Eight Disciplines of Problem Solving (8D)

– Eight Disciplines of Problem Solving –

⇓   Introduction to 8D

⇓   What is 8D

⇓   Why Apply 8D

⇓   When to Apply 8D

⇓   How to Apply 8D

Quality and Reliability Support | Quality-One

Introduction to Eight Disciplines of Problem Solving (8D)

The Eight Disciplines of Problem Solving (8D) is a problem solving methodology designed to find the root cause of a problem, devise a short-term fix and implement a long-term solution to prevent recurring problems. When it’s clear that your product is defective or isn’t satisfying your customers, an 8D is an excellent first step to improving Quality and Reliability.

Ford Motor Company developed this problem solving methodology, then known as Team Oriented Problem Solving (TOPS), in the 1980s. The early usage of 8D proved so effective that it was adopted by Ford as the primary method of documenting problem solving efforts, and the company continues to use 8D today.

8D has become very popular among manufacturers because it is effective and reasonably easy to teach. Below you’ll find the benefits of an 8D, when it is appropriate to perform and how it is performed.

What is Eight Disciplines of Problem Solving (8D)

The 8D problem solving process is a detailed, team oriented approach to solving critical problems in the production process. The goals of this method are to find the root cause of a problem, develop containment actions to protect customers and take corrective action to prevent similar problems in the future.

The strength of the 8D process lies in its structure, discipline and methodology. 8D uses a composite methodology, utilizing best practices from various existing approaches. It is a problem solving method that drives systemic change, improving an entire process in order to avoid not only the problem at hand but also other issues that may stem from a systemic failure.

8D has grown to be one of the most popular problem solving methodologies used for Manufacturing, Assembly and Services around the globe. Read on to learn about the reasons why the Eight Disciplines of Problem Solving may be a good fit for your company.

8D - Problem Solving Format

Why Apply Eight Disciplines of Problem Solving (8D)

The 8D methodology is so popular in part because it offers your engineering team a consistent, easy-to-learn and thorough approach to solving whatever problems might arise at various stages in your production process. When properly applied, you can expect the following benefits:

  • Improved team oriented problem solving skills rather than reliance on the individual
  • Increased familiarity with a structure for problem solving
  • Creation and expansion of a database of past failures and lessons learned to prevent problems in the future
  • Better understanding of how to use basic statistical tools required for problem solving
  • Improved effectiveness and efficiency at problem solving
  • A practical understanding of Root Cause Analysis (RCA)
  • Problem solving effort may be adopted into the processes and methods of the organization
  • Improved skills for implementing corrective action
  • Better ability to identify necessary systemic changes and subsequent inputs for change
  • More candid and open communication in problem solving discussion, increasing effectiveness
  • An improvement in management’s understanding of problems and problem resolution

8D was created to represent the best practices in problem solving. When performed correctly, this methodology not only improves the Quality and Reliability of your products but also prepares your engineering team for future problems.

When to Apply Eight Disciplines of Problem Solving (8D)

The 8D problem solving process is typically required when:

  • Safety or Regulatory issues has been discovered
  • Customer complaints are received
  • Warranty Concerns have indicated greater-than-expected failure rates
  • Internal rejects, waste, scrap, poor performance or test failures are present at unacceptable levels

How to Apply Eight Disciplines of Problem Solving (8D)

The 8D process alternates inductive and deductive problem solving tools to relentlessly move forward toward a solution. The Quality-One approach uses a core team of three individuals for inductive activities with data driven tools and then a larger Subject Matter Expert (SME) group for the deductive activities through brainstorming, data-gathering and experimentation.

D0: Prepare and Plan for the 8D

Proper planning will always translate to a better start. Thus, before 8D analysis begins, it is always a good idea to ask an expert first for their impressions. After receiving feedback, the following criterion should be applied prior to forming a team:

Collect information on the symptoms

Use a Symptoms Checklist to ask the correct questions

Identify the need for an Emergency Response Action (ERA), which protects the customer from further exposure to the undesired symptoms

D1: Form a Team

A Cross Functional Team (CFT) is made up of members from many disciplines. Quality-One takes this principle one step further by having two levels of CFT:

  • The Core Team Structure should involve three people on the respective subjects: product, process and data
  • Additional Subject Matter Experts are brought in at various times to assist with brainstorming, data collection and analysis

Teams require proper preparation. Setting the ground rules is paramount. Implementation of disciplines like checklists, forms and techniques will ensure steady progress.  8D must always have two key members: a Leader and a Champion / Sponsor:

  • The Leader is the person who knows the 8D process and can lead the team through it (although not always the most knowledgeable about the problem being studied)
  • The Champion or Sponsor is the one person who can affect change by agreeing with the findings and can provide final approval on such changes

D2: Describe the Problem

The 8D method’s initial focus is to properly describe the problem utilizing the known data and placing it into specific categories for future comparisons. The “Is” data supports the facts whereas the “Is Not” data does not. As the “Is Not” data is collected, many possible reasons for failure are able to be eliminated. This approach utilizes the following tools:

  • Problem Statement
  • Affinity Diagram (Deductive tool)
  • Fishbone/Ishikawa Diagram (Deductive tool)
  • Problem Description

D3: Interim Containment Action

In the interim, before the permanent corrective action has been determined, an action to protect the customer can be taken. The Interim Containment Action (ICA) is temporary and is typically removed after the Permanent Correct Action (PCA) is taken.

  • Verification of effectiveness of the ICA is always recommended to prevent any additional customer dissatisfaction calls

D4: Root Cause Analysis (RCA) and Escape Point

The root cause must be identified to take permanent action to eliminate it. The root cause definition requires that it can be turned on or off, at will. Activities in D4 include:

  • Comparative Analysis listing differences and changes between “Is” and “Is Not”
  • Development of Root Cause Theories based on remaining items
  • Verification of the Root Cause through data collection
  • Review Process Flow Diagram for location of the root cause
  • Determine Escape Point, which is the closest point in the process where the root cause could have been found but was not

D5: Permanent Corrective Action (PCA)

The PCA is directed toward the root cause and removes / changes the conditions of the product or process that was responsible for the problem. Activities in D5 include:

  • Establish the Acceptance Criteria which include Mandatory Requirements and Wants
  • Perform a Risk Assessment /  Failure Mode and Effects Analysis (FMEA) on the PCA choices
  • Based on risk assessment, make a balanced choice for PCA
  • Select control-point improvement for the Escape Point
  • Verification of Effectiveness for both the PCA and the Escape Point are required

D6: Implement and Validate the Permanent Corrective Action

To successfully implement a permanent change, proper planning is essential. A project plan should encompass: communication, steps to complete, measurement of success and lessons learned. Activities in D6 include:

  • Develop Project Plan for Implementation
  • Communicate the plan to all stakeholders
  • Validation of improvements using measurement

D7: Prevent Recurrence

D7 affords the opportunity to preserve and share the knowledge, preventing problems on similar products, processes, locations or families. Updating documents and procedures / work instructions are expected at this step to improve future use. Activities in D7 include:

  • Review Similar Products and Processes for problem prevention
  • Develop / Update Procedures and Work Instructions for Systems Prevention
  • Capture Standard Work / Practice and reuse
  • Assure FMEA updates have been completed
  • Assure Control Plans have been updated

D8: Closure and Team Celebration

Teams require feedback to allow for satisfactory closure. Recognizing both team and individual efforts and allowing the team to see the previous and new state solidifies the value of the 8D process. Activities in D8 include:

  • Archive the 8D Documents for future reference
  • Document Lessons Learned on how to make problem solving better
  • Before and After Comparison of issue
  • Celebrate Successful Completion

8D - D0 Reference Card

8D and Root Cause Analysis (RCA)

The 8D process has Root Cause Analysis (RCA) imbedded within it. All problem solving techniques include RCA within their structure. The steps and techniques within 8D which correspond to Root Cause Analysis are as follows:

  • Problem Symptom is quantified and converted to “Object and Defect”
  • Problem Symptom is converted to Problem Statement using Repeated Whys
  • Possible and Potential Causes are collected using deductive tools (i.e. Fishbone or Affinity Diagram)
  • Problem Statement is converted into Problem Description using Is / Is Not
  • Problem Description reduces the number of items on the deductive tool (from step 3)
  • Comparative Analysis between the Is and Is Not items (note changes and time)
  • Root Cause theories are developed from remaining possible causes on deductive tool and coupled with changes from Is / Is Not
  • Compare theories with current data and develop experiments for Root Cause Verification
  • Test and confirm the Root Causes

Is Is Not Example

Example: Multiple Why Technique

The Multiple / Repeated Why (Similar to 5 Why) is an inductive tool, which means facts are required to proceed to a more detailed level. The steps required to determine problem statement are:

  • Problem Symptom is defined as an Object and Defect i.e. “Passenger Injury”
  • Why? In every case “SUV’s Roll Over”
  • Why? In every case, it was preceded by a “Blown Tire”
  • Why? Many explanations may be applied, therefore the team cannot continue with another repeated why past “Blown Tire”
  • Therefore, the Problem Statement is “Blown Tire”
  • Why? Low (Air) Pressure, Tire Defect (Degradation of an Interface) and High (Ambient) Temperature
  • Counter measures assigned to low pressure and tire defect

This example uses only 4 of the 5 Whys to determine the root causes without going further into the systemic reasons that supported the failure. The Repeated Why is one way to depict this failure chain. Fault Tree Analysis (FTA) could also be used.

3 Legged 5 Why

Learn More About Eight Disciplines of Problem Solving (8D)

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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.

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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

quality management problem solving tools

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

quality management problem solving tools

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.

quality management problem solving tools

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

quality management problem solving tools

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.

quality management problem solving tools

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.

quality management problem solving tools

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.

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7 basic quality tools

What are the 7 basic quality tools, and how can they change your business for the better?

Reading time: about 6 min

What are the 7 basic quality tools?

  • Stratification
  • Check sheet (tally sheet)
  • Cause and effect diagram (fishbone or Ishikawa diagram)
  • Pareto chart (80-20 rule)
  • Scatter diagram
  • Control chart (Shewhart chart)

The ability to identify and resolve quality-related issues quickly and efficiently is essential to anyone working in quality assurance or process improvement. But statistical quality control can quickly get complex and unwieldy for the average person, making training and quality assurance more difficult to scale. 

Thankfully, engineers have discovered that most quality control problems can be solved by following a few key fundamentals. These fundamentals are called the seven basic tools of quality. 

With these basic quality tools in your arsenal, you can easily manage the quality of your product or process, no matter what industry you serve.

Learn about these quality management tools and find templates to start using them quickly.

Where did the quality tools originate?

Kaoru Ishikawa, a Japanese professor of engineering, originally developed the seven quality tools (sometimes called the 7 QC tools) in the 1950s to help workers of various technical backgrounds implement effective quality control measures.

At the time, training programs in statistical quality control were complex and intimidating to workers with non-technical backgrounds. This made it difficult to standardize effective quality control across operations. Companies found that simplifying the training to user-friendly fundamentals—or seven quality tools—ensured better performance at scale

7 quality tools

1. stratification.

Stratification analysis is a quality assurance tool used to sort data, objects, and people into separate and distinct groups. Separating your data using stratification can help you determine its meaning, revealing patterns that might not otherwise be visible when it’s been lumped together. 

Whether you’re looking at equipment, products, shifts, materials, or even days of the week, stratification analysis lets you make sense of your data before, during, and after its collection.

To get the most out of the stratification process, consider which information about your data’s sources may affect the end results of your data analysis. Make sure to set up your data collection so that that information is included. 

stratification example

2. Histogram

Quality professionals are often tasked with analyzing and interpreting the behavior of different groups of data in an effort to manage quality. This is where quality control tools like the histogram come into play. 

The histogram represents frequency distribution of data clearly and concisely amongst different groups of a sample, allowing you to quickly and easily identify areas of improvement within your processes. With a structure similar to a bar graph, each bar within a histogram represents a group, while the height of the bar represents the frequency of data within that group. 

Histograms are particularly helpful when breaking down the frequency of your data into categories such as age, days of the week, physical measurements, or any other category that can be listed in chronological or numerical order. 

histogram example

3. Check sheet (or tally sheet)

Check sheets can be used to collect quantitative or qualitative data. When used to collect quantitative data, they can be called a tally sheet. A check sheet collects data in the form of check or tally marks that indicate how many times a particular value has occurred, allowing you to quickly zero in on defects or errors within your process or product, defect patterns, and even causes of specific defects.

With its simple setup and easy-to-read graphics, check sheets make it easy to record preliminary frequency distribution data when measuring out processes. This particular graphic can be used as a preliminary data collection tool when creating histograms, bar graphs, and other quality tools.

check sheet example

4. Cause-and-effect diagram (also known as a fishbone or Ishikawa diagram)

Introduced by Kaoru Ishikawa, the fishbone diagram helps users identify the various factors (or causes) leading to an effect, usually depicted as a problem to be solved. Named for its resemblance to a fishbone, this quality management tool works by defining a quality-related problem on the right-hand side of the diagram, with individual root causes and sub-causes branching off to its left.   

A fishbone diagram’s causes and subcauses are usually grouped into six main groups, including measurements, materials, personnel, environment, methods, and machines. These categories can help you identify the probable source of your problem while keeping your diagram structured and orderly.

cause-and-effect diagram example

5. Pareto chart (80-20 rule)

As a quality control tool, the Pareto chart operates according to the 80-20 rule. This rule assumes that in any process, 80% of a process’s or system’s problems are caused by 20% of major factors, often referred to as the “vital few.” The remaining 20% of problems are caused by 80% of minor factors. 

A combination of a bar and line graph, the Pareto chart depicts individual values in descending order using bars, while the cumulative total is represented by the line.

The goal of the Pareto chart is to highlight the relative importance of a variety of parameters, allowing you to identify and focus your efforts on the factors with the biggest impact on a specific part of a process or system. 

Pareto chart

6. Scatter diagram

Out of the seven quality tools, the scatter diagram is most useful in depicting the relationship between two variables, which is ideal for quality assurance professionals trying to identify cause and effect relationships. 

With dependent values on the diagram’s Y-axis and independent values on the X-axis, each dot represents a common intersection point. When joined, these dots can highlight the relationship between the two variables. The stronger the correlation in your diagram, the stronger the relationship between variables.

Scatter diagrams can prove useful as a quality control tool when used to define relationships between quality defects and possible causes such as environment, activity, personnel, and other variables. Once the relationship between a particular defect and its cause has been established, you can implement focused solutions with (hopefully) better outcomes.

scatter diagram example

 7. Control chart (also called a Shewhart chart)

Named after Walter A. Shewhart, this quality improvement tool can help quality assurance professionals determine whether or not a process is stable and predictable, making it easy for you to identify factors that might lead to variations or defects. 

Control charts use a central line to depict an average or mean, as well as an upper and lower line to depict upper and lower control limits based on historical data. By comparing historical data to data collected from your current process, you can determine whether your current process is controlled or affected by specific variations.

Using a control chart can save your organization time and money by predicting process performance, particularly in terms of what your customer or organization expects in your final product.

control chart with action plan example

Bonus: Flowcharts

Some sources will swap out stratification to instead include flowcharts as one of the seven basic QC tools. Flowcharts are most commonly used to document organizational structures and process flows, making them ideal for identifying bottlenecks and unnecessary steps within your process or system. 

Mapping out your current process can help you to more effectively pinpoint which activities are completed when and by whom, how processes flow from one department or task to another, and which steps can be eliminated to streamline your process. 

manufacturing flow example

Learn how to create a process improvement plan in seven steps.

Lucidchart, a cloud-based intelligent diagramming application, is a core component of Lucid Software's Visual Collaboration Suite. This intuitive, cloud-based solution empowers teams to collaborate in real-time to build flowcharts, mockups, UML diagrams, customer journey maps, and more. Lucidchart propels teams forward to build the future faster. Lucid is proud to serve top businesses around the world, including customers such as Google, GE, and NBC Universal, and 99% of the Fortune 500. Lucid partners with industry leaders, including Google, Atlassian, and Microsoft. Since its founding, Lucid has received numerous awards for its products, business, and workplace culture. For more information, visit lucidchart.com.

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quality management problem solving tools

In this article we’ll talk about how to improve visualization, even if you are not a visual presentation expert.

quality management problem solving tools

Struggling to decide which process improvement methodology to use? Learn about the top approaches—Six Sigma, Lean, TQM, Just-in-time, and others—and the diagrams that can help you implement these techniques starting today.

Bring your bright ideas to life.

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5 Root Cause Analysis Tools for More Effective Problem-Solving

Paul Foster Square Scaled Resized

Next to defining a problem accurately, root cause analysis is one of the most important elements of problem-solving in quality management. That’s because if you’re not aiming at the right target, you’ll never be able to eliminate the real problem that’s hurting quality.

So which type of root cause analysis tool is the best one to use? Manufacturers have a range of methods at their fingertips, each of which is appropriate for different situations. Below we discuss five common root cause analysis tools, including:

  • Pareto Chart
  • Fishbone Diagram
  • Scatter Diagram
  • Failure Mode and Effects Analysis (FMEA)

Download our free Root Cause Analysis 101 Guidebook

1. pareto chart.

A Pareto chart is a histogram or bar chart combined with a line graph that groups the frequency or cost of different problems to show their relative significance. The bars show frequency in descending order, while the line shows cumulative percentage or total as you move from left to right.

Pareto Chart of Failures by Category

The Pareto chart example above is a report from layered process audit software that groups together the top seven categories of failed audit questions for a given facility. Layered process audits (LPAs) allow you to check high-risk processes daily to verify conformance to standards. LPAs identify process variations that cause defects, making Pareto charts a powerful reporting tool for analyzing LPA findings.

Pareto charts are one of the seven basic tools of quality described by quality pioneer Joseph Juran. Pareto charts are based on Pareto’s law, also called the 80/20 rule, which says that 20% of inputs drive 80% of results.

Learn how to create Pareto charts in this post or download the Pareto Chart Tip Sheet and Sample Excel File

The 5 Whys is a method that uses a series of questions to drill down into successive layers of a problem. The basic idea is that each time you ask why, the answer becomes the basis of the next why. It’s a simple tool useful for problems where you don’t need advanced statistics, so you don’t necessarily want to use it for complex problems.

One application of this technique is to more deeply analyze the results of a Pareto analysis. Here’s an example of how to use the 5 Whys:

Problem: Final assembly time exceeds target

  • Why is downtime in final assembly higher than our goal? According to the Pareto chart, the biggest factor is operators needing to constantly adjust Machine A
  • Why do operators need to constantly adjust Machine A? Because it keeps having alignment problems
  • Why does Machine A keep having alignment problems? Because the seals are worn
  • Why are Machine A’s seals worn? Because they aren’t being replaced as part of our preventive maintenance program
  • Why aren’t they being replaced as part of our preventive maintenance program? Because seal replacement wasn’t captured in the needs assessment

Of course, it may take asking why more than five times to solve the problem—the point is to peel away surface-level issues to get to the root cause.

Learn more about the 5 Whys method in this blog post or download our free 5 Whys worksheet

3. Fishbone Diagram

A fishbone diagram sorts possible causes into various categories that branch off from the original problem. Also called a cause-and-effect or Ishakawa diagram, a fishbone diagram may have multiple sub-causes branching off of each identified category.

Example of Fishbone Diagram-EASE

Learn more about how to use a fishbone diagram in this blog post and download our free set of fishbone diagram templates

4. Scatter Plot Diagram

A scatter plot or scatter diagram uses pairs of data points to help uncover relationships between variables. A scatter plot is a quantitative method for determining whether two variables are correlated, such as testing potential causes identified in your fishbone diagram.

Making a scatter diagram is as simple as plotting your independent variable (or suspected cause) on the x-axis, and your dependent variable (the effect) on the y-axis. If the pattern shows a clear line or curve, you know the variables are correlated and you can proceed to regression or correlation analysis.

Download a free tip sheet to start creating your own scatter diagrams today!

5. Failure Mode and Effects Analysis (FMEA)

Failure mode and effects analysis (FMEA) is a method used during product or process design to explore potential defects or failures. An FMEA chart outlines:

  • Potential failures, consequences and causes
  • Current controls to prevent each type of failure
  • Severity (S), occurrence (O) and detection (D) ratings that allow you to calculate a risk priority number (RPN) for determining further action

When applied to process analysis, this method is called process failure mode and effects analysis (PFMEA). Many manufacturers use PFMEA findings to inform questions for process audits , using this problem-solving tool to reduce risk at the source.

No matter which tool you use, root cause analysis is just the beginning of the problem-solving process. Once you know the cause, the next step is implementing a solution and conducting regular checks to ensure you’re holding the gain and achieving sustainable continuous improvement.

Root Cause Analysis

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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 .

Flowchart Template 7 Basic Quality Tools

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.

Histogram Example 7 Basic Quality Tools

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.

Fishbone Diagram 7 Basic Tools of Quality

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.

Scatter Diagram 7 Basic Quality Tools

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.

Check Sheet Template 7 Quality Tools

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.

Control Chart Seven Basic Quality Tools

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.

Pareto Chart 7 Quality ToolsControl Chart Seven Basic Quality Tools

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

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.

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.

More Related Articles

Process Mapping Guide: Definition, How-to and Best Practices

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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MindManager Blog

Nine essential problem solving tools: The ultimate guide to finding a solution

October 26, 2023 by MindManager Blog

Problem solving may unfold differently depending on the industry, or even the department you work in. However, most agree that before you can fix any issue, you need to be clear on what it is, why it’s happening, and what your ideal long-term solution will achieve.

Understanding both the nature and the cause of a problem is the only way to figure out which actions will help you resolve it.

Given that most problem-solving processes are part inspiration and part perspiration, you’ll be more successful if you can reach for a problem solving tool that facilitates collaboration, encourages creative thinking, and makes it easier to implement the fix you devise.

The problem solving tools include three unique categories: problem solving diagrams, problem solving mind maps, and problem solving software solutions.

They include:

  • Fishbone diagrams
  • Strategy maps
  • Mental maps
  • Concept maps
  • Layered process audit software
  • Charting software
  • MindManager

In this article, we’ve put together a roundup of versatile problem solving tools and software to help you and your team map out and repair workplace issues as efficiently as possible.

Let’s get started!

Problem solving diagrams

Mapping your way out of a problem is the simplest way to see where you are, and where you need to end up.

Not only do visual problem maps let you plot the most efficient route from Point A (dysfunctional situation) to Point B (flawless process), problem mapping diagrams make it easier to see:

  • The root cause of a dilemma.
  • The steps, resources, and personnel associated with each possible solution.
  • The least time-consuming, most cost-effective options.

A visual problem solving process help to solidify understanding. Furthermore, it’s a great way for you and your team to transform abstract ideas into a practical, reconstructive plan.

Here are three examples of common problem mapping diagrams you can try with your team:

1. Fishbone diagrams

Fishbone diagrams are a common problem solving tool so-named because, once complete, they resemble the skeleton of a fish.

With the possible root causes of an issue (the ribs) branching off from either side of a spine line attached to the head (the problem), dynamic fishbone diagrams let you:

  • Lay out a related set of possible reasons for an existing problem
  • Investigate each possibility by breaking it out into sub-causes
  • See how contributing factors relate to one another

MindManager Fishbone Diagram 1

Fishbone diagrams are also known as cause and effect or Ishikawa diagrams.

2. Flowcharts

A flowchart is an easy-to-understand diagram with a variety of applications. But you can use it to outline and examine how the steps of a flawed process connect.

Flowchart | MindManager

Made up of a few simple symbols linked with arrows indicating workflow direction, flowcharts clearly illustrate what happens at each stage of a process – and how each event impacts other events and decisions.

3. Strategy maps

Frequently used as a strategic planning tool, strategy maps also work well as problem mapping diagrams. Based on a hierarchal system, thoughts and ideas can be arranged on a single page to flesh out a potential resolution.

Strategy Toolkit MindManager 2018

Once you’ve got a few tactics you feel are worth exploring as possible ways to overcome a challenge, a strategy map will help you establish the best route to your problem-solving goal.

Problem solving mind maps

Problem solving mind maps are especially valuable in visualization. Because they facilitate the brainstorming process that plays a key role in both root cause analysis and the identification of potential solutions, they help make problems more solvable.

Mind maps are diagrams that represent your thinking. Since many people struggle taking or working with hand-written or typed notes, mind maps were designed to let you lay out and structure your thoughts visually so you can play with ideas, concepts, and solutions the same way your brain does.

By starting with a single notion that branches out into greater detail, problem solving mind maps make it easy to:

  • Explain unfamiliar problems or processes in less time
  • Share and elaborate on novel ideas
  • Achieve better group comprehension that can lead to more effective solutions

Mind maps are a valuable problem solving tool because they’re geared toward bringing out the flexible thinking that creative solutions require. Here are three types of problem solving mind maps you can use to facilitate the brainstorming process.

4. Mental maps

A mental map helps you get your thoughts about what might be causing a workplace issue out of your head and onto a shared digital space.

Mental Map | MindManager Blog

Because mental maps mirror the way our brains take in and analyze new information, using them to describe your theories visually will help you and your team work through and test those thought models.

5. Idea maps

Mental Map | MindManager Blog

Idea maps let you take advantage of a wide assortment of colors and images to lay down and organize your scattered thought process. Idea maps are ideal brainstorming tools because they allow you to present and explore ideas about the best way to solve a problem collaboratively, and with a shared sense of enthusiasm for outside-the-box thinking.

6. Concept maps

Concept maps are one of the best ways to shape your thoughts around a potential solution because they let you create interlinked, visual representations of intricate concepts.

Concept Map | MindManager Blog

By laying out your suggested problem-solving process digitally – and using lines to form and define relationship connections – your group will be able to see how each piece of the solution puzzle connects with another.

Problem solving software solutions

Problem solving software is the best way to take advantage of multiple problem solving tools in one platform. While some software programs are geared toward specific industries or processes – like manufacturing or customer relationship management, for example – others, like MindManager , are purpose-built to work across multiple trades, departments, and teams.

Here are three problem-solving software examples.

7. Layered process audit software

Layered process audits (LPAs) help companies oversee production processes and keep an eye on the cost and quality of the goods they create. Dedicated LPA software makes problem solving easier for manufacturers because it helps them see where costly leaks are occurring and allows all levels of management to get involved in repairing those leaks.

8. Charting software

Charting software comes in all shapes and sizes to fit a variety of business sectors. Pareto charts, for example, combine bar charts with line graphs so companies can compare different problems or contributing factors to determine their frequency, cost, and significance. Charting software is often used in marketing, where a variety of bar charts and X-Y axis diagrams make it possible to display and examine competitor profiles, customer segmentation, and sales trends.

9. MindManager

No matter where you work, or what your problem-solving role looks like, MindManager is a problem solving software that will make your team more productive in figuring out why a process, plan, or project isn’t working the way it should.

Once you know why an obstruction, shortfall, or difficulty exists, you can use MindManager’s wide range of brainstorming and problem mapping diagrams to:

  • Find the most promising way to correct the situation
  • Activate your chosen solution, and
  • Conduct regular checks to make sure your repair work is sustainable

MindManager is the ultimate problem solving software.

Not only is it versatile enough to use as your go-to system for puzzling out all types of workplace problems, MindManager’s built-in forecasting tools, timeline charts, and warning indicators let you plan, implement, and monitor your solutions.

By allowing your group to work together more effectively to break down problems, uncover solutions, and rebuild processes and workflows, MindManager’s versatile collection of problem solving tools will help make everyone on your team a more efficient problem solver.

Download a free trial today to get started!

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MindManager® helps individuals, teams, and enterprises bring greater clarity and structure to plans, projects, and processes. It provides visual productivity tools and mind mapping software to help take you and your organization to where you want to be.

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Educational Business Articles

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)


  • 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

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

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

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

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.

Check Sheet

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.

Pareto Example

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.

Bar Chart

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

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

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

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

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.

dotplot example

(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

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 management problem solving tools

22 Quality Management Tools to Elevate Your Performance as a Quality Manager


Quality management leaders in every organization are expected to perform so many tasks daily, from problem-solving to improving process efficiency to tracking quality metrics to much, much more. It’s a lot— but there is good news. There are a variety of Quality management Tools that can make these tasks a lot easier. Ultimately, the goal is to ensure that organizational standards are maintained at each stage of the product lifecycle.

Quality Management Tools have gobbled up a substantial market share. As per Grand View Research, the global Quality Management Software market is sized at $8.25 billion as of 2020. By 2028, this market is expected to increase at a compound annual growth rate of 9.7%.

What are Quality Management Tools?

Quality Management Tools are technology-driven products that help organize, collect, analyze, interpret and understand data representing the products, services, and employees. The tools further help maintain quality standards of the products and services that the organizations manufacture to abide by the industry standards of quality and assurance.

The quality management tools that we will discuss in our guide are useful for quality assurance professionals, regardless of the size of your organization.

The list of tools in this article is organized into four sections: problem-solving, improving processes, capturing metrics, and data/task organization.

Ready to dive in a build your QA Toolkit? Then let’s begin.

Problem-Solving Tools

1. cause-and-effect diagram.


The cause-and-effect diagram is a graphical representation that helps you understand, sort, display, and identify the cause behind a specific event or problem. You can use this tool by identifying the problem, defining the process that needs to be examined, brainstorming the further causes with the team members, and structuring it to analyze the solution.

2. Andon board

Andon board is an alerting system that informs operators about any product or service line issues as soon as it occurs. All you have to do is press the Andon board’s cord when problems occur. Identify the problem through lights, sounds, and numbers and act on it immediately.

3. Tree diagrams


A tree diagram is a tool that defines tasks and subtasks in a hierarchy that are needed to be completed. It starts with a task with its branches as subtasks and clarifies quality assurance managers about what needs to be done next. To use this tool, develop particular tasks and actions as solutions and analyze the process to derive possible solutions.

4. Kaizen’s value stream mapping


Kaizen’s value stream mapping is a flowchart tool that documents each step in the process, identifies issues, and proposes solutions for the same. To use this tool, map each step in the process, create timelines, and document everything precisely to brainstorm potential issues and solutions.

5. Five Whys


The five whys is a quality control technique that solves problems effectively. With this tool, you can find the reason behind a particular situation by asking a sequence of five ‘why’ questions. To use this tool, ask five different whys and note down the causes to address the root cause of the problem.

6. Storyboard

A storyboard is a visual representation tool automatically sketches a video’s progression to bring your ideas to life. It graphically represents how the animation, film, or video will take place, one shot after another. To use this diagram, take the scenes you want to address and make a list of shots, sketch the scenes, fill in words and other details and wait for the graphical representation to occur. Then, any video issues can be ruled out by understanding how each element will look shot after shot.

Process Improvement Tools

7. control chart.


A control chart is a graphical representation that help you study a process change in a specific time period. With this tool, you plot data in a timely order and compare it with the central line (average) upper control limit and lower control limit. Control charts help you understand the degree to which a firm’s products differ from the specified standard and help in correcting them.

8. Scatter diagram


A scatter diagram is a graphical representation showing the relationship between two numerical variables. It links the component of the process and the fault in its quality on the two axes. With the help of a scatter diagram, you can optimize processes by paring the numerical data into dependent and independent variables and determining the relationship between the two to identify problems and solutions.

9. Flow chart


The flowchart identifies the quality cost by analyzing the data frequencies and identifies the output and input branches involved. It helps improve processes after you identify all steps in the process sequentially. You can use this tool by defining the major concerns and branching out the sub-tasks to understand the situation better.

10. Vendor audit checklist

A quality audit checklist is used for quality management by tracking questions and answers during a quality audit. The quality record helps in continuous process improvement. You can use this tool to determine the focus of your audit, prepare for the same, and finally perform it. Report the results in the findings report and conduct corrective actions to solve issues.

11. Process decision program chart


The process decision program chart is a management planning tool that organizes and identifies everything that can go wrong in a developing plan. To use this tool, one needs to draw a tree diagram, brainstorm the issues, review the problems and brainstorm the solutions to organize everything in the tree to make decisions accordingly.

12. Nominal Group Technique


The nominal group technique is a quality management tool that structures small-group discussions to reach a conclusion. This tool gathers information from a moderator who asks individuals certain things, and ideas are prioritized based on each group member. Then, the suggestions/ideas are implemented for process improvement.

Metrics Capturing Tools

13. check sheet.


A check sheet is a structured form used to collect and analyze data for different purposes. To use this tool, decide the problem you want to assess, collect the data needed, and design the form. To improve the procedure, use the form after labeling all the blank spaces to identify event patterns, defects, problems, and more.

14. Pareto chart


A Pareto chart is a six sigma tool that helps in quality management through a bar graph representation to show how much a particular input contributes towards an output. You can use this tool to determine causes, measurements, and timeframe to analyze data and build the chart.

15. Matrix diagram


Matrix diagrams are quality tools that analyze data within an organizational structure and define the relationship between them. The tool can collect different data types, select a matrix type, compare the data, and draw conclusions from the same.

Data/Task Organization Tools

16. histogram.

A histogram is a tool that helps in quality control by representing a data set precisely. The bar-chart type representation graphs how often continuous data occurs, enabling you to analyze it thoroughly. You can use a histogram by collecting at least 50 data sets of a particular process and plot them on the x and y axis to get a visual representation and comparison of data.

17. Affinity diagrams

An affinity diagram is a quality control tool to organize several ideas into their natural relationships after a brainstorming session. You can use this tool to organize, consolidate, segregate and generate information related to the process, its faults, and potential solutions. All you have to do to use this tool is to identify the objective, group categories, and additional factors to each category to analyze the data.

18. Stratification


The stratification quality assurance tool is used to sort data, information, objects, and more into different groups based on different factors. This helps you understand the data’s meaning, reveals patterns contributing to quality errors, and enables you to fix them accordingly.

19. Prioritisation matrices


Prioritization matrices, as the name suggests, evaluate several options and prioritize them according to importance. To use this tool, you have to establish weighted criteria and evaluate all options against the criteria to figure out your top priority of solution or issue to look after.

20. Activity network/arrow diagram


Arrow diagrams create a visual representation of the various steps in a process that is needed to complete a particular task. It reveals the causes needed for the tasks and helps quality assurance managers determine the task sequence and separate tasks accordingly.

21. Mind Mapping

A mind map is a diagram that organizes large amounts of information into a visual hierarchy and shows relationships among different pieces altogether. To use this tool, you need to define a core idea under which you figure out sub-core ideas as branches which will help you brainstorm about the process and its improvement.

22. Eisenhower Matrix


The time management tool, Eisenhower Matrix, helps prioritize tasks according to their delivery date. It segregates urgent tasks from less important ones and enables QA managers to use this tool by putting different tasks into different quadrants based on their urgency.


While we understand that this might be an overwhelming list of quality tools you can use to maintain quality standards, we assure you that this list is all you need to improve your quality management game as a quality management professional.

Use the data/task organization tools to segregate each piece of information precisely, then go onto the problem-solving tools if you are facing an issue within a process or a step.

Use process improvement tools to better the existing process after solving the problem, and finally capture metrics through the metrics capturing tools for implying them to the process for better results.

Are you ready to start using these top-quality management tools? What features of these tools are most beneficial to you and your business?

Related Posts

22 Quality Management Tools to Elevate Your Performance as a Quality Manager

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quality management problem solving tools

Combining Quality Tools for Effective Problem Solving

Using the classic seven and the seven new.

Published: Monday, October 23, 2017 - 11:30

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Q uality tools can serve many purposes in problem solving. They may be used to assist in decision making, selecting quality improvement projects, and in performing root cause analysis. They provide useful structure to brainstorming sessions, for communicating information, and for sharing ideas with a team. They also help with identifying the optimal option when more than one potential solution is available. Quality tools can also provide assistance in managing a problem-solving or quality improvement project.

Seven classic quality tools

The Classic Seven Quality tools were compiled by Kaoru Ishikawa in his book, Guide to Quality Control (Asian Productivity Organization, 1991). Also known as “The Seven Tools” and “The Seven Quality Tools,” these basic tools should be understood by every quality professional. The Classic Seven Tools were first presented as tools for production employees to use in analyzing their own problems; they are both simple enough for everybody to use, yet powerful enough to tackle complex problems.

The seven tools are: 1. Cause and effect diagrams 2. Scatter diagrams 3. Control charts 4. Histograms 5. Check sheets 6. Pareto charts 7. Flow charts

A cause-and-effect-diagram is used to list potential causes of a problem. It is also known as an Ishikawa diagram or fishbone diagram. Typically, the main branches are the “6Ms,” or man, material, methods, milieu (environment), machine, and measurement. Sub-branches are listed under the main branches with “twigs” containing the potential problem causes. A cause-and-effect diagram can be used to assist when the team is brainstorming, and it can also be used to quickly communicate all potential causes under consideration.

quality management problem solving tools

A scatter diagram graphically depicts paired data points along an X and Y axis. The scatter diagram can be used to quickly identify potential relationships between paired data points. Figure 2 depicts various potential correlations ranging from no correlation to a strong negative and strong positive correlation. It is important to remember that a strong correlation does not necessarily mean there is a direct relationship between the paired data points; they may be following third, unstudied factor.

quality management problem solving tools

Figure 2: Scatter diagram. (Click here for larger image)

Control charts are used to evaluate and monitor the performance of a process ( Wheeler 1995 ). There are many types of control charts available for statistical process control (SPC), and different charts are used deepening on the sample size and the type of data used. An individuals chart is used when the sample size is one. The formulas for an individuals chart are shown in table 1, and an example of an individuals chart for a shaft diameter is shown in figure 3. The data are in a state of statistical control when all values are within the control limits, which contain 99.7 percent of all values.

quality management problem solving tools

Histograms are used to visualize the distribution of data ( McClave and Sincich 2009 ). The y-axis shows the frequency of occurrences, and the x-axis shows the actual measurements. Each bar on a histogram is a bin, and bin size can be determined by taking the square root of the number of items being analyzed. Using a histogram can quickly show if the data are skewed in one direction or another. Figure 4 shows a histogram for data that fit a normal distribution, with half of all values above and below the mean.

quality management problem solving tools

Check sheets are used for the collection of data ( Borror 2009 ), such as when parts are being inspected. The various failure categories or problems are listed, and a hash mark is placed next to the label when the failure or problem is observed (see figure 5). The data collected in a check sheet can be evaluated using a Pareto chart.

quality management problem solving tools

A Pareto chart is used for prioritization by identifying the 20 percent of problems that result in 80 percent of costs ( Juran 2005 ). This can be useful when searching for improvement projects that will deliver the most impact with the least effort. Figure 6 shows a Pareto chart with three out of seven problems accounting for 80 percent of all problems. Those three would be the priority for improvement projects.

quality management problem solving tools

A flowchart is used to gain a better understanding of a process ( Brassard 1996 ). A flowchart may provide a high-level view of a process, such as the one shown in figure 7, or it may be used to detail every individual step in the process. It may be necessary to create a high-level flowchart to identify potential problem areas and then chart the identified areas in detail to identify steps that need further investigation.

quality management problem solving tools

Seven new management and planning tools

The seven new management and planning tools are based on operations research and were created between 1972 and 1979 by the Japanese Society for Quality Control . They were first translated into English by GOAL/QPC in 1983 ( Brassard 1996 ).

These seven tools are: 1. Affinity diagram 2. Interrelationship diagram 3. Tree diagram 4. Arrow diagram 5. Matrix diagram 6. Prioritization matrix 7. Process decision program chart (PDPC)

An affinity diagram identifies points by logically grouping concepts ( ReVelle 2004 ). Members of a team write down items that they believe are associated with the problem under consideration, and these ideas are then grouped into categories or related points.

quality management problem solving tools

The interrelationship diagram depicts cause-and-effect relationships between concepts and is created by listing problems on cards ( Westcott 2014 ). These cards are then laid out, and influences are identified with arrows pointing at the items that are being influenced. One item with many arrows originating from it is a cause that has many influences, and much can be achieved by correcting or preventing this problem.

quality management problem solving tools

A tree diagram assists in moving from generalities to the specifics of an issue ( Tague 2005 ). Each level is broken down into more specific components as one moves from left to right in the diagram.

quality management problem solving tools

An arrow diagram is used to identify the order in which steps need to be completed to finish an operation or project on time ( Brassard 1996 ). The individual steps are listed, together with the duration, in the order that they occur. Using an arrow diagram such as the one in figure 11 can show steps that must start on time to prevent a delay in the entire project or operation.

quality management problem solving tools

The matrix diagram is used to show relations between groups of data ( Westcott 2014 ). The matrix diagram in Figure 12 depicts three suppliers as well as their fulfillment of the three characteristics listed on the left side of the table. In this example, only two suppliers share the characteristic “ISO certification.”

quality management problem solving tools

The prioritization matrix is used to select the optimal option by assigning weighted values to the characteristics that must be fulfilled, and then assessing the degree to which each option fulfills the requirement ( ReVelle 2004 ). The prioritization matrix in figure 13 is being used to select the best option for a staffing problem.

quality management problem solving tools

Process decision program charts (PDPC) map out potential problems in a plan and their solutions ( Tague 2005 ). The example in figure 14 shows the potential problems that could be encountered when conduction employee training, as well as solutions to these problems.

quality management problem solving tools

Example of combining quality tools

Multiple quality tools can be used in succession to address a problem ( Barsalou 2015). The tools should be selected based on the intended use, and information from one tool can be used to support a later tool. The first step is to create a detailed problem description that fully describes the problem. In this hypothetical example, the problem description is “coffee in second-floor break room tastes bad to the majority of coffee drinkers; this was first noticed in February 2017.” The hypothetical problem-solving team then creates the flowchart shown in figure 15 to better understand the process.

quality management problem solving tools

The team then brainstorms potential causes of the problem. These ideas come from the team members’ experience with comparable, previous issues as well as technical knowledge and understanding of the process. The ideas are written on note cards, which are grouped into related categories to create an affinity diagram based around the 6Ms that are used for a cause-and-effect diagram (see figure 16).

quality management problem solving tools

The affinity diagram is then turned into the cause-and-effect diagram depicted in figure 17. The team can then expand the cause-and-effect diagram if necessary. The cause-and-effect diagram provides a graphical method of communicating the many root-cause hypotheses. This makes it easy to communicate the hypotheses, but it’s not ideal for tracking the evaluation and results.

quality management problem solving tools

Cause-and-effect diagram items are then transferred to a worksheet like the one shown in figure 18. The hypotheses are then prioritized so that the most probable causes are the first ones to be investigated. A method of evaluation is then determined, a team member is assigned the evaluation action item, and a target completion date is listed. A summary of evaluation results is then listed, and the conclusions are color-coded to indicate if they are OK, unclear, or potentially the root cause. Unclear items as well as potential root causes should then be investigated further, and OK items are moved from consideration.

quality management problem solving tools

Figure 19 shows a close up view of the cause-and-effect worksheet. Often, the cause-and-effect diagram item is not clean in how it is related to the problem. In such a situation, it can be expand in the worksheet to turn it into a clearer hypotheses. For example, “Water” in the cause-and-effect diagram can be changed to “Water from the city water system containing chemicals leading to coffee tasting bad” in the worksheet.

quality management problem solving tools

A prioritization matrix can be used to evaluate multiple potential solutions to the problem. In this example, the team has identified three potential solutions: The team can clean and repair the old machine, buy a new machine, or buy an expensive new machine. They want to avoid high costs, but do not want to spend too much time on implementing the solution, and they want something with long-term value. Therefore the prioritization matrix shown in figure 20 is used to find the ideal solution.

quality management problem solving tools

There is no one right quality tool for every job, so quality tools should be selected based on what must to be accomplished. Information from one tool can be transferred to a different tool to continue the problem-solving process. Actions items resulting from a cause-and-effect diagram should be entered into a tracking list. This assists the team leader in tracking the status of items, makes it easier to ensure action items are completed, and is also useful for reporting the result of action items.

References 1. Barsalou, Matthew A. Root Cause Analysis: A Step-by-Step Guide to Using the Right Tool and the Right Time . Boca Raton, FL: CRC Press, 2015. 2. Borror, Connie M., ed. The Certified Quality Engineer Handbook, Third Edition . Milwaukee, WI: ASQ Quality Press, 2009. 3. Brassard, Michael. The Memory Jogger Plus + Featuring the Seven Management and Planning Tools , First Edition . Salem, NH: GOAL/QPC, 1996. 4. Ishikawa, Kaoru. Guide to Quality Control, Second Edition . (Translated by Asian Productivity Organization.) Tokyo, Japan: Asian Productivity Organization, 1991. 5. Juran, J. M. “The non-Pareto Principle Mea Culpa.” From Stephens, K.S., ed. Juran, Quality, and a Century of Improvement , pp. 185–188. Milwaukee, WI: ASQ Quality Press, 2005. 6. McClave, James T. and Terry Sinich. Statistics , Eleventh Edition . Upper Saddle River, NJ: Pearson Education, 2009. 7. ReVelle, Jack B. Quality Essentials: A Reference Guide from A to Z . Milwaukee, WI: ASQ Quality Press, 2004. 8. Tague, Nancy R. The Quality Toolbox, Second Edition . Milwaukee, WI: ASQ Quality Press, 2005. 9. Westcott, Russell T., ed. The Certified Manager of Quality/Organizational Excellence Handbook , Fourth Edition . Milwaukee, WI: ASQ Quality Press, 2013. 10. Wheeler, Donald J. Advanced Topics in Statistical Process Control: The Power of Shewhart’s Charts . Knoxville, TN: SPC Press, 1995.

Originally presented as a conference paper for the 2016 International Conference on Quality Engineering and Management.

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About The Author

Matthew barsalou.

Matthew Barsalou is an ASQ Fellow and IAQ Academician who works in the automotive industry in Germany. He is an ASQ-certified Six Sigma Black Belt, quality engineer, and quality technician; a TÜV-certified quality manager, quality management representative, and quality auditor; and a Smarter Solutions-certified lean Six Sigma Master Black Belt. He has a bachelor’s degree in industrial sciences, and master’s degrees in business administration and industrial engineering, and liberal studies with emphasis in international business. Barsalou is author of the books Root Cause Analysis , Statistics for Six Sigma Black Belts , The ASQ Pocket Guide to Statistics for Six Sigma Black Belts , The Quality Improvement Field Guide , and Practical Statistical Methods for Quality , and co-author of the book Applied Statistics Manual , as well as writing research and practitioner journal papers .

Back to Basics

Great to see Mark getting back to basics and avoiding the material that is irrelevant to process improvement, not to mention avoiding the ridiculous dpmo.  As Dr Deming put it:"The student should avoid passages in books that treat confidence intervals and tests of significance, as such calculations have no application in analytic problems in science and industry." (W. Edwards Deming, Out of the Crisis, page 639.)"Analysis of variance, t- test, confidence intervals, and other statistical techniques taught in the books, however interesting, are inappropriate because they bury the information contained in the order of production." (W. Edwards Deming, Out of the Crisis, page 132.)

Out of the Crisis, Page 639

Interesting quote from page 639.  What edition of, "Out of the Crisis" are you using?  Both my copies (two different editions) are just under 500 pages each.

quality management problem solving tools

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  • 8D Customer Complaint Resolution Report - Solve customer complaints through an eight step analysis that elevates organizational focus on the customer
  • A3 Problem Solving Report​ - Concisely describe and document a problem solving process, similar to a Storyboard
  • Analytic Cause Tree  - Determine root causes of a problem and develop corrective actions to remedy it
  • Clean Sheet Process Redesign  - Empower a team to move away from current state and enable a complete transformation of a work flow process
  • Community Stakeholder Services Map - Develop a visual representation of where services are physically located in relation to each other
  • Consensus Decision Making Matrix - Divide an issue into primary and secondary components as a framework for achieving consensus
  • Diagnostic Force Field Analysis  - Expand a Force Field Analysis to include relative strength of drivers and restrainers
  • Mind Mapping  - Develop a non-linear graphical diagram to link and organize information about an issue
  • Nine Windows  - Visualize alternatives to current state by viewing a problem through nine different lenses
  • Population Health Driver Diagram - Identify primary and secondary drivers of a community health issue, as a starting point for development of targeted improvements
  • Process Value Analysis - Enable a team to analyze each step in a process to determine its value, developing a ratio of function to cost
  • SCAMPER Technique  - Generate a list of ideas focused on customer needs and optimum process improvements
  • SIPOC+CM+CE Collection Form  - Identify and analyze the major elements of organizational core processes
  • Solvability and Control Matrix - Explore and assess process problems to determine which can be easily solved and which should be brought to a quality improvement team
  • Find more resources to support performance improvement in the Public Health Improvement Resource Center
  • Develop successful performance management systems using the  Performance Management Toolkit
  • Review quality improvement courses in the TRAIN Learning Network
  • Learn about customized technical assistance to apply QI tools and techniques

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  • Quality Management

7 Best Quality Management Tools For Process Improvement

Quality Management Tools - Invensis Learning

Quality management emerged as an area of expertise when organizations understood the importance of delivering products and services at optimal levels. A lot of organizations started using a different variety of quality management tools. Earlier, the main focus of all companies was to produce on time. As long as the deliveries went out at the given deadline, nothing else would matter. Over time, they realized that customer satisfaction was not just based on timely deliveries. It was, in fact, focused on delivering services at a superior quality.

This is what quality management takes care of. Quality management is a set of tools and processes utilized by organizations of all sizes across many industries to help them deliver their products and services of consistent and high quality on time. Quality management has several benefits, which are discussed in the article below. The article also talks about the most fundamental tools of quality management.

Benefits of Quality Management Tools

Quality management tools have a lot of benefits when implemented correctly. The main goal for organizations is to work hard, not smart, and then create an environment that encourages productivity and achievement of business goals. Some of the most widely known advantages of quality management tools are:

  • Quality management tools are cost-efficient options. In research conducted by the Center of Economic and Business Research, it was noted that the benefits of investment in quality management were sixteen fold. For every dollar invested in a quality management tool,  the organization saved $16 . They also increased their profit margin by $3
  • Quality management tools help improve end-user satisfaction. Since the main goal of quality management is to improve the quality of the deliveries, it results in improving the satisfaction level of the end-user or the customer
  • Quality management tools improve efficiency. Quality management tools are methods that eliminate errors and focus on the improvement of processes. This way, teams and the organization as a whole can operate in a more efficient manner
  • Quality management tools improve productivity. Quality management tools help employees eliminate chances of error and reduce the time it takes to do tasks. This motivates teams and helps boost productivity
  • Quality management tools help reduce waste. There are many different types of waste that an organization can incur. Waste of time, human resources, energy, physical assets, and more. Quality management tools optimize processes, thereby reducing waste significantly

Many such benefits come with using quality management tools. They help reduce errors, create a more driven culture and work environment, improve communication, help companies maintain compliance, and more. Adopting the right quality management tool can help companies save a lot of time and resources, improve the overall quality of delivery and processes, as well as generate a high ROI. Some of the most commonly used quality management tools are listed below.

Lean Six Sigma Green Belt - Invensis Learning

7 Basic Quality Management Tools 

Quality management tools listed below were greatly emphasized upon by  Kaoru Ishikawa , who was instrumental in creating total quality management and maximizing productivity by improving the quality of deliveries in the manufacturing industry. These seven basic quality management tools are also known as the ‘old’ seven or the ‘first’ seven. They are:

  • Cause and effect diagram or the Fishbone diagram
  • Control chart
  • Pareto chart


  • Check sheet
  • Scatter diagram

The Fishbone Diagram

Kaoru Ishikawa created the Fishbone diagram or the cause and effect diagram. It was created as a means for problem-solving purposes. The diagram is also referred to as a Fishbone diagram because it resembles a fishbone upon completion. The cause and effect diagram lists out a problem and then lists out the possible causes for the problem and its effect or result.

The main problem that impacts quality is listed out on the right side of the diagram, and all the possible causes leading up to the problem are listed out on the left side. 

Control Chart

A control chart is used to maintain the quality assurance of a product or service. It takes all historical data into account to find an average or mean line of quality, which is drawn out on a graph. Other limits are added to the chart (both upper and lower) using data to see what type of variations are taking place. Once the variations have been listed out on the graph, quality management professionals or quality assurance professionals can find the causes of what is affecting the process, both positively and negatively.

A control chart helps monitor the quality of deliveries and expectations from the end-users or customers. It helps create a predictable outcome with each delivery and helps the quality management team identify negative variations that need to be worked on or eliminated.

Pareto Chart

A Pareto chart is also known as the 80-20 rule of quality management. Here, organizations assume that most of the problems they face with quality management in any process are caused by the biggest factors. These problems are listed out as 80% of all problems, and their causes are listed out to be 20% of the biggest factors.

A Pareto chart is a combination of a line graph and a bar graph. The values are shown by using the bar graph in the Pareto chart, and the line graph shows the total impact. This way, organizations can find the biggest causes of their problems with quality and implement measures to reduce them.

Stratification is used to divide different factors that could affect the quality of delivery into separate groups. All the collected data is split up to create and observe different patterns of factors that affect quality. The stratification method is widely used for data analysis in terms of quality assurance.

Check Sheet

A check sheet is a quality management and assurance tool used to find the frequency of an error or problem or a specific value. This makes it easier to spot errors or patterns causing errors and defects, as well as the frequency of their occurrence in a process. Creating a check sheet is simple. It is also fairly easy to understand. It is often used as a preliminary tool for other tools in quality management because it simplifies the whole process of problem identification.

A histogram helps quality analysts and management professionals accurately analyze different types of information they have available on different data groups to help create controls to improve the quality of any process.

A sample is taken and divided into different groups, after which the frequency of the data is calculated. This helps in the identification of areas of improvement in a process. The low performing areas show up in less frequency on the histogram, and quality management professionals can then find the root cause of the problem and solve it.

Scatter Diagram

A scatter diagram is used to find the relationship between A and B. For example, if B is facing an issue with packaging, a scatter diagram can be used to find A, which is the main reason that B takes place. This way, all possible causes to the defects to the quality of a product or process can be identified easily, after which the quality management professionals can create and implement focused solutions to solve the main cause.

Final Thoughts

Quality management is based on continuously improving all processes, regularly monitoring them, and looking out for any flaws or defects. Quality management professionals need to be certified to have the knowledge and experience that they need to implement thoughtful and valuable changes to the production and development processes so that they can deliver at the optimal level, regularly and consistently.

Some of the popular quality management certification courses that individuals and enterprise teams can take up are:

Lean Six Sigma Yello Belt Certification Training

Lean Six Sigma Green Belt Certification Training

Lean Six Sigma Black Belt Certification Training

Lean Fundamentals Certification Training

Lean IT Certification Training

RCA Through Six Sigma Certification Training

7QC Tools Certification Training

Value Stream Mapping Certification Training


Types of Quality Management Systems

Types of Quality Management Systems

What is Quality Control (QC)

What is Quality Control (QC)?

Quality Manager Interview Questions and Answers

Quality Manager Interview Questions [Updated 2024]

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The Thriving Small Business

The Thriving Small Business

Tips And Tools For Small Business Owners

7 Management Tools for Quality Control

May 8, 2019 By Patricia Lotich

Estimated reading time: 6 minutes

Many organizations use quality tools to help monitor and manage their quality initiatives.

There are several types of tools that can be used.  However, there are seven management tools for quality control that are the most common.

Different tools are used for different problem-solving opportunities, and many of the tools can be used in different ways.

The trick is to become familiar and comfortable with all of these quality tools so you can pull the appropriate one out of your toolbox when there is a problem that needs to be solved.

7 Management Tools For Quality Control

1. flowchart.

Most of us are familiar with flowcharts. You have seen flowcharts of reporting relationships in organizational structures .

Flowcharts are also used to document work process flows.

7 Management tools for quality control

This tool is used when trying to determine where the bottlenecks or breakdowns are in work processes.

Flowcharting the steps of a process provides a picture of what the process looks like and can shed light on issues within the process.

Flowcharts are also used to show changes in a process when improvements are made or to show a new workflow process.

This example provides a picture so those checking children in will know the steps each takes depending on whether it is their first time or a child who has been there before.

Example Flowchart

example flowchart

2. Check Sheet

A check sheet is a basic quality tool that is used to collect data. A check sheet might be used to track the number of times a certain incident happens.

As an example, a human resource department may track the number of questions by employees per category per day.

In this particular check sheet, the tool shows the total number of questions received by the human resources department.

This information helps that department identify opportunities to proactively share information with employees in an effort to reduce the number of questions asked.

Example Check Sheet

human resource questions check sheet example

3. Cause and Effect (fishbone) Diagram

A cause and effect diagram, also known as a fish-bone diagram, shows the many possible causes of a problem.

To use this tool, you need to first identify the problem you are trying to solve and simply write it in the box (head of the fish) to the right.

Next, you will list the major causes of the problem on the spine of the fish.

Causes are typically separated into categories of people, processes, materials, and equipment.

Causes are then identified through brainstorming with a group familiar with the problem.

Once all of the possible causes are identified, they can be used to develop an improvement plan to help resolve the identified problem.

Example Cause and Effect (Fish Bone) Diagram

fish bone cause and effect diagram

4. Pareto Chart

A Pareto chart is a bar graph of data showing the largest number of frequencies to the smallest.

In this example, we are looking at the number of product defects in each of the listed categories.

When you look at the number of defects from the largest to the smallest occurrences, it is easy to see how to prioritize improvement efforts.

The most significant problems stand out and can be targeted first.

Example Pareto Chart

pareto chart example

5. Control Charts

Control charts or run charts are used to plot data points over time and give a picture of the movement of that data.

These charts demonstrate when data is consistent or when there are high or low outliers in the occurrences of data.

It focuses on monitoring performance over time by looking at the variation in data points.

And it distinguishes between common cause and special cause variations . The Dow Jones Industrial Average is a good example of a control chart.

Example Control (Run) Charts

control (run) chart example

6. Histograms

Histograms are bar chart pictures of data that show patterns that fall within typical process conditions.

Changes in a process should trigger the new collection of data.

A minimum of 50-75 data points should be gathered to ensure an adequate number of data points have been collected.

The patterns that are detected demonstrate an analysis that helps understand variation.

In this example, it shows that the receptionist received the most phone calls about contribution statements for that period.

Example Histogram

histogram example

7. Scatter Diagrams

Scatter diagrams are graphs that show the relationship between variables. Variables often represent possible causes and effects.

As an example, a scatter diagram might show the relationship between how satisfied volunteers are that attend orientation training.

The diagram shows the relationship between volunteer satisfaction scores and volunteer orientation training.

Example Scatter Diagram

scatter diagram example

Each of these quality tools has unique advantages for certain situations. And, not all tools are used for all problem-solving.

Once a tool is learned, it can be adapted to different problem-solving opportunities.

Additionally, as with anything else, using tools properly takes practice and experience. Simply start using each of the tools, and over time, you will become proficient and a great problem solver!

What problems does your organization have that could benefit from one of these tools?

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Six Sigma Tools: Here’s Top Powerful Tools You Should Know in 2024

  • Written by John Terra
  • Updated on October 13, 2022

Six Sigma Tools

Six Sigma tools enable organizations to increase quality, reduce waste, and eliminate errors in processes and product and service development. Learn all about how you can leverage these powerful tools and methodologies to foster excellen ce.

Six Sigma is a data-driven project management methodology that employs a five-step process to address outstanding organizational issues, ultimately relying on statistical analysis to minimize defects and product variations.

But every process needs tools. Moreover, every process requires the right tools. And sometimes, the choices can be overwhelming. You’ve undoubtedly heard the saying, “The right tool for the right job.” That’s excellent advice, but how do you know what tool is “right?”

This article tackles the subject of Six Sigma tools. We will discuss the best and most important Six Sigma tools, including Lean Six Sigma tools, how to pick the right tools. We will also cover specific details such as DMAIC Six Sigma.

Let’s begin our journey of Six Sigma knowledge by examining what constitutes a Six Sigma tool.

All About Six Sigma Tools

As we have already touched upon in previous articles, Six Sigma is a methodology that helps organizations eliminate waste and inefficiency within business processes. In addition, Six Sigma tools are methodologies and techniques that help analyze and improve those processes.

In many other situations (e.g., coding, programming, writing), the word “tools” typically refers to software, apps, extensions, and actual downloadable resources. But in Six Sigma’s case, tools typically refer to ideas or procedures rather than a software suite you purchase and download. However, there are definitely applications and utilities you can buy and install.

So, Six Sigma tools are problem-solving tools used to enhance and support Six Sigma and related process improvement efforts. The tools help to identify weaknesses and flaws and, in doing so, improve your organization’s efficiency.

How to Pick the Right Six Sigma Tools

Not every Six Sigma tool is appropriate for every situation. Therefore, there is no universal solution. However, you can use a process to help you choose the Six Sigma tools that are right for you, your organization, and the tasks at hand.

Whenever you need to decide which Six Sigma tools are right for you, employ the following steps:

  • Learn about the tools. For starters, understand the tools and what they’re used for. Although this may take a little time and effort, it will apply to all future tool decisions once you do it.
  • Consider the context. Pick a tool that fits your unique environment.
  • Employ expert guidance. Put Lean Six Sigma into effect and ensure your team members have sufficient appropriate training.
  • Supporting resources. Be aware of extra resources such as software, graphs, charts, and more, which can play a pivotal role in your Six Sigma activities.

Now that we know what Six Sigma tools are and how to pick the Six Sigma tools that fit your needs best, it’s time to dive into specifics. So here are the best Six Sigma tools available today.

Presenting the Best Six Sigma Tools

These tools are presented in no specific order, but they all are proven assets in Six Sigma processing. In addition, some tools described below are used in other listed tools, so expect to see some overlap and redundancy.

This data-driven tool works exceptionally well with Lean Six Sigma. It’s an acronym for Define, Measure, Analyze, Improve, and Control, representing the five stages of DMAIC. Six Sigma DMAIC is the primary and most used tool in Six Sigma operations. It helps improve manufacturing methods by employing data and measured objectives. However, you can use many other Six Sigma tools to accomplish each DMAIC Six Sigma stage.

This Six Sigma tool is like DMAIC, but the tool develops new products, processes, or services in this case, while DMAIC works best to improve existing processes. DMADV is an acronym for the stages of Define, Measure, Analyze, Design, and Verify.

The 5S System

The 5S System focuses on workplace and workflow material management and optimization. This tool best deals with waste generated by poor conditions or workstations. When done correctly, this results in a clean, safe, uncluttered, and organized workplace to reduce waste and optimize productivity. The five S’s are:

  • Seiri (Sort): Leave only necessary items. Remove any extra items from current production.
  • Seiton (Set in order): Reduce clutter by organizing all items and labeling them accordingly.
  • Seiso (Shine): Keep the work area clean and regularly inspect everything in the area.
  • Seiketsu (Standardize): Write up your standards, then sort them and set them in order.
  • Shitsuke (Sustain): Apply and enforce your company’s standards and get everyone in the habit of following them regularly.

The Five Whys

Here’s another tool that comes in fives. The Five Whys is used to determine the root cause of your organization’s issues and involves progressively asking “Why?” until you discover the source of the problem. This procedure breaks down into these steps:

  • Identify and write down the problem so each team member can see and focus on it
  • Ask why the issue happened
  • If your first answer doesn’t identify the problem’s primary cause, ask “Why?” again
  • Repeat the process at least five times until you arrive at the problem’s primary cause
  • You’re not limited to five questions; you can ask more questions if necessary

The Five Whys is typically used during DMAIC’s Analyze phase.

The Kanban System

Kanban is a Japanese word for “billboard” and describes a supply chain control system that focuses on reducing costs by using a just-in-time inventory control approach. Put simply, Kanban activates the supply chain only when needed.

For instance, when you go to the supermarket, you buy things based on your short-term needs, not for months or years in advance. Similarly, the supermarket will not stock inventory that it doesn’t expect to sell soon. Instead, your shopping list reflects your immediate needs, and the store adjusts its product supply to reflect customer demand.

Value Stream Mapping

This tool, also called VSM, is another resource used during DMAIC’s Analyze phase and is also well-suited for Lean Manufacturing. The value stream map was developed to show a process’s material, and information flows to help improve and optimize flow throughout the organization.

VSM is a two-stage process. First, the team draws a visual representation of every function in the information and material flow, creating a production path from start to finish. Then, the group draws a map of the future state, showing how the value should ideally flow.

Value mapping identifies the following three elements:

  • Value Enabling Activities. These are activities that, when enabled, add value to the process.
  • Value-Adding Activities. These activities add value to the process.
  • Non-value adding activities. This procedure identifies and eliminates activities that do not add value to the process.

Voice of the Customer

This tool, also called VOC for short, answers the question, “What does the customer need?” The Six Sigma technique focuses on collecting customers’ requirements and viewpoints using in-person interviews, focus groups, warranty claims, surveys, and social media, among others. Once the team measurably presents the finding, the VOC can provide vital insights into what steps must be taken to improve or resolve the defined problem. The team can better understand these steps by creating a Voice of the Customer Table (VOCT).

Poka-Yoke is a Japanese term that means “mistake proofing.” It is a Lean technique designed to prevent and correct mechanical and human errors in the manufacturing or production process as early as possible. In addition, Poka-Yoke uses standardization to help avoid mistakes.

Pareto Chart

This chart illustrates a graphic representation of the Pareto Principle, which tells us that, in any given situation, 20 percent of the input produces 80 percent of the output. The chart combines a vertical bar and a line graph. The chart combines a vertical bar and a line graph. The bar graph section shows various business process component metrics, from largest to smallest, while the line graph shows the cumulative total of these metrics.

The Pareto Chart is a tool that helps team members visualize what part of the process influences output the most and gives the team a clear idea of what requires their immediate attention. The team must first figure out the process’s components and how to measure them, then place the findings into the Pareto Chart. This process helps the team see how big of an influence each part’s outcome has.

Here’s a sample Pareto Chart provided by Tallyfy.com .

sample Pareto Chart

Kaizen is a Japanese word meaning “continuous improvement.” Kaizen is the practice of continuously observing, identifying, and implementing incremental improvement in the manufacturing process. This process involves all employees and managers and encourages them to initiate improvements in the manufacturing process.

Kaizen rectifies the minor daily inefficiencies using everyone working in the organization’s collective talents, experience, and knowledge. It also helps reduce waste in the production process.

The RACI Matrix

Also called the Responsibility Assignment Matrix, the RACI Matrix is a table outlining each team member’s responsibilities in every task. RACI is an acronym, and it’s short for Responsible, Accountable, Consulted, and Informed.

  • Responsible. Refers to whose role it is to complete the task.
  • Accountable. The team member assigns tasks to everyone else, then monitors their progress.
  • Consulted. Describes the experts on the subject matter and who will guide the people working on the tasks.
  • Informed. Covers the people who the team notifies when the task is done.

Here’s a sample RACI Matrix, courtesy of Tallyfy.com :

sample RACI Matrix

Project Charter

This tool is such an obvious, common-sense maneuver that, surprisingly, it isn’t a fundamental part of every Six Sigma process. The project charter is a document that outlines and defines the project’s purpose and scope, acting as both the blueprint for the business process and the project’s legal authorization. Project charters typically include the project overview and scope, relevant details about the team and its resources, and the timeline. The charter gives the team all the necessary basic information about the project and clarifies its main points.

The project charter helps the team maintain a clear understanding of the project, assisting people to maintain focus and cut down on chaos.

Do You Want to Master Six Sigma Tools?

Lean Six Sigma is a popular process, so there is an increased likelihood of encountering it during your professional career. It would be helpful to you if you prepared for this eventuality by taking this valuable Lean Six Sigma Certification bootcamp and getting a head start on the competition.

This Post Graduate Program in Lean Six Sigma, delivered by Simplilearn in collaboration with UMass Amherst, will transform you into a Lean Six Sigma expert. The course dramatically boosts your career in quality management while teaching you necessary and valuable Lean Six Sigma skills. You will benefit from masterclasses conducted by the Isenberg faculty and solve real-world business problems using an outstanding collection of hands-on projects and case studies.

The Lean Six Sigma Certification course teaches you:

  • Agile Management
  • Digital Transformation
  • Lean Management
  • Lean Six Sigma Black Belt
  • Lean Six Sigma Green Belt

The program is aligned with IASSC-Lean Six Sigma and is taught by respected industry professionals active in their specialized fields.

Stay current, and don’t fall behind. Check out this essential course and better equip yourself to face the challenges of today’s fast-paced and ever-changing business world. Make your first move into Six Sigma today!

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Top 9 Data Quality Software Tools & Solutions of 2024

Searching for the best data quality software? Discover our top 9 picks.

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eWEEK content and product recommendations are editorially independent. We may make money when you click on links to our partners. Learn More .

Data quality software plays an essential role in optimizing data for analytics: these software tools cleanse, structure, and enrich raw data to improve its quality and usability.

Clearly the need for data quality software is great: Data in its raw form is barely usable – it gives little to no meaningful insight and may contain errors, inconsistencies, and inaccuracies. Raw data lacks structure, context, and organization, making extracting valuable information or drawing accurate conclusions challenging. Consequently, most enterprise managers are always seeking top choices for data quality solutions.

To aid in this process, we analyzed the best data quality software, including their features, costs, pros and cons, and suitability for business scenarios.


Top Data Quality Software Comparison

Talend icon.

Talend: Best for Scalability

Overall rating: 3.4.

  • Feature set: 5
  • Ease of use: 4
  • Support: 3.5

Talend data quality software is designed to clean and mask your data in real-time. It uses machine learning to handle data quality issues as data flows through your systems. Our analysis of the platform found Talend’s data quality features to be well-equipped to handle large volumes of data. It can process data in parallel and leverage distributed computing capabilities to handle big data workloads ably, meaning it can scale to meet the needs of companies dealing with enormous amounts of data.

Talend data quality seamlessly integrates with other Talend products, such as Talend Data Integration and Talend Data Catalog. This allows users to build end-to-end data management solutions that can handle large and complex data sets while maintaining data quality.

Talend data console showing Talend Trust Score.

Pros and Cons

Pricing for the solution is not publicly available. Contact the company for a custom quote.

  • Data profiling and preparation capabilities.
  • Built-in Talend Trust Score gives you an actionable assessment of confidence in your data.
  • It automatically cleanses incoming data with machine learning-enabled deduplication, validation, and standardization.
  • Compliance with internal and external data privacy and data protection regulations.

Ataccama icon.

Ataccama ONE Data Quality: Best for AI Capabilities

Overall rating: 3.05.

Ataccama’s data quality functionalities are built natively with AI , enabling businesses to leverage machine learning algorithms to automate data quality tasks and remediation processes.

The software can automatically detect data quality issues such as missing values, duplicates, outliers, and inconsistencies and provide suggestions for resolving these issues. Ataccama ONE reduces the need for manual intervention by providing AI-assisted cleansing, standardization, and issue resolution capabilities within a synergistic data catalog.

Our study found that Ataccama ONE Data Quality can integrate existing ETL (Extract, Transform, Load) processes, CI/CD (Continuous Integration/Continuous Deployment) pipelines, and analytics platforms. This integration enables you to implement data quality checks at various stages of the data lifecycle, ensuring that only high-quality data enters your business systems.

Ataccama data quality monitoring dashboard.

Though Ataccama doesn’t advertise its rates on its website, publicly available data shows Ataccama ONE Unified Data Management Cloud Platform costs $90,000 per year, while the Ataccama Upgrade Unit costs $10,000 per unit. That said, we recommend contacting the Ataccama sales team to get your actual pricing information.

  • Uses AI to automate the data preparation and validation process.
  • You can integrate data quality checks with your existing ETL, CI/CD pipelines, and analytics platforms.
  • Automate data quality remediation at various stages.
  • Streamline data quality preparation, remediation, and other processes with data quality co-pilots and assistants.
  • Deployable on-premise, in the cloud, or in hybrid environments.

Informatica icon.

Informatica: Best for Data Profiling and Cleansing

Overall rating: 3.78.

Informatica provides a comprehensive suite of data quality products that include data profiling, data cleansing, data monitoring, and data governance capabilities.

The platform allows you to analyze and understand the quality of your data through ample data profiling capabilities, helping you identify data anomalies, inconsistencies, and patterns to assess the overall data quality. On top of that, Informatica provides advanced cleansing capabilities to standardize, correct, and enrich data, ensuring its accuracy and integrity. It includes many data cleansing functions, such as address validation, formatting, deduplication, and enrichment.

Informatica’s AI engine, CLAIRE, leverages metadata-driven artificial intelligence to deliver intelligent recommendations for data quality rules. It can detect data similarity automatically. This is critical for identifying and managing duplicate data, which can challenge data quality management.

Informatica data quality, asset dashboard.

While Informatica doesn’t advertise its rates on its website, we found that one bundle of its Intelligent Data Management Cloud (IDMC), of which data quality is a part, costs $129,600 per year, $259,200 for two years, and $388,800 for a three-year subscription.

  • Data discovery and observability.
  • AI-driven insights.
  • Self-service data quality for business users.
  • Low-code/no-code capabilities.

Oracle icon.

Oracle Enterprise Data Quality: Best for Large Enterprises with Complex Data Quality Requirements

Overall rating: 3.40.

  • Ease of use: 4.5

Our research found that Oracle Enterprise Data Quality (EDQ) offers tools capable of meeting the needs of enterprises with complex data needs, as it provides a comprehensive set of capabilities for data profiling, audit, parsing, and standardization; match and merging; address verification; and product data extension. Oracle EDQ offers global address verification and geocoding coverage, adding geocodes to city or postal codes for over 240 countries.

The platform’s ability to profile and audit data can help organizations uncover and quantify hidden data problems, while data parsing and standardization let users transform and standardize data, such as names, addresses, dates, and phone numbers. The match and merge feature allows for matching and merging parties at individual, group, or household levels, with flexible rules that can be tailored to suit specific business needs.

Oracle EDQ data quality health check.

Contact the company for quotes.

  • Parsing and standardization.
  • Match and merge capabilities.
  • Case management functionality.
  • Address verification.

SAP icon.

SAP: Best for Analytics and Supply Chain Management

Overall rating: 3.63.

SAP Data Quality Management (DQM) helps businesses improve the quality of their data by ensuring its accuracy, completeness, and consistency. The company’s DQM has three versions of SAP solutions: SAP HANA smart data quality, SAP Data Quality Management, microservices for location data, and SAP Data Services.

SAP HANA smart data quality offers a high-performance, rule-based solution to cleanse and merge data, such as address data, to identify duplicates in the data sources. The service for location data within SAP Data Quality Management specifically focuses on improving the quality of location-related information. It helps businesses ensure that their location data is correct and up-to-date. This includes addresses, geocodes, coordinates, postal codes, and other location-specific information.

By integrating the location data microservice into enterprise systems, businesses can improve the accuracy of their customer databases, reduce shipping errors, optimize logistics and routing, enhance location-based services, and ultimately provide better customer experiences.

SAP Data Quality Management, microservice for location data.

SAP Data Quality Management, microservices for location data costs $864, but contact the company for a more comprehensive quote.

  • Geolocation enrichment services.
  • Built-in integration with SAP applications.
  • Address validation and geocoding.
  • Type-ahead autocompletion.

Precisely icon.

Precisely: Best for Data Enrichment

Overall rating: 3.13.

  • Support: 2.5

Precisely offers several data quality solutions, such as data matching and entity resolution, data validation and enrichment, address validation and standardization, CRM & ERP data validation, customer 360, and data observability tools.

These products provide customers across various sectors with the means to ensure accurate and reliable data in their systems. Our analysis of the Precisely platform reveals that its data enrichment tool is highly regarded for its robust capabilities.

Precisely’s data enrichment tool leverages a vast database of internal and external sources to provide up-to-date information, enabling businesses to gain deeper insights. For example, its location intelligence tool offers a catalog of over 400 datasets containing 9,000+ attributes. This allows organizations to enrich their location or address data with a wide range of information, including points of interest, property attributes, demographic data, and dynamic data like weather changes.

Precisely Data360 Govern, data quality check.

Contact the company for a custom quote.

  • Geo addressing and spatial analytics.
  • Automated validation and cleansing.
  • End-to-end DQ.
  • Users can collaborate on data quality metrics and visualizations with the ability to annotate on dashboards and capture point-in-time feedback.

IBM icon.

IBM InfoSphere: Best for Unified Data Quality Management

Overall rating: 3.35.

If you are looking for a tool to help you cleanse data and monitor data quality in a centralized environment, IBM InfoSphere Information Server for Data Quality is a top choice. It offers many data quality features, including data profiling, classification, investigation, standardization, matching, survivorship, address verification, and monitoring.

The platform enables you to understand your data and its relationships, continuously analyze and monitor data quality, cleanse, standardize, match data, and maintain data lineage. The tool also includes support for USAC and AVI address cleansing and validation, which can be valuable for organizations that deal with address data.

IBM InfoSphere MDM Express dashboard.

Contact the company for a quote.

  • Automates data investigation, information standardization, and record matching based on business rules.
  • Data monitoring capability.
  • Data standardization and validation.
  • Classification function.

Atlan icon.

Atlan: Best for Collaboration

Overall rating: 2.88.

Atlan simplifies the process of working with data by allowing teams to store, clean, analyze, and collaborate on data on a centralized platform. The platform provides several features, including data cataloging, discovery, quality assessment, and lineage tracking.

Atlan collaborative features enable multiple team members to collaborate on real-time data analysis, visualizations, and reporting. You can send questions directly to your team’s Slack channel from Atlan or create a Jira ticket directly from Atlan.

Atlan also offers a Chrome plugin that lets you access its metadata within your BI tool, enhancing the data-driven analysis experience. The platform provides a Slackbot that enables anyone in the team to search for and access business definitions. This helps maintain consistency and understanding of data across the organization, as users can quickly retrieve definitions and context within the Slack messaging platform.

Atlan Data Stack dashboard.

Atlan requires interested buyers to contact their sales team for quotes. Publicly available information shows that Atlan Active Metadata Platform costs $120,000 per year, $220,000 for 24 months, and $340,000 for 36 months. Contact the Atlan sales team for a quote to get your actual rate.

  • Automatically mask sensitive data.
  • Integration with third-party apps such as Slack, GitHub, Google Drive, Confluence, Jira, Figma, and Notion.
  • Metadata management.
  • Natural language search.
  • Search using SQL syntax.

Cloudingo icon.

Cloudingo: Best for Improving Salesforce Data Quality

Overall rating: 2.43.

  • Feature set: 1.75

Cloudingo is a cloud-based data quality and deduplication tool for Salesforce. It helps organizations maintain clean and accurate customer data by identifying and merging duplicate records, as well as standardizing and enriching data.

The platform’s capabilities include automated deduplication, merging of duplicate records, data cleansing, and enrichment to enhance data quality. Our research found that Cloudingo provides customizable matching rules to identify and merge duplicate records based on different criteria. It also offers real-time syncing to ensure data consistency across different Salesforce objects and modules.

Cloudingo multi-select filters for action.

A 10-day free trial is available.

  • Standard: $2,500 per year. Single user account.
  • Professional: $6,000 per year. 3 user accounts.
  • Enterprise: $10,000 per year. 8 user accounts.
  • Discover duplicates using user-defined filters.
  • Schedule dedupe jobs — you can set it for daily or weekly.
  • Undo and restore merges.
  • Progress and tracking reports.
  • Mass update and mass delete records capabilities.

How to Choose the Best Data Quality Software for Your Business

The best data quality software should offer a combination of user-friendliness, customization, and scalability to meet the needs of your team and organization. Before buying a data quality tool, start by understanding your specific data quality needs.

  • What are the problems you are trying to solve?
  • Do you need to clean and standardize data, identify duplicates, or validate data integrity?

Make a list of features and functionalities that are essential for your business. This will guide your decision-making. We analyzed each tool’s features, pros, and cons, as well as the cost data of each tool, to help you determine the best option for your organization – weigh each of these key factors.

Before buying any data quality software, read reviews from current users and determine how closely their situations match your circumstances.

How We Evaluated the Best Data Quality Software

Cost – 25%.

The cost category accounted for 25% of our evaluation criteria. We looked at factors such as the availability of free trials, pricing plans, and the transparency of pricing visibility.

Feature set – 35%

We assessed whether the software performs data profiling, enables data visualization, includes AI capability, and supports data governance. These capabilities were essential in determining the software’s effectiveness in improving data quality.

Ease of use – 25%

We examined the overall user interface of the data quality software we reviewed to determine whether it required expert set-up and the level of automation it offered. A user-friendly interface and automation features are essential in ensuring that users with varying technical expertise can quickly adopt and operate the software.

Support – 15%

We considered the support provided by each software. This included evaluating factors such as customer service hours, availability of live chat support, email/ticket support, and the presence of a comprehensive knowledge base.

Frequently Asked Questions (FAQs) About Data Quality Software

What are the standard features of data quality software.

Common features of data quality software include data profiling, cleansing, standardization, enrichment, matching, monitoring, governance, integration, and security capabilities.

Is data quality software only for large enterprises?

No, data quality software is not exclusively for large enterprises. Organizations of all sizes can benefit from data quality software if they have data-related challenges that must be addressed.

What deployment options are available for data quality software?

Data quality software can be deployed on-premises, in the cloud, or in hybrid environments, depending on the preferences and requirements of the organization. Some vendors also offer software as a service (SaaS) or platform as a service (PaaS) options.

Bottom Line: Data Quality Software 

Data that has not been properly prepared can significantly impact your business, leading to inefficient processes, poor decision-making, and wasted resources. The best data quality software can address your organization’s data quality challenges, streamline processes, minimize errors, and provide reliable and accurate insights. By investing in the right data quality software, your company can improve its data quality, enhance decision-making processes, and drive overall business success.

For a deeper understanding of the many factors that drive optimal use of data, see our guide: What is Data Analytics  

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