using ChatGPT to extract data from free text without extensive task-specific human annotation and model training.

In medical data extraction, our study has demonstrated the advantages of adopting ChatGPT over traditional methods in terms of cost-effectiveness and efficiency. Traditional approaches often require labor-intensive annotation processes that may take weeks and months from medical professionals, while ChatGPT models can be fine-tuned for data extraction within days, significantly reducing the time investment required for implementation. Moreover, our economic analysis revealed the cost savings associated with using ChatGPT, with processing over 900 pathology reports incurring a minimal monetary cost (less than $10 using GPT 3.5 Turbo and less than $30 using GPT-4 Turbo). This finding underscores the potential benefits of incorporating ChatGPT into medical data extraction workflows, not only for its time efficiency but also for its cost-effectiveness, making it a compelling option for medical institutions and researchers seeking to streamline their data extraction processes without compromising accuracy or quality.

A critical requirement for effectively utilizing an LLM is crafting a high-quality “prompt” to instruct the LLM, which has led to the emergence of an important methodology referred to as “prompt engineering.” Two fundamental principles guide this process: firstly, the provision of appropriate context, and secondly, delivering clear instructions about subtasks and the requirements for the desired response and how it should be presented. For a single query for one-time use, the user can experiment with and revise the prompt within the conversation session until a satisfactory answer is obtained. However, prompt design can become more complex when handling repetitive tasks over many input data files using the OpenAI API. In these instances, a prompt must be designed according to a given data feed while maintaining the generality and coverage for various input data features. In this study, we found that providing clear guidance on the output format, emphasizing evidence-based inference, providing chain of thought prompting by asking for tumor size information, and providing specific examples are critical in improving the efficiency and accuracy of extracting structured data from the free-text pathology reports. The approach employed in this study effectively leverages the OpenAI API for batch queries of ChatGPT services across a large set of tasks with similar input data structures, including but not limited to pathology reports and EHR.

Our evaluation results show that the ChatGPT (gpt-3.5-turbo-16k) achieved an overall average accuracy of 89% in extracting and estimating lung cancer staging information and histology subtypes compared to pathologist-curated data. This performance is very promising because some scanned pathology reports included in this study contained random characters, missing parts, typos, varied formats, and divergent information sections. ChatGPT also outperformed traditional NLP methods. Our case analysis shows that most misclassifications were due to a lack of knowledge of detailed pathology terminology or very specialized information in the current versions of ChatGPT models, which could be avoided with future model training or fine-tuning with more domain-specific knowledge.

While our experiments reveal ChatGPT’s strengths, they also underscore its limitations and potential risks, the most significant being the occasional “hallucination” phenomenon 27 , 28 , where the generated content is not faithful to the provided source content. For example, the responses to blank or near-blank reports reflect this issue, though these instances can be detected and corrected due to convergence towards an “attractor”.

The phenomenon of ‘hallucination’ in LLMs presents a significant challenge in the field. It is important to consider several key factors to effectively address the challenges and risks associated with ChatGPT’s application in medicine. Since the output of an LLM depends on both the model and the prompt, mitigating hallucination can be achieved through improvements in GPT models and prompting strategies. From a model perspective, model architecture, robust training, and fine-tuning on a diverse and comprehensive medical dataset, emphasizing accurate labeling and classification, can reduce misclassifications. Additionally, enhancing LLMs’ comprehension of medical terminology and guidelines by incorporating feedback from healthcare professionals during training and through Reinforcement Learning from Human Feedback (RLHF) can further diminish hallucinations. Regarding prompt engineering strategies, a crucial method is to prompt the GPT model with a ‘chain of thought’ and request an explanation with the evidence used in the reasoning. Further improvements could include explicitly requesting evidence from input data (e.g., the pathology report) and inference rules (e.g., AJCC rules). Prompting GPT models to respond with ‘Unknown’ when information is insufficient for making assertions, providing relevant context in the prompt, or using ‘embedding’ of relevant text to narrow down the semantic subspace can also be effective. Harnessing hallucination is an ongoing challenge in AI research, with various methods being explored 5 , 27 . For example, a recent study proposed “SelfCheckGPT” approach to fact-check black-box models 29 . Developing real-time error detection mechanisms is crucial for enhancing the reliability and trustworthiness of AI models. More research is needed to evaluate the extent, impacts, and potential solutions of using LLMs in clinical research and care.

When considering using ChatGPT and similar LLMs in healthcare, it’s important to thoughtfully consider the privacy implications. The sensitivity of medical data, governed by rigorous regulations like HIPAA, naturally raises concerns when integrating technologies like LLMs. Although it is a less concern to analyze public available de-identified data, like the lung cancer pathology notes used in this study, careful considerations are needed for secured healthcare data. More secured OpenAI services are offered by OpenAI security portal, claimed to be compliant to multiple regulation standards, and Microsoft Azure OpenAI, claimed could be used in a HIPAA-compliant manner. For example, de-identified Osteosarcoma pathology notes were analyzed by Microsoft Azure OpenAI covered by the Business Associate Agreement in this study. In addition, exploring options such as private versions of these APIs, or even developing LLMs within a secure healthcare IT environment, might offer good alternatives. Moreover, implementing strong data anonymization protocols and conducting regular security checks could further protect patient information. As we navigate these advancements, it’s crucial to continuously reassess and adapt appropriate privacy strategies, ensuring that the integration of AI into healthcare is both beneficial and responsible.

Despite these challenges, this study demonstrates our effective methodology in “prompt engineering”. It presents a general framework for using ChatGPT’s API in batch queries to process large volumes of pathology reports for structured information extraction and estimation. The application of ChatGPT in interpreting clinical notes holds substantial promise in transforming how healthcare professionals and patients utilize these crucial documents. By generating concise, accurate, and comprehensible summaries, ChatGPT could significantly enhance the effectiveness and efficiency of extracting structured information from unstructured clinical texts, ultimately leading to more efficient clinical research and improved patient care.

In conclusion, ChatGPT and other LLMs are powerful tools, not just for pathology report processing but also for the broader digital transformation of healthcare documents. These models can catalyze the utilization of the rich historical archives of medical practice, thereby creating robust resources for future research.

Data processing, workflow, and prompt engineering

The lung cancer data we used for this study are publicly accessible via CDSA ( https://cancer.digitalslidearchive.org/ ) and TCGA ( https://cBioPortal.org ), and they are de-identified data. The institutional review board at the University of Texas Southwestern Medical Center has approved this study where patient consent was waived for using retrospective, de-identified electronic health record data.

We aimed to leverage ChatGPT to extract and estimate structured data from these notes. Figure 7a displays our process. First, scanned pathology reports in PDF format were downloaded from TCGA and CDSA databases. Second, R package pdftools, an optical character recognition tool, was employed to convert scanned PDF files into text format. After this conversion, we identified reports with near-empty content, poor scanning quality, or missing report forms, and those cases were excluded from the study. Third, the OpenAI API was used to analyze the text data and extract structured data elements based on specific prompts. In addition, we extracted case identifiers and metadata items from the TCGA metadata file, which was used to evaluate the model performance.

a Illustration of the use of OpenAI API for batch queries of ChatGPT service, applied to a substantial volume of clinical notes — pathology reports in our study. b A general framework for integrating ChatGPT into real-world applications.

In this study, we implemented a problem-solving framework rooted in data science workflow and systems engineering principles, as depicted in Fig. 7b . An important step is the spiral approach 30 to ‘prompt engineering’, which involves experimenting with subtasks, different phrasings, contexts, format specifications, and example outputs to improve the quality and relevance of the model’s responses. It was an iterative process to achieve the desired results. For the prompt engineering, we first define the objective: to extract information on TNM staging and histology type as structured attributes from the unstructured pathology reports. Second, we assigned specific tasks to ChatGPT, including estimating the targeted attributes, evaluating certainty levels, identifying key evidence of each attribute estimation, and generating a summary as output. The output was compiled into a JSON file. In this process, clinicians were actively formulating questions and evaluating the results.

Our study used the “gpt-3.5-turbo” model, accessible via the OpenAI API. The model incorporates 175 billion parameters and was trained on various public and authorized documents, demonstrating specific Artificial General Intelligence (AGI) capabilities 5 . Each of our queries sent to ChatGPT service is a “text completion” 31 , which can be implemented as a single round chat completion. All LLMs have limited context windows, constraining the input length of a query. Therefore, lengthy pathology reports combined with the prompt and ChatGPT’s response might exceed this limit. We used OpenAI’s “tiktoken” Python library to estimate the token count to ensure compliance. This constraint has been largely relaxed by the newly released GPT models with much larger context windows. We illustrate the pseudocode for batch ChatGPT queries on a large pathology report set in Supplementary Fig. 5 .

Model evaluation

We evaluated the performance of ChatGPT by comparing its output with expert-curated data elements provided in the TCGA structured data using the testing data set. Some staging records in the TCGA structured data needed to be updated; our physicians curated and updated those records. To mimic a real-world setting, we processed all reports regardless of data quality to collect model responses. For performance evaluation, we only used valid reports providing meaningful text and excluded the reports with near-empty content, poor scanning quality, and missing report forms, which were reported as irregular cases. We assessed the classification accuracy, F1, Kappa, recall, and precision for each attribute of interest, including pT, pN, overall stage, and histology types, and presented results as accuracy and confusion matrices. Missing data were excluded from the accuracy evaluation, and the coverage rate was reported for predicted values as ‘unknown’ or empty output.

Reporting summary

Further information on research design is available in the Nature Research Reporting Summary linked to this article.

Data availability

The lung cancer dataset we used for this study is “Pan-Lung Cancer (TCGA, Nat Genet2016)”, ( https://www.cbioportal.org/study/summary?id=nsclc_tcga_broad_2016 ) and the “luad” and “lusc” subsets from CDSA ( https://cancer.digitalslidearchive.org/ ). We have provided a reference regarding how to access the data 32 . We utilized the provided APIs to retrieve clinical information and pathology reports for the LUAD (lung adenocarcinoma) and LUSC (lung squamous cell carcinoma) cohorts. The pediatric data are the EHR data from UTSW clinic services. The data is available from the corresponding author upon reasonable request and IRB approval.

Code availability

All codes used in this paper were developed using APIs from OpenAI. The prompt for the API is available in Fig. 2 . Method-specific code is available from the corresponding author upon request.

Vaswani, A. et al. Attention is all you need. Adv. Neural Info. Processing Syst. 30 , (2017).

Devlin, J. et al. Bert: Pre-training of deep bidirectional transformers for language understanding . arXiv preprint arXiv:1810.04805, 2018.

Radford, A. et al. Improving language understanding by generative pre-training . OpenAI: https://cdn.openai.com/research-covers/language-unsupervised/language_understanding_paper.pdf (2018).

Touvron, H. et al. LLaMA: Open and efficient foundation language models . arXiv preprint arXiv:2302.13971 (2023).

OpenAi, GPT-4 Technical Report . arXiv:2303.08774: https://arxiv.org/pdf/2303.08774.pdf (2023).

Anil, R. et al. Palm 2 technical report . arXiv preprint arXiv:2305.10403 (2023).

Turner, B. E. W. Epic, Microsoft bring GPT-4 to EHRs .

Landi, H. Microsoft’s Nuance integrates OpenAI’s GPT-4 into voice-enabled medical scribe software .

Hao, T. et al. Health Natural Language Processing: Methodology Development and Applications. JMIR Med Inf. 9 , e23898 (2021).

Article   Google Scholar  

Pathak, J., Kho, A. N. & Denny, J. C. Electronic health records-driven phenotyping: challenges, recent advances, and perspectives. J. Am. Med. Inform. Assoc. 20 , e206–e211 (2013).

Article   PubMed   PubMed Central   Google Scholar  

Crichton, G. et al. A neural network multi-task learning approach to biomedical named entity recognition. BMC Bioinforma. 18 , 368 (2017).

Wang, J. et al. Document-Level Biomedical Relation Extraction Using Graph Convolutional Network and Multihead Attention: Algorithm Development and Validation. JMIR Med Inf. 8 , e17638 (2020).

Liu, Y. et al. Roberta: A robustly optimized BERT pretraining approach . arXiv preprint arXiv:1907.11692 (2019).

Rasmy, L. et al. Med-BERT: pretrained contextualized embeddings on large-scale structured electronic health records for disease prediction. npj Digit. Med. 4 , 86 (2021).

Wu, H. et al. A survey on clinical natural language processing in the United Kingdom from 2007 to 2022. npj Digit. Med. 5 , 186 (2022).

Amin, M. B. et al. AJCC cancer staging manual . 1024: Springer 2017.

Goldstraw, P. et al. The IASLC Lung Cancer Staging Project: Proposals for the Revision of the TNM Stage Groupings in the Forthcoming (Seventh) Edition of the TNM Classification of Malignant Tumours. J. Thorac. Oncol. 2 , 706–714 (2007).

Article   PubMed   Google Scholar  

Yang, D. M. et al. Osteosarcoma Explorer: A Data Commons With Clinical, Genomic, Protein, and Tissue Imaging Data for Osteosarcoma Research. JCO Clin. Cancer Inform. 7 , e2300104 (2023).

The Lancet Digital, H., ChatGPT: friend or foe? Lancet Digital Health . 5 , e102 (2023).

Nature, Will ChatGPT transform healthcare? Nat. Med. 29 , 505–506 (2023).

Patel, S. B. & Lam, K. ChatGPT: the future of discharge summaries? Lancet Digit. Health 5 , e107–e108 (2023).

Article   CAS   PubMed   Google Scholar  

Ali, S. R. et al. Using ChatGPT to write patient clinic letters. Lancet Digit. Health 5 , e179–e181 (2023).

Howard, A., Hope, W. & Gerada, A. ChatGPT and antimicrobial advice: the end of the consulting infection doctor? Lancet Infect. Dis. 23 , 405–406 (2023).

Mialon, G. et al. Augmented language models: a survey . arXiv preprint arXiv:2302.07842 (2023).

Brown, T. et al. Language Models are Few-Shot Learners . Curran Associates, Inc. (2020).

Wei, J. et al. Chain of thought prompting elicits reasoning in large language models . Adv Neural Inf Processing Syst 35 , 24824–24837 (2022).

Ji, Z. et al. Survey of Hallucination in Natural Language Generation. ACM Comput. Surv. 55 , 1–38 (2023).

Alkaissi, H. & S. I. McFarlane, Artificial Hallucinations in ChatGPT: Implications in Scientific Writing. Cureus , (2023).

Manakul, P. A. Liusie, & M. J. F. Gales, SelfCheckGPT: Zero-Resource Black-Box Hallucination Detection for Generative Large Language Models . 2023.

Boehm, B. W. A spiral model of software development and enhancement. Computer 21 , 61–72 (1988).

OpenAi. OpenAI API Documentation . Available from: https://platform.openai.com/docs/guides/text-generation .

Gao, J. et al. Integrative analysis of complex cancer genomics and clinical profiles using the cBioPortal. Sci. Signal. 6 , 1–19 (2013).

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Acknowledgements

This work was partially supported by the National Institutes of Health [P50CA70907, R35GM136375, R01GM140012, R01GM141519, R01DE030656, U01CA249245, and U01AI169298], and the Cancer Prevention and Research Institute of Texas [RP230330 and RP180805].

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Jingwei Huang, Donghan M. Yang, Ruichen Rong, Kuroush Nezafati, Colin Treager, Shidan Wang, Xian Cheng, Yujia Guo, Guanghua Xiao, Xiaowei Zhan & Yang Xie

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Contributions

J.H., Y.X., X.Z. and G.X. designed the study. X.Z., K.N., C.T. and J.H. prepared, labeled, and curated lung cancer datasets. D.M.Y., X.C., Y.G., L.J.K. prepared, labeled, and curated osteosarcoma datasets. Z.C. provided critical inputs as pathologists. Y.X., G.X., E.P. provided critical inputs for the study. J.H. implemented experiments with ChatGPT. R.R. and K.N. implemented experiments with N.L.P. J.H., Y.X., G.X. and S.W. conducted data analysis. Y.X., G.X., J.H., X.Z., D.M.Y. and R.R. wrote the manuscript. All co-authors read and commented on the manuscript.

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Correspondence to Xiaowei Zhan or Yang Xie .

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Huang, J., Yang, D.M., Rong, R. et al. A critical assessment of using ChatGPT for extracting structured data from clinical notes. npj Digit. Med. 7 , 106 (2024). https://doi.org/10.1038/s41746-024-01079-8

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Enabling reliable usability assessment and comparative analysis of medical software: a comprehensive framework for multimodal biomedical imaging platforms

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• Published: 01 May 2024

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• Elena Denisova 1 , 2 , 3 ,
• Eleonora Tiribilli 1 , 2 , 3 ,
• Alessio Luschi 1 ,
• Piergiorgio Francia 1 ,
• Leonardo Manetti 2 , 3 ,
• Leonardo Bocchi 1 , 3 &
• Ernesto Iadanza   ORCID: orcid.org/0000-0002-7291-4990 4  

A literature review reveals that, at the moment, all usability tests for Software as a Medical Device (SaMD) are designed in compliance with international standards but it also reveals a lack of formalization in the implementation and administration of such usability tests, which prevents the comparison of results from different tests for the same class of SaMD. This study aims to provide a reproducible usability testing framework for SaMD to establish a standardized protocol which can ensure repeatability and comparisons of similar SaMD for the visualization of medical images and data.

The devised protocol aligns with international standards and literature recommendations for usability and human factors engineering. It encompasses participant selection, testing environments, equipment setup for various testing methods (HDMI vs. wireless), and hardware interfaces (keyboard/mouse vs. touchscreen), as well as the roles of the required testers. The protocol consists of two distinct sections: exploratory tasks and specific scenarios, to assess software functions and real-life tasks, respectively. Effectiveness and efficiency are evaluated using video analysis and a custom Stopwatch software, while user satisfaction is measured through post-test questionnaires.

The usability testing protocol was applied to a Multimodal Biomedical Imaging Platform All-in-One software developed by Imaginalis S.r.l. (Sesto Fiorentino, Italy) for validation. The results of the usability testing protocol applied to the case-study software demonstrate good values of software’s effectiveness and efficiency, along with user satisfaction supporting the prior heuristic evaluation. The outcomes confirm the robustness, applicability, and reproducibility of the usability testing protocol, aligning with best practices.

Conclusions

The proposed usability testing framework enables reliable usability assessment and comparative analysis of medical software. Furthermore, the obtained results can serve as a reference for assessing other biomedical imaging platforms under development or ready for release.

Avoid common mistakes on your manuscript.

1 Introduction

In healthcare systems, new technologies and medical devices (MDs) have become more significant during the latter part of the last century [ 1 ]. The increasing use of MDs contributed to the improvement of health care and its quality, leading to new requirements regarding their characteristics and safety. In this sense, the usability of MDs gained interest, making the adoption of standards such as IEC 62366-1:2015 [ 2 ] essential for new products released in the market. As a consequence, usability is now part of the whole risk management process and is systematically considered and evaluated in the design, construction and implementation of MDs. The content of standards and scientific literature dealing with usability shows that the concept of usability is widespread [ 3 ].

Among standards addressing usability, UNI EN ISO 26800:2011 describes ergonomic principles for interfaces to improve safety, performance and usability by analysing the target audience, environment, goals, and expected results [ 4 ]. EN ISO 9241-11:2018 provides a framework for understanding the concept of usability and applying it to situations where people use interactive systems, other types of systems (including built environments), products (including industrial and consumer products), and services (including technical and personal services). The standard describes usability as “the extent to which a system, product, or service can be used by specified users to achieve specified goals with effectiveness, efficiency, and satisfaction in a specified context of use” [ 5 ]. Finally, EN ISO 25066:2019 addresses various usability testing approaches such as inspection and heuristics review of the interface, tests and post-market surveys [ 6 ]. The term usability is, therefore, very broad, and additional features to the list of ISO parameters are included in the scientific literature, such as ease of use, learnability, flexibility, attitude, and memorability [ 7 ], considered very important in promoting positive outcomes for both healthcare professionals and patients [ 3 ].

Given the complexity of MD usability issues across sectors, disciplines such as Human Factors Engineering (HFE) actually study the topic. HFE addresses the user interface in addition to the design of tools, machines, and systems, by taking into account human capabilities, limitations, and characteristics [ 8 ]. The goal is to ensure safe, comfortable, and effective use. Ergonomics, usability engineering, and user-centred design are considered synonyms [ 9 ]. The elements that influence user experience, especially in the use of medical software, need to be studied extensively because the way people perceive and use informatics tools can affect how well they understand the data and the outcomes of the analysis [ 10 , 11 ]. Because of this, it is becoming more crucial to research the usability of medical software because a poorly made or designed interface might be challenging to use and lead to mistakes when using it [ 12 ]. Problems affecting medical device interfaces can also be the cause of recalls due to software interface errors. In this sense, interface usability testing is a highly-effective methodology for identifying usage errors and barriers, as well as a practical method for improving the efficacy and efficiency of products, services and systems [ 13 ].

Usability testing can be performed during the development stage to reduce errors and optimize the design. Furthermore, testing can be repeated after the product has been distributed, allowing for a prompt identification of problems, and highlighting critical issues [ 14 ]. Conducting usability evaluations can face numerous obstacles, such as the lack of adequate and validated guidelines [ 15 ] and clear indications of the environment, parameters, data type, and team characteristics. Moreover, the costs associated with evaluating the usability of MDs can be a major limitation. The description of the current context related to usability testing shows that there is an urgent need to define a systematic method to design a cost-effective usability validation procedure.

Zhang et al. [ 16 ] modified the existing heuristic evaluation method for software usability evaluation, applying it to medical devices, and using it to evaluate the patient safety of the device by identifying and evaluating usability problems. Shin and Lee [ 17 ] proposed a method to design and implement a time-cost effective test procedure for a comprehensive usability validation test by selecting the scenario with the lowest time–cost, starting from an activity diagram based on uFMEA (Use Failure Mode and Effects Analysis). Quality Function Deployment (QFD) is a structured approach to defining customer needs or requirements and translating them into specific plans to produce products to meet those needs. Despite being more suited to different kinds of analysis [ 18 ], it may also be used as a tool to develop usability evaluation models. However, using the QFD methodology has limitations, being not a procedure that searches for the optimal solution, but rather a technique designed to match designers’ and users’ needs in designing a product. Moreover, the QFD methodology is insufficient to understand the correlations among the physical design factors of a product, which is indeed a crucial outcome of usability tests [ 19 ].

The literature review reveals that, at the moment, all usability tests for Software as a Medical Device (SaMD) are designed in compliance with international standards or with few changes to the protocol, as described by Zhang et al. [ 16 ]. The review also reveals a lack of formalization in the implementation and administration of such usability tests, preventing the comparison of results from different tests for the same class of SaMD. The scope of this study is to provide a reproducible usability testing protocol for medical software to ensure repeatability and comparisons of similar SaMD for visualising medical images and data.

The developed protocol was applied to a Multimodal Biomedical Imaging Platform All-in-One, designed by Imaginalis S.r.l. (Sesto Fiorentino, Italy) with different users tested in a real-life scenario. To ensure the reproducibility of the testing protocol, custom software was designed and developed for recording and calculating test results (see Section  2.5 ).

2 Materials and methods

The Graphic User Interface (GUI) of the tested software allows users to view medical data, images, and other relevant information. The designed protocol admits only two modalities for mirroring the screen during the test: cabled (via High-Definition Multimedia Interface - HDMI connection) or wireless. These modalities are available on all possible devices on which the tested SaMD can be installed regardless of its type: workstations, laptops, and tablets. These modalities are mandatory and cannot be changed to reduce variability and ensure the reproducibility of the testing protocol. Therefore, the machine on which the SaMD is installed must have an Operative System (OS) that supports display mirroring and at least one HDMI port or a stable WiFi connection.

According to the IEC 62366-1:2015 [ 2 ], the goal of usability testing is reducing risks. However, for this specific scope, the fastest access to all basic functionalities and overall user satisfaction was identified as the main goal beyond the evaluation of the risks. Moreover, the usability test may also reveal missing useful functionalities in the current release of the software [ 20 ] which were not detected with analytical approaches.

2.1 The multimodal biomedical imaging platform

The platform under testing is intended for pre-, post-, and intra-operative usage in the human and veterinary fields. Despite the imaging platform supports the visualization of any DICOM (Digital Imaging and COmmunications in Medicine) image, it was mainly developed to satisfy the needs of orthopaedics, and, therefore, is mainly focused on Computed Tomography (CT), fluoroscopy, and radiography. However, at the moment of preparing the first iteration of the usability testing procedure, the CT modality was the one with the highest level of readiness, leading us to limit the tasks in the administered tests, as described in this work, to CT acquisitions only. The proposed software provides a three-dimensional (3D) representation of the CT volumetric data, including Multiplanar Reformation (MPR) and 3D volumetric reconstruction views (see Fig.  1 ). The basic controls (zoom, pan, rotation, and scroll) enable the series navigation. The MPR functionalities include image enhancement, colour inversion, slab thickness control, annotation and measurement, histogram window control, and intensity presets. 3D functionalities cover different volume crop and rendering modes, auto-play, transfer functions control, and preset saving. Moreover, advanced functionalities such as compare, surgical planning, and multislice viewing are supported.

Multimodal Biomedical Imaging Platform All-in-One

The set of proposed functionalities is based on the interview of a large group of orthopaedics, radiologists, and veterinaries. Additionally, the imaging software systems already present in the market were analysed. The GUI was developed according to Gestalt visual design principles. Moreover, the law that predicts the time taken to acquire a target (Fitts) and the human choice-reaction time (Hick-Human) were taken into account.

After completing the first proposal of the GUI design, the method of heuristic evaluation proposed by Zhang was applied. The result of the evaluation was analysed and the requested modifications and fixes were implemented. The heuristic evaluation process was repeated until only minor issues remained. At that point, the development was suspended and the current version of the software was used for usability testing.

2.2 Participants

The complexity of the software and the environment in which it is meant to be utilized determine the optimal number of participants. According to research [ 21 , 22 , 23 ], between three and twenty people can yield trustworthy results, with five to ten being a good start. Generally speaking, a higher number of testers is needed for more difficult, risky initiatives, but fewer participants are needed to test more creative ideas. Following these considerations, twelve volunteers were recruited to compose the testing population.

2.3 Environment

According to the above-mentioned requirements, only two modalities are allowed for mirroring the screen during the administration of the usability test: HDMI cable and wireless. In both modalities, the testing occurred in person.

2.3.1 HDMI testing

The environment for the HDMI test consisted of two adjacent rooms: one room designated as the test room and a second one as the observation room (see Fig.  2 ).

Test Environment Scheme

The chosen rooms were adjacent to allow an HDMI cable to be passed through. That enabled the duplication of the test machine screen on the monitor of the observer (see Section  2.4 ). As a precaution, the test machine was not connected to the Internet, while superfluous operative system processes were suspended to avoid compromising software productivity (see Appendix A ).

2.3.2 Wireless testing

For wireless testing, no external cable was needed for mirroring, as a Google Meet session was set up on the same machine where the tested software was installed to share the screen. In this scenario, the superfluous operative system processes were not suspended, to evaluate their impact on the performance of the SaMD during the test.

2.4 Test conductors

The testing procedures require a minimum set of two people for conducting the test:

Moderator : in charge of managing the progress of the test; responsible not only for administering the tasks, but also for observing the user’s facial expressions, resolving any problems, and answering the possible questions arising during the session;

Observer : responsible for reporting the user’s performance of the tasks, tracking down the time taken to perform each task, and leaving comments on eventual issues and user’s difficulties. In specific cases, when reporting the task performance while taking notes may result complicated, the presence of more than one Observer can be useful.

Optionally, a third person (namely the Recorder ) can be involved. The Recorder observes and analyses the footage coming from the camera which frames the user from the entire scene’s perspective during the test. In the absence of this third person, the footage recorded with the external camera can still be analysed after the conclusion of the test.

2.5 Equipment

A list of tools needed for carrying out a usability test for both HDMI and wireless modalities for touchscreen and mouse/keyboard configuration was defined in Appendix A . The settings for the different modalities/configurations are quite similar and are described in Tables A.1 and A.2 .

Custom Stopwatch software was developed to ease the observer’s tasks. The software is developed in C/C++ and the source code has been made publicly available at https://github.com/eletiri93/Stopwatch . The software enables the observer to record the amount of time spent on each task during the usability test while also noting any noteworthy user behavior: the GUI shows the current task, a stopwatch, and a space for taking notes. On the right side of the screen, a table summarises the recorded times and notes. After the completion of each task, the observer is able to export a CSV (Comma Separated Values) file containing the recorded times and notes.

2.6 Exploratory tasks and specific scenarios

Based on the experience acquired during the heuristics evaluation, the list of 55 exploratory tasks (see Appendix F ) was produced. The objective was to ensure that participants did not become overly fatigued, while covering all of the most crucial capabilities within realistic time constraints. The tasks had to be clear, short, and as independent as possible (e.g., the failure of one task should not compromise the success of the following tasks). Moreover, four specific scenarios were developed with the help of an external radiologist consultant (see Appendix G ). The exploratory tasks and specific scenarios can be modified to allow the testing protocol to be tailored to the specific application and the provided functionalities of the tested software.

2.7 Test evaluation

Tests were evaluated in terms of effectiveness, efficiency, and user satisfaction. The first two parameters were evaluated with the aid of a purposely developed Stopwatch software, notes taken by the Observer, and a camera footage. User satisfaction was evaluated by using a post-test questionnaire administered at the end of each test session.

More specifically, the effectiveness evaluates the participant’s capacity to finish each suggested task, independent of the amount of time required. It is evaluated through the following score system:

Score: 1. Failure. The user fails to complete the task, despite some suggestions

Score: 2. Partial success. The task is partially completed or completed after suggestions

Score: 3. Complete success. The task is completed without any difficulties or suggestions

On the other hand, the efficiency measures how fast each participant completes each assignment and is evaluated by timing the performance of each task. The above-mentioned Stopwatch software was used to record timestamps. The recorded value corresponds to the time interval between the end of the reading of the task by the moderator, and the moment when the user asserts the completion of the task.

Finally, scores given to each of the statements proposed in the post-test questionnaire were analysed to assess user satisfaction. The agreement scale was used, where 5 represented the fully agree and 1 represented strongly disagree options. All statements were designed to have consistent meanings (e.g., “The software is intuitive to use”, “I had no problem using the basic features”).

For comparison purposes, it is important to evaluate only the functionalities common to all thecompared SaMD. This enables a direct comparison of effectiveness and efficiency, task by task, and scenario by scenario. It is also crucial for assessing the user satisfaction evaluation: if the tasks and scenarios differ between the assessed SaMD, user satisfaction may be higher for the simpler test suite and lower for the specific and innovative features tested. However, the methods for comparing similar SaMD using the proposed testing protocol are beyond the scope of this paper.

2.8 Statistical analysis

Efficiency, effectiveness, and user satisfaction variables’ distribution were tested using the Shapiro-Wilk test. The variables were statistically described as mean ± standard deviation (SD) for normally distributed quantitative data; median and interquartile range (IQR) for non-normally distributed data; frequency count and percentage for qualitative data. The difference between the groups of participants and the hardware modalities was evaluated using the independent t-test for normally distributed quantitative variables and the Mann-Whitney test for non-normally distributed quantitative variables. The relationship between efficiency, effectiveness, and user satisfaction was tested with the Spearman test. When a significant difference was detected, Cohen’s d (for normal distribution) or Cliff’s delta (for non-normal distribution) was calculated as a measure of the difference. The significance level for all tests was set to 0.05 ( \(p < 0.05\) ).

2.9 Pilot testing

Three weeks before the test administrations, the Pilot Test in touchscreen mode was carried out to validate the proposed test method, as well as the above-described environment, equipment, and tasks. Four persons were involved in the pilot test administration: a moderator, two observers, and a user. The observers prepared all the necessary environment and equipment, while the moderator made sure that all the procedures were followed correctly. The pilot test was very useful, as it uncovered some task-related issues, such as the duration of some of them or the used lexicon.

2.10 Testing procedure

After the administration of the pilot test and its further analysis, the final testing procedure was set up. Before the participant arrived, the moderator and the observers verified the instrumentation, making sure that nothing was missing or abnormally working by using a dedicated checklist (see Appendix B ). A single testing session performed by one user took about 1.5 h and consisted of the following steps:

Introduction to the test, including the software description and the desirable goals (about 5 mins). See Appendix C

Signing of the recording agreement (about 2 mins). See Appendix E

Compilation of the pre-test questionnaire (about 5 mins). See Appendix D

Execution of exploratory tasks (45-50 mins). See Appendix F

Specific scenarios (10-15 mins). See Appendix G

Compilation of the post-test questionnaire, including user’s feedback (10-15 mins). See Appendix H

Figure  3 illustrates the entire workflow of the testing protocol as described in this section.

The flow chart of the proposed testing protocol illustrates the sequence of steps to perform before testing (I), during testing (II), and after testing (III). Dashed-border boxes represent the steps that could be repeated more than once

Tests were conducted from October 12, 2022, to November 24, 2022. Figure  4 illustrates the environment and equipment configuration.

Test Environment & Equipment Setup

According to the observations, done in Section  2.2 , twelve users were recruited for the testing. Six of the participants had a clinical background, and six had an engineering background (see the detailed distribution of the sample of users in Fig.  5 ). Seven tests were conducted via HDMI connection and five using Google Meet. Ten tests were administrated in touchscreen modality, while the remaining two were administrated using a mouse/keyboard.

Pretest questionnaire results. Distribution of test samples in terms of gender ( a ), experience ( b ), frequency of use of medical software ( c ), approach to new technologies ( d ), and professions ( e )

The statistical analysis of the participants did not reveal any significant differences between the groups of engineers and clinicians. Only two explorative tasks showed a significant difference in the efficiency (task 6 with Cliff’s \(\delta = -0.6944\) , and task 33 with Cliff’s \(\delta = -1\) ). One task showed a significant difference in the efficiency between the two modalities (HDMI vs. wireless - test 7 with Cliff’s \(\delta = -0.8857\) ), and one showed a significant difference, again on the efficiency only, between mouse/keyboard vs. touchscreen (task 19 with Cliff’s \(\delta = -1\) ). Consequently, the results of all participants were combined for evaluation. Data collected during the pilot test was not included in the analysis, as the final version of the protocol was edited afterwards due to the subsequent considerations.

Figure  6 shows the statistical description of the effectiveness as frequency count and percentage for each explorative task, while Fig.  7 shows the statistical description of the efficiency for each task in terms of median and IQR. Figure  8 presents effectiveness and efficiency for the specific scenarios.

Effectiveness for explorative tasks, evaluated as frequency count and percentage obtained for each task

Efficiency evaluation for explorative tasks. In the graph, the box represents the IQR, spanning from the 25th to the 75th percentile. Higher IQRs suggest significant variability in the time taken to complete the task. Smaller IQRs with medians (red line inside the box) close to the bottom indicate tasks completed very quickly. Outliers are denoted as (+)

Effectiveness and efficiency evaluation for specific scenarios. Effectiveness: frequency count and percentage. Efficiency: median, IQR, range, and outliers

Figure  9 reports the statistical description of user satisfaction as frequency count and percentage for each assessing question.

Post-test questionnaire. Responses in a range from 1 to 5, were evaluated as frequency count and percentage obtained for each question

The statistical analysis of efficiency and effectiveness indicated a statistically significant negative monotonic relationship ( \(\rho = -0.658495\) , see Figs.  10 and  11 ), while no statistically significant relationship with satisfaction was found. Two outliers were detected.

Top to bottom: effectiveness in terms of success percentage; efficiency in terms of overall time spent. Two outliers were detected

Correlation between effectiveness and efficiency. Each point on the scatter plot represents the relationship between effectiveness (y-coordinate) and efficiency (x-coordinate), providing a visual representation of the distribution and spread of data and confirming the presence of two outliers

At the end of testing, user feedback was collected to improve the existing functionalities in future software updates.

4 Discussion

A number of considerations were made at the end of the first usability testing iteration.

As demonstrated in Section  3 , the analysis of the two environmental testing modes (HDMI and wireless) revealed no significant variations. This suggests that any of the two modes can be chosen for testing, based on hardware specifications and the preferences of the test conductors. Furthermore, the results highlight that the suspension of superfluous operating system processes on the test machine has no impact on the performance of the software and the test suite, and it is therefore discretionary.

Remote testing may allow a larger group of participants while obtaining similar results as those performed in-person [ 24 , 25 ], but it shows some limitations and drawbacks. The main challenge of remote testing consists of the participants being in charge of the whole environment and equipment set-up, which may lead to an unwanted and unexpected set of problems. Another issue which might be faced are the possible different time zones for the participants and the test conductors. Due to these reasons, the developed usability protocol takes into consideration only in-person testing, minimizing the sources of variability that remote testing could introduce, thus improving its reproducibility and consistency.

It is worth noting, that the test description and the terminology used can greatly influence the success (or failure) of the test results. It is indeed very important to carefully formulate the tests and the tasks, asking, when possible, for the help of an external specialised end user for implementing the appropriate terminology and lexicon.

The results show that none of the participants from the selected testing group chooses to learn a new technology by reading the technical documentation.

Overall, the results for user satisfaction showed that the tested software was deemed intuitive to use and that the majority of users believed that it could improve their work. Users did not encounter any difficulties using basic features in the mouse/keyboard or in the touchscreen configuration. However, the vast majority of them reported the need for initial support in the software usage. The touchscreen was preferred by the majority of involved users.

The results also highlight that statistically significant differences emerged only on the efficiency of four exploratory tasks: engineers were faster in performing tasks 6 and 33, task 7 was completed faster with HDMI compared to the wireless setting, and task 19 was completed more quickly with mouse than with touchscreen. This aspect underlines that, together with the HDMI modality and the mouse configuration, the academic background/profession is the only personal feature among the analysed five users (Fig.  5 ) that can slightly influence the performance of the test in terms of time. Finding no significant differences in the effectiveness points out that the successful completion of each task is not related to any personal background or administration modality. Therefore, the effectiveness outcomes of the tested software reveal that some specific tasks (e.g., task no. 7, 12, 22, 24) actually shed light on possible weak points of the GUI. Moreover, the statistical analysis of efficiency and effectiveness indicated a statistically significant negative monotonic relationship, which suggests that as more time passes during task execution, the probability of successfully completing the task decreases.

5 Conclusion

This work presents a usability study on medical imaging software, focusing on the Multimodal Biomedical Imaging Platform All-in-One by Imaginalis S.r.l., compliant with the DICOM standard. The article provides a formal protocol for repeatable analysis, allowing for comparison of tests on similar SaMD for the visualization of medical images and data.

The protocol adheres to international standards, covering participant selection, testing environment setup, minimum number of required testers, as well as their roles and specific assignments, equipment requirements for HDMI and wireless modalities, and hardware interfaces (keyboard/mouse, touchscreen). The usability test comprises exploratory tasks and specific scenarios for evaluating software functions in real-life tasks.

Results were evaluated in terms of effectiveness, efficiency, and user satisfaction. The study validates the initial heuristic evaluation of the GUI, confirming the protocol’s robustness, applicability, and reproducibility, aligned with best practices.

The exploratory tasks and specific scenarios are the only aspects of the proposed protocol that may need adjustment for different visualization SaMD. This is because different software may have varying functionalities.

Thus, the proposed usability testing framework enables reliable usability assessment and comparative analysis of medical software. Besides, the obtained results can serve as a reference for comparing biomedical imaging platforms under development or ready for release.

Availability of data and material

Test equipment, checklist, test introduction, pre-test questionnaire, record agreement, exploratory tasks, specific scenarios, and post-test questionnaire are provided as Supplementary Materials .

Code availability

Not applicable.

Pecchia L, Pallikarakis N, Magjarevic R, Iadanza E. Health technology assessment and biomedical engineering: global trends, gaps and opportunities. Med Eng Phys. 2019;72:19–26.

Article   Google Scholar  

ISO/TC 210. IEC 62366-1:2015. Medical devices — Part 1: Application of usability engineering to medical devices. 1st ed. International Organization for Standardization; 2015.

Formicola R, Amici C, Mor M, Bissolotti L, Borboni A. Design of medical devices with usability in mind: a theoretical proposal and experimental case study using the lepre device. Designs. 2023. https://doi.org/10.3390/designs7010009 .

ISO/TC 159/SC 1. EN ISO 26800:2011. Ergonomics - General approach, principles and concepts. 1st ed. International Organization for Standardization; 2011.

ISO/TC 159/SC 4. EN ISO 9241-11:2018. Ergonomics of human-system interaction - Part 11: Usability: Definitions and concepts. 2nd ed. International Organization for Standardization; 2018.

ISO/TC 159/SC 4. EN ISO/IEC 25066:2019. Systems and software engineering - Systems and software Quality Requirements and Evaluation (SQuaRE). 1st ed. International Organization for Standardization; 2019.

Shackel B. Usability – context, framework, definition, design and evaluation. Interact Comput. 2009;21(5–6):339–46. https://doi.org/10.1016/j.intcom.2009.04.007 .

Iadanza E. Clinical engineering handbook. 2nd ed. 2019. https://doi.org/10.1016/C2016-0-04298-5 .

Book   Google Scholar  

Gosbee J. Human factors engineering and patient safety. Qual Saf Health Care. 2003;11:352–4. https://doi.org/10.1136/qhc.11.4.352 .

Luschi A, Caltagirone L, Mondovecchio C, Miniati R, Iadanza E. Assessing the impact of a CIS/PACS technology for a cardiology department using QFD methodology. IFMBE Proceedings. 2016;57:965–8.

Iadanza E, Fabbri R, Luschi A, Melillo P, Simonelli F. A collaborative restful cloud-based tool for management of chromatic pupillometry in a clinical trial. Heal Technol. 2019;10:25–38.

Machado Paixão-Cortes VS, Dos Santos da Silva Tanus M, Paixão-Cortes WR, De Souza ON, De Borba Campos M, Silveira MS. Usability as the key factor to the design of a web server for the CREF protein structure predictor: the WCREF. Information. 2018. https://doi.org/10.3390/info9010020 .

Hass C. A practical guide to usability testing. Springer International Publishing; 2019, Ch. A Practical Guide to Usability Testing, p. 107–24.

Dumas JF. A practical guide to usability testing. Intellect Books; 1999.

Google Scholar  

Russ AL, Saleem JJ. Ten factors to consider when developing usability scenarios and tasks for health information technology. J Biomed Inform. 2018;78:123–33.

Zhang J, Johnson TR, VL Patel, Paige DL, Kubose T. Using usability heuristics to evaluate patient safety of medical devices. J Biomed Inform. 2003;36(1):23–30 Patient Safety.

Shin J, Lee H. Optimal usability test procedure generation for medical devices. Healthcare. 2023. https://doi.org/10.3390/healthcare11030296 .

Luschi A, Monti M, Iadanza E. Assisted reproductive technology center design with quality function deployment approach. IFMBE Proc. 2015;51:1587–90.

Jin B, Ji YG, Choi K, Cho G. Development of a usability evaluation framework with quality function deployment: from customer sensibility to product design. Hum Factors Ergon Manuf Serv Ind. 2009;19:177–94. https://doi.org/10.1002/hfm.20145 .

Markonis D, Holzer M, Baroz F, De Castaneda RLR, Boyer C, Langs G, Müller H. User-oriented evaluation of a medical image retrieval system for radiologists. Int J Med Informatics. 2015;84(10):774–83.

Virzi RA. Refining the test phase of usability evaluation: how many subjects is enough? Hum Factors. 1992;34:457–68.

Faulkner L. Beyond the five-user assumption: benefits of increased sample sizes in usability testing. Behav Res Methods Instrum Comput. 2003;35:379–83.

Turner C, Lewis J, Nielsen J. Determining usability test sample size, vol. 3. CRC Press; 2006, Ch. Determining Usability Test Sample Size, p. 3076–80.

Andreasen MS, Nielsen HV, Schrøder SO, Stage J. What happened to remote usability testing? an empirical study of three methods. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, CHI ’07. Association for Computing Machinery; 2007. p. 1405–14.

Brush AJB, Ames MG, Davis J. A comparison of synchronous remote and local usability studies for an expert interface. In: Dykstra-Erickson E, Manfred T. CHI ’04 Extended Abstracts on Human Factors in Computing Systems. New York: Association for Computing Machinery; 2004. pp. 1179–82.

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Acknowledgements

The authors would like to thank Laura Gatti for setting up the initial draft of the proposed protocol, and Alice Mati for designing the specific testing scenarios.

Open access funding provided by Università degli Studi di Siena within the CRUI-CARE Agreement.

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Elena Denisova, Eleonora Tiribilli, Alessio Luschi, Piergiorgio Francia & Leonardo Bocchi

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Elena Denisova, Eleonora Tiribilli & Leonardo Manetti

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Elena Denisova, Eleonora Tiribilli, Leonardo Manetti & Leonardo Bocchi

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Elena Denisova and Eleonora Tiribilli work for Imaginalis S.r.l. (Sesto Fiorentino, Italy) and are currently PhD candidates at the Department of Information Engineering at the University of Florence (Italy). Leonardo Manetti works for Imaginalis S.r.l. (Sesto Fiorentino, Italy). Leonardo Bocchi coordinates the joint lab “Eidolab”, between the Department of Information Engineering of the University of Florence and Imaginalis S.r.l. The other authors have no conflicts of interest.

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Denisova, E., Tiribilli, E., Luschi, A. et al. Enabling reliable usability assessment and comparative analysis of medical software: a comprehensive framework for multimodal biomedical imaging platforms. Health Technol. (2024). https://doi.org/10.1007/s12553-024-00859-2

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• AI-Based Training Tools: Customizes learning modules based on employees' learning styles and needs to improve their skill sets.
• AI-driven Customer Relationship Management (CRM): Personalizes customer interactions based on behavior and preferences, improving satisfaction.

Envision a work environment where you can accomplish routine tasks with incredible speed and increased accuracy . By learning and then performing repetitive work processes, AI dramatically reduces the occurrence of errors and accelerates the pace of completing tasks. Many AI tools, such as robotic process automation(RPA), intelligent virtual assistants (IVAs), and advanced analytics platforms, can handle routine tasks. These tools are reshaping traditional work methods, making them faster and more efficient.

Integrating AI doesn't mean it will replace you; rather, AI augments your ability to accomplish more. This technological shift liberates and enables you to focus your knowledge and skills on more mission-critical work.

Examples of what AI tools can do include:

• RPA Tools : These tools automate and streamline repetitive tasks such as managing databases and responding to common questions.
• Intelligent Assistants: Tools like Alexa for Business handle day-to-day tasks like scheduling and reminders, improving productivity.
• Analytics Platforms: Platforms like Microsoft Power BI and Tableau identify data patterns, providing strategic decision-making assistance.

Let's examine two cases where AI has significantly improved operational efficiency in different organizations.

Case Study 1: Health Care

A top US hospital has significantly reduced manual workloads by employing AI to handle administrative duties such as patient scheduling and insurance pre-authorization. This automation has facilitated administrative staff's shifting focus to more significant aspects of patient care, thus elevating their daily operation efficiency.

Case Study 2: Finance

A global bank utilized an AI-driven analytics tool for efficient data processing, drastically reducing decision-making times, enabling early detection of potential fraud, and safeguarding the institution and its clientele.

Improving Your Decision-Making

Decision-making is a part of every job, and with supporting data and insights, your decisions can positively impact your organization's business goals. However, with the sheer volume of data at your disposal, analyzing that data quickly and accurately is next to impossible, sometimes leaving you with no choice but to use your intuition and hope for the best. Conversely, AI can quickly look at large amounts of data and provide the insights you need to make data-driven decisions.

AI uses machine learning to analyze, discover, and understand patterns found in large datasets, providing actionable insights to help you make decisions. Some of the tools that can help with decision-making include:

• Pattern Recognition Tools: AI can sift through vast amounts of data to identify recurring trends or anomalies, offering valuable insights that might otherwise go unnoticed.
• Predictive Analytics: AI can leverage historical data to provide clear foresight into potential opportunities or risks.
• Natural Language Processing: AI can understand human language, allowing organizations to analyze customer sentiments from social media, emails, or customer reviews.
• Algorithmic Trading: AI algorithms can make highly accurate predictions about financial markets and execute trades quickly, reducing errors and ensuring better returns.
• People Analytics Tools: AI can analyze data and predict employee turnover, enhance employee engagement, help retain key talent, detect bias, and drive inclusive change.

Integrating these AI-driven analytic tools into your workflows allows you to streamline operations and make more effective and informed decisions, leading to increased profits and growth.

Let's look at two case studies that show how organizations have harnessed the power of AI to revamp and improve their decision-making process.

Case Study 1: Retail Inventory Management

A national supermarket chain used an AI model to address its inventory inefficiencies and waste. This model predicted demand using sales trends and external factors, optimizing stock levels and automating replenishment. The result was significant cost savings, improved customer satisfaction, and less waste, leading to an enhanced reputation for sustainability.

Case Study 2: Patient Care Streamlining

A large healthcare provider successfully integrated AI into its patient care system to improve patient outcomes. AI algorithms were employed to analyze patient data and assist in diagnosis. AI was able to interpret complex clinical data quickly, allowing doctors to make critical and accurate treatment decisions faster.

Increasing Innovation

Developing new ideas or ways of doing things can be challenging when repetitive or mundane tasks bog you down. Using AI to handle routine tasks and discover patterns and insights in large amounts of data will give you more time to think creatively and strategically to discover solutions to problems and create new or upgrade existing products and services.

Furthermore, AI doesn't just execute tasks; it also continuously learns and refines its approaches. AI learning promotes a virtuous circle of continuous improvement and innovation, as it helps you uncover new and more efficient ways of working.

There are many ways AI can help support creativity and innovation, including in areas such as:

• Product Development: AI can streamline product development by using AI algorithms to analyze customer feedback and identify what works and doesn't to refine existing products or develop new ones.
• Service Delivery: AI-powered chatbots and virtual assistants provide round-the-clock service and instant responses, increasing customer satisfaction.
• Data Analysis: AI can analyze vast amounts of data more accurately and recognize patterns that can lead to breakthroughs in various fields.
• Imagination and Creativity: AI can create everything from realistic video game environments to generating new recipes.

Let's delve into some case studies to illuminate AI's contribution to innovation.

Case Study 1: AI for Personalization

A large e-commerce organization harnessed the power of artificial intelligence to innovate personalized shopping experiences for millions of users. The site uses AI algorithms to analyze customer search and purchase history to offer customized product recommendations, improving the customer experience and increasing revenue.

Case Study 2: AI for Content Moderation

A social media organization uses AI technology to monitor and filter out inappropriate or harmful content, making the platform safer for its users. Through machine-learning models, AI can identify and remove such content faster than human moderators.

Enhancing Your Customers’ Experience

Your customers expect prompt and personalized service, and with the help of AI, you can meet and exceed these expectations by understanding and predicting customer behavior, providing tailored recommendations, and ensuring fast and efficient customer service around the clock.

AI-powered tools like chatbots and personalized recommendations are transforming customer service. Chatbots provide consistent, round-the-clock support, efficiently managing customer inquiries. Meanwhile, AI-generated personalized recommendations help organizations understand customer needs, enabling targeted marketing and boosting the overall customer experience.

Here are sector-specific instances demonstrating how AI optimizes customer interactions:

• In retail , AI-deployed recommendation engines can suggest products based on a customer's browsing and purchasing history.
• Chatbots in the banking industry can handle services 24/7, such as account inquiries and transaction details, and assist in opening new accounts.
• AI-powered software in the healthcare sector can offer patients advice on minor ailments and suggest treatment options.
• Travel and hospitality sectors leverage AI to provide personalized travel recommendations based on consumer preferences, providing a streamlined booking experience.

Like any other, your organization is focused on growth and operational efficiency to reduce costs and increase revenue. AI gives you the competitive edge to succeed in today’s marketplace by providing significant workplace benefits such as increased operational efficiency, improved decision-making, innovation, better customer experiences, and upskilling opportunities. Though integrating AI can appear daunting, viewing it as a beneficial tool can help you overcome these challenges. Equipping yourself and your organization with knowledge and skills enables you to leverage AI to its fullest potential and gain valuable insights that fuel your success.

Integrating AI into workflows might provoke employee apprehension, so it is crucial to openly discuss AI implementation and offer training and support to ensure employees have the skills to leverage AI's power best. Embrace AI, not as a foe or replacement but as a valuable collaborator, fostering smarter, faster, and more innovative ways for you to work.

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Computer Science > Distributed, Parallel, and Cluster Computing

Title: experiences porting distributed applications to asynchronous tasks: a multidimensional fft case-study.

Abstract: Parallel algorithms relying on synchronous parallelization libraries often experience adverse performance due to global synchronization barriers. Asynchronous many-task runtimes offer task futurization capabilities that minimize or remove the need for global synchronization barriers. This paper conducts a case study of the multidimensional Fast Fourier Transform to identify which applications will benefit from the asynchronous many-task model. Our basis is the popular FFTW library. We use the asynchronous many-task model HPX and a one-dimensional FFTW backend to implement multiple versions using different HPX features and highlight overheads and pitfalls during migration. Furthermore, we add an HPX threading backend to FFTW. The case study analyzes shared memory scaling properties between our HPX-based parallelization and FFTW with its pthreads, OpenMP, and HPX backends. The case study also compares FFTW's MPI+X backend to a purely HPX-based distributed implementation. The FFT application does not profit from asynchronous task execution. In contrast, enforcing task synchronization results in better cache performance and thus better runtime. Nonetheless, the HPX backend for FFTW is competitive with existing backends. Our distributed HPX implementation based on HPX collectives using MPI parcelport performs similarly to FFTW's MPI+OpenMP. However, the LCI parcelport of HPX accelerated communication up to a factor of 5.

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