Quality assurance (QA) is a vital process for any project that aims to deliver high-quality products or services that meet the expectations and needs of customers and stakeholders. QA involves planning, implementing, and monitoring quality standards, guidelines, and procedures throughout the project lifecycle to prevent defects, errors, and failures. QA also strives for continuous improvement and customer satisfaction.

But how can you ensure that your QA process is effective and efficient? One way is to use quality assurance tools that can help you measure, analyze, and improve the quality of your project outputs. Quality assurance tools are methods and techniques that can help you identify the root causes of quality problems, prioritize the most critical issues, and implement corrective actions.

Many quality assurance tools are available, but some of the most widely used and recognized ones are the seven essential quality tools. These simple yet powerful tools can help you solve most of the standard quality issues in your projects. 

This blog post will review the seven essential quality tools and compare their advantages and disadvantages. We will also show you how to use them in your projects with some examples and tips.

What Are the Seven Basic Quality Tools?

The seven basic quality tools are:

• Stratification
• Histogram
• Check sheet
• Cause and effect diagram
• Pareto chart
• Scatter diagram
• Control chart

These tools were first introduced by Kaoru Ishikawa, a Japanese quality expert and the father of quality circles. He believed these tools could be used by anyone in the organization, not just quality specialists, to improve quality and productivity. 

He also emphasized the importance of involving all the stakeholders in the quality improvement process, from top management to frontline workers.

Let’s take a closer look at each of the seven essential quality tools and see how they can help you with your QA process.

Stratification

Stratification is a technique that involves dividing a set of data into smaller groups or categories based on some common characteristics or attributes. 

This can help you reveal patterns, trends, or relationships that might be hidden or obscured in the whole data set. Stratification can also help you identify the sources of variation or the factors that influence the quality of your project outputs.

For example, you want to analyze the customer satisfaction ratings of your project deliverables. You can stratify the data by different criteria, such as product type, customer segment, delivery date, or feedback channel. This can help you see which products, customers, or delivery methods have the highest or lowest satisfaction ratings and why.

To use stratification, you need to:

• Collect data on the quality characteristic or parameter that you want to analyze.
• Identify the criteria or factors you want to use to stratify the data.
• Sort the data into subgroups or categories based on the criteria or factors.
• Compare and analyze the subgroups or categories to find patterns, trends, or relationships.

You can use a spreadsheet or a table to record and display the stratified data. You can also use graphs or charts, such as pie charts, bar charts, or line charts, to visualize the data and make it easier to understand.

Histogram

A histogram is a visual representation illustrating the frequency distribution of a dataset. It takes the form of a bar chart, presenting the number or percentage of observations within distinct intervals or bins. This graphical tool aids in discerning the data's shape, spread, and central tendency, while also facilitating the identification of outliers, gaps, or clusters within the dataset.

For example, you want to analyze the defect rates of your project deliverables. You can use a histogram to show how many deliverables have zero defects, one defect, two defects, and so on. This can help you see the distribution of faults and the variation in quality.

To use a histogram, you need to:

• Collect data on the quality characteristic or parameter that you want to analyze.
• Determine the number and size of the intervals or bins you want to group the data. You can use a formula, such as the square root of the number of observations, or a rule of thumb, such as the 2 to the k rule, to decide the number of bins. You can also use a software tool like Excel to create the containers automatically.
• Count the number or percentage of observations that fall within each bin.
• Create a bar chart with bins represented on the horizontal axis and frequency or percentage on the vertical axis. Ensure that the bars are adjacent to each other and maintain equal width.

You can also add a line or a curve, such as a normal distribution curve, to the histogram to compare the actual data with a theoretical or expected distribution.

Cause and Effect Diagram

A cause and effect diagram, alternatively referred to as a fishbone diagram or Ishikawa diagram, serves as a visual instrument aiding in identifying and analyzing potential causes behind a quality problem or effect. 

Functioning as a brainstorming tool, it organizes ideas into categories and subcategories. This diagram proves valuable in pinpointing the root causes of a quality issue, contributing to effective preventive measures.

For example, you want to analyze why your project deliverables are delayed. You can use a cause-and-effect diagram to list all the potential factors affecting the delivery time, such as people, materials, methods, machines, environment, and measurement. You can then drill down into each factor and find the specific causes responsible for the delay.

To use a cause and effect diagram, you need to:

• Specify the quality problem or effect for analysis and record it on the right side of a sizable sheet of paper or a whiteboard.
• Draw a horizontal line from the problem or effect and label it as the spine of the fish.
• Identify the major categories or factors that can influence the problem or effect, draw diagonal lines from the spine, and label them as the bones of the fish. You can use generic categories, such as the 6Ms (manpower, machinery, materials, methods, measurement, and mother nature) or specific types relevant to your project.
• Brainstorm the possible causes or sub-factors that belong to each category or factor, draw sub-branches from the bones, and label them as the sub-bones of the fish. You can use the 5 Whys technique or other methods to investigate the causes.
• Analyze the diagram and prioritize the most critical or frequent causes that must be addressed.

You can use software tools like Excel, PowerPoint, or Visio to create and edit the cause-and-effect diagram. You can use colors, symbols, or ratings to highlight or rank the causes.

Pareto Chart

A Pareto chart is a graphical tool that helps you prioritize the most important or significant causes of a quality problem or effect. It is a type of bar chart that shows the frequency or percentage of each cause in descending order, along with a cumulative line that shows the total rate of the reasons. Utilizing a Pareto chart facilitates the application of the Pareto principle, commonly recognized as the 80/20 rule, asserting that 80% of the effects stem from 20% of the causes.

For example, you want to analyze which types of defects are causing the most rework or waste in your project. You can use a Pareto chart to show how many defects are caused by each type, such as design, manufacturing, testing, or packaging. This can help you see which defects are the most frequent or severe and need to be addressed first.

To use a Pareto chart, you need to:

• Collect data on the quality problem or effect and the possible causes you want to analyze.
• Count the frequency or percentage of each cause and rank them in descending order.
• Draw a bar chart that shows the causes on the horizontal axis and the frequency or percentage on the vertical axis. Ensure the bars are aligned from left to right according to their rank.
• Draw a line chart showing the cumulative percentage of the causes on the same vertical axis. Start from the leftmost bar and add the share of each bar to the previous one until you reach 100%.
• Draw a vertical line at 80% on the cumulative percentage axis and identify the causes on the left side of the line. These are the vital few causes that account for 80% of the problem or effect.

You can use a software tool like Excel to create and edit the Pareto chart. You can also use colors, symbols, or labels to highlight or annotate the causes.

Scatter diagram

A scatter diagram, also known as a scatter plot or a scatter graph, is a graphical tool that helps you explore the relationship or correlation between two variables or factors that affect the quality of your project outputs. 

It is a plot illustrating the values of one variable on the horizontal axis and another on the vertical axis. Each data pair is depicted as a point on the plot. A scatter diagram aids in assessing the correlation between the two variables, revealing whether it is positive, negative, or non-existent and indicating the strength or weakness of the correlation.

For example, you want to analyze how the temperature and the humidity affect the performance of your project deliverables. You can use a scatter diagram to show the temperature and humidity values for each deliverable and see if there is a pattern or trend in the data. This can help you determine if there is a causal or an influential relationship between the two variables and how to control or optimize them.

To use a scatter diagram, you need to:

• Collect data on the two variables or factors that you want to analyze.
• Plot the values of one variable on the horizontal axis and the importance of another variable on the vertical axis. Ensure that the axes' scales and ranges are appropriate and consistent.
• Draw a point for each pair of values on the plot. You can use different colors, shapes, or sizes to distinguish or group the points.
• Examine the shape, direction, and density of the points on the plot to discern whether there is a nonlinear, linear, or no correlation between the two variables. Additionally, consider employing a line or curve, such as a regression line or a curve of best fit, to illustrate the most accurate approximation of the relationship between the two variables.

You can use a software tool like Excel to create and edit the scatter diagram. You can also use labels, legends, or annotations to explain or emphasize the points.

Control chart

A control chart, also known as a Shewhart chart or a process behavior chart, is a graphical tool that helps you monitor and control the variation or stability of a process or a system that affects the quality of your project outputs. 

It is a type of line chart that shows the values of a quality characteristic or parameter over time, along with a center line that shows the average or target value and two control limits that show the upper and lower boundaries of the variation. A control chart can help you see if the process or the system is in control or out of control and if there are any special or common causes of variation.

For example, suppose you want to monitor and control the cycle time or the duration of your project activities. You can use a control chart to show the cycle time values for each activity and see if they are within the control limits. This can help you detect and eliminate any abnormal or assignable causes of variation, such as errors, defects, or changes, and maintain or improve the quality and efficiency of your project.

To use a control chart, you need to:

• Collect data on the quality characteristic or parameter that you want to monitor and control over time.
• Calculate the center line, which is usually the mean or the median of the data, and the control limits, which are usually based on the standard deviation or the range of the data. You can use different formulas or methods, such as the X-bar and R chart, the P chart, or the C chart, depending on the type and the distribution of the data.
• Draw a line chart that shows the values of the quality characteristic or parameter on the vertical axis and the time or the sequence on the horizontal axis. Make sure that the scales and the intervals of the axes are appropriate and consistent.
• Draw the center line and the control limits on the same chart and label them accordingly.
• Observe the points on the chart and see if they are within or outside the control limits or if they show any patterns or trends that indicate a lack of control or stability. You can use different rules or tests, such as the Western Electric or Nelson rules, to identify the signals or outliers.

You can use a software tool like Excel to create and edit the control chart. You can also use colors, symbols, or annotations to highlight or explain the points.

Next Steps

The seven basic quality tools are versatile for your QA process, aiding in data collection, analysis, and display to enhance project output quality and resolve issues. While valuable, they aren't the only QA tools available. 

Additional tools like the seven new quality tools, seven management and planning tools, Six Sigma tools, agile tools, and lean tools can complement them. 

Choose tools based on your project's nature, scope, goals, and customer and stakeholder needs. If you’re looking for help with your QA strategy or managed QA, MSH is here for you.