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7 Powerful Problem-Solving Root Cause Analysis Tools

The first step to solving a problem is to define the problem precisely. It is the heart of problem-solving.

Root cause analysis is the second important element of problem-solving in quality management. The reason is if you don't know what the problem is, you can never solve the exact problem that is hurting the quality.

Manufacturers have a variety of problem-solving tools at hand. However, they need to know when to use which tool in a manner that is appropriate for the situation. In this article, we discuss 7 tools including:

• The Ishikawa Fishbone Diagram (IFD)
• Pareto Chart
• Failure Mode and Effects Analysis (FMEA)
• Scatter Diagram
• Affinity Diagram
• Fault Tree Analysis (FTA)

1. The Ishikawa Fishbone Diagram IFD

The model introduced by Ishikawa (also known as the fishbone diagram) is considered one of the most robust methods for conducting root cause analysis. This model uses the assessment of the 6Ms as a methodology for identifying the true or most probable root cause to determine corrective and preventive actions. The 6Ms include:

• Measurement,
• Mother Nature- i.e., Environment

Related Training: Fishbone Diagramming

2. Pareto Chart

The Pareto Chart is a series of bars whose heights reflect the frequency or impact of problems. On the Chart, bars are arranged in descending order of height from left to right, which means the categories represented by the tall bars on the left are relatively more frequent than those on the right.

Related Training: EFFECTIVE INVESTIGATIONS AND CORRECTIVE ACTIONS (CAPA) Establishing and resolving the root causes of deviations, problems and failures

This model uses the 5 Why by asking why 5 times to find the root cause of the problem. It generally takes five iterations of the questioning process to arrive at the root cause of the problem and that's why this model got its name as 5 Whys. But it is perfectly fine for a facilitator to ask less or more questions depending on the needs.

Related training: Accident/Incident Investigation and Root Cause Analysis

4. Failure Mode and Effects Analysis (FMEA)

FMEA is a technique used to identify process and product problems before they occur. It focuses on how and when a system will fail, not if it will fail. In this model, each failure mode is assessed for:

• Severity (S)
• Occurrence (O)
• Detection (D)

A combination of the three scores produces a risk priority number (RPN). The RPN is then provided a ranking system to prioritize which problem must gain more attention first.

Related Training: Failure Mode Effects Analysis

5. Scatter Diagram

A scatter diagram also known as a scatter plot is a graph in which the values of two variables are plotted along two axes, the pattern of the resulting points revealing any correlation present.

To use scatter plots in root cause analysis, an independent variable or suspected cause is plotted on the x-axis and the dependent variable (the effect) is plotted on the y-axis. If the pattern reflects a clear curve or line, it means they are correlated. If required, more sophisticated correlation analyses can be continued.

Related Training: Excel Charting Basics - Produce Professional-Looking Excel Charts

6. Affinity Diagram

Also known as KJ Diagram, this model is used to represent the structure of big and complex factors that impact a problem or a situation. It divides these factors into small classifications according to their similarity to assist in identifying the major causes of the problem.

7. Fault Tree Analysis (FTA)

The Fault Tree Analysis uses Boolean logic to arrive at the cause of a problem. It begins with a defined problem and works backward to identify what factors contributed to the problem using a graphical representation called the Fault Tree. It takes a top-down approach starting with the problem and evaluating the factors that caused the problem.

Finding the root cause isn't an easy because there is not always one root cause. You may have to repeat your experiment several times to arrive at it to eliminate the encountered problem. Using a scientific approach to solving problem works. So, its important to learn the several problem-solving tools and techniques at your fingertips so you can use the ones appropriate for different situations.

ComplianceOnline Trainings on Root Cause Analysis

P&PC, SPC/6Sigma, Failure Investigation, Root Cause Analysis, PDCA, DMAIC, A3 This webinar will define what are the US FDA's expectation for Production and Process Control / Product Realization, the use of statistical tehniques, 6 sigma, SPC, for establishing, controlling , and verifying the acceptability of process capability and product characteristics, product acceptance or validation and other studies. Non-conformance, OOS, deviations Failure Investigations, and Root Cause Analysis, PDCA, DMAIC, and similar project drivers to improvement, A# and similar dash boards.

Accident/Incident Investigation and Root Cause Analysis If a major workplace injury or illness occurred, what would you do? How would you properly investigate it? What could be done to prevent it from happening again? A properly executed accident/incident investigation drives to the root causes of the workplace accident to prevent a repeat occurrence. A good accident/incident investigation process includes identifying the investigation team, establishing/reviewing written procedures, identifying root causes and tracking of all safety hazards found to completion.

Root Cause Analysis - The Heart of Corrective Action This presentation will explain the importance of root cause analysis and how it fits into an effective corrective and preventive action system. It will cover where else in your quality management system root cause analysis can be used and will give examples of some of the techniques for doing an effective root cause analysis. Attendees will learn how root cause analysis can be used in process control.

Addressing Non-Conformances using Root Cause Analysis (RCA) RCA assumes that systems and events are interrelated. An action in one area triggers an action in another, and another, and so on. By tracing back these actions, you can discover where the issue started and how it grew into the problem you're now facing.

Risk Management Under ISO 14971 ISO 14971:2019 is the definitive standard for risk management for medical devices and IVDs. The standard lays out a comprehensive approach to managing risks in the life sciences. The course will discuss practical approaches to complying with the standard.

Introduction to Root Cause Investigation for CAPA If you have reoccurring problems showing up in your quality systems, your CAPA system is not effective and you have not performed an in-depth root cause analysis to be able to detect through proper problem solving tools and quality data sources, the true root cause of your problem. Unless you can get to the true root cause of a failure, nonconformity, defect or other undesirable situation, your CAPA system will not be successful.

Root Cause Analysis and CAPA Controls for a Compliant Quality System In this CAPA webinar, learn various regulations governing Corrective and Preventive Actions (CAPA) and how organization should collect information, analyze information, identify, investigate product and quality problems, and take appropriate and effective corrective and/or preventive action to prevent their recurrence.

How to Design and Implement a Dynamic Control Plan This webinar training will discuss how to design a dynamic control plan that combines FMEA and the control plan by extending the FMEA to encompass the elements of the control plan and create a living document that helps to drive continual improvement.

An Easy to Implement Integrated Risk Management Approach Compliant with ISO 14971 This integrated risk management training for medical devices will discuss how to incorporate risk management as per ISO 14971 guidelines in all phases of medical device development. It will highlight the documentation needed to support the decisions made as part of the risk management process.

The Use and Mis-use of FMEA in Medical Device Risk Management The presentation will discuss the proper use of FMEA in risk management and how to recognize and avoid the traps associated with this tool in order to have a more efficient risk management process. Most medical device manufacturers use FMEA as a part of their risk management system. Most medical device manufacturers use FMEA as a part of their risk management system.

Root Cause Analysis for CAPA Management (Shutting Down the Alligator Farm) Emphasis will be placed on realizing system interactions and cultural environment that often lies at the root of the problem and prevents true root cause analysis. This webinar will benefit any organization that wants to improve the effectiveness of their CAPA and failure investigation processes.

Root Cause Analysis for Corrective and Preventive Action (CAPA) The Quality Systems Regulation (21 CFR 820) and the Quality Management Standard for Medical Devices (ISO 13485:2003), require medical device companies to establish and maintain procedures for implementing corrective and preventive action (CAPA) as an integral part of the quality system.

Strategies for an Effective Root Cause Analysis and CAPA Program This webinar will provide valuable assistance to all regulated companies, a CAPA program is a requirement across the Medical Device, Diagnostic, Pharmaceutical, and Biologics fields. This session will discuss the importance, requirements, and elements of a root cause-based CAPA program, as well as detailing the most effective ways to determine root cause and describing the uses of CAPA data.

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Problem Solving

– Methodologies and Techniques –

⇓   Introduction to Problem Solving

⇓   What is Problem Solving

⇓   Problem Solving Services

⇓   Learn More About Problem Solving

Introduction to Problem Solving

In the current world market, consumers and organizations have a vast amount of choices regarding the brand or manufacturer of products, parts and materials available to them. In order to not merely survive but thrive in this ever increasingly competitive market, an organization must provide the most value and the highest quality possible. Most organizations have effective quality systems in place. Unfortunately, we cannot always prevent or detect problems before they reach the customer.  Whether your customer is a Tier 1 automotive manufacturer or the end user, problems sometimes occur. Even the companies held up as benchmarks for quality in their industry eventually encounter problems with their product or process. The most important factors at that time are how timely and effectively the problem is resolved and prevented from re-occurring.  Problems happen so we must be skillful and systematic in resolving the problems as they arise.

What is Problem Solving

Problem Solving is the process undertaken to find solutions to complex or difficult issues by taking an analytical approach using scientific methods. Effective problem solving requires the issue to be recognized and fully understood by the problem solver(s). Then, various problem solving methods and tools can be used to drive down to the root cause of the issue and take appropriate corrective actions to not only fix the problem, but to ensure it does not re-occur. Recurring problems are expensive, drive down brand equity and can damage the supplier / customer relationship. Customers could determine that your organization is not capable of resolving problems within your products or processes. There are many problem solving tools and approaches that are all effective if used properly. The following is a sample list with a brief description of each method.

5 Why is a problem solving method that asks the question “Why” enough times until you get down to the root cause of a problem. The 5 Why exercise can be used as a stand- alone tool or applied within a larger problem solving activity. 5 Why is commonly used during the Analyze phase of the DMAIC process and the Plan phase of the PDCA process. The responses should be based on facts or data and should focus on process or systems errors. The facilitator should ask the team if the cause identified were corrected, could the failure mode or problem still occur. If the answer is yes, then move on to the second “Why” and then the third, fourth, fifth and so on until the answer is no.

Eight Disciplines of Problem Solving (8D)

Eight Disciplines of Problem Solving (8D) is a detailed problem solving method primarily used within the automotive industry but has more recently been utilized by other industries. 8D is typically a team exercise utilized mainly by quality engineers or managers and other professionals. The 8D approach employs statistical analysis of the process and stresses the importance of determining the root causes of the problem.  The basic elements of the 8D method are to identify the problem, form a team, determine root causes, develop corrective actions, both interim and permanent, and ultimately, to prevent the problem from reoccurring. It is also an effective tool for use during product and process improvement initiatives.

The A3 Report has its roots in the PDCA method.  The A3 Report format is an effective tool for communicating all pertinent information with greater visual impact. A3 gained its name from the size of paper used during the exercise. By literally writing and drawing it all out on one sheet, it clearly communicates what is being done at each step of the problem solving activity improving team communication. The A3 format is a valuable problem solving and critical thinking tool that can foster continuous improvement.

Corrective Action Preventive Action (CAPA)

Corrective Action Preventive Action (CAPA) is usually part of an overall Quality Management System (QMS) . The Corrective / Preventive Action process is generally a documented procedure used to collect and analyze information, identify any non-conformances and take appropriate action (corrective or preventive) to resolve problems and prevent recurrence. The CAPA process closely follows the PDCA methodology of Plan, Do, Check, Act.  The use of data to drive actions is prevalent in most CAPA systems. In some cases, Statistical Process Control (SPC) data is incorporated into the process.  Corrective actions are directed at eliminating known causes of failure or other product or process issues. Preventive actions are derived from structured risk analysis and focused on eliminating the cause of a potential failure.

Is / Is Not

The Is / Is Not tool is adaptable in that it can be used as a stand-alone problem solving tool or by establishing boundaries during a larger problem solving activity using one of the methodologies discussed above. It may be used to define the problem and determine the scope of what will be considered and what will not be considered during the problem solving exercise. The Is / Is Not simply asks the questions about the problem and determines what the problem is and is not. For example, a manufacturer starts getting feedback from their dealers of a particular problem. By entering the answers to the questions in a basic diagram, you can identify the scope of the problem and then determine where to apply resources and focus on the real problem.

The Is / Is Not tool produces results by allowing you to focus on the facts of the problem, and specifically on the boundaries created by determining what is and is not involved. Your team can then focus their efforts and attention on the likely causes and take action.

Plan Do Check Act (PDCA)

Plan-Do-Check-Act (PDCA) is also sometimes referred to as the Shewert circle is an excellent method for problem solving or continuous improvement. The basics of the PDCA cycle are to Plan or identify the problem. Do or perform a process study or root cause analysis to determine cause and potential improvements. Check or measure the results of the corrective action or improvement. And then Act, take action based upon the results of the study. The PDCA is not a straight line but a circle or cycle. Once the actions have been validated then use the knowledge acquired to plan additional improvements and begin the cycle again.

No matter which method you select, they all have some basic steps in common. The problem must be defined, the root causes identified, effective temporary and permanent countermeasures put in place, the results measured, monitored and validated. Through this process, you can resolve a problem and prevent recurrence.  While problem solving methods are valuable tools in your quality toolbox, some of them can be applied to a product or process before a failure occurs or during a continuous improvement initiative (i.e. Kaizen ). By using these tools, a potential failure may be foreseen, analyzed, and actions can be taken to prevent the failure from ever occurring. Tools such as Failure Modes and Effects Analysis (FMEA) , both Design FMEA and Process FMEA , can be utilized to reduce the likelihood of failures occurring.

Problem Solving Services

At Quality-One, we offer many services directed at helping you resolve any current problems or prevent problems from occurring. Our experienced team of highly trained professionals will provide a customized approach for developing your people and processes based on your unique problem solving needs. At Quality-One our services include:

• Consulting to provide assistance or guidance in developing a plan to deploy a new problem solving initiative
• Training to help your teams understand and drive improvement
• Support in building and implementing your selected problem solving process, which may include Facilitation, Auditing and / or Contract Services

Learn More About Problem Solving

Quality-One offers Quality and Reliability Support for Product and Process Development through Consulting, Training and Project Support. Quality-One provides Knowledge, Guidance and Direction in Quality and Reliability activities, tailored to your unique wants, needs and desires. Let us help you Discover the Value of Problem Solving Consulting, Problem Solving Training or Problem Solving Project Support.

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Solving quality issues and problems: go beyond root cause to ‘real’ cause.

There is a tendency in the quality management field to confuse the root cause of a problem with the problem’s real cause. A root cause is objective evidence of a quality problem. The real cause of a quality problem, however, is the actual finding or nonconformance .

Uncovering real causes of quality issues and problems requires different, deeper scrutiny than identifying root causes. Mistaking one for the other can lead to the perpetuation of cycles such as this one:

• A severe quality problem occurs at a production facility after a change is made.
• A team of stakeholders and possibly consultants convene to investigate the problem.
• A root cause is found.
• A corrective action / preventive action (CAPA) is implemented.
• The problem goes away.
• When another change occurs, the cycle repeats itself with a different yet related issue.

If you’re a quality professional who has been with the same organization for multiple years, this recursive pattern is likely to sound familiar. When multiple change-related root causes arise, it soon becomes evident that they are symptomatic of a deeper-seated cause.

Six Real Causes of Quality Issues Problems

In his foundational book on management audits, Allan Sayle concluded that there are just six real causes of all quality problems. (1) For each of the six causes, Sayle outlined specific sub-cause indicators, the identification of which can enable an auditor to properly assign a real cause for a quality problem. Attributing a quality problem to one or more of the sub-causes listed below can help your company identify the real cause and devise a change to mitigate or eliminate it.

#1. Lack of Organization

• Undetermined responsibilities and authorities (i.e., confusion about who is supposed to perform and be responsible for specific jobs that result in a product that is fit for purpose).
• Undefined management systems (i.e., the methods and means of communication between departments and individuals doesn’t form a complete and continuous chain).
• Inadequate communication, especially as it pertains to information generated by a particular department that is needed by specialists.

#2. Lack of Training  

• Personnel are not trained in the systems/methods in place or are not told with whom they are supposed to interface.
• Inadequate company training (e.g., managers produce and distribute a quality assurance manual but users aren’t trained on its contents).

#3. Lack of Discipline

• Workers follow bad examples set by supervisors and managers.
• Quality campaigns do not extend across the enterprise and subsequently build up frictions, become demotivators, and lead to disillusionment.
• Personal attributes that prevent employees from following the agreed upon methods.
• Inflexible systems that stifle innovation, quick thinking, and human problem-solving creativity.
• Demotivating environments.

#4. Lack of Resources

• Overly complex management systems that drain valuable resources.
• Irresponsible attitudes (i.e., resources are always completely used up in proportion with their allocation).
• Uneven allocation.
• Unrealistic estimates.
• Inadequate reinvestment (e.g., resource allocations are based on previous years’ budgets without taking market changes into account).
• Failure to modernize and seek potential applications for new technologies.

#5. Lack of Time

• Overly complex systems that waste time and/or create needless tasks.
• Irresponsible attitudes (e.g., personnel whose work always expands to fill the allotted time).
• Unrealistic commitments that are promised to customers without consideration for the time it takes to properly deliver a quality product.
• Selfishness that increasingly piles on pressures downline as a product gets closer to delivery.
• Excessive workloads.

#6. Lack of Top Management Support

• Attitude/motivation (i.e., a corporate culture that does not prioritize quality and assumes it is automatic).
• Managers who are inadequately educated to the importance of quality and the means of achieving it.
• Time management (e.g., quality managers spend more time fighting fires than proactively addressing quality, which typically results in a self-defeating cycle).
• “Cancer of complacency” (i.e., the false belief that reputation and past performance will always outweigh any quality issues that may arise).

Now that you know what problems to look for, the next step is ensuring your personnel have the right tools and skillsets to identify and rectify them.

Quality Problem Identification Certifications

Quality practices can vary widely across different industries and countries. That being the case, there is not a blanket quality problem identification certification that applies globally to all business sectors. However, there are a variety of specialized certifications, such as those offered by the American Society for Quality ( ASQ ), that formally recognize an individual’s proficiency within, and comprehension of, specific quality knowledge.

ASQ offers professional certifications in the following areas:

• Management (i.e., organizational excellence and supplier quality).
• Foundational quality (i.e., quality improvement and process analysis).
• Inspections (including equipment calibration).
• Engineering (including software development, implementation, testing, verification, and validation).
• Auditing (including certifications specific to quality practices for food safety, pharmaceutical, and medical device industries).
• Six Sigma techniques for process improvement.

For professionals seeking quality problem identification programs, ASQ offers Certified Quality Inspector (CQI) training. CQI certification ensures an inspector has learned proven techniques for inspecting products, measuring process performance, recording data, evaluating hardware documentation, performing laboratory procedures, and preparing formal reports.

Real Cause Identification Requires Tools Built for the Job

Unearthing and correcting real causes can dramatically reduce the occurrence and severity of quality problems. Determining real causes also helps diminish the dysfunctions caused by CAPA overload. But you need the right set of tools to identify real causes efficiently and effectively.

A digital, fully integrated quality management system (QMS)  simplifies real cause discovery. It’s much easier to identify the real causes of problems when you can rely on a unified platform that connects quality data across your products’ life cycles and within a common architecture. A connected QMS platform gives you greater real-time visibility into quality data, which pushes real problems to the fore.

To learn how your organization can identify real causes with greater speed and accuracy, visit MasterControl’s product life cycle managementplatform page .

• “ Management Audits: The Assessment of Quality Management Systems ,” Sayle, Allan J., 1988, McGraw-Hill, pp. 18.21-34.

James Jardine is the editor of the GxP Lifeline blog and the marketing content team manager at MasterControl, Inc., a leading provider of cloud-based quality, manufacturing, and compliance software solutions. He has covered life sciences, technology and regulatory matters for MasterControl and various industry publications since 2007. He has a bachelor’s degree in communications with an emphasis in journalism from the University of Utah. Prior to joining MasterControl, James held several senior communications, operations, and development positions. Working for more than a decade in the non-profit sector, he served as the Utah/Idaho director of communications for the American Cancer Society and as the Utah Food Bank’s grants and contracts manager.

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HEALTHCARE SERVICE DELIVERY

Quality improvement through problem solving.

First published 25 Oct. 2014 Latest update 31 Oct. 2021

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QUALITY PROBLEMS

A quality problem is defined as any instance where the desired quality characteristic is not present or not up to the intended level. In other words, it is an instance of failure to conform to standards or specifications. It can also be considered as the “Quality Gap”.

THE ATTITUDE TOWARDS PROBLEMS

It is disappointing to encounter problems despite putting in a good design and scrupulous control. However, problems should be seen as a challenge to put out a better product or service. Problems should not be brushed off or ignored but efforts need to be made to know what problems exist and how serious. Each problem should be subjected to further inquiry regarding why they happen and what can be done to avoid them.

THE PROBLEM SOLVING CYCLE

The first step is to identify, clarify and verify the existence of a quality problem. Then, an approach must be found to solve these problems. The problem solving process is based on the scientific approach. The approach is depicted below as a cycle of recurring activities. Outline of The Problem Solving Steps

PROBLEM IDENTIFICATION

a. Problem Identification via Statistical Quality Control The main way to identify problems is by detecting non-conformance through quality control. According to J.M Juran, in ‘Quality by Design’, Quality control is “the regulatory process through which we measure the actual performance, compare it with standards and act on the difference”. In the last part of this definition, Juran has incorporated quality improvement as part of control. A defective product / unsatisfactory result can occur by chance. Knowing the frequency of occurrence is therefore important. Statistical Quality control is the detection of the rate of non-conformance in a sizable quantity of products produced or delivered. In clinical practice, statistical quality control takes the form of Clinical or Medical audit.

b. Customer Complaints Through stringent quality control non-conformant items are rejected. If however substantial numbers of customers are still unhappy, there is a problem in the quality control or the design. Customer opinion regarding quality should be actively sought for through Customer Satisfaction Surveys or Complaint Boxes c. Employee Complaints Any complaint from employees about the process, the equipment or the work environment, should be considered as a problem. To encourage reporting, complaints can be disguised as Employee suggestion (see later). d. Incident Reporting Incidents occurring during production, delivery and use of products should be identified as problems and studied closely. The occurrence of incidents should be reported by employees and sought from customer complaints.

To be effective, the problem solving process need to be orderly and scientific in approach. The first step is to identify, clarify and verify the existence of a quality problem. The causes must then be found. Consequently, methods must be found to solve these problems. The approach is depicted below as a cycle of activities. Often not all aspects of a problem can be corrected at any one time. Also, new problems keep on being detected. Therefore quality improvement efforts is continuous. It is appropriate perhaps to name it as “The Problem Solving Cycle”.

The problem solving exercise needs to be approached from two distinct perspectives:

• theoretical

The context within which the problem occurs need to be known. The possible causes are postulated from a knowledge of the input, processes, and environment. Data is then collected to clarify what factors are in operation when the defective product was made or unsatisfactory service was delivered. The corrective action or remedy involves a level of experimentation outside of the operations domain. Only after the suggested remedial action is proven to be effective is it adopted.

Therefore, even though the changes are meant to be gradual, the problem solving approach need to be taken as a project. There is a need for proper planning, organization, scheduling, and control.

“The Quality Improvement Cycle”

Elaboration of the Steps of the Problem Solving Activity/Project

The steps of the Problem Solving exercise, is elaborated below:

Step 1. Assess Quality of Service Collect data to measure current performance. This step is actually the activity of Quality control. In clinical medical practice medical audit is used for this purpose. Step 2. Identify Problem A Quality problem is said to occur if there is a quality gap or deficit (shortfall in quality) based on the outcome results compared to the standard set. Step 3. Analyze Problem At this step a theoretical analysis of the factors that may contribute to the occurrence is performed. Factors may include input, processes, the environment, and organization of the system as a whole. The production process / service delivery process needs to be clarified by studying existing work flow charts or redrawing them. Step 4. Postulate Causes Tools such as relations diagram (Bubble chart) and Ishikawa Herring Bone chart may be used to demonstrate and clarify cause and effect. Step 5. Identify data required and how to obtain them Theoretical postulates put forward at the previous step need to be proven by a study of actual happenings. This would require the collection of relevant data. To do this, questions of what data, where to obtain them and how must be answered. Step 6. Plan Data Collection At this stage it is necessary to know whether data required already exists or new data need to be collected (e.g., via observation). Decision must be made on data collection techniques, responsibility for data collection and data storage. Performing all these is equivalent to designing a research study. Step 7. Collect Data This step is the actual activity of data gathering and collation (put together). Step 8. Analyze Data Data that have been collected are tabulated, analysed and presented using simple statistical tools. Step 9. Derive Causes of Problems The results of data analysis are interpreted to prove or disprove postulates made previously. Collected data may also reveal or suggest other possible causes. Step 10. Plan Corrective/Remedial Measures Strategies for Improvement need to be formulated and planned with care. Based on the causes identified above, various factors requiring correction are identified. Alternative solutions to solving the problem may be identified and shortlisted through Employee suggestion, Literature Review and Benchmarking. In the long term, research and innovation may provide better solutions. Step 11. Carry out Remedial Measures The most effective strategy to use in implementation of remedial measures is the use of the Shewhart PDCA cycle as described below:

Application of the PDCA Cycle to Carrying out Remedial Actions

In this approach, the remedy being suggested is first planned properly and put to the test (the Do step). This test is done as simulation, trial or pilot project and data is collected to confirm it’s effectiveness or otherwise (the “Check” stage). When it is a complete success it can be adopted and institutionalized. If it is not entirely acceptable it can be amended or adapted and tried again. A complete failure warrants re-planning (back to the drawing board) and a repeat of the whole cycle. Step 12. Re-evaluate the problem Collect data to determine the frequency and seriousness of the problem. This step means the continuation of the Quality control activities. If the problem has not been solved the problem may require re-analysis or study. It may also mean that the remedial measures chosen were not carried out fully or they wee not effective. Step 13. Prevent the problem from recurring If corrective actions / measures have been successful, all changes made need to be adopted and institutionalized. This usually means that the changes are incorporated into policies, the work procedures and work culture. Continuous vigilance through quality control will ensure that the problems do not recur.

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13 Quality Management Tools to Drive Process Improvements

There are some essential and popular quality management tools that’ve been around since the dawn of time (or at least it seems that way).

Why are they used?

When used correctly, they can help identify issues, trends and root causes, quickly. And provide the often-overlooked element of process improvement and problem solving… that’s using data and facts to eliminate problems for good.

Remember, the usual message is this: When problem solving, you must use inductive and deductive reasoning to really eliminate issues.

This means that you must use judgement and theories, based around data and fact.

And so, using quality management tools helps add the data to your argument.

Add these ingredients to a structured problem solving methodology like DMAIC, or PDCA,   and you have a recipe for eliminating improvements for good.

Why are They Called Quality Management Tools?

Most of the quality management tools had their inception from quality management gurus like Deming and Juran (Total Quality Management) and Ishikawa (Quality Circles).

But essentially, they are there to do exactly what it says, implement effective management of quality.

Good quality of processes, people and outcomes, ensures you have less problems as a business.

And it also ensures your customers are delighted with your high-quality level of service.

The effective use of these 13 quality management tools requires the people who run their processes, to use them.

This ensures that the culture is about observing what’s going on and making improvements as second nature.

The 13 Essential Quality Management Tools for Process Improvement (and Problem Solving)

I’ve put together a list of 13 of the best (and most popular) quality management tools that you should use. They consist of the 7 foundational quality management tools, plus 6 more that are good to have in the toolbox. (And which I regularly use myself.)

Here they are in their full glory:

• PDCA / DMAIC (or some process improvement framework)

Statistical Process Control

Process mapping.

• Cause and Effect Diagrams (and Cause and effect with cards, often called CEDAC)

Brainstorming

• Pareto Charts

Control Charts

• Check Sheets

Matrix Analysis

Scatter diagrams.

• Dot Plot charts

Before using any quality management tool, you need to have a framework to use it all within. It’s like having an operating system with your laptop. The operating system ensures that you get to use the computer for all its capabilities and effectiveness. And Use it in a structured way.

That’s why we start with the use of a process improvement framework.

Process Improvement Framework

There’s no point going gung-ho, without a way of understanding what to do when you find a problem.

The best way to tackle problem solving and process improvement is through a structured problem solving process. This has been covered in other articles, but some of the most popular methods are:

• Plan-Do-Check-Act Framework
•  DMAIC Methodology

Each one provides a clear roadmap of what to do to tackle problems and eliminate them for good.

And once you have your framework in place, it’s time to use some other tools.

Here’s a brief description of the remaining 12 quality management tools and why you should use them.

Or SPC as its commonly abbreviated to. It’s one of the 7 ‘foundational’ quality management tools. It’s a framework for measuring and reducing variation in a process’ output.

Variations in processes cause all sorts of inconsistencies from product quality, to lead time, to cost, and even attitudes and behaviours.

Variables cause the most common quality problems in processes. By that I mean, something(s) that’s causing a process to be hugely inconsistent. One minute you get it right. The next, it’s producing nothing but poor output.

And the theory goes that by controlling these variables in any process, you can control the outcome. Thus, making it more consistent.

And with consistent output comes stable processes.

And with stable processes, you get less time spent firefighting and handholding things through that process.

You also get great confidence it in being right every time. Thus, you can even offer services that your competitors can’t.

The automotive manufacturer, KIA have a 7-year warranty on all their vehicles.

Why? Because they are so confident that their cars are produced to such a high and consistent standard… They’re willing to put their reputation on it… and tell the world about it… And win more customers, too.

SPC is a way of measuring the quality within a certain process. This data is tracked normally using a Run Chart (or control chart).

The reason for using SPC is that you get real time information to see how stable the process is and can:

• reduce variability and defects
• improve productivity
• Reduce costs and lost time through firefighting
• Uncover hidden process trends
• Instantly react to process changes and variation
• Make real-time decisions in the business

Should every process be measured, using SPC?

No. It would be too much effort and cost to measure absolutely everything to the nth degree. And its overkill.

The biggest impact would be to measure your key processes. This means that you’ll probably want to understand 5-6 of your business’ critical processes better.

This is the second of the 7 foundational quality management tools. Control charts are one of the main methods of measuring SPC.

It’s an easy way of showing trends over time, and how a process is performing.

And whether it’s in control or not. On a Control Chart, you’ll find upper and lower control limits.

These are statistical indicators that show whether the process is statistically in control.

If it isn’t, it’s time to get to work to stabilise the process.

That stabilisation means you need to find the root causes of that inconsistency.

Control charts use the mean and standard deviations to measure whether a process is statistically in control or not. And if it’s not, it’ll show you when it’s happening.

Here’s a very simple version of a control chart (below) measuring output over time.

Notice how easy it is to see if, and when it’s out of control?

Control Chart

One of the first steps to understand a process is to map it. By mapping, we can gain a picture as to what actually happens.

Not what we think or what should happen.

This give us a tremendous insight into the process and what’s going on. And where the potential issues are that may be affecting the output and inconsistencies in our process.

ICOR is a great tool to help do this. ICOR stands for:

By looking at the inputs, controls, outputs and resources, we can see clues to help us find the reasons for inconsistency of output.

Let’s stop for a second. Let’s assume that we’re measuring a critical process’ output.

This process is a Valve making process.

The process involves some machine work, pre-assembly and assembly work as well.

The Valves must not leak in test. And as we measure, our control charts are showing that there’s too much inconsistency. Some pass and some don’t.

We can stop and tackle the problem there and then.

And often one of the first things we’d do, is to map the process, to see what is happening when we observe it.

We want to detect any potential issues that we can bring forward to investigate further. And either dismiss or prove that it’s having a potential impact.

If you take this example, and using ICOR… our map would have several factors that go into the whole process. 1 or 2 of these factors are causing this inconsistency.

And by mapping it all out and observing the process, first, you can see potential problems and factors to investigate further.

And the beauty of this is that it gives you so much to think about… So many clues to investigate and ask questions…

Before any assumptions or further actions are made.

Here’s an example of a process map (This is an interpretation and not the only interpretation of a process map):

Process Map Example

The yellow boxes are simply steps in the process. Above each step is the required output for each step (in blue). And the green section below represents all the inputs to that step. Notice that each input is labelled either C = Controlled; or N = not controlled.

This is important. It allows us to see how well each input is controlled to prevent variation and issues and gives us clues to see what may be impacting our process. And where we need to tighten things up a little.

Some factors worth investigating further, in our valve manufacturing example, could be:

• The raw material thickness may be too inconsistent, which prevents a stable output in our business
• The environment. The humidity or heat may affect the CNC machine
• The way the operator places the material in the jig
• Is the jig stable or does it move slightly?
• What about capability of machine? When was the last time it was serviced and looked after?
• What’s the skill requirements of the job?
• Is the operator skilled enough and had adequate training?
• Are the seals being damaged during assembly?
• Is the lapping process needed?
• Does the lapping cause undue variation?
• Is the tool moving?
• Is the tool blunt?
• Can we see when the tool is about to lose its sharpness?

In one map, you can see the process, the inputs and the clues as to what could be causing this variation, all on one sheet.

It allows us to break the process down into small segments, and see how they all fit into the bigger whole or process outcome.

Cause and Effect Diagram

The Cause and Effect Diagram is another one of the 7 foundational quality management tools. I’ve written an article on this before, but an adaptation on the classic Fishbone is the CEDAC method.

This stands for Cause and Effect with Cards. This method helps you add observed data to the fishbone diagram and then add improvement ideas to that section.

Effectively, you have two cards, one is the idea for improvement; the other is the data card.

CEDAC Fishbone Diagram

With CEDAC (Cause and Effect Diagram with the Addition of Cards), the effect side of the diagram is a quantified description of the problem at the fish head.

In The cause section (the spines of the fish) there are two different coloured cards for writing the facts and the ideas.

The facts are gathered and written on the left of the spines, and the ideas for improvement on the right of the cause spines.

The team then evaluate them and select, based on feasibility and impact in improving the problem.

You can use the Fishbone Diagram or CEDAC alternative to help identify root causes, using data.

In our Valve example, we may take a few subjective ideas from our map, and drill down to find potential root causes and improvement ideas, using several CEDAC diagrams.

Brainstorming is another core member of the quality management tools suite. It’s used with a team to generate ideas, quickly and effectively.

It can be used in conjunction with identifying root causes through 5 why sessions and using the cause and effect diagram.

In fact, it can be used just about on any subject where you have a small team analysing something.

And it’s a structured way of getting input from the team. And doing it effectively.

The easiest method is to get each team member to write their ideas on post it notes.

One post it per idea and in a short space of 5 minutes, get them to write as many ideas as possible.

Add these to the chart (fishbone diagram, ideas board, etc.).

Then discuss. Group the post its that are similar.

Then ask for another round of brainstorming (if they have more ideas)

When the team run out of ideas, get them to agree their priority thoughts and actions by each scoring their top 1-3 ideas.

Why use it? Each member of the group inputs their ideas of potential root causes and improvement.  Using this method, no idea is a bad idea.

The object is to get as many ideas out on paper, quickly, until the group runs out of thoughts. At which point, it’s then a case of assigning priorities and actions for the ideas chosen.

Pareto Analysis

Pareto analysis is based around the 80/20 rule, whereby often the vital few things cause the biggest effect.

That’s 80% of sales come from 20% customers…

80% of defects come from 20% root causes…

It might not be exactly 80/20, but you’ll find that the vital few things cause the major effect.

It’s simple in its approach.

And it’s depicted in the form of a bar chart, whereby frequency or impact is show in descending order, against specific cause codes, or reasons of failure / problems.

Using this method, you can quickly, see the biggest impact from the vital few causes.

And once you have this information, you can get to work improving the vital few root causes.

Here’s as an example of a Pareto Chart:

Pareto Chart Example

Check Sheet

Check sheets are another simple but effective means within the quality management tools suite.

Check sheets are simple tally charts, typically showing the number of occurrences things happen.

Data is collected and ordered by adding tally or check marks against predetermined categories of items or measurements.

It simplifies the task of analysis.

Once you find a problem affecting the process, tick it immediately. Employees refer to the check list to understand whether changes incorporated in the system have brought permanent improvement or not.

Improvement teams can use it to gather important information for further analysis, too.

In our Valve example, let’s suppose that after we’ve mapped the process, and we want to see how many times over the next month, these variables happen. We can do it using a Pareto Chart.

First, we could create a simple check sheet that the operators tally when they spot an occurrence of the problem, in a similar way to the above chart.

Then we can collate this information into a nice visual tool like the Pareto, which’ll show us the biggest offenders from the data gathered…

We’ve now got an even better understanding of our processes.

Bar charts are another of the 7 foundational quality management tools. They are a very simple way of demonstrating data; the height of each bar shows the frequency of the result.

Again, in any form of communication, the less complexity the better, and Bar Charts are a very simple way of showing results of data.

Here’s a case in point. What’s easier to read?

• A list of data, collected from source.
• Or a bar chart summarising that data, visually?

Which one is easiest to read?

Which one can you use to spot trends?

It’s a no-brainer, right?

Bar charts are a good way of measuring lots of data, quickly and easily.

Bar Charts could be used in the following examples:

• Expenditure each month
• Delivery performance each month
• Attendance scores
• Customer returns / complaints each week

In our Valve example, it could be that we just want to measure number of failures each day, or defects per shift. (So we can see if there is a variance caused between shifts).

A matrix analysis is a simple way of showing the relationship between two data points.

Here’s an example of a matrix to help select the right improvement project, using Ease and Impact as the two correlations:

Project Selection Matrix

Again, notice how clear it is to decipher?

If you’re about to choose the right improvement project, you’d choose from the top right of the matrix (high impact and relative ease to implement).

In our Valve example, we may want to take all our identified variables from our ICOR process map and feed them into a cause and effect matrix.

We can then score each factor based on importance to our customer.

What we can then do is filter out the high scoring factors from the low scoring ones. And then bring these high scoring ones forward for further analysis.

Using this method, we can plough through our ideas and observations quickly and effectively. And, highlight the biggest impact variables from the rest.

Here’s what it could look like if we sorted all our valve production variables in a Cause and Effect Matrix:

Cause and effect matrix

A Scatter diagram aims to show a relationship between two variables. And how one changes in relation to the other.

Why use a scatter diagram?

In lots of cases, we make judgements based on what we see, and often assume that because one thing happens, and so too another at the same time, then they must be linked.

For example, two customer returns have been received in the last week. When we quickly look, we find that both jobs were manufactured on the night shift…

It’s very easy to say that there’s a fundamental link between quality and the type of shift that produced it. But there could just be other factors that we don’t see that are causing it.

And it could also have been a coincidence that both happened on one shift.

Here’s an example of a scatter diagram:

Scatter Diagram

A scatter diagram can help by collating data over time to see if these variables are linked.

In our Valve example, we could pair factors together to see if they do indeed correlate. This correlation could help identify the root cause and how we can go about controlling them.

In this example, we may have uncovered that the thickness of the raw material has a direct correlation to whether the valve leaks or not… this analysis will give us greater understanding of the process… and how to control the leaks.

We now know more and can make a more informed decision .

In statistics, there are many coincidences that happen, and using scatter diagrams helps to see how correlated they are, before jumping to opinionated conclusions.

Dot plot Charts

Dot plots can be used to keep plotting output from a process that you’re measuring, using a simple dot for each occurrence.

They’re a great way of showing the dispersion of data and how far the data spreads across values.

You can also use it to see if the process is random or whether there is special cause variation.

By random, you should be able to see a bell curve in the data (which normally signifies the process being stable).

Here’s an example:

dotplot chart with bell shape

In a lot of instances, if you get something other than a bell curve, there may be special cause variation and additional factors that are caused big variation in the process output.

(This is a big subject, and will be touched on in other articles, so stay tunedJ)

A simple way of thinking about this tool is when using dice. You can easily set up a dot plot to count the number of times the dice falls on each number, when rolled. Because the dice can only be either a 1, 2, 3, 4, 5, 6, you can plot them at the bottom of a dot plot and add a dot for every occurrence the dice falls on each number.

Histogram is a graphical representation showing the intensity of a problem.

They’re classified as one of the foundational quality management tools.

Histograms are like bar charts and dot plots but they group numbers into ranges.

In a similar way to the dot plot, histograms help identify the causes of problems in a process, by both the shape and width of the distribution.

What separates them form the dot plot is that the histogram should be used for larger data sets. This is because the data ranges can be grouped together.

In the case of our Valve example, we may want to measure the size of every Valve being produced.

As it’s continuous data that can have be any size measurement (and not pre-set sizes like our dice example) the histogram could be used instead of the dot plot. Because data ranges can be grouped at the bottom of the axis.

For example, our size ranges might go:

We can now add the number of occurrences to the histogram.

By measuring this, we can add upper and lower specification limits to the graph. These specification limits show the tolerances as to what’s good quality and what’s not.

Like the dot plot, you can then gauge how much of your process output falls within acceptable limits.

If the distribution is too wide, you can set about improving it.

Histogram with ucl and lcl

In this example, we can see that much of the output from the process, falls outside of the upper and lower control limits.

The distribution is too wide.

And the mean is slightly skewed to the lower end.

The result being that there’s a high number of defects. And there’s plenty of analysis to do to narrow the distribution and control the process.

Use These Quality Management Tools to Suit Your Needs

These are the 13 common quality management tools to use in analysing your processes and problems.

Notice how they can all work together to give you greater insight BEFORE finding the root cause(s).

Use them within a proven problem solving methodology (as in step 1 above), and you have a powerful way of measuring and improving your business.

Do you have to use all the tools every time? No. You simply use what you need, to get to the root cause.

Some problem-solving projects may require extensive analysis, using even more tools than these 13 quality management tools.

Others may need just 2-3 of them.

The important thing is to use data to understand processes and problems to drive problem solving.

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Quality Observations: Key Strategies for Effective Problem Solving

• The problem tends to be described incorrectly;
• There may be a lack of or insufficient structure in the problem solving process;
• A lack of urgency;
• Management impatience;
• A lack of follow-through to prevent the problem from recurring;
• The problem solving effort has been “expedited” by skipping process steps; or
• Poor execution of or ineffective corrective actions. The Future of Quality

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7 Basic Tools of Quality for Process Improvement

Japan is known worldwide for its quality products and services. One of the many reasons for this is its excellent quality management. How did it become so? Japan has Dr. Kaoru Ishikawa to thank for that.

Postwar Japan underwent a major quality revolution. Companies were focused on training their employees in statistical quality control. But soon they realized that the complexity of the subject itself could intimidate most of the workers; so they wanted more basic tools.

Dr. Kaoru Ishikawa, a member of the Japanese Union of Scientists and Engineers (JUSE), took it to his hands to make quality control easier for everyone – even those with little knowledge of statistics – to understand. He introduced the 7 basic tools of quality. They were soon adopted by most companies and became the foundation of Japan’s astonishing industrial resurgence after World War 2.

This post will describe the 7 basic quality tools, how to use them and give you access to templates that you can use right away.

Quality Tools: What Are They?

How can teams and organizations use the 7 basic quality tools, cause and effect diagram, scatter diagram, check sheets.

• Control chart
• Pareto chart

The 7 basic tools of quality, sometimes also referred to as 7 QC tools – represent a fixed set of graphical tools used for troubleshooting issues that are related to quality.

They are called basic quality tools because they can be easily learned by anyone even without any formal training in statistics. Dr. Kaoru Ishikawa played the leading role in the development and advocacy of using the 7 quality tools in organizations for problem-solving and process improvement.  

The 7 basic quality tools include;

• Cause-and-effect diagram
• Scatter diagram
• Check sheet

The 7 quality tools were first emphasized by Kaoru Ishikawa a professor of engineering at the University of Tokyo, who is also known as the father of “Quality Circles” for the role he played in launching Japan’s quality movement in the 1960s. During this time, companies were focused on training their employees in statistical quality control realized that the complexity of the subject could intimidate most of the workers; hence they opted for simpler methods that are easy to learn and use. 7 basic tools of quality were thus incorporated company-wide.

Quality tools are used to collect data, analyze data, identify root causes, and measure results in problem-solving and process improvement. The use of these tools helps people involved easily generate new ideas, solve problems, and do proper planning.

• Structured approach: They provide a systematic approach to problem-solving and process improvement, ensuring that efforts are well-organized and focused.
• Data-driven decision making: The tools enable data collection, analysis, and visualization, empowering teams to make informed decisions based on evidence.
• Improved communication and collaboration: Visual representations and structured tools facilitate effective communication and collaboration among team members, leading to shared understanding and alignment.
• Problem identification and prioritization: The tools help identify and prioritize problems or improvement opportunities, enabling teams to allocate resources efficiently and address critical issues first.
• Continuous improvement: By using these tools, teams can establish a culture of continuous improvement, as they provide a framework for ongoing monitoring, analysis, and refinement of processes.

7 Basic Quality Tools Explained with Templates

The 7 quality tools can be applied across any industry.  They help teams and individuals analyze and interpret the data they gather and derive maximum information from it.

Flowcharts are perhaps the most popular out of the 7 quality tools. This tool is used to visualize the sequence of steps in a process, event, workflow, system, etc. In addition to showing the process as a whole, a flowchart also highlights the relationship between steps and the process boundaries (start and end).

Flowcharts use a standard set of symbols, and it’s important to standardize the use of these symbols so anyone can understand and use them easily. Here’s a roundup of all the key flowchart symbols .

• To build a common understanding of a process.
• To analyze processes and discover areas of issues, inefficiencies, blockers, etc.
• To standardize processes by leading everyone to follow the same steps.

Real-world examples of usage

• Documenting and analyzing the steps involved in a customer order fulfillment process.
• Mapping out the workflow of a software development lifecycle.
• Visualizing the process flow of patient admissions in a hospital.

Enhances process understanding, highlights bottlenecks or inefficiencies, and supports process optimization and standardization efforts.

How to use a flowchart

• Gather a team of employees involved in carrying out the process for analyzing it.
• List down the steps involved in the process from its start to end.
• If you are using an online tool like Creately , you can first write down the process steps and rearrange them later on the canvas as you identify the flow.
• Identify the sequence of steps; when representing the flow with your flowchart, show it from left to write or from top to bottom.
• Connect the shapes with arrows to indicate the flow.

Who can use it?

• Process improvement teams mapping and documenting existing processes for analysis.
• Business analysts or consultants analyzing workflow and process optimization opportunities.
• Software developers or system designers documenting the flow of information or interactions in a system.

To learn more about flowcharts, refer to our Ultimate Flowchart Tutorial .

A histogram is a type of bar chart that visualizes the distribution of numerical data. It groups numbers into ranges and the height of the bar indicates how many fall into each range.

It’s a powerful quality planning and control tool that helps you understand preventive and corrective actions.

• To easily interpret a large amount of data and identify patterns.
• To make predictions of process performance.
• To identify the different causes of a quality problem.
• Analyzing the distribution of call wait times in a call center.
• Assessing the distribution of product weights in a manufacturing process.
• Examining the variation in delivery times for an e-commerce business.

Provides insights into process performance and variation, enabling teams to target areas for improvement and make data-driven decisions.

How to make a histogram

• Collect data for analysis. Record occurrences of specific ranges using a tally chart.
• Analyze the data at hand and split the data into intervals or bins.
• Count how many values fall into each bin.
• On the graph, indicate the frequency of occurrences for each bin with the area (height) of the bar.
• Process engineers or data analysts examining process performance metrics.
• Financial analysts analyzing expenditure patterns or budget variances.
• Supply chain managers assessing supplier performance or delivery times.

Here’s a useful article to learn more about using a histogram for quality improvement in more detail.

This tool is devised by Kaoru Ishikawa himself and is also known as the fishbone diagram (for it’s shaped like the skeleton of a fish) and Ishikawa diagram.

They are used for identifying the various factors (causes) leading to an issue (effect). It ultimately helps discover the root cause of the problem allowing you to find the correct solution effectively.

• Problem-solving; finding root causes of a problem.
• Uncovering the relationships between different causes leading to a problem.
• During group brainstorming sessions to gather different perspectives on the matter.
• Investigating the potential causes of low employee morale or high turnover rates.
• Analyzing the factors contributing to product defects in a manufacturing process.
• Identifying the root causes of customer complaints in a service industry.

Enhances problem-solving by systematically identifying and organizing possible causes, allowing teams to address root causes rather than symptoms.

How to use the cause and effect diagram

• Identify the problem area that needs to be analyzed and write it down at the head of the diagram.
• Identify the main causes of the problem. These are the labels for the main branches of the fishbone diagram. These main categories can include methods, material, machinery, people, policies, procedures, etc.
• Identify plausible sub-causes of the main causes and attach them as sub-branches to the main branches.
• Referring to the diagram you have created, do a deeper investigation of the major and minor causes.
• Once you have identified the root cause, create an action plan outlining your strategy to overcome the problem.
• Cross-functional improvement teams working on complex problems or process improvement projects.
• Quality engineers investigating the root causes of quality issues.
• Product designers or engineers seeking to understand the factors affecting product performance.

The scatter diagram (scatter charts, scatter plots, scattergrams, scatter graphs) is a chart that helps you identify how two variables are related.

The scatter diagram shows the values of the two variables plotted along the two axes of the graph. The pattern of the resulting points will reveal the correlation.  

• To validate the relationship between causes and effects.
• To understand the causes of poor performance.
• To understand the influence of the independent variable over the dependent variable.
• Exploring the relationship between advertising expenditure and sales revenue.
• Analyzing the correlation between employee training hours and performance metrics.
• Investigating the connection between temperature and product quality in a production line.

Helps identify correlations or patterns between variables, facilitating the understanding of cause-and-effect relationships and aiding in decision-making.

How to make a scatter diagram

• Start with collecting data needed for validation. Understand the cause and effect relationship between the two variables.
• Identify dependent and independent variables. The dependent variable plotted along the vertical axis is called the measures parameter. The independent variable plotted along the horizontal axis is called the control parameter.
• Draw the graph based on the collected data. Add horizontal axis and vertical axis name and draw the trend line.
• Based on the trend line, analyze the diagram to understand the correlation which can be categorized as Strong, Moderate and No Relation.  
• Data analysts exploring relationships between variables in research or analytics projects.
• Manufacturing engineers investigating the correlation between process parameters and product quality.
• Sales or marketing teams analyzing the relationship between marketing efforts and sales performance.

Check sheets provide a systematic way to collect, record and present quantitative and qualitative data about quality problems. A check sheet used to collect quantitative data is known as a tally sheet.

It is one of the most popular QC tools and it makes data gathering much simpler.

• To check the shape of the probability distribution of a process
• To quantify defects by type, by location or by cause
• To keep track of the completion of steps in a multistep procedure (as a checklist )
• Tracking the number of defects or errors in a manufacturing process.
• Recording customer complaints or inquiries to identify common issues.
• Monitoring the frequency of equipment breakdowns or maintenance needs.

Provides a structured approach for data collection, making it easier to identify trends, patterns, and areas for improvement.

How to make a checksheet

• Identify the needed information.
• Why do you need to collect the data?
• What type of information should you collect?
• Where should you collect the data from?  
• Who should collect the data?
• When should you collect the data?
• How should you measure the data?
• How much data is essential?

Construct your sheet based on the title, source information and content information (refer to the example below).

Test the sheets. Make sure that all the rows and columns in it are required and relevant and that the sheet is easy to refer to and use. Test it with other collectors and make adjustments based on feedback.

• Quality inspectors or auditors who need to collect data on defects or issues.
• Process operators or technicians responsible for tracking process parameters or measurements.
• Customer service representatives who record customer complaints or inquiries.

Control Chart

The control chart is a type of run chart used to observe and study process variation resulting from a common or special cause over a period of time.

The chart helps measure the variations and visualize it to show whether the change is within an acceptable limit or not. It helps track metrics such as defects, cost per unit, production time, inventory on hand , etc.

Control charts are generally used in manufacturing, process improvement methodologies like Six Sigma and stock trading algorithms.

• To determine whether a process is stable.
• To monitor processes and learn how to improve poor performance.
• To recognize abnormal changes in a process.
• Monitoring the variation in product dimensions during a manufacturing process.
• Tracking the number of customer complaints received per day.
• Monitoring the average response time of a customer support team.

Enables real-time monitoring of process stability, early detection of deviations or abnormalities, and prompt corrective actions to maintain consistent quality.

How to create a control chart

• Gather data on the characteristic of interest.
• Calculate mean and upper/lower control limits.
• Create a graph and plot the collected data.
• Add lines representing the mean and control limits to the graph.
• Look for patterns, trends, or points beyond control limits.
• Determine if the process is in control or out of control.
• Investigate and address causes of out-of-control points.
• Regularly update the chart with new data and analyze for ongoing improvement.
• Production supervisors or operators monitoring process performance on the shop floor.
• Quality control or assurance personnel tracking variation in product quality over time.
• Service managers observing customer satisfaction levels and service performance metrics.

Pareto Chart

The Pareto chart is a combination of a bar graph and a line graph. It helps identify the facts needed to set priorities.

The Pareto chart organizes and presents information in such a way that makes it easier to understand the relative importance of various problems or causes of problems. It comes in the shape of a vertical bar chart and displays the defects in order (from the highest to the lowest) while the line graph shows the cumulative percentage of the defect.

• To identify the relative importance of the causes of a problem.
• To help teams identify the causes that will have the highest impact when solved.
• To easily calculate the impact of a defect on the production.
• Analyzing customer feedback to identify the most common product or service issues.
• Prioritizing improvement efforts based on the frequency of quality incidents.
• Identifying the major causes of delays in project management.

Helps focus improvement efforts on the most significant factors or problems, leading to effective allocation of resources and improved outcomes.

How to create a Pareto chart

• Select the problem for investigation. Also, select a method and time for collecting information. If necessary create a check sheet for recording information.
• Once you have collected the data, go through them and sort them out to calculate the cumulative percentage.
• Draw the graph, bars, cumulative percentage line and add labels (refer to the example below).
• Analyze the chart to identify the vital few problems from the trivial many by using the 80/20 rule . Plan further actions to eliminate the identified defects by finding their root causes.
• Quality managers or improvement teams looking to prioritize improvement initiatives.
• Project managers seeking to identify and address the most critical project risks.
• Sales or marketing teams analyzing customer feedback or product issues.

What’s Your Favorite Out of the 7 Basic Quality Tools?  

You can use these 7 basic quality tools individually or together to effectively investigate processes and identify areas for improvement. According to Ishikawa, it’s important that all employees learn how to use these tools to ensure the achievement of excellent performance throughout the organization.

Got anything to add to our guide? Let us know in the comments section below.

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FAQs about 7 Basic Quality Tools

What is quality control, what are the common quality problems organizations face.

Quality problems in an organization can manifest in various forms and affect different areas of operations.

• Product defects: Products may have defects or non-conformities that deviate from quality specifications, leading to customer dissatisfaction, returns, or warranty claims.
• Service errors: Service errors can occur when services do not meet customer expectations, such as incorrect billing, delays in delivery, or inadequate customer support.
• Process inefficiencies: Inefficient processes can lead to delays, errors, or rework, resulting in increased costs, decreased productivity, and customer dissatisfaction.
• Poor design or innovation: Inadequate product design or lack of innovation can lead to products that do not meet customer needs, lack competitive features, or have usability issues.
• Supplier quality issues: Poor quality materials or components from suppliers can affect the overall quality of the final product or service.
• Ineffective quality management systems: Inadequate quality management systems, such as lack of quality standards, processes, or documentation, can contribute to quality problems throughout the organization.

What are the basic quality improvement steps?

The basic quality improvement steps typically follow a systematic approach to identify, analyze, implement, and monitor improvements in processes or products.

• Clearly articulate the problem or identify the area for improvement.
• Collect relevant data and information related to the problem.
• Analyze the collected data to identify patterns, root causes, and opportunities for improvement.
• Brainstorm and generate potential improvement ideas or solutions.
• Assess the feasibility, impact, and effectiveness of the generated improvement ideas.
• Develop an action plan to implement the chosen solution.
• Continuously monitor and measure the results of the implemented solution.
• Based on the monitoring results, evaluate the effectiveness of the implemented solution.
• Once the improvement is successful, document the new processes, best practices, or standard operating procedures (SOPs).
• Iterate through the steps to continuously improve processes and products.

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Amanda Athuraliya is the communication specialist/content writer at Creately, online diagramming and collaboration tool. She is an avid reader, a budding writer and a passionate researcher who loves to write about all kinds of topics.

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THE VEEVA INDUSTRIES BLOG

Common quality management pitfalls and how to overcome them.

April 01, 2020

Daniel Borges Madureira

Daniel Borges Madureira is the Director of QualityOne Chemical Strategy. He has a passion for looking into ways of taking quality processes to the next level by changing mindsets, behaviors and actions through new solutions. With a background in industrial engineering and experience working with the top 5 automotive, semiconductor and chemical companies in the world, Daniel knows the pains and gains of running quality processes with and without intelligently designed tools.

Visit our Quality Solution Page to learn more about QualityOne.

In recent years, organizations have faced significant challenges impacting global supply chains, underscoring the critical role of quality management in consumer-centric industries.

While businesses strive for consistent quality, compliance, and continuous improvement, common pitfalls can still emerge. Effective quality management is essential not just for competitiveness and regulatory compliance, but also for factors like revenue, labor costs, and brand reputation, which have all been significantly impacted in recent times. 

To prevent quality issues from escalating and maintain a competitive edge, proactive quality management is critical. If your company is facing quality challenges, you're certainly not alone. Let's explore seven common pitfalls and how to address them effectively.

7 Quality Management Issues

1. leveraging technology.

While traditional methods like spreadsheets and paper trails were once the norm for quality management, the digital revolution has spurred advancements in efficiency. 

However, many firms haven't kept pace, clinging to outdated practices. This manual approach is susceptible to errors and bottlenecks, hindering competitiveness in today's dynamic market. Modern technology offers a solution – robust quality management systems can streamline processes, improve accuracy, and empower businesses to thrive.

Related Post: 5 Best Practices for Securing the Right Cloud-Based Software to Achieve Your Digital Transformation

Modern Quality Management Software (QMS) empowers data-driven decision-making and continuous improvement. These cloud-based solutions streamline processes, automate tasks, and provide real-time insights for proactive quality control. Unlike legacy systems, QMS scales seamlessly with your organization, ensuring ongoing agility and strategic alignment.

2. Siloing Quality Management

The last recent years have underscored the need for a holistic approach to quality management. A siloed department solely responsible for quality hinders true organizational excellence. This structure fosters a culture where quality becomes the sole responsibility of a single team, neglecting the crucial contributions of frontline staff, managers, and suppliers. 

According to a Forbes and ASQ survey of 1850+ executives , 20% of surveyed companies identified as siloed or struggling with their quality efforts. The same survey found that 84% believe quality issues, to some degree, are holding back their business’s ability to compete, and 85% say they have incurred some revenue loss due to ongoing, quality-related issues.

Modern quality management demands integration across the entire value chain, from raw materials to customer experience. Technology plays a vital role in this transformation, facilitating streamlined quality procedures, document management, and collaborative training across all departments and external partners. By fostering a culture of shared accountability and leveraging digital tools, organizations can achieve vigilant quality oversight at every stage, ensuring resilience in today's dynamic market landscape.

3. aligning Quality Management systems to business goals 

In today's competitive landscape, quality management isn't just about compliance – it's a strategic driver for profitability and sustainability. Beyond the immediate disruptions of the past two years, strong quality practices directly impact revenue, brand equity, and productivity. Investing in employee training and fostering a culture of quality excellence empowers businesses to deliver consistent, high-quality products. Partnering with a quality modernization expert can help implement best practices, ensuring long-term success and a resilient brand reputation.

4. Covering highly Complex Supply Chains

Proactive management of your supplier network, encompassing qualification, training, and ongoing compliance, is essential. Today's globalized supply chains are far more complex than their localized predecessors, presenting unique quality challenges. Managing this vast network can be overwhelming without the proper tools. Spreadsheets and paper-based systems are simply inadequate. Unidentified quality issues can lead to costly product recalls, tarnishing your brand and placing the blame on your quality team for supplier errors.

Related Post: 4 Ways to Leverage Your Quality Management Processes During Unprecedented Supply Chain Disruption

Modern technology empowers proactive quality management. Robust Quality Management Systems (QMS) provide real-time visibility and transparency across your entire supply chain, enabling early detection of potential problems before they impact your brand. Invest in tech solutions to optimize your supply chain for seamless operations and ensure consistent product quality.

5. Staying Up to Date with  Quality Management System Trends 

The rapid pace of change in today's market demands agile businesses, but outgrowing your quality management system can be disastrous. Before launching a new product, ensure your quality processes are adaptable and aligned with evolving needs. Efficiency is paramount – new products must meet strict compliance, safety, and quality standards while hitting the market quickly. Agile quality checks are key to faster market entry and maintaining competitiveness.

Embrace technology to automate quality management processes. This empowers your business to adapt to market shifts, seize new opportunities swiftly, and minimize production issues, ensuring consistent quality for your customers.

6. moving from Reactive to proactive Quality Management

Businesses must stay agile to seize trends and new markets swiftly. However, outpacing your quality management system can lead to significant issues. Before launching a new product, ensure your quality processes are adaptable and aligned with evolving needs. Efficiency is key for businesses in a dynamic marketplace – new products must meet strict compliance, safety, and quality standards while hitting the market quickly. Agile quality checks are key to faster market entry and maintaining competitiveness.

Related Post: What is Quality Improvement? The Ultimate Guide

Discovering an effective quality management process tailored to your business is crucial. But many businesses overlook the importance of evaluating and refining their quality practices regularly. This negligence can lead to costly overcorrections when issues arise. The recent Boeing 737 Max crisis serves as a stark reminder of the consequences of neglecting proper quality checks during development. Just like the human body needs regular checkups to maintain optimal health, so too does your quality management system. Quality management is a dynamic process, not a static one.

7. Anticipating Quality Management Issues

Manufacturing thrives on quality. A robust quality management system isn't just about catching problems – it's a proactive shield for your entire operation. By fostering a culture of quality and embracing innovative technology, you empower your team to identify and address potential issues before they disrupt production.

Flexible and efficient quality management solutions, integrated with real-time data, provide continuous insights to anticipate problems and ensure smooth operations in today's dynamic landscape. This proactive approach not only elevates your brand reputation but also saves valuable time and resources.

Veeva Can Help You Solve Your QMS Challenges

Struggling with Quality Management? Explore Veeva QualityOne. It's user-friendly, cloud-based, and committed to streamlining operations for enhanced customer loyalty through quality.

Enhance your quality management, training, and H&S strategies with Veeva's QualityOne. Learn more about its powerful features on our Quality Hub.  

Updated on April 26, 2024

Further Reading

September 11, 2024

By Kera Binns

September 04, 2024

August 28, 2024

By Ed Van Siclen

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7 QC Tools | 7 Quality Tools | Process Improvement Tools

7 QC Tools are also known as Seven Basic Quality Tools and Quality Management Tools. These graphical and statistical tools are used to analyze and solve work-related problems effectively.

The 7 Quality Tools are widely applied by many industries for product and process improvements, and to solve critical quality problems.

7QC tools are extensively used in various Problem Solving Techniques which are listed below:

• 8D Problem Solving Methodology.
• PDCA Deming Cycle for Continuous improvement in product and processes.
• Lean Manufacturing for 3M Waste elimination from processes.
• Various phases of Six Sigma-DMAIC to reduce process variations .

Table of Contents

WHAT ARE 7 QC TOOLS?

The 7 quality tools are simple graphical and statistical tools but very powerful in solving quality problems and process improvement.

These statistical tools are very easy to understand and can be implemented without any complex analytical competence or skills.

The 7 tools of quality are generally used by quality control and quality assurance engineers to solve product or process-related quality issues on a daily/weekly/monthly basis and to reduce/eliminate non-value-added activities like product rework, repair, and rejection.

7 QC Tools List | Quality Tools

The list of 7 QC tools are:

Check Sheet

Fishbone diagram, pareto chart, control chart, scatter diagram.

• Stratification Diagram (Some lists replace stratification with  Process Flowchart )

Click on the above links to Explore QC tools.

7 Tools of quality | Brief Explanation

The check sheet is used for collecting, recording, and analyzing the data. Data collection is an important activity in the problem-solving process as it provides a basis for further action. Data may be numerical, observations and opinions, etc.

Fishbone diagram is also called as Cause and Effect diagram and Ishikawa diagram . It helps to Identify all possible potential causes and select the real/best potential cause which contributes to the problem/effect. The brainstorming technique is used for potential cause identification.

In a brainstorming session, all 4M or 6M factors are taken into consideration to identify the potential causes. 4M or 6M factors are – Man, Machine, Method, Material, Measurement, and Mother nature also called Environment.

A Histogram is a pictorial representation of a set of data, and the most commonly used bar graph for showing frequency distributions of data/values. Histogram frequency distribution chart is widely used in Six Sigma problem solving process.

The Pareto chart helps to Narrow the problem area or prioritize the significant problems for corrective measures. The pareto principle is based on the 80-20 rule. It means that 80 percent of the problems/failures are caused by 20 percent of the few major causes/factors which are often referred to as Vital Few .

And the remaining 20 percent of the problems are caused by 80 percent of many minor causes which are referred to as Trivial Many . Hence, it gives us information about Vital few from Trivial many.

A control chart is also known as the SPC chart or Shewhart chart. It is a graphical representation of the collected information/data and it helps to monitor the process centering or process behavior against the specified/set control limits.

A control chart is a very powerful tool to Investigate/disclose the source of Process Variations present in the manufacturing processes. Tells when to take necessary action to eliminate the Common or Random or Chance variations and Special causes of variations.

The control chart helps to measure and analyze the process capability and performance  ( Cp and Cpk and Pp and Ppk ) of the production process.

A Scatter diagram is also known as Correlation Chart, Scatter Plot, and Scatter Graph. A Scatter graph is used to find out the relationship between two variables. In other words, it shows the relationship between two sets of numerical data. Scatter graph shows a Positive or Negative correlation between two variables.

Independent variable data and dependent Variable data are customarily plotted along the horizontal X-axis and Vertical Y-axis respectively. Independent variable is also called controlled parameters.

Stratification Diagram

A technique used to analyze and divide a universe of data into homogeneous groups is called -Strata. Stratification tools are used when the data come from different sources or conditions, such as data collected from different shifts, machines,  people, days,  suppliers and population groups, etc.

Process Flow Chart

A  Process Flow Chart  (PFC) is a diagram of the separate steps of a operations/process in sequential order. PFC is also known as  process flow diagram  (PFD), and Process Map.

WHY DO WE NEED 7 QC TOOLS

We need Quality Tools for :

• Problem Solving – making decisions & judgments.
• For Process Measurement.
• For continual improvement in products, processes, and services.
• To improve Quality , Productivity, and Customer Satisfaction.

“95% of the problem is solved when clearly defined”

“95% of quality-related problems in the organization can be solved by using seven fundamental quantitative tools.”

7QC Tools benefits

The major benefits of QC tools are:

• To analyze and solve quality problems effectively.
• Improve product and process quality .
• Enhance customer satisfaction.
• Reduce cost due to poor quality.
• Helps in investigating the potential causes and real root cause of the problem for taking effective countermeasures.
• Check sheet helps in data collection and recording for quality problem analysis.  
• Identify and reduce the process variation using the SPC quality tool .
• The Pareto QC tool helps to narrow down the quality problem using the 80/20 rule.
• Helps in identifying the various sources of variations present in the process.
• Improve the employee’s analytical and problem-solving skills.

The new seven QC Tools are used for planning, goal setting, and problem-solving. These are explained below :

Affinity Diagram – KJ Method. This tool is used for Pinpointing the Problem in a Chaotic Situation and generating solution strategies.

Gathers large amounts of verbal data such as ideas, opinions, and issues, and organizes the data into groups based on natural relationships.

Tree Diagram – Also known as Systematic diagram or Dendrograms, Hierarchy diagram, Organisation chart, and Analytical Tree.

This diagram is used for systematically pursuing the best strategies for achieving an objective.

The advantages of the tree diagram are that it facilitates agreement among the team and is extremely convincing with strategies.

Relation Diagram – It is used for cause identification. For finding solutions strategies by clarifying relationships with Complex Interrelated Causes.

Allows for “Multi-directional” thinking rather than linear. Also known as Interrelationship diagrams.

Process Decisions Program Charts (PDPC) – Also called Decision Process Chart. It is used to produce the desired result from many possible outcomes.

The chart is used to plan various contingencies.

PDPC enables problems to be pinpointed.

Matrix Diagram – used for Clarifying Problems. It clarifies relationships among different elements.

Matrix Data Analysis – Matrix + Num. Analysis.

This can be used when the Matrix diagram does not give sufficient information.

This is used in various fields like process analysis, new product planning, market surveys, etc.

Arrow Diagram – Gantt Chart + PERT/CPM Chart.

An arrow diagram is employed for understanding optimal schedules and controlling them effectively.

This shows relationships among tasks needed to implement a plan.

This diagram is extensively used in PERT (Program Evaluation and Review Technique) and CPM (Critical Path Method).

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Guide: 5W1H Is/Is Not Problem Definition

Author: Daniel Croft

Daniel Croft is an experienced continuous improvement manager with a Lean Six Sigma Black Belt and a Bachelor's degree in Business Management. With more than ten years of experience applying his skills across various industries, Daniel specializes in optimizing processes and improving efficiency. His approach combines practical experience with a deep understanding of business fundamentals to drive meaningful change.

Being effective at solving problems can often be difficult particularly when you dont know where to start. This is where the 5W1H Is/Is Not technique is useful. This technique uses six basic questions (5W) Who, What, Where, When, Why, and (1H) How to help you really understand a problem before diving into solving it. This used along side the Is/Is not Problem definition method further helps create a strong understanding what is in scope of the problem and what is not in scope.

What is 5W1H Is/Is Not Problem Definition?

The 5W1H Is/Is Not Problem Definition is a structured approach to problem-solving that aims to provide a clear understanding of a particular issue by exploring the issues from all angle. The acronym stands for “Who, What, Where, When, Why, and How.” In this method, you ask these questions to understand the boundaries of the problem for example:

• Who: Who is affected by the problem? Who are the stakeholders?
• What: What is the issue? What is not the issue?
• Where: Where is the problem occurring? Where is it not occurring?
• When: When does the problem happen? When does it not happen?
• Why: Why is this a problem? Why might it have occurred?
• How: How does the problem manifest? How can it be solved?

By asking “Is” and “Is Not” for each of these categories, you’re setting the scope of the problem, making it easier to focus on what needs to be addressed. This method is particularly useful for complex issues where multiple factors could be at play.

Below is an example of a simple completed 5Wh1H Is/Is not table.

Why is 5W1H Is/Is Not Problem Definition Important?

While the method used to create a problem definition may not be important, the creation of an effective problem definition is to ensure you have the focus on the correct problem as it is easy to have the focus go beyond the scope. Using 5W1H and Is/Is not is a useful tool for achieving this and can provide multiple benefits such as:

Proving Clarity: A well defined problem statement using 5W1H helps in clearly defining the problem, eliminating any ambiguity. This is critical for stakeholders to gain a clear understanding.

Setting the Scope: By asking ‘Is Not’ questions, the method helps in setting the boundaries, ensuring that the team does not stray into unrelated issues, thereby conserving resources. One of the biggest risks to projects is scope creep leading to the project scope being too vast to address effectively.

Root Cause Analysis: The ‘Why’ and ‘How’ questions are particularly useful for understanding the problem and provide a useful first step in getting to the root cause of the problem.

Stakeholder Involvement: By identifying ‘Who’ is affected, you can ensure you involve the right people in the problem-solving process.

How to Use 5W1H Is/Is Not Problem Definition

Step 1: create your team.

Get everyone who is impacted by or involved in solving the problem to be part of the team this can be those that work for the company as well as suppliers and customers where necessary to ensure a all angles are covered.

Step 2: Start with ‘What’

Using a 5W1H Is/Is Not template start with the first question of “What” and explain What the problem IS and what the problem IS Not and ensure that all the stakeholders agree before moving on to the next questions.

Step 3: Go Through Each Question

Now go through each of the remaining questions carefully answering the Is and the Is not for each.

For example:

• Who: The production team
• What: Faulty widgets from Machine A
• Where: Production Line 1
• When: During the second shift
• Why: Calibration issue in Machine A
• How: Incorrect settings

Also, note down what each aspect is not. This sets boundaries.

Step 4: Review and Refine

Once you’ve answered all the questions, review them. Make sure they are specific and agreed upon by everyone. If they are not specific and agreed they should be reviewed and clarified by the team to ensure everyone is on the same page when moving forward with the project or solving the problem.

Step 5: Take Action

Now that you’ve clearly defined the problem, it’s time to solve it. Since you’ve also asked ‘How’ and ‘Why,’ you probably have some ideas for solutions.

For techniques around addressing problems can consult our comprehensive list of guides.

In Conclusion, the 5W1H Is/Is Not template is a useful tool for delving into a topic and gaining a better understanding of it. You can create a clear understanding of a topic and identify any misconceptions or areas of confusion by asking and answering the six questions. You can also clarify any misunderstandings and distinguish your topic from similar topics by addressing the “Is Not” section of the template.

• Knop, K. and Mielczarek, K., 2018. Using 5W-1H and 4M Methods to Analyse and Solve the Problem with the Visual Inspection Process-case study. In  MATEC Web of Conferences  (Vol. 183, p. 03006). EDP Sciences.
• Yusoff, N.M., Zakaria, N.A. and Harum, N., 2019. Problem analysis of RPL overhead in 6LOWPAN using 5W1H model .  Int. J. Innov. Technol. Explor. Eng ,  8 (12), pp.5300-5305.
• Changqing, G., Kezheng, H. and Fei, M., 2005. Comparison of innovation methodologies and TRIZ .  The TRIZ Journal, Issue (September 2005) .

A: The 5W1H Is/Is Not problem definition is a technique used to clearly define a problem by answering six fundamental questions: Who, What, When, Where, Why, and How.

A: The 5W1H Is/Is Not problem definition helps to eliminate ambiguity and ensure a thorough understanding of the problem at hand. It provides a structured approach to defining problems, which aids in effective problem-solving and decision-making.

A: The technique involves asking a series of questions: Who is involved? What is the problem? When does the problem occur? Where does it happen? Why is it happening? And how is it happening? Additionally, answering the corresponding “Is Not” questions helps to set boundaries and clarify what the problem is not.

Daniel Croft

Hi im Daniel continuous improvement manager with a Black Belt in Lean Six Sigma and over 10 years of real-world experience across a range sectors, I have a passion for optimizing processes and creating a culture of efficiency. I wanted to create Learn Lean Siigma to be a platform dedicated to Lean Six Sigma and process improvement insights and provide all the guides, tools, techniques and templates I looked for in one place as someone new to the world of Lean Six Sigma and Continuous improvement.

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Scientific Problem Solving using the 7 Quality Tools

Master analytical techniques and quality improvement strategies, integrating the power of the 7 Quality Tools within scientific contexts, to identify, analyze, and solve problems efficiently

Lectures - 32

Resources - 20

Duration - 3 hours

Training 5 or more people ?

Get your team access to 10000+ top Tutorials Point courses anytime, anywhere.

Course Description

These tools help to identify, examine, and solve queries related to quality, process, and performance. They're simple to learn, but still effective, making them perfect for anyone involved in quality improvement. These tools are easy to use and understand, and they can be applied to a wide range of industries and situations.

This course includes:

Self-Paced Complete Video Tutorial

Downloadable & Customizable Templates 

PDF Tutorials

This course is designed to equip students with knowledge, and skills to:

• The Scientific Approach: A3 Thinking 
• The 7 QC Tools with video tutorials

Prerequisites

No prerequisites are required to take this course. 

Check out the detailed breakdown of what’s inside the course

Instructor Details

Ahmed Radwan

A seasoned professional with over 14 years of experience in lean manufacturing and operational excellence. Ahmed holds a Master of Business Administration and a deep understanding of various continuous improvement concepts, tools and methodologies. 

His credentials include:

• Certified Lean Six Sigma Black Belt (IASSC)
• Certified Lean Six Sigma Master Black Belt (CSSC)
• Certified Lean Bronze (Shingo Institute)
• Certified Professional Scrum Master (Scrum.org)
• Hoshin Kanri (Lean Enterprise Institute)
• Project Management Professional (PMI)

Ahmed's expertise extends beyond certifications. He brings a practical approach, honed through years of real-world experience, to ensure that our training translates into tangible results for your organization.

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What is Software Quality Management, and Why is It Essential?

• Written by Contributing Writer
• Updated on September 3, 2024

Software that fails to meet quality standards can lead to lost time, increased costs, and dissatisfied users. Software quality management (SQM) offers a solution to this problem. By establishing clear standards, meticulous planning, and rigorous testing, SQM ensures that your software meets high-quality benchmarks. Quality management systems help avoid issues and make the development process smoother.

Six Sigma helps improve processes and fix defects. Combining it with SQM can take your software quality to the next level, making each project successful.

This blog will explore SQM’s role and significance and discuss how adopting best practices can transform your development process.

Consider integrating Six Sigma training into your strategy to enhance your SQM efforts and achieve even greater quality control.

What is Software Quality Management?

Software quality management is a holistic approach that ensures software meets high-quality standards throughout its development. SQM involves three main components:

Software Quality Assurance (SQA)

SQA establishes standards, guidelines, and processes early in the development cycle to prevent defects. It also ensures that everyone on the team understands their responsibilities and follows best practices to create high-quality software.

Software Quality Planning (SQP)

SQP integrates the guidelines from SQA into the project’s roadmap. It involves creating a detailed quality plan that outlines when and how quality checks will be performed, who is responsible, and what resources are needed.

Software Quality Control (SQC)

In SQC, we test and review the software to ensure it meets the quality standards set by SQA and outlined in the SQP. SQC aims to identify and fix defects before the software goes live, ensuring it performs as expected.

Also Read: What is Process Capability? Index, Formula, Example & Everything to Know

Desirable Qualities of Software

The ultimate goal of SQM is to balance multiple software quality attributes. This ensures the software performs as intended and meets its specific objectives. Here are the main aspects of software quality.

• Reliability : The software should operate consistently without failures under defined conditions.
• Usability : It must be easy to use and understand, providing a good user experience.
• Efficiency : The software should use resources like memory and processing power optimally.
• Maintainability : It should be easy to modify, extend, or fix.
• Portability : The software should function with minimal changes across different environments and platforms.
• Security : Protecting the software and its data from unauthorized access and breaches is crucial.

Why Managing Software Quality is Important

High-quality software helps a business outpace competitors and attract customers who demand reliability, security, and exceptional user experiences.

Let’s dig into the main benefits of software quality management systems:

• Streamlines processes and identifies issues early, allowing the team to focus on adding value.
• Ensures the software meets high standards, leading to a more reliable and robust product.
• Provides accurate and up-to-date defect tracking, improving testing strategies for better results.
• Identifies and addresses defects early, saving money and speeding up development.
• Strengthens product development and test management strategies, leading to better decision-making.
• Prevents costly late-stage fixes, helping to stay on schedule and within budget.
• Enhances the company’s reputation, potentially leading to increased profits and customer loyalty.
• Delivers high-quality products that meet user expectations, resulting in happier customers and a better user experience.

Also Read: What is Zero Defect? What it Means, its Applications, and Limitations

What Approaches Do Quality Engineers Use to Ensure Software Quality?

• Static Analysis: This involves analyzing the software’s code without executing it, using tools to detect potential issues like syntax errors, security vulnerabilities, and code complexity.
• Dynamic Testing: Quality engineers run the software under different conditions to check its behavior, focusing on finding defects and ensuring it meets its functional and non-functional requirements.
• Automated Testing: Automation tools execute tests and compare actual outcomes with expected results. This is particularly useful for regression testing, where changes are frequently made to the software.
• Code Reviews: Peer reviews of the software’s code help identify defects early and ensure adherence to coding standards.
• Continuous Integration/Continuous Deployment (CI/CD): This approach involves integrating changes regularly and deploying them automatically, ensuring defects are quickly caught.
• Quality Assurance Audits: Periodic audits help ensure that the processes and standards followed during development align with the organization’s quality policies.

Key Stages of Managing Software Quality

The following are the stages in software quality management.

Defining Quality Objectives

The first step is to define clear quality objectives. These objectives should align with the project’s goals and the customer’s needs. For instance, if you’re working on an e-commerce website, your quality objectives might include ensuring the site loads quickly and securely processes payments.

Project managers and quality managers lead this effort. They work with stakeholders to set specific, measurable goals for the project. For example, they might set a goal that the website should load within three seconds under normal conditions and process payments with 99.9% accuracy.

Requirements Analysis

The next step is to understand and document the software requirements thoroughly. This ensures everyone is clear on what needs to be developed and what quality standards must be met. For instance, if you’re building a project management tool, your requirements might include features like task tracking, team collaboration, and reporting capabilities.

Business analysts and requirements engineers are crucial in this stage. They gather detailed information from stakeholders, such as project managers and team members, and ensure the development team fully understands these needs. This step helps avoid confusion and ensures the final product aligns with user expectations and business goals.

Also Read: Quality Management Breakdown: What is Measurement System Analysis?

Quality Planning

Quality planning involves creating a detailed plan to achieve the quality objectives. This includes deciding on testing methods, review processes, and performance benchmarks. For example, suppose you’re building a new social media platform. In that case, your plan might include manual and automated testing strategies to ensure the platform can handle many simultaneous users.

Quality analysis (QA) specialists and project managers are responsible for developing this plan. They outline how to test the software, what processes to follow for reviews, and how to measure performance. Their work ensures that quality is built into every stage of development.

Risk Assessment

Risk assessment identifies potential software quality risks and develops strategies to address them. For example, if you’re creating a healthcare app, a risk might be that sensitive user data could be exposed. You need to plan for strong data encryption and regular security audits.

Risk managers and QA specialists are crucial in this stage. They identify possible risks, such as data breaches or system failures, and create plans to mitigate these issues. Proactively addressing risks help ensure the software remains secure and reliable.

Quality Assurance

Quality assurance involves implementing processes and practices to ensure adherence to quality standards throughout development. This includes conducting regular reviews, audits, and inspections to identify defects early. For instance, if you’re developing a video streaming service, you might conduct regular code reviews and performance tests to ensure smooth playback and high video quality.

QA analysts and testers handle these tasks. They check the software regularly, perform inspections, and ensure that quality standards are consistently met throughout the development cycle.

Quality Control

Quality control focuses on executing testing procedures to find defects and verify that the software meets specified requirements. This includes unit testing, integration testing, system testing, and user acceptance testing.

Let’s say you’re working on a banking application. Here, unit testing might involve checking individual components like login functions, while user acceptance testing ensures the app is easy for customers to use. Testers and quality control engineers perform these tests. They identify and fix defects, ensuring the final product works as intended and meets user requirements.

Continuous Monitoring

Continuous monitoring involves tracking the software development process to identify issues and deviations from the quality plan. For example, if a new feature is added to an app, continuous monitoring helps ensure it integrates well with existing features and does not introduce new problems.

Project managers and QA leads monitor the development process, track progress, and address any issues promptly. Their constant supervision keeps the project on track and fixes any new problems quickly.

Metrics and Measurement

Finally, collecting and analyzing metrics helps assess the software’s quality and performance. For example, tracking user feedback, defect rates, and performance metrics can provide insights into how well the software performs and whether it meets quality standards. Data analysts and QA specialists collect and review these metrics. They use the information to assess the effectiveness of quality management and suggest ways to improve.

Also Read: Six Sigma Calculator: How to Use It?

Top Metrics for Software Quality Management Systems

SQM metrics are quantitative measures used to assess, monitor, and improve software quality throughout its development and maintenance. Here are some key metrics to watch out for:

Meantime To Recover (MTTR)

MTTR tells you how fast your team can fix serious issues. A short MTTR means problems are resolved quickly, keeping your software running smoothly and users satisfied.

Cycle time measures how long it takes to complete a task from start to finish. Knowing this helps you predict how long future tasks might take and better manage your deadlines.

Application Crash Rate

This shows how often your app or website crashes. A lower crash rate means your code is more stable, which leads to a better user experience and fewer disruptions.

Lead time tracks the period from the start of a project to the delivery of a feature. It helps you see how efficiently your team works and whether you meet your deadlines.

Team Velocity

Team velocity tells you how many user stories or tasks your team finishes in a sprint. This metric helps you understand your team’s productivity and plan future sprints more accurately.

Defect Count Per Sprint

This counts the number of defects found during each sprint. It helps you assess the work’s quality and identify areas for improvement.

First-Time Pass Rate

This metric shows how many test cases pass on the first try. A high rate means your development and testing practices are strong.

Software Quality Management Best Practices

To keep your software running smoothly and meet quality standards, here are some best practices to follow:

Separate Security and Performance Testing

Security and performance testing require different skills. Having separate teams for these tasks ensures that each area gets the focus it needs. Security teams handle vulnerabilities, while performance teams focus on speed and efficiency.

Use a Bug-Tracking Tool

A bug-tracking tool helps you organize and track software bugs. It allows you to categorize bugs by severity and priority, track their resolution, and monitor improvements. This type of quality management systems software keeps everyone in the loop and makes it easier to manage quality.

Collaborate Closely with Your Development Team

Clear communication with your development team is essential. Regular updates and clear expectations help ensure everyone understands the quality standards and has the resources needed. Tools like JIRA and Slack can facilitate smooth interactions and project management.

Simulate the End-User Environment

Testing your software as end-users would use it helps uncover real-world issues. Conduct user testing to collect feedback and fix problems before launching the product. This ensures your software meets user needs and expectations.

Use a Two-Tier Test Automation Approach

Combining manual and automated testing helps you cover all bases. Manual testing can identify issues that automation might miss, while automated tests speed up repetitive tasks. This approach ensures thorough testing within a reasonable timeframe.

Run Regression Tests

Regression testing checks if new changes or updates haven’t disrupted existing features. Running these tests before releasing updates helps confirm that your software continues functioning as intended.

Testing early in the development process helps identify issues before they escalate. Identifying and fixing problems sooner saves time and effort and ensures the final product meets quality standards.

Also Read: Six Sigma Certification Cost: Here’s A Comprehensive Guide

Master SQM and Boost Your Career with Six Sigma Expertise

Understanding SQM is crucial for producing dependable and user-friendly software. It’s a must-have skill for you if you’re interested in roles like quality Control Manager, QA Specialist, Project Manager, or Product Engineer. The knowledge of SQM will enable you to contribute effectively to a team, manage projects smoothly, and ensure the final product meets user expectations.

Take the next step and consider enrolling in our comprehensive Six Sigma program to deepen your expertise and enhance your skills. This 12-week online bootcamp, endorsed by top universities, offers real-world case studies, KPMG capstone projects, and exclusive GenAI modules. Learn from top faculty, gain practical experience, and receive an industry-recognized certificate upon course completion.

You might also like to read:

Six Sigma Control Charts: An Ultimate Guide

All About Six Sigma Yellow Belt Salaries

Who is a Quality Manager? Job Description, Skills & Salary

Lean Thinking: Transforming Efficiency in Your Business

What is a Quality Engineer? A Comprehensive Guide to the Profession

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• MoSCoW Method

What is the MoSCoW Method?

The MoSCoW Method is a prioritization tool that helps professionals in managing their time and effort .

To do so, it proposes to classify the importance of the different characteristics of a product (or a Project) according to their importance .

Its name is an acronym of the 4 Prioritization Categories proposed (adding two “o”):

• M ust Have .
• S hould Have .
• C ould Have .
• W on’t Have .

Four Prioritization Categories

Must Have : Essential Requirements that the product or project must have.

• Critical Features without replacement.

Should Have : Important desired Requirements for the product or project.

• They can be substituted if necessary.

Could Have : Improvements to the product or project.

• There are different alternatives.

Won’t have : Characteristics agreed not to be adopted .

• No one will waste time implementing them.

Let’s see the first example:

MoSCoW Method example

Imagine that you have been hired to create a Website for a Law firm.

They want a professional Site where people can Register and, once inside, track their court cases .

Since you want to deliver the best possible Site on time, you decide to follow the MoSCoW method .

How does it look like?

Must Have :

• Solid programming without any bugs.
• A Solid Register System.
• A Safe and Reliable personal directory.

Should Have :

• A Fast Site.
• An outstanding Design.
• Notifications sent by e-mail.

Could Have :

• Custom menus.
• Suggestions.
• A Blog section with latest news.

Won’t Have :

• Paid content.
• A Public Members section.

As we usually say, this Method may seem obvious.

Then… Why is it important?

Why is the MoSCoW Method important?

Many of professionals end up wasting time , effort and resources on useless task s that are ultimately not essential at all.

Surely you have experienced this situation working in a Team:

• Everyone spends hours modifying a minor feature and, ultimately, the important thing is missing .

That is why this Method is so important:

• Because it concentrates your efforts and forces you to think about what is really important .

As you can imagine, this Tool can be employed in practically all kinds of situations.

But when do we especially recommend it?

When should you use the MoSCoW Method?

We highly recommend to use the MoSCoW Method:

• To put order and prioritization.
• To avoid wasting time with non-essential touch-ups.
• In order to meet the Essential Requirements.
• When the product can have very different characteristics.

Now, let’s see more examples:

MoSCoW Method examples

We have chosen different real examples where the MoSCoW Method can be of great help for the development of certain products.

Let’s begin:

A Wallet - MoSCoW Method example

Let’s imagine that you are developing a wallet .

As you know, wallets are very modular products.

They can have:

• Several or few departments for cards.
• Coin purse… or not.
• 1 or 2 bill slots.

There is not a canonical wallet (one that is the benchmark for all the others).

• That is why you decided to use the MoSCoW Method to develop it.

After some thoughts, you decide that your wallet:

• 2 bill slots.
• 8 compartments for credit cards.
• High resistance materials and sewing.
• Leather as its main material.
• A translucid Credit card compartment.
• A transverse horizontal compartment.
• A striking color on the inside of the bill slots.
• Completely black exterior color.
• One translucid compartment for small photos.
• A Coin purse.
• A Passport compartment.

Making a Cake - MoSCoW Method example

In this example, we’ll imagine that you are preparing a wedding Cake .

• You have a very rigid deadline (the wedding day, of course).

In addition, as you also know, Cakes can have lots of variations.

• We could say they are very modular .

That is why you decide to use the MoSCoW Method.

How does it look?

Well, your Cake:

• White coating.
• Two sugar figurines on top.
• 6 layers of sponge cake inside.
• Belgian chocolate between the layers.
• Decorations on the edges
• Sugar flowers.
• Chocolate balls.
• Scattered sugar pearls.
• Multicolor layers.
• An excessive amount of decoration.
• Fruit flavor.

Designing a Poster - MoSCoW Method example

You are now an artist hired to Design a poster for a Rock concert.

Obviously, this is a Design job with infinite variations possible.

• Also, you have a close deadline to finish it.

No need to mention that you will use the MoSCoW Method.

Finally, the Poster:

• The name of the Main rock band, very prominent.
• Images and colors that best suit their style.
• A typeface that best suits the musical style.
• An illustration related to Rock in the middle.
• The name of the rest of the bands that will play.
• Where and when it will take place.
• Where you can buy the tickets.
• Nearby metro and bus stations.
• The name of the city.
• The maximum capacity of the stadium
• At what time each band will play.

Summarizing

The MoSCoW Method is a prioritization tool that helps professionals in managing their time and effort.

It proposes to classify the importance of the different characteristics of a product in 4 Categories :

• M ust Have.
• S hould Have.
• C ould Have.
• W on’t Have.

Although this Method can be used in all kinds of situations, we highly recommend to use it:

• When working in a team .
• In Design tasks .
• When there is a close deadline .
• With modular products or projects .
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MoSCoW Method of Prioritization explained

MoSCoW Method: This article explains MoSCoW Method in a practical way. Next to what it is (meaning, acronym and origin), and which advantages are connected to using this model, this article also highlights the MoSCoW Method requirements, including a practical example. You will also learn how applying this method will enable you and the team to reach deadlines in time. Enjoy reading!

What is the MoSCoW Method of Prioritization?

Prioritising is often challenging. Particularly when it comes the implementation of new ideas and / or technologies. Everyone in an organisation always wants everything to be done right away and that is practically impossible. There are several tools available to make prioritisation easier. The MoSCoW Method of Prioritization is one them.

The MoSCoW Method is a prioritization technique, which can be used in a variety of situations.

Origin and advantages of the MoSCoW Method

The method was developed by  Dai Clegg, a developer working for the software company Oracle .

Originally, it was used to categorize product features, derived from user stories. It was later used in the Dynamic System Development Method (DSDM) . The method contains multiple prioritization categories, with labels for each requirement, making it easier to prioritise.

Even though the origin of this prioritize method is in software development, it is also highly applicable for agile project management, market launches, product releases, starting a new business or change processes.

With the MoSCoW Method, requirements are determined for the result of the project or product. It is about setting requirements by order of priority. The most important requirements need to be met first for a greater chance of success.

Meaning and acronym of the MoSCoW Method

Moscow is an acronym made up of the first letters. The two Os have been added to make the word ‘moscow’ readable, they don’t have any meaning themselves. The M stands for ‘Must haves’ , S for ‘Should haves’ , C for ‘Could haves’ and W for ‘Won’t haves’ or ‘Would haves’ .

Figure 1 – the MoSCoW Method acronym

The requirements when you start with the MoSCoW Method

It’s a good idea to first specify the requirements together with all team members before starting the MoSCoW Method. When determining the requirements, you should take into account what is important to all the stakeholders. Brainstorming with everyone involved will lead to good, qualitative requirements.

The requirements are prioritised to prevent them from becoming to expensive or unrealistic. The main goal is to come up with requirements that add the most value for the company. The project requirements are divided into one of the following categories:

M – Must haves

These are about the minimal requirements that are determined in advance that the end-result has to meet.

Without meeting these requirements, the project fails and the product won’t be use-able. They are a necessity for a workable product and there is no alternative. The ‘Must haves’ are essential. MUST is also explained as an acronym that stands for Minimum Use-able SubseTs.

As an extra exam assignment, University of Applied Sciences Automotive students have been asked to design a car that can at least drive (minimal requirements).

It’s okay if the car only has a chassis, without any bodywork. It’s about the construction of the individual parts and drive train to the combustion engine. In this case, the Must have is that they have a drivable car by the end of the academic year.

S – Should haves

These are additional and much desired requirements that have a high priority, but are not essential for a usable end product. The product will be usable even if these requirements aren’t met. When they are met, they will only add to the value of the product. Depending on the available time, you can always return to these requirements at a later time.

The University of Applied Sciences Automotive student might like to add a tow bar to the car (should have), but as long as the car can drive without the tow bar, their project will be successful. They can always add the tow bar at a later stage.

C – Could haves

These requirements can be considered if there’s time left. If not, it’s no problem and will not have a negative effect on the final result. The ‘Could haves’ have a lower priority than the ‘Should haves’ .

This option will only be included if there really is more than enough time to make it work. This category is also referred to as ‘nice to have’; they’re more a wish than an absolute requirement.

The University of Applied Sciences Automotive students would perhaps like to install a tachometer in the car. It’s not an important (exam) requirement, but it’d be great if they manage to do it.

W – Won’t haves (and would haves)

These are about wishes for the future that are often impossible to realise or cost a lot of time. If it’s simply not possible, it’s best not to waste any energy on it.

If it is achievable, then a lot of time (and money) will have to be invested and it’s labelled a ‘Would have’. ‘Would haves’ are often followed upon at a later stage after the initial project is finished.

The University of Applied Sciences Automotive students don’t have to make a car that will actually drive on public roads.

It’s meant for study. If they do want to take it on public roads, it will need bodywork and comply with safety standards. It also involves getting approval from the Vehicle Standards Agency in elaborate process.

How to reach deadlines using the MoSCoW Method of Prioritization?

Correctly applying and sticking to the MoSCoW Method will lead to a clear way to lead a project. Everyone involved with the project will know what needs to be done first, when it has to be finished and why it’s important. By assigning priorities to requirements, a project becomes more manageable and it’ll be easier to meet the deadline.

It’s Your Turn

What do you think? How do you apply the MoSCoW analysis in your project or organisation? Do you recognize the practical explanation or do you have more additions? What are your success factors for applying the MoSCoW Method?

Share your experience and knowledge in the comments box below.

More information

• Baxter, R. (2004). Software engineering is software engineering . In 26th International Conference on Software Engineering, W36 Workshop Software Engineering for High Performance System (HPCS) Applications (pp. 4-18).
• Stephens, R. (2015). Beginning Software Engineering . Wrox Publishing .
• Hatton, S. (2008). Choosing the right prioritisation method. In Software Engineering, 2008. ASWEC 2008 . 19th Australian Conference on (pp. 517-526). IEEE.
• Robson, W.A., Simon, Shena. (2014). Moscow in the making . Taylor & Francis Ltd.

How to cite this article: Mulder, P. (2017). MoSCoW Method of Prioritization . Retrieved [insert date] from Toolshero: https://www.toolshero.com/project-management/moscow-method/

Original publication date: 05/12/2017 | Last update: 05/27/2024

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Patty Mulder

Patty Mulder is an Dutch expert on Management Skills, Personal Effectiveness and Business Communication. She is also a Content writer, Business Coach and Company Trainer and lives in the Netherlands (Europe). Note: all her articles are written in Dutch and we translated her articles to English!

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One response to “moscow method of prioritization explained”.

Thanks for providing a concise and easily understandable explanation. The one thing that stood out to me however, is the example for the Should Have section. Tow bars are clearly “Could have” at best and in this situation would probably end up in the “Won’t have” bucket simply because there’s no justification for them at all on an experimental vehicle that will not be driven on a public road. To make this more believable I’d recommend changing the example for “Should Haves” to either: Seats – the vehicle should have a seat for the driver but as long as someone can drive it somehow it’s not critical. Or Steering Wheel – ideally the vehicle should have a steering wheel, but as long as it CAN be steered (perhaps by levers) then the project will pass. Otherwise, this is a really useful article. Thanks again.

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