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The 7 Quality Control Tools: A Comprehensive Guide for Quality Excellence

July 8th, 2024

Quality proves pivotal for organizational endurance and success. Whether a seasoned quality guiding hand or a newcomer to the field, the 7 Quality Control tools stand as treasured companions to advance one’s abilities.

Esteemed quality pioneer Kaoru Ishikawa unveiled these 7 tools amid Japan’s post-war awakening, fashioning statistical quality principles accessible for all experiences and enabling company-wide effectiveness.

Graphical techniques help pinpoint, unravel, and solve quality matters, the 7 tools offer structured, evidence-guided approaches for problem-solving, process refinement, and decision-making.

Teams thus steer confidently by comprehension over assumption or intuition.

For quality stewards dedicated to performance-boosting and relationship-building through shared knowledge, these classic tools remain trusted aids.

This discussion explores each technique’s nuanced gifts, illuminating their staying power for continual optimization wherever quality matters most.

Key Highlights

• Understand the historical context and significance of the 7 quality control tools, and how they revolutionized Japan’s industrial resurgence after World War II.
• Cause-and-Effect Diagram ( Fishbone/Ishikawa Diagram )
• Check Sheets (Tally Sheets)
• Control Charts (Shewhart Charts)
• Pareto Charts
• Scatter Diagrams
• Stratification (Flowcharts/Run Charts)
• Learn best practices for creating, interpreting, and effectively using each of these tools, with step-by-step guidance and industry-proven techniques.
• Explore case studies and success stories that showcase the powerful impact of integrating the 7 quality control tools.
• Discover strategies for seamlessly incorporating these tools into your organization’s problem-solving and continuous improvement efforts, fostering a data-driven culture of excellence.
• Gain insights into the future of quality control tools in the digital age and how they can be adapted to meet the evolving needs of modern businesses.

Introduction to the 7 Quality Control Tools

Where quality is the cornerstone of success, the 7 quality control tools stand as indispensable allies for organizations seeking to achieve and sustain excellence.

These tools, collectively known as the 7 QC tools, are a set of graphical techniques designed to simplify the intricate concepts of statistical quality control, making them accessible to professionals across various industries and backgrounds.

Definition and overview of the 7 quality control tools

The 7 quality control tools encompass a comprehensive suite of techniques that empower organizations to identify, analyze, and solve quality-related issues with precision and efficiency.

Each tool serves a specific purpose, providing a structured and data-driven approach to problem-solving, process improvement , and decision-making, enabling teams to make informed choices based on evidence rather than guesswork or intuition.

Historical background and importance

The origins of the 7 quality control tools can be traced back to the post-war era in Japan, where the esteemed Kaoru Ishikawa, a pioneer in the field of quality management , recognized the need to simplify the complex concepts of statistical quality control.

During this pivotal period, Japanese organizations were focused on training their workforce in these advanced techniques but soon realized that the inherent complexity could intimidate and deter many workers from embracing these methodologies effectively.

Ishikawa’s visionary solution was to introduce the 7 quality control tools, which distilled the essence of statistical quality control into a set of user-friendly, graphical techniques.

Benefits of using the 7 quality control tools

The adoption of the 7 quality control tools offers numerous benefits to organizations committed to continuous improvement and customer satisfaction.

These tools facilitate:

Effective Problem-Solving: By providing a structured framework for identifying root causes , analyzing data, and visualizing relationships, the 7 QC tools equip teams with the necessary insights to address quality issues effectively.

Process Improvement: Through data-driven analysis and monitoring, these tools enable organizations to identify areas for improvement, streamline processes, and eliminate inefficiencies, ultimately enhancing productivity and reducing waste.

Data-driven Decision Making: The 7 quality control tools empower teams to base their decisions on objective data and statistical analysis, minimizing the risk of biases or unfounded assumptions, and leading to more informed and effective decision-making processes.

The 7 Quality Control Tools Explained

1. cause-and-effect diagram (fishbone diagram).

The Cause-and-Effect Diagram, also known as the Fishbone Diagram or Ishikawa Diagram , is a powerful tool designed to facilitate root cause analysis and identify potential causes contributing to a specific problem or effect.

Named after its creator, Kaoru Ishikawa, this diagram visually represents the relationship between an effect and its potential causes, resembling the skeletal structure of a fish.

The primary purpose of the Cause-and-Effect Diagram is to systematically explore and organize the various factors that could potentially contribute to a particular issue or outcome.

How to create and use a cause-and-effect diagram

Creating an effective Cause-and-Effect Diagram involves the following steps:

• Define the problem or effect: Clearly state the issue or outcome you wish to analyze, which will be represented as the “fish head” on the diagram.
• Identify the main cause categories: Determine the primary categories or broad areas that could potentially contribute to the problem, such as materials, methods, machinery, environment, or personnel. These categories will form the “bones” or main branches of the fishbone diagram .
• Brainstorm potential causes: For each main category, engage in a structured brainstorming session to identify specific potential causes or contributing factors. These sub-causes will be represented as smaller “bones” branching off from the main categories.
• Analyze and prioritize causes: Once all potential causes have been identified, analyze the diagram to determine which causes are most likely to be contributing to the problem. Prioritize these causes based on their perceived impact or likelihood of occurrence.
• Develop and implement countermeasures: Based on the prioritized causes, develop and implement targeted countermeasures or corrective actions to address the root causes and mitigate the problem effectively.

2. Check Sheets (Tally Sheets)

Check sheets, also known as tally sheets , are straightforward yet powerful tools designed to facilitate the systematic collection and organization of data related to quality issues, defects, or process performance.

These sheets serve as a structured means of recording and tabulating data, enabling organizations to identify patterns, trends, and areas for improvement.

The primary purpose of check sheets is to streamline the process of data collection and analysis, allowing teams to gather quantitative or qualitative information consistently and efficiently.

Types of check sheets

Check sheets can be categorized into three main types, each serving a specific purpose:

• Defect Location Check Sheets: These sheets are designed to record the location or specific area where a defect or issue occurred, providing valuable insights into potential problem areas or hotspots within a process.
• Tally Check Sheets: As the name implies, tally check sheets are used to record the frequency or occurrences of specific events, defects, or phenomena. These sheets typically feature a simple tally or check mark system, making it easy to quickly capture and quantify data.
• Defect Cause Check Sheets: These sheets are particularly useful for identifying and categorizing the potential causes or contributing factors associated with observed defects or issues. By capturing this information, organizations can gain valuable insights into the root causes underlying quality problems.

How to create and use check sheets

Creating and utilizing check sheets involves the following steps:

• Identify the data to be collected: Determine the specific information or metrics that need to be captured, such as defect types, locations, frequencies, or potential causes.
• Design the check sheet: Based on the identified data requirements, create a structured check sheet with appropriate columns or sections for recording the relevant information. Ensure that the sheet is user-friendly and easy to understand for those responsible for data collection.
• Train data collectors: Provide clear instructions and training to the individuals responsible for collecting data, ensuring they understand the purpose of the check sheet and the proper methods for recording information.
• Collect data: Implement the check sheet in the relevant areas or processes, and consistently record data as it becomes available or as events occur.
• Analyze and interpret data: Once sufficient data has been collected, analyze the check sheet for patterns, trends, or areas of concern. Use the information gathered to identify opportunities for improvement or further investigation.

3. Control Chart (Shewhart Chart)

Control charts, also known as Shewhart charts, are powerful statistical tools used for monitoring and analyzing process performance over time.

Named after Walter A. Shewhart, a pioneer in the field of statistical quality control, these charts are designed to help organizations determine whether a process is stable and predictable, or if it is subject to undesirable variations that require intervention.

The primary purpose of control charts is to enable organizations to practice statistical process control (SPC) , which involves monitoring and controlling a process to ensure that it operates within predetermined statistical limits.

Components of a control charts

A typical control chart consists of the following key components:

• Control Limits
• Center Line (Mean)
• Data Points

How to create and interpret control charts

Creating and interpreting control charts involves the following steps:

• Collect data: Gather relevant data on the process characteristic or quality metric you wish to monitor, ensuring that the data is representative and collected under stable conditions.
• Calculate control limits and center line: Using statistical methods (e.g., X-bar and R charts , individuals, and moving range charts ), calculate the upper and lower control limits, as well as the center line (mean) for the process characteristic.
• Plot data points: Plot the collected data points or subgroup averages on the control chart, positioning them relative to the control limits and center line.
• Interpret patterns and signals: Analyze the control chart for patterns or signals that indicate potential issues or variations in the process . Common signals include points outside the control limits , runs above or below the center line, or unusual patterns or trends.
• Investigate and take action: When signals or patterns indicate a potential issue, investigate the root causes and take appropriate corrective actions to bring the process back within control limits and ensure consistent performance.

4. Histogram

A histogram is a powerful data visualization tool that graphically represents the frequency distribution of a set of data.

It is a type of bar chart that displays the number of occurrences or observations within specific ranges or intervals, providing a clear visual representation of how data is distributed.

How to create and interpret histograms

Creating and interpreting histograms involves the following steps:

• Collect data: Gather the relevant data that you wish to analyze and visualize.
• Determine bin ranges: Divide the range of data into intervals or “bins” of equal width, ensuring that each data point falls into one of the defined bins.
• Calculate frequencies: Count the number of data points that fall into each bin, representing the frequency of occurrences within that range.
• Construct the histogram: Plot the bins on the horizontal axis and the corresponding frequencies on the vertical axis, creating a bar for each bin with a height proportional to its frequency.
• Analyze the distribution: Interpret the shape, center, and spread of the distribution by observing the patterns and characteristics displayed in the histogram, such as skewness, modality, and outliers.

5. Pareto Chart

The Pareto chart, named after the Italian economist Vilfredo Pareto, is a powerful tool that helps organizations prioritize issues or factors based on their relative importance or impact.

It is based on the Pareto principle, also known as the 80/20 rule , which suggests that a majority of consequences (typically around 80%) are often influenced by a minority of causes (approximately 20%).

How to create and interpret Pareto charts

Creating and interpreting Pareto charts involves the following steps:

• Collect data: Gather data on the various factors or issues you wish to analyze, such as defect types, causes of customer complaints, or sources of waste.
• Categorize and rank data: Categorize the data into logical groups or factors, and rank them in descending order based on their frequency, impact, or importance.
• Construct the Pareto chart: On the left vertical axis, plot the frequency or impact of each factor using bars, arranged in descending order from left to right. On the right vertical axis, plot the cumulative percentage represented by a line graph.
• Identify the “vital few”: Analyze the chart to identify the factors or issues that contribute to a significant portion of the overall problem or outcome, typically around 80% or more. These are considered the “vital few” that should be prioritized.
• Prioritize and take action: Based on the identified vital few factors, prioritize and implement targeted improvement efforts or corrective actions to address the most significant contributors to the problem.

6. Scatter Diagram

A scatter diagram, also known as a scatter plot, is a graphical tool used to analyze and visualize the relationship between two variables.

It plots pairs of numerical data, with one variable represented on the horizontal (x) axis and the other variable on the vertical (y) axis, forming a collection of data points.

The primary purpose of a scatter diagram is to identify and understand the nature and strength of the relationship between two variables.

How to create and interpret scatter diagrams

Creating and interpreting scatter diagrams involves the following steps:

• Identify variables: Select the two variables you wish to analyze for potential relationships, typically an independent variable (x-axis) and a dependent variable (y-axis).
• Collect data: Gather pairs of data points representing the values of the two variables.
• Plot data points: On a coordinate plane, plot each pair of data points by representing the independent variable’s value on the x-axis and the dependent variable’s value on the y-axis.
• Positive correlation: Data points form an upward-sloping pattern, indicating that as one variable increases, the other tends to increase as well.
• Negative correlation: Data points form a downward-sloping pattern, indicating that as one variable increases, the other tends to decrease.
• No correlation: Data points are randomly scattered, indicating no apparent relationship between the variables.

7. Stratification (Flowchart, Run Chart)

Stratification, also known as a flowchart or run chart , is a quality control tool used to categorize and visually represent data or process steps in a structured manner.

It involves dividing or grouping data into distinct categories or strata based on specific characteristics or factors, enabling organizations to identify patterns, trends, or potential areas for improvement within each stratum.

The primary purpose of stratification is to enhance process understanding by revealing insights that may be obscured when data is analyzed as a whole.

How to create and use stratification

Creating and using stratification involves the following steps:

• Identify stratification factors: Determine the factors or characteristics that will be used to categorize the data, such as product type, manufacturing shift, supplier, or geographic region.
• Collect and categorize data: Gather relevant data and categorize it based on the identified stratification factors, ensuring that each data point is assigned to the appropriate stratum or category.
• Construct the stratification diagram: Visually represent the categorized data using a flowchart, run chart , or other suitable graphical representation, clearly distinguishing the different strata or categories.
• Analyze within strata: Examine the data within each stratum or category, looking for patterns, trends, or variations that may be specific to that particular group or factor.
• Compare across strata: Compare the patterns and trends observed across different strata to identify potential sources of variation or areas where improvements can be made.
• Implement targeted improvements: Based on the insights gained from the stratification analysis, develop and implement targeted improvement efforts or corrective actions tailored to specific strata or factors.

Integrating the 7 Quality Control Tools

While each of the 7 quality control tools serves a specific purpose, their true power lies in their integrated use for comprehensive problem-solving and process improvement efforts.

By combining the strengths of these tools, organizations can gain a holistic understanding of quality issues, identify root causes , and develop effective solutions.

By integrating the 7 quality control tools into a cohesive problem-solving framework, organizations can leverage their collective power, ensuring a comprehensive and data-driven approach to continuous improvement and quality excellence.

Incorporating the tools into quality management methodologies

The 7 quality control tools have become indispensable components of various quality management methodologies and frameworks, such as Lean, Six Sigma , and Total Quality Management (TQM) .

These methodologies provide structured approaches to quality improvement, and the 7 QC tools serve as essential techniques for data collection, analysis, and decision-making within these frameworks.

For instance, in the Six Sigma methodology, the 7 quality control tools are commonly used throughout the DMAIC (Define, Measure, Analyze, Improve, Control) cycle:

• Define: Flowcharts and cause-and-effect diagrams can be used to define the problem and identify potential root causes.
• Measure: Check sheets and stratification can be employed to collect and categorize data for analysis.
• Analyze: Histograms, Pareto charts, and scatter diagrams can provide insights into process performance, prioritize issues, and identify relationships between variables.
• Improve: Based on the analysis, targeted improvements can be implemented using the insights gained from the various tools.
• Control: Control charts can be used to monitor process performance and ensure sustained improvements.

These 7 quality control tools / companions emerge as invaluable allies across industries.

Born from Kaoru Ishikawa’s pioneering perceptiveness, they prove themselves repeatedly – empowering problem exposure, unraveling, and solving with sureness and efficiency.

Their true gift lies in simplicity and reach. Distilling statistical quality’s complexities insightfully, these graphical friends democratize quality’s pursuit, including diverse talents in continuous progress coordination.

Individual tools interconnect, a toolkit illuminating root causes, prioritizing concerns, and implementing targeted remedies.

Their integration further strengthens quality systems like Lean, Six Sigma , and Total Quality Management .

Whether a guiding veteran, up-and-coming practitioner, or business leader invested in operational excellence , embrace these seven gifts.

Foster opportunity and culture for constantly honing comprehension. Weave their methods wherever quality presides.

Steered thus, organizations stay on course addressing today’s and tomorrow’s challenges, and leadership in quality for decades ahead.

May shared insights propel all committed to thoughtful cooperation, service improvement and relationships uplifted through challenges met together.

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7 Basic Tools of Quality for Process Improvement

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

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

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

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

Quality Tools: What Are They?

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

• Control chart
• Pareto chart

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

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

The 7 basic quality tools include;

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

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

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

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

7 Basic Quality Tools Explained with Templates

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

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

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

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

Real-world examples of usage

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

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

How to use a flowchart

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

Who can use it?

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

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

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

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

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

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

How to make a histogram

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

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

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

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

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

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

How to use the cause and effect diagram

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

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

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

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

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

How to make a scatter diagram

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

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

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

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

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

How to make a checksheet

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

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

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

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

Control Chart

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

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

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

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

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

How to create a control chart

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

Pareto Chart

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

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

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

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

How to create a Pareto chart

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

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

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

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

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FAQs about 7 Basic Quality Tools

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

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

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

What are the basic quality improvement steps?

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

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

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

Guide: PDCA Cycle

Author: Daniel Croft

What is the PDCA Cycle?

The PDCA cycle was originally developed by A. Shewhart who was a statistician at Bell Telephone Laboratories. Shewhart was known as a pioneer in the field of quality management and is also referred to as the father of statistical quality control. He developed the concept of the PDCA cycle in the 1920s as a model for continuous improvement, emphasizing the importance of using data to make informed decisions.

The Four stages of PDCA:

What types of projects can pdca be used for.

The PDCA cycle is quite versatile and can be applied in a range of projects, particularly those that involve:

The Components of PDCA and How to Apply it

Within this stage, you will generally do the following:

This phase is where you review the data collected during the trial and determine if the changes made led to an improvement.

Additional Useful Information on PDCA

Pdca and its variations, why variations matter.

Context-Specific : Different variations may be more suitable depending on the complexity and nature of the process you are aiming to improve.

Integration with Other Tools

A: PDCA stands for Plan-Do-Check-Act, which is a four-step iterative management method used for continuous improvement.

Daniel Croft

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

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PDCA (Plan-Do-Check-Act)

What is the PDCA (Plan-Do-Check-Act) Cycle

Plan-Do-Check-Act Cycle (PDCA) is a four-step, iterative by-design method used for control and continual improvement of processes and products. It is also known as the Plan-Do-Study-Act (PDSA) cycle, Deming cycle, Control Circle/Cycle or the Shewhart cycle.

PDCA is an evidence-based participatory approach to problem-solving and is found to be an effective tool for quality improvement.

Origin of PDCA

The beginnings of PDCA emerged from the principles of the ‘Scientific Method’, which originated with Galileo but has its roots in the teachings of Aristotle. It is a method for developing ideas based on observation, then testing them through experiments and finally refining, changing, or eliminating the ideas. [2]

Dr. Walter Shewhart first adapted the scientific method for industry and presented it as a linear flow of ‘specification’, ‘production’ and ‘inspection’. In 1939, he changed the linear sequence to a cycle to show how refinement and change lead to an iterative approach to product development.

The Shewhart cycle was further developed by W. Edwards Deming in what became known as the ‘Deming Wheel’.

In 1950, Deming presented his ideas to the Japanese Union of Scientists and Engineers (JUSE) which then was popularized as the Plan, Do, Check, Act cycle or PDCA. [2]

Why use PDCA

Organizations often plan and then intend to execute, but the reality is neither linear nor predictable for this approach to be effective in reaching the target conditions.

Regardless of how well a plan is made, they must navigate a zone of uncertainty commonly referred to as the “Grey Zone.” Unforeseen problems, abnormalities, false assumptions, and obstacles will appear along the path to any target.

A good analogy is a person climbing stairs in the dark with a flashlight. Because the target condition lies beyond the reach of the flashlight, the path to attaining it cannot be predicted with exactness. Thus, the person must find that path by experimenting.

This is the central approach of PDCA. To expect uncertainty and pay attention to adjust along the way based on learnings. PDCA provides a practical means of attaining a challenging target condition by formulating hypotheses and testing them with information obtained from direct observation.

The Plan-Do-Check-Act (PDCA) cycle

The procedure or steps of experimentation in the PDCA cycle are summarized as below:

The four stages of PDCA

PDCA’s four stages constitute a scientific process of acquiring knowledge and are explained in more detail as follows:

P is for Plan

In the Planning stage, problems are identified and analyzed according to the following order:

• Select and prioritize the problems to be analyzed
• Clearly define the problem and establish a precise problem statement
• Perform situation analysis (to be used as baseline data)
• Set a measurable goal
• Perform root cause analysis (identify potential causes of problems)
• Identify intervention(s) that will address the root causes of problems
• Select an intervention and develop an action plan

D is for Do

At this stage, the team implements an action plan developed in the previous stage to make the desired changes. This involves the following steps:

• Execute the action plan on a trial or pilot basis
• Practice the proposed method(s)
• Make the changes
• Don’t strive for perfection but look for what can be done in a practical way

C is for Check

At this stage , data is collected once again to measure if the actions taken have improved the situation. It involves the following steps:

• Check whether the standard is being followed
• Measure the indicator and compare it with the baseline. Record the results
• Check what is working and what is not
• Identify systematic changes
• Practice and improve the activities as per the defined method

A is for Act

In the Act phase, interventions that are found to be effective are standardized by developing Standard Operating Procedures (SOPs), which involve the following steps:

• Continue activities that went as planned and were found effective
• Review (why) activities that did not perform well and propose changes
• Adopt the intervention(s)/ solution(s) as standard (standardize)
• Plan ongoing monitoring of the intervention(s)/ solution(s)
• Continue to look for incremental improvements and refine intervention(s)/ solution(s)
• Look for the next improvement opportunity

At the end of the fourth stage, the PDCA cycle restarts with the aim to solve another problem (or further improve the same problem) to achieve a continuous and uninterrupted improvement.

Seven steps in the PDCA cycle

PDCA cycle consists of seven steps spread over four stages, as shown:

Step 1: Selection and problem prioritization

A problem is a brief description/statement of the weakness in the process or an issue to be solved. The tool most often used in this step is a Flowchart [6] . Alternatively, if a single problem is to be selected from a set of problems, a Selection Matrix [7] or a Fish Bone Diagram [8] may be used.

Selecting a problem is an iterative process where subsequent steps could lead to further refinement of the definition. A good problem should:

• Be customer‑focused.
• Complement the company’s and division’s goals.
• Address a weakness
• Be measurable
• Have a high probability of success within a reasonable time frame (3‑4 months)
• Be well-framed in one complete sentence
• Avoid the use of abstract words, acronyms, and location‑specific lingo
• Be action‑oriented
• Avoid the use of absolutes
• Address one of the 5 evils (defects, delays, mistakes, waste, accidents).
• Avoid stating the cause in the problem definition. (This is jumping to Step 3.)
• Avoid stating the solution in the problem definition. (This is jumping to Step 4.)

Problems can be prioritized based on:

• Their impact on the business
• Whether there are enough resources available to address them
• The ease of observing changes
• The extent to which team members have control

Step 2: Situation analysis

In this step, the focus is on gathering facts about the problem. The tool most often used at this point are Checksheets [9] and Pareto Charts [10] . Following are some of the key aspects of situation analysis:

• Before collecting data, all possible causes must be brainstormed.
• Ask 4W and 1H when collecting data: – Who is involved? – What problem/type of problem occurs? – When does it occur? – Which part of the process/type of product does it involve? – How much/many products/defects/etc. are involved?
• Limit data collection to what is needed. (Often, a sample will be sufficient.)
• Stratify (group) the data in many forms [11] .
• Zero down on a few probable causes using a Pareto chart.

Step 3: Root cause analysis

A root cause is the fundamental reason behind negative process outcomes. A fishbone diagram [8] is the primary tool for root cause analysis. The root cause must be controllable and is found using the following approach:

• Answer the question, “Why did this ‘problem’ occur?”
• Brainstorm around: – Contributing factors. – The root cause of the contributing factors.
• Follow a fact-based approach. Assuming to know the cause can be counterproductive.
• Interview people who know the process.
• Construct/refer to a Flowchart of the process.
• Construct a Cause/Effect Diagram.
• Recycle back to Step 2 if required.

Step 4: Identification of intervention

This step brings ideas together to address a problem’s root cause. It is important to be open to options and think creatively. Affected individuals must be involved, and preference must be given to improving existing processes before revamping them entirely. Experiments are run to test solutions.

The proposed intervention must:

• Prevent the reoccurrence of the root cause.
• Be practical to implement, efficient and affordable.
• Be free from conflict with other processes or activities.
• Address the 4W’s and 1H (discussed in Step-2).
• Have a timeline describing the implementation schedule.
• Have management support.
• Establish metrics that will confirm that the solution worked.

Step 5: Implementation of the intervention

Putting the implementation plan into action involves carrying out the ordered steps outlined below, implementing the change itself, and collecting the information that will indicate success.

• Review the objectives of the solution(s).
• Develop an action plan.
• Share the action plan with section staff.
• Identify the potential resistance.
• Determine the prerequisite(s) of the implementation.
• Develop a step-by-step guide to implement the action plan (Usually, the time for implementation is about 2 to 3 months, while the total time for one PDCA cycle is about 6 months).
• Assign responsibility for each activity.
• Determine what information is needed to monitor progress (using a checklist).

Teams must establish checkpoints periodically to verify if the implementation is going as planned and update everyone involved on the progress.

Step 6: Checking the effectiveness of implementation

Using tracking indicators, effectiveness can be checked through the following steps:

• Review data collection methods in Step 2
• Collect data using the same methodology
• Compare frequency before and after PDCA and calculate incremental reduction/ increase rate
• Make a Run Chart to observe the trend over time [12]
• Check achievement against the target set earlier in the aim statement.

The situation before and after PDCA can also be portrayed using a graph as shown below:

A Run Chart can be used to observe improvements over time. For example, the run chart (below) shows a decreasing trend in the number of patients who did not follow prescribed medication. This indicates the PDCA measures adopted by the hospital to address the issue have shown improvements over time.

Step 7: Standardization of effective interventions

At this stage, the activities found to be effective in reducing or eliminating the problems are standardized using the following steps:

• List effective interventions identified in the previous step.
• Develop documentation (SOPs) to adopt successful intervention(s).
• Develop a checklist to assess the progress of implementing standardized activities.
• Share the plan and checklist with all concerned.

Standardization brings several benefits such as:

• Reduces variability.
• Ease in training new staff.
• Reduced chance of strain and injuries (ensures safety for internal/ external clients).
• Ease of following well-established practices reduces task time.
• Increases staff confidence & motivation.

Discipline is the key to successful standardization of an effective intervention.

PDCA at Toyota

No organization has ever come close to matching Toyota’s stellar performance in automobile manufacturing. It has cultivated a culture of excellence, efficiency, and customer satisfaction like no other.

PDCA at Toyota uses “Rapid Cycles,” where individual PDCA cycles are turned as quickly as possible, sometimes even taking only minutes each. The idea is to not wait for a perfect solution but to take the step at the earliest with available resources so that teams can spot the next challenge.

Toyota believes that a provisional step “now” is preferable to a perfect step “later”, and invests in prototypes and experiments up front, which may seem like an extra expense but has proven to reduce cost in the long run.

Toyota uses single-factor experiments, that is, to address one problem at a time and only change one thing at a time in a process. This helps see cause and effect and better understand the process.

Toyota’s success is not due to sudden innovation or having air-tight plans but the ability to execute more effectively in the face of unforeseeable obstacles and difficulties. They spot problems at the process level much earlier when the problems are still small and address them quickly while uncovering information along the way.

Example of PDCA (the Toyota way)

Consider the process of getting up and going to work with a target condition of being in the car and ready to drive 60 minutes after waking up.

Here is one possible PDCA cycle for the process:

Assume that with the above PDCA plan, a person sits in the car to find that the morning routine took 64 minutes, or four minutes over the target condition.

What has he learned about the process from this experiment?

As depicted in the figure above, not much! The total time taken was over 60 minutes (too long), but it cannot be said where in the morning routine the problem lies. Also, it is too late to make an adjustment that would still achieve the target condition.

There are two things wrong with this PDCA experiment:

• The “check” comes too late to learn anything useful or to adjust on the way.
• The target condition specifies only an outcome. (it is not actually a target condition at all.)

Many seemingly large and sudden changes develop slowly. The problem is that organizations either fail to notice the little shifts taking place along the way or they do not take them seriously.

No problem is too small for a response. To be consciously adaptive, an organization must recognize abnormalities and changes as they arise and are still small and easy to grasp.

To be able to experiment in shorter cycles, a more detailed target condition is necessary. Such a target condition must generally include the following information:

• The steps of the process, their sequence, and their times
• Process characteristics
• Process metrics
• Outcome metrics

While a longer overall PDCA cycle must check the outcome, many short PDCA cycles must check process metrics along the way. Every step on the “staircase toward a target condition” is a PDCA cycle. Each step is a hypothesis, where what is learned from testing that hypothesis may influence the next step.

Accordingly, a modified and more effective experiment for the process of getting up and going to work, beginning with a better target condition, will look as follows:

As seen from the figure, the step “Make breakfast” has taken four minutes longer than the planned time. From this, it is not only known where the problem is, but an adjustment can also be made to the remaining steps to still achieve the 60-minute outcome.

Questions critical to PDCA

PDCA phase of the improvement, after a target condition has been established, needs to answer the following five questions that are built on one another.

The sequence of these five questions acts as a device to give a routine and a mental pattern for approaching any process or situation. These questions distill part of the improvement down to a point where it becomes accessible and usable by anyone.

1. “The plan-do-check-act procedure”. Whale Design, https://www.shutterstock.com/image-vector/plandocheckact-procedure-deming-cycle-fourstep-model-2169522173 Accessed 22 Jul 2023

2. “Shewhart cycle”. Praxis Framework, https://www.praxisframework.org/en/library/shewhart-cycle Accessed 19 Jul 2023

3. “Walter A Shewhart”. Wikipedia, https://en.wikipedia.org/wiki/Walter_A._Shewhart Accessed 19 Jul 2023

4. “W. Edwards Deming Photo Gallery”. The Deming Institute, https://deming.org/w-edwards-deming-photo-gallery/ Accessed 19 Jul 2023

5. “Toyota Kata: Managing People for Improvement, Adaptiveness and Superior Results”. Mike Rother, https://www.amazon.com/Toyota-Kata-Managing-Improvement-Adaptiveness-ebook/dp/B002NPC0Q2https://www.amazon.com/Toyota-Kata-Managing-Improvement-Adaptiveness-ebook/dp/B002NPC0Q2 Accessed 19 Jul 2023

6. “WHAT IS A FLOWCHART?”. American Society for Quality, https://asq.org/quality-resources/flowchart Accessed 20 Jul 2023

7. “WHAT IS A DECISION MATRIX?”. American Society for Quality, https://asq.org/quality-resources/decision-matrix Accessed 20 Jul 2023

8. “FISHBONE DIAGRAM”. American Society for Quality, https://asq.org/quality-resources/fishbone Accessed 20 Jul 2023

9. “CHECK SHEET”. American Society for Quality, https://asq.org/quality-resources/check-sheet Accessed 20 Sep 2023

10. “WHAT IS A PARETO CHART?”. American Society for Quality, https://asq.org/quality-resources/pareto Accessed 20 Sep 2023

11. “WHAT IS STRATIFICATION?”. American Society for Quality, https://asq.org/quality-resources/stratification Accessed 20 Jul 2023

12. “Run Chart: Creation, Analysis, & Rules”. Six Sigma Study Guide, https://sixsigmastudyguide.com/run-chart/ Accessed 21 Jul 2023

13. “PDCA Manual for Quality Improvement”. Quality Improvement Secretariat (QIS), Health Economics Unit, Health Services Division, Ministry of Health and Family Welfare, http://qis.gov.bd/wp-content/uploads/2019/04/2019_02_07_1549518374_241pdca.pdf Accessed 21 Jul 2023

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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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Applying the PDCA Cycle: A Blueprint for Continuous Improvement

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Also known as Shewhart Cycle and Deming Wheel.

Variants include PDSA Cycle and OPDCA.

The Plan-Do-Check-Act Cycle (PDCA Cycle) is a four-step model for systematic problem solving and continuous improvement. It offers a simple and structured way for resolving business-related issues and creating positive change . This framework is widely recognized as the basis for enhancing the quality of processes, products, and services by following a logical sequence of four steps: Plan, Do, Check, and Act.

The PDCA cycle model can be applied in most kinds of projects and improvement activities, whether they are breakthrough changes or smaller incremental enhancements. For example, it can be effectively utilized when aiming to enhance employee skill levels within an organization, change the supplier of a product or service, or increase the quality of care and patient engagement within a hospital.

A common practical example of the PDCA cycle can be illustrated when dealing with customer complaints. This scenario involves steps like reviewing, categorizing, and prioritizing the existing complaints, generating potential solutions for addressing the most frequent complaints, conducting pilot surveys with sample customers to test new options, collecting and analyzing customer data and feedback, and ultimately implementing lessons learned on a larger scale. The above steps represent the PDCA cycle in action.

The Four Phases of the PDCA Cycle

The PDCA cycle begins with the Planning phase which involves the identification of the problem and objectives. During this phase, a collaborative effort is made to agrees on the problem to be solved or the process to be improved. Subsequently, an in-depth analysis of the existing as-is situation is conducted, alternative solutions are identified, and the most promising solution is selected and scheduled for implementation.

In the Do phase, the selected solution is put into action on a limited scale. This phase also involves ongoing progress measurement, data collection, and feedback gathering to facilitate subsequent analyses.

The Check phase involves analyzing the collected data and feedback and comparing the outcome against pre-established objectives. This phase allows to evaluate how well the solution has worked and where further enhancement may be needed. Additionally, it involves the identification of unexpected issues and the gathering of key learnings. It is important to note that the Do and Check phases may need to be repeated until the desired results are achieved.

The Act phase is the point at which the chosen solution is fully integrated. This phase requires taking actions based on the insights acquired from the Check phase. A plan for full-scale implementation is carried out, taking into account the associated costs and benefits. The Act phase also concerned with standardizing , documenting, sustaining the improved process, as well as integrating it into the organization’s system.

The utilization of the PDCA cycle doesn’t necessarily stop once the Act phase is completed. The improved process often becomes the new baseline, which may prompt a return to the Plan phase. Multiple iterations of the PDCA cycle may be essential for a permanent resolution of the problem and the attainment of the desired future state. Each cycle brings one closer to their goals and extends their knowledge further.

A common example often used to illustrate the PDCA cycle is when a team is initiating a new product development.

Another example is when a lab team is planning to solve a customer complaint about the delayed test results at a laboratory.

In the 1990s, a modified version of the PDCA cycle was introduced. It was called PDSA cycle where ‘S’ stands for Study. It is believed that data analysis is important for any improvement effort, and “Checking” does not really imply studying and analyzing the data.

OPDCA is another version of PDCA where ‘O’ stands for Observe . The Observe is added at the front of the cycle to emphasize the need to observe before creating any plan. The goal of observation is to find out what is really happening and what can be improved.

You may find it useful to use the following tools in each phase of the PDCA/PDSA cycle:

• Plan – process mapping , brainstorming, waste analysis , prioritization matrix , improvement roadmap , gap analysis , and force field analysis .
• Do – Gantt chart , dashboard, data collection methods , sampling, observation , check sheet , and control chart.
• Check/Study – graphical analysis , statistical analysis, 5 whys , fishbone diagram , Pareto analysis , root cause analysis, and decision-making techniques .
• Act – process mapping , Gantt chart , dashboard, control chart, control plan, visual management , and standard work .

Several tools are available to aid in planning and monitoring project activities using the PDCA model. One of the most straightforward methods is to use this  PDCA template .

Wrapping Up

PDCA represents the logical way of thinking we tend to follow when resolving problems and implementing continuous improvement. The objective is to make significant progress towards achieving the intended goal. Furthermore, it is important to note that the PDCA model stands at the core of almost all quality management systems. TQM, ISO standards and the A3 thinking process are all based around the PDCA philosophy.

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7 Powerful Problem-Solving Root Cause Analysis Tools

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

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

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

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

1. The Ishikawa Fishbone Diagram IFD

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

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

Related Training: Fishbone Diagramming

2. Pareto Chart

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

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

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

Related training: Accident/Incident Investigation and Root Cause Analysis

4. Failure Mode and Effects Analysis (FMEA)

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

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

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

Related Training: Failure Mode Effects Analysis

5. Scatter Diagram

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

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

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

6. Affinity Diagram

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

7. Fault Tree Analysis (FTA)

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

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

ComplianceOnline Trainings on Root Cause Analysis

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

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

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

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

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

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

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

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

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

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

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

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

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

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The PDCA Cycle: A Practical Approach to Problem-Solving

PDCA (Plan-Do-Check-Act) is a problem-solving iterative method for improving processes and products continuously. Let’s discover each stage of the PDCA cycle and the benefits it will bring to your processes.

• What Is Lean Management?
• The 5 Principles of Lean
• What Is Shared Leadership?
• What Is Lean Manufacturing?
• What Is Value in Lean?
• 7 Wastes of Lean
• What Is Mura?
• What Is Muri?
• What Is 5S?
• What Is the Cost of Delay?
• What Is Value Stream Mapping?
• What Is a Pull System?
• What Is a Bottleneck?
• Just-in-Time Manufacturing
• Implementing a Kanban Pull System
• Pull System on the Portfolio Level
• What Is Kaizen?
• What Is Continuous Improvement?
• Built-In Quality Management
• What Is the Poka-Yoke Technique?
• What Is the PDCA (Plan Do Check Act) Cycle?

5 Whys: The Ultimate Root Cause Analysis Tool

Gemba Walk: Where the Real Work Happens

• A3 Problem-Solving: Fight the Root Cause
• How To Perform Root Cause Analysis?
• Root Cause Analysis Tools
• What Is a Pareto Chart?
• What Is a Scatter Diagram?
• What Is a Fishbone Diagram?
• What Is Hoshin Kanri?
• What Is Hoshin Kanri Catchball?
• Demystifying the Hoshin Kanri X Matrix
• The Lean Transformation Model Explained
• Lean Transformation Roadmap - 8 Comprehensive Steps
• What Is Cycle Time?
• What Is Little's Law?
• What Is Takt Time?
• What Is Heijunka?
• What Is Jidoka?
• What Is Andon?
• Lean Six Sigma Principles
• Lean Six Sigma Tools
• Lean Six Sigma Implementation
• What Is Six Sigma?
• What Is DMADV?
• What Is DMAIC?
• Lean Project Management

What Is the PDCA (Plan-Do-Check-Act) Cycle?

Explained briefly, the Plan-Do-Check-Act cycle is a model for carrying out change. It is a simple four-stage method that enables teams to avoid recurring mistakes and improve processes. It is an essential part of the Lean manufacturing philosophy and a key prerequisite for continuous improvement of people and processes.

First proposed by Walter Shewhart and later developed by William Deming, the PDCA cycle became a widespread framework for constant improvements in manufacturing, management, and other areas.

Now that we've explained the PDCA's meaning let’s explore the topic further and learn more about this problem-solving model.

Brief History of PDCA 

The American statistician and physicist Walter Shewhart is considered the father of PDCA. He was passionate about statistical analysis and quality improvement, and he built the foundation of PDCA recorded in numerous publications.

At first, he developed a 3-step repeating cycle for process improvement also known as "the Shewhart cycle". The three phases of this cycle were: 

Years later, inspired by Shewhart’s ideas, William Deming expanded the model into a learning and improvement cycle consisting of the following steps: 

This model was redesigned by the Japanese Union of Scientists and Engineers (JUSE) in 1951 and became what we know today as a PDCA cycle.   

What Are the 4 Steps of the PDCA Cycle? 

PDCA cycle is an iterative process for continually improving products, people, and services. It became an integral part of what is known today as Lean management . The Plan-Do-Check-Act model includes solutions testing, analyzing results, and improving the process.

For example, imagine that you have plenty of customer complaints about the slow response rate of your support team. Then you will probably need to improve the way your team works to keep customers satisfied. That is the point where PDCA comes into play.

Let’s take a closer look at the four stages of the PDCA process.

Step 1. PLAN

At this stage, you will literally plan what needs to be done. Depending on the project's size, planning can take a major part of your team’s efforts. It will usually consist of smaller steps so that you can build a proper plan with fewer possibilities of failure.

Before you move to the next stage, you need to be sure that you answered some basic concerns:

• What is the core problem we need to solve?
• What resources do we need?
• What resources do we have?
• What is the best solution for fixing the problem with the available resources?
• In what conditions will the plan be considered successful? What are the goals?

Keep in mind you and your team may need to go through the plan a couple of times before being able to proceed. In this case, it is appropriate to use a technique for creating and maintaining open feedback loops, such as Hoshin Kanri Catchball . It will allow you to collect enough information before you decide to proceed.

After you have agreed on the plan, it is time to take action. At this stage, you will apply everything that has been considered during the previous stage.

Be aware that unpredicted problems may occur at this phase. This is why, in a perfect situation, you may first try to incorporate your plan on a small scale and in a controlled environment.

Standardization is something that will definitely help your team apply the plan smoothly. Make sure that everybody knows their roles and responsibilities.

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Step 3. CHECK

This is probably the most important stage of the PDCA cycle. If you want to clarify your plan, avoid recurring mistakes, and apply continuous improvement successfully, you need to pay enough attention to the CHECK phase.

This is the time to audit your plan’s execution and see if your initial plan actually worked. Moreover, your team will be able to identify problematic parts of the current process and eliminate them in the future. If something goes wrong during the process, you need to analyze it and find the root cause of the problems.

Step 4. ACT

Finally, you arrive at the last stage of the Plan-Do-Check-Act cycle. Previously, you developed, applied, and checked your plan. Now, you need to act.

If everything seems perfect and your team managed to achieve the original goals, then you can proceed and apply your initial plan.

It can be appropriate to adopt the whole plan if objectives are met. Respectively, your PDCA model will become the new standard baseline. However, every time you repeat a standardized plan, remind your team to go through all steps again and try to improve carefully.

Implementing the PDCA Cycle: Best Practices to Consider

Implementing the PDCA (Plan-Do-Check-Act) cycle effectively requires attention to detail and a structured approach. To get the most out of it, there are a few good practices to follow for each stage and overall. Let’s briefly review them.    Strong Planning Foundation    Identify the process you want to improve and outline the problems that need to be solved. Once defined, set clear SMART goals to guide your team and ensure focus and consistency. Gather data to support the planning process, ensuring decisions are based on evidence rather than assumptions. You can use tools like root cause analysis, fishbone diagrams, and SWOT analysis to understand the problem and its context.     Lastly, involve all key stakeholders in the planning process to gather diverse viewpoints and ensure buy-in.    Effective Do Stage    To minimize risks, test the proposed changes on a small scale before rolling them out company-wide. Ensure that you have all necessary resources, including time, budget, and, most importantly, people, to effectively implement the planned changes and achieve desired results.    Consistent Check Phase    Don’t just collect data; analyze it. Define critical for your process metrics to measure the impact of the implemented changes and whether they are delivering the expected results.     Actionable Act Stage     If the changes are successful, document and integrate the new standard operating procedures into regular workflows. If the changes did not meet expectations, analyze why they failed and what can be improved.      Either way, as the PDCA cycle is an iterative method, don’t solely rely on the learnings from this one-time round. Apply the most critical outcomes in the next session to enhance operational performance and refine the approach each time.    Bonus Tips: 

• Ensure top-level management support.  
• Share lessons learned with all employees. 
• Don’t stop after the first run of the cycle. Instead, install it as a recurring task in your team and organization’s operations for continuous improvement of your processes. 
• Leverage digital tools and software to facilitate data collection, analysis, and tracking of PDCA cycles.  

Why Is PDCA Important for Your Business?  

The PDCA methodology is widely used for problem-solving and to create quality process improvements. By deploying this model, organizations aim to enhance their internal and external processes by eliminating any issues along the way of the work process. 

The cyclical nature of this model allows teams to identify and remove defects early in the process and restart the cycle until the desired outcome is reached. This increases efficiency and eliminates ineffective elements until the optimal solution can be identified. 

Because of the continuous approach of PDCA, organizations can use this model to gather relevant information before considering whether to progress with a plan or make improvements. This data-driven approach provides a ground basis for organizations’ continuous improvement of processes, products, services, and people. 

When to Use the PDCA Cycle? 

A specific characteristic of PDCA is that it is relatively versatile. This trait of the cycle allows it to be used across various businesses, organizations, departments, and even individual teams. There is no limitation in terms of its implementation, and it could be applied in the following scenarios: 

• Developing a new product or service  
• Optimizing current processes or products 
• Kicking off a new process improvement project 
• Exploring new opportunities for continuous improvement 
• Implementing change  
• Detecting process issues and working toward removing them 

Real-Life Examples of Companies Using PDCA

Example #1: nestlé .

Reducing waste in all aspects of work is an all-time mission for Nestlé. To respond to this message, the company successfully rolled out the concept of Lean management. Furthermore, they introduced the Kaizen method to make sure that everyone in the company meets the idea of continuous improvement. Following the principle of Kaizen that every slight improvement should be made to increase efficiency and reduce costs, the company implemented the PDCA cycle to provide guidelines. (Source: reverscore.com )

In addition, Nestlé Waters is an example of how techniques such as Value Stream Mapping (VSM) can help illustrate the flow of materials and information from raw material to the final product. As a result of implementing this process, the bottling plant has experienced a significant increase in its process efficiency. 

Example #2: Lockheed Martin

Lockheed Martin operates in the aerospace industry and is a bright example of how the Kaizen methodology brings results to a company's operations. Implementing the PDCA cycle has standardized the projects and increased the quality of the products and services by targeting a problem and solving it through multiple iterations. Improvements were noticed in the period 1992-1997 when the company made 38% reduction in manufacturing costs, 50% reduction in inventory, and a reduction in delivery time from 42 to 21.5 months. (Source: 6Sigma.com )

Example #3: Nike

Nike embraced Lean manufacturing with the belief that this continuous improvement philosophy is the foundation of their advanced sustainable manufacturing and empowering their workforce. To improve the quality of work conditions and deliver the highest-quality product while eliminating non-value-added activities, Nike implemented the PDCA cycle as part of their process improvement training. (Source: OpEx Learning )

Continuously Improving through PDCA

The PDCA cycle is a simple but powerful framework for fixing issues on any level of your organization. It can be part of a bigger planning process, such as Hoshin Kanri .

The repetitive approach helps your team find and test solutions and improve them through a waste-reducing cycle.

The PDCA process includes a mandatory commitment to continuous improvement, and it can have a positive impact on productivity and efficiency.

Finally, keep in mind that the PDCA model requires a certain amount of time, and it may not be appropriate for solving urgent issues.

What Makes the PDCA Cycle Different from Other Change Management Methods?

What is the difference between pdca and six sigma .

Six Sigma is a quality and process improvement approach that provides organizations with a set of tools and techniques to improve work performance and increase the quality of products and services. One of the tools included in that toolset is the PDCA cycle.  While Six Sigma provides the framework for determining what is slowing the process, methods like PDCA explain the steps to identify and eliminate issues.  

What Is the Difference between PDCA and PDSA? 

PDCA stands for "Plan-Do-Check-Act", whereas PDSA is for "Plan-Do-Study-Act". Even though these two 4-step models are designed to bring improvements into processes, the difference between them is one stage in each cycle.  

At the "Check" stage in PDCA, the team needs to audit its plan’s execution and see if its initial plan worked. In contrast, the "Study" stage in PDSA aims to analyze in depth the results of any change applied at each step, ensuring long-term process improvements. Either way, you can use both models by studying and checking the results obtained from tests. 

What Is the Difference between PDCA and Kaizen? 

Both PDCA and Kaizen strive for continuous improvement through small, incremental changes and creating an organizational culture of Lean thinkers and problem-solvers. The developed Kaizen methodology includes doing small experiments and monitoring results, then adjusting when new improvements are suggested. To apply this concept in practice, the PDCA cycle provides a framework to promote improvements continuously.   

What Is the Difference between PDCA and Total Quality Management (TQM)? 

TQM is a broader management approach focused on long-term success through customer satisfaction and employee engagement. It is applied organization-wide and requires a cultural shift, where quality becomes a core value. TQM incorporates various tools and methods, including the PDCA's philosophy. 

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Guide to Problem-Solving Methodologies: 8D, PDCA, DMAIC, and Kaizen

Welcome 2024! Embracing and mastering problem-solving methodologies is essential for organizations on their continuous improvement journey throughout the year. By learning these techniques, teams can streamline and enhance their problem-solving processes, fostering a culture of innovation and resilience in the face of challenges.

This proactive approach will empower organizations to navigate uncertainties, drive efficiency, and achieve sustainable growth in the dynamic landscape of 2024 and beyond.

This article explores four widely adopted methodologies: 8D (Eight Disciplines), PDCA (Plan-Do-Check-Act), DMAIC (Define-Measure-Analyze-Improve-Control) , and Kaizen .

Each methodology brings a unique approach to problem-solving, tailored to different contexts and challenges.

Problem-Solving Methodologies

1. 8d (eight disciplines).

The 8D problem-solving methodology is structured into eight steps, providing a systematic approach to identifying, solving, and preventing problems.

The steps include:

• D1: Form a Team
• D2: Define the Problem
• D3: Develop Interim Containment Actions
• D4: Identify the Root Cause
• D5: Choose Permanent Corrective Actions
• D6: Implement Corrective Actions
• D7: Prevent Recurrence
• D8: Congratulate the Team

8D emphasizes teamwork, data-driven analysis, and a focus on both short-term containment and long-term solutions. It encourages a thorough investigation into the root cause to prevent recurrence.

2. PDCA (Plan-Do-Check-Act)

PDCA, also known as the Deming Cycle, is a continuous improvement method popularized by W. Edwards Deming.

The PDCA cycle comprises four stages:

• Plan : Identify the problem and plan for change
• Do : Execute the plan on a small scale
• Check : Analyze the results and compare against the expected outcomes
• Act : Implement necessary changes on a larger scale and standardize improvements

PDCA is iterative, promoting a constant feedback loop for ongoing improvement. It is versatile and applicable across various industries and processes.

3. DMAIC (Define-Measure-Analyze-Improve-Control)

DMAIC is a core component of the Six Sigma methodology, designed to improve processes by eliminating defects. The five stages of DMAIC are:

• Define : Clearly articulate the problem, project goals, and customer requirements
• Measure : Collect relevant data to understand the current state of the process
• Analyze : Identify root causes of problems through data analysis
• Improve : Develop and implement solutions to address the root causes
• Control : Sustain the improvements and monitor the process to prevent regression

DMAIC emphasizes data-driven decision-making and statistical analysis to achieve measurable and sustainable improvements.

Kaizen , a Japanese term meaning “continuous improvement,” is a philosophy that promotes incremental, continuous changes.

Key principles of Kaizen include:

• Standardize processes
• Practice 5S (Sort, Set in order, Shine, Standardize, Sustain)
• Empower employees to suggest and implement improvements
• Focus on small, manageable changes

Kaizen fosters a culture of continuous improvement at all organizational levels, encouraging employees to contribute to the evolution of processes and systems.

Related Article: Understanding the 5S Methodology: Streamlining Success in Workspaces

Choosing the Right Tool or the Right Problem-Solving Methodologies

While each methodology offers a unique approach, the most effective one depends on the specific context:

• 8D:  Ideal for complex problems, customer complaints, and team-based problem-solving.
• PDCA:  Suitable for quick improvements, testing new ideas, and cyclical progress.
• DMAIC:  Effective for data-driven, statistically controlled process optimization and defect reduction.
• Kaizen:  Perfect for fostering a culture of continuous improvement, small incremental changes, and employee engagement.

Final Thoughts

Effective problem-solving is essential for organizational success and continuous improvement. The 8D , PDCA, DMAIC , and Kaizen methodologies offer distinct approaches, allowing organizations to choose the one that aligns best with their goals and context.

By incorporating these methodologies, businesses can enhance their problem-solving capabilities, driving efficiency, quality, and overall success.

As the New Year begins, I wish you all lots of happiness and good luck in your projects!

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Integral tool in Total Quality Management (TQM)

The QC Story is an integral tool in Total Quality Management (TQM) aimed at addressing problems in a structured manner. It is based on the PDCA (Plan-Do-Check-Act) principle and involves presenting a problem-solving story in nine steps, from case selection to achieving a thorough solution. While not as widely recognized as other methodologies, the content and purpose of QC Story are equivalent or identical to the well-known A3 analysis or 8D report.

Traditionally, QC Story is formalized on paper, boards, or posters. Larger formats, such as 2×2 meters, are particularly popular in companies with well-developed visual management systems. By visually depicting the case as a story, it facilitates a better breakdown of the problem, its resolution, and, most importantly, comprehension. However, managing information and the database can be relatively challenging with such displays.

To address this, our company has developed a web application called APS (Advanced Problem Solving), which enhances information management. APS is a versatile tool that not only complements QC Story but also replaces other conventional methods like A3 and 8D reports. Moreover, APS enables even more structured and efficient implementation of projects focused on eliminating losses within PDCA, DMAIC, or 6Sigma frameworks. An additional advantage is the ability to use APS across various devices, including computers, tablets, and smartphones.

Key Objectives of QC Story:

Problem Resolution: Resolving problems is vital for any competitive company today. Instead of merely applying corrective or firefighting actions, QC Story aims to identify the root causes of issues and find solutions. This approach fosters continuous improvement in all areas, such as quality, workplace safety, reliability, and cost reduction.

Communication Tool: QC Story serves as a powerful communication tool. By presenting problems in a clear and understandable manner, it engages a wider circle of employees. As a result, an increasing number of employees gain a better understanding of work processes and the underlying causes of issues. Gradually, everyone, including operators, becomes involved in problem-solving, leading to new challenges and the creation of higher added value in their roles.

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What is 8D ? 8D CAPA Report | Eight Disciplines of “Problem Solving”

“ 8D ” Methodology basically uses eight disciplines or principles of “ Problem Solving “. This Problem Solving Technique is widely used by quality engineers and managers of automotive industries. 

This approach is also commonly used by other professionals working in Manufacturing, Government, Construction, Healthcare, IT/BPO, and other service sectors.

The objective/purpose of the 8D Methodology is to identify and define the problem statement effectively for necessary Corrective and Preventive actions – CAPA to stop/prevent the recurrence and occurrence of the problem.

The corrective actions are basically taken on the identified root cause to prevent the recurrence of the problem whereas preventive actions are taken in advance on potential causes of failure to prevent the occurrence of the problem.

The horizontal deployment of corrective action i.e. corrective actions implementations in other products, machines, or services sometimes referred to as preventive actions also.

The basic 7 QC Tools are commonly used in 8D Report generation and problem-solving methodology/approach/steps.

And apart from 8D , there are various Problem-Solving techniques or methodologies like PDCA Deming Cycle, Quality Circle , and Six Sigma – DMAIC , etc. that are commonly applied in a variety of organizations to identify and solve work-related quality problems.

8D CAPA Report is mainly demanded by all OEMs and IATF 16949 certified companies from their suppliers ( at least ISO 9001 certified) to solve customer complaints or quality-related issues.

Table of Contents

8D Approach | 8D Problem-Solving Steps

The eight disciplines for process improvement or problem-solving are as follows:

8D Step – D1: Establish the Team

• Identify team leader and team members.
• Establish a team of competent people with product/process knowledge.
• Cross-functional team-CFT members must be related to the concerned problem.
• Identify the team’s goals and objectives.

D2: Defining the problem

• Define the problem clearly using the 5W2H approach and Process flow diagram-PFD.
• Problem definition shall be based on facts, not opinions.

D3: Containment or Interim Actions

• Containment action is also known as Interim action or Short term action.
• Interim actions are immediate actions/first aid taken against the problem to stop defects/suspected material outflow at the customer end.
• Interim actions protect the customer’s production line from the arisen quality problem until we define the root cause and implement necessary countermeasures.
• Examples of containment actions are: Displaying of QAN-Quality Alert Note, customer complaint awareness training to all concerned, defective or suspected material/parts segregation at the WIP stage, store location, ready for the dispatch-RFD stage, supplier end, transit, and customer end.

D4: Identifying & Verifying Root Cause

Root Cause Analysis-RCA is a systematic approach to determining and identifying the Root Cause of the problem. We can use 7 QC tools,5 Whys, 4M or 6M factors, and a Fishbone diagram for RCA.

Steps for Root Cause Identification:

• Use the Brainstorm technique and Fishbone diagram to identify all possible potential causes related to your problem. Consider all 4M or 6M factors in potential cause identification.
• Verify/Validate the identified potential causes.
• Now, Select the best potential cause that contributes to the problem/effect.
• Drill down the selected potential cause using the 5-Why approach to arrive at the root cause of the problem.
• Identify the root cause on both the Occurrence and Detection or Inspection side.
• Verify the root cause for necessary measures.

Note: Don’t end the root cause with the operator’s negligence, lack of training, etc. while identifying the root cause using the 5Why tool. The problem always occurred when there is a gap in the system/procedure/standards.

D5: Identify Permanent Corrective Actions-PCA

• Identify and Select the permanent corrective actions that address and correct the root cause. In other words, the selected PCA will resolve the problem of the customer.
• Solutions/PCA determined to be the best of all the alternatives.
• Document and verify the Permanent Corrective Action (PCA).

D6: Implementing the Permanent Corrective Action

• Implement the best permanent corrective actions (PCA) and ensure effective monitoring of implemented actions.
• Detect any undesirable side effects of implemented corrective actions.
• Return to root cause analysis, if necessary. In other words, if a still problem exists, you may need to fine-tune your actions or re-analyze the problem to identify a new root cause.

D7: Preventive Actions

• Ensure horizontal deployment of corrective actions, i.e. Ensure similar types of problems will not occur in other machines, products, and services.
• Update the Systems, Processes, Procedures, and Documents like PFC , control and FMEA to prevent a recurrence.
• Implement Poka-Yoke (mistake-proofing or error-proofing) to make the system or processes safer and more reliable.
• Ensure effectiveness/sustenance monitoring of permanent corrective actions.

8D Step – D8: Team Recognition

• Congratulations to your team.
• Celebrate the successful conclusion of the problem-solving effort.
• Organization to express thanks to the team.
• Document lesson learned card-LLC and display at all respective areas.

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