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7 Powerful Problem-Solving Root Cause Analysis Tools

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

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

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

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

1. The Ishikawa Fishbone Diagram IFD

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

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

Related Training: Fishbone Diagramming

2. Pareto Chart

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

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

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

Related training: Accident/Incident Investigation and Root Cause Analysis

4. Failure Mode and Effects Analysis (FMEA)

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

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

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

Related Training: Failure Mode Effects Analysis

5. Scatter Diagram

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

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

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

6. Affinity Diagram

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

7. Fault Tree Analysis (FTA)

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

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

ComplianceOnline Trainings on Root Cause Analysis

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

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

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

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

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

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

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

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

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

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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

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.

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 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

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.

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

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7 QC Tools: Your Ultimate Guide To Quality Improvement

Introduction to 7 QC tools

Quality management is an important aspect of any organization, and achieving it requires effective problem-solving strategies. In this regard, the 7 QC tools offer a comprehensive approach to problem-solving and quality improvement. These tools are designed to help organizations identify the root cause of problems, make data-driven decisions, and ultimately improve the quality of their products or services. In this post, we will explore the importance of the 7 QC tools, their history and evolution, how to select the right tool for quality control, and detailed explanations of each of the 7 QC tools.

Importance of 7 QC tools in quality management

The importance of 7 QC tools in quality management cannot be overstated. These tools help organizations to improve quality by providing a systematic approach to problem-solving. They enable organizations to analyze data, identify problem areas, and make data-driven decisions. By using these tools, organizations can reduce costs, increase productivity, and improve customer satisfaction. The 7 QC tools are widely used in various industries, including manufacturing, healthcare, and service sector. They are easy to use, cost-effective, and can be applied to various types of problems.

History and evolution of 7 QC tools

The history and evolution of the 7 QC tools can be traced back to the early 1920s when Dr. Walter A. Shewhart introduced the concept of statistical process control (SPC). Over time, additional techniques were added to the original seven, and the tools evolved to include Pareto charts, cause-and-effect diagrams, check sheets, histograms, scatter diagrams, and control charts. Today, the 7 QC tools are widely used in quality management and have become an integral part of Lean and Six Sigma methodologies.

How to select the right tool for quality control

Here are some points to consider when selecting the right tool for quality control:

• Identify the problem: Before selecting a tool, it is important to clearly identify the problem at hand. This will help determine which tool is best suited for the job.
• Understand the data: Understanding the data available is crucial for selecting the right tool. Some tools are better suited for qualitative data, while others work best with quantitative data.
• Determine the scope: Consider the scope of the problem and the level of detail required to solve it. Some tools are better suited for analyzing specific details, while others provide a more holistic view of the problem.
• Consider the complexity: Some problems are more complex than others, and require more sophisticated tools to solve. Consider the level of complexity and choose a tool that is appropriate for the problem at hand.
• Evaluate the strengths and limitations: Each tool has its own strengths and limitations. It is important to understand these before selecting a tool, so that you can choose one that is best suited for the problem at hand.
• Seek expert advice: If you are unsure which tool to use, seek advice from experts in the field. They can provide valuable insights and help you select the right tool for the job.

By considering these factors, you can select the right tool for quality control and ensure that your problem-solving efforts are effective and efficient.

7 QC Tools Explained

1. Pareto Chart

A Pareto chart is a graph that displays the relative frequency or size of problems in descending order of importance. It is a tool for identifying the most significant causes of a problem or the largest sources of variation in a process. The chart uses a vertical bar graph to show the frequency or size of each problem, with the bars arranged in order of decreasing importance. The chart also includes a cumulative percentage line that shows the cumulative percentage of problems accounted for by each cause. Pareto charts are useful for prioritizing problems and identifying the root causes that should be addressed to have the most significant impact on process improvement.

2. Cause-and-effect diagram

A cause-and-effect diagram, also known as a fishbone diagram or Ishikawa diagram, is a tool used to identify the root causes of a problem. It is a structured approach that helps to identify and categorize the possible causes of a problem, based on the various factors that could contribute to it. The diagram starts with a problem statement at the head of the diagram and uses a structured approach to identify the possible causes, grouping them into categories such as people, process, equipment, materials, and environment. Cause-and-effect diagrams are useful for identifying the root causes of a problem and for organizing and structuring the potential causes in a way that can be easily analyzed and addressed.

3. Check sheet

A check sheet is a tool used to collect data in a structured way. It is a simple form that is used to record data in a standardized format, making it easy to collect and analyze data across different processes or situations. Check sheets can be used to track defects or errors, record the frequency of events, or collect other types of data. They are useful for identifying patterns and trends in data, as well as for tracking progress and improvement over time.

4. Histogram

A histogram is a graph that shows the distribution of data. It is a visual representation of how frequently certain values occur within a set of data, using a series of vertical bars. The bars are grouped into categories or ranges of values, with the height of each bar representing the number of data points that fall within that category. Histograms are useful for identifying the shape of the distribution, including the mean and standard deviation, and for identifying outliers or unusual data points.

5. Scatter diagram

A scatter diagram also known as a scatter plot, is a graph that shows the relationship between two variables. It is a visual representation of how one variable changes in response to changes in the other variable. Each data point is plotted on the graph as a point, with one variable represented on the x-axis and the other variable represented on the y-axis. Scatter diagrams are useful for identifying correlations or patterns in data, and for identifying outliers or unusual data points. They are commonly used in quality control and process improvement to identify relationships between process variables and product quality or performance.

6. Control Charts

A control chart is a tool used to monitor and control a process over time. It is a graphical representation of data collected from a process, plotted against established control limits. The chart shows how the process is performing and alerts the user to any changes or variations that may occur. Control charts are useful for identifying trends, detecting shifts or changes in the process, and for identifying the sources of variation that may be causing problems. They can be used to monitor any process that produces data, from manufacturing to healthcare to financial services.

7. Flow Charts

A flow chart is a diagram that shows the steps in a process or system. It is a visual representation of the sequence of activities involved in a process, from start to finish. Flow charts are used to help understand a process, identify bottlenecks or inefficiencies, and to design or improve a process. The chart consists of boxes, symbols, and arrows that indicate the flow of the process. Boxes represent steps or actions in the process, while arrows represent the flow of materials or information between steps. Flow charts are useful for analyzing and improving any process, from simple to complex, and can be used in a variety of industries, including manufacturing, healthcare, and software development.

7 QC Tools: A Summary Table

These 7 QC tools are often used in combination with each other and with other quality management tools to improve quality and productivity, reduce costs and waste, and enhance customer satisfaction. The 7 QC Tools can be applied across various industries, including manufacturing, healthcare, finance, and service industries. These tools help to identify problems, analyze data, and improve processes, leading to better quality control and customer satisfaction. Knowing how and when to use each tool is essential to their effectiveness and achieving process improvement.

7 QC Tools Limitations:

While the 7 QC tools are widely used and effective for quality management, there are some limitations to their application. Here are some of the common limitations:

• Limited scope: The 7 QC tools are primarily focused on identifying and analyzing data related to quality issues and do not address other important aspects of quality management such as customer satisfaction, process improvement, and strategic planning.
• Lack of guidance: While the 7 QC tools provide a structured approach to data analysis, they do not provide guidance on how to implement solutions or make improvements based on the results.
• Data interpretation: The accuracy and usefulness of the data analyzed using the 7 QC tools depend on the quality and reliability of the data collected. Incorrect data or incomplete data can lead to incorrect conclusions and ineffective solutions.
• Limited application: The 7 QC tools are designed for use in manufacturing and industrial settings, and may not be as relevant or applicable in service industries or other non-manufacturing settings.
• Insufficient for complex problems: The 7 QC tools are useful for identifying and analyzing simple quality problems with a single cause or factor, but may be insufficient for more complex problems that have multiple causes and variables.
• Overreliance on data: The 7 QC tools rely heavily on data analysis and may overlook other important factors that contribute to quality, such as employee involvement, leadership, and culture.

Alternative Approach to 7QC Tools:

There are several other quality management tools and methodologies that organizations can use in addition to or instead of the 7 QC tools. Some of these alternatives include:

• Six Sigma: A data-driven approach to quality management that aims to minimize defects and variability in processes and products by using statistical methods and tools.
• Lean Manufacturing: A methodology focused on reducing waste and improving efficiency in manufacturing processes by eliminating non-value-added activities, streamlining production flows, and increasing responsiveness to customer demands.
• Root Cause Analysis (RCA): A problem-solving technique used to identify the underlying causes of a problem or failure, and develop solutions to prevent recurrence.
• Failure Mode and Effects Analysis (FMEA): A proactive risk management tool that helps identify and mitigate potential failures and defects in products or processes before they occur.
• Statistical Process Control (SPC): A method for monitoring and controlling a process by using statistical techniques to identify and correct deviations and abnormalities in the process.
• Kaizen: A continuous improvement philosophy that emphasizes small, incremental changes in processes and systems, and encourages employee involvement and empowerment.

These tools and methodologies can be used alone or in combination with each other, depending on the specific needs and goals of the organization.

In conclusion, the 7 QC tools offer a comprehensive approach to problem-solving and quality improvement. They are data-driven, cost-effective, and provide a systematic approach to quality management. By using these tools, organizations can reduce costs, increase productivity, and improve customer satisfaction. However, it is important to select the right tool for the problem at hand, and to understand the strengths and limitations of each tool. The 7 QC tools have a rich history and have become an integral part of Lean and Six Sigma methodologies, making them an essential tool for any organization that wants to improve the quality of its products or services.

References:

Goetsch, D. L., & Davis, S. B. (2014). Quality management for organizational excellence. Upper Saddle River, NJ: Pearson.

Ishikawa, K. (1985). What is Total Quality Control? The Japanese Way. Englewood Cliffs, NJ: Prentice Hall.

Batch vs. One Piece Flow Manufacturing: Which Is Right For Your Business?

Maximizing Quality And Efficiency: The Power Of Design For Six Sigma (DFSS)

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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.

Conclusion:

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?

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

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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. 

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. 

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.

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.

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. 

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.

 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.

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. 

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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7 Basic Tools of Quality for Process Improvement

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

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

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

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

Quality Tools: What Are They?

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

• Control chart
• Pareto chart

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

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

The 7 basic quality tools include;

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

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

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

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

7 Basic Quality Tools Explained with Templates

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

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

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

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

Real-world examples of usage

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

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

How to use a flowchart

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

Who can use it?

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

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

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

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

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

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

How to make a histogram

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

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

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

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

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

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

How to use the cause and effect diagram

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

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

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

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

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

How to make a scatter diagram

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

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

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

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

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

How to make a checksheet

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

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

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

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

Control Chart

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

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

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

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

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

How to create a control chart

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

Pareto Chart

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

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

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

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

How to create a Pareto chart

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

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

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

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

Join over thousands of organizations that use Creately to brainstorm, plan, analyze, and execute their projects successfully.

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.

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

13 Quality Management Tools to Drive Process Improvements

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

Why are they used?

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

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

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

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

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

Why are They Called Quality Management Tools?

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

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

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

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

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

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

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

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

Here they are in their full glory:

• PDCA / DMAIC (or some process improvement framework)

Statistical Process Control

Process mapping.

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

Brainstorming

• Pareto Charts

Control Charts

• Check Sheets

Matrix Analysis

Scatter diagrams.

• Dot Plot charts

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

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

Process Improvement Framework

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

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

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

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

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

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

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

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

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

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

And with consistent output comes stable processes.

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

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

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

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

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

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

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

Should every process be measured, using SPC?

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

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

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

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

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

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

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

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

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

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

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

Control Chart

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

Not what we think or what should happen.

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

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

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

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

This process is a Valve making process.

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

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

We can stop and tackle the problem there and then.

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

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

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

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

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

Before any assumptions or further actions are made.

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

Process Map Example

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

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

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

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

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

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

Cause and Effect Diagram

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

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

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

CEDAC Fishbone Diagram

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

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

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

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

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

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

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

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

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

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

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

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

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

Then discuss. Group the post its that are similar.

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

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

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

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

Pareto Analysis

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

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

80% of defects come from 20% root causes…

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

It’s simple in its approach.

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

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

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

Here’s as an example of a Pareto Chart:

Pareto Chart Example

Check Sheet

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

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

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

It simplifies the task of analysis.

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

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

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

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

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

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

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

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

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

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

Which one is easiest to read?

Which one can you use to spot trends?

It’s a no-brainer, right?

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

Bar Charts could be used in the following examples:

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

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

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

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

Project Selection Matrix

Again, notice how clear it is to decipher?

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

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

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

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

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

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

Cause and effect matrix

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

Why use a scatter diagram?

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

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

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

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

Here’s an example of a scatter diagram:

Scatter Diagram

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

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

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

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

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

Dot plot Charts

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

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

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

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

Here’s an example:

dotplot chart with bell shape

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

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

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

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

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

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

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

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

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

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

For example, our size ranges might go:

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

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

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

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

Histogram with ucl and lcl

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

The distribution is too wide.

And the mean is slightly skewed to the lower end.

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

Use These Quality Management Tools to Suit Your Needs

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

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

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

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

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

Others may need just 2-3 of them.

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

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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 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 .

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 :

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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Research: How Different Fields Are Using GenAI to Redefine Roles

• Maryam Alavi

Examples from customer support, management consulting, professional writing, legal analysis, and software and technology.

The interactive, conversational, analytical, and generative features of GenAI offer support for creativity, problem-solving, and processing and digestion of large bodies of information. Therefore, these features can act as cognitive resources for knowledge workers. Moreover, the capabilities of GenAI can mitigate various hindrances to effective performance that knowledge workers may encounter in their jobs, including time pressure, gaps in knowledge and skills, and negative feelings (such as boredom stemming from repetitive tasks or frustration arising from interactions with dissatisfied customers). Empirical research and field observations have already begun to reveal the value of GenAI capabilities and their potential for job crafting.

There is an expectation that implementing new and emerging Generative AI (GenAI) tools enhances the effectiveness and competitiveness of organizations. This belief is evidenced by current and planned investments in GenAI tools, especially by firms in knowledge-intensive industries such as finance, healthcare, and entertainment, among others. According to forecasts, enterprise spending on GenAI will increase by two-fold in 2024 and grow to $151.1 billion by 2027 .

• Maryam Alavi is the Elizabeth D. & Thomas M. Holder Chair & Professor of IT Management, Scheller College of Business, Georgia Institute of Technology .

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