Seven basic quality tools consist of techniques that facilitate data collection, data analysis and data visualization. PMBOK 5th edition specifically mentioned the complete list of the seven basic quality tools. However, PMBOK 6th edition has grouped all tools and techniques under six distinct categories. Hence this post briefly describes all seven basic quality tools like Pareto chart, Check sheets, Control Charts etc.
Seven Basic Quality Tools
The following paragraph enumerates seven basic quality tools Hence this post briefly describes all seven basic quality tools that assist in problem solving and process improvements. Dr. Kaoru Ishikawa in 1968 first proposed the seven basic quality tools in his book.
- Data Gathering Tools
- Check sheets
- Data Representation Tools
- Cause-and-effect diagram
- Control Charts
- Scatter diagrams
- Flow charts
- Data Analysis Tools
- Pareto diagrams
The first tool of the seven basic quality control tools is a check sheet. Tally Sheets or check sheets act as a checklist when gathering data. Check sheets organize facts in a manner that facilitate effective collection of useful data on potential quality problems. They are especially useful for gathering attributes data while performing inspections to identify defects. For e.g. pareto diagram can often display number of frequencies or consequences of defects collected in check sheets.
The second tool of the seven basic quality control tools is a cause-and-effect diagram. Fishbone / Ishikawa or why-why diagram is the alternate name for this quality tool.
The “head” of the fishbone carries the problem statement. The major categories of potential causes form the structural “bones” and likely causes make up the “ribs”.
The causes are found by looking at the problem statement and asking “Why” until the actionable root cause has been identified or until the reasonable possibilities have been exhausted.
Fishbone diagrams often prove useful in linking the undesirable effects seen as special variation to the assignable cause upon which project teams should implement corrective actions to eliminate the special variation detected in a control chart.
The third tool of the seven basic quality control tools is a control chart. Control chart is a time oriented diagram that determines if a process is stable or not. It also indicates if a process has predictable performance.
Each control chart has a centerline, statistical control limits, and the control data. Some control chart also contain specification limit. The centerline is solid line that represents the mean or the arithmetic average of the measurement of counts. There are two statistical control limits. The first limit is the upper control limit for values greater than the mean. The second limit is the lower control limit for values less than the mean.
Standard statistical calculations and principles determine the control limits. Control limits ultimately establish the natural capability for a stable process. Upper and lower control limits are different from specification limits. Upper and lower specification limits are based on requirements of the agreement. They reflect the maximum and minimum values allowed for a process.
The project manager and appropriate stakeholders may use the statistically calculated control limits to identify the points to initiate corrective actions to prevent unnatural process performance. The corrective action typically seeks to maintain the natural stability of a stable and capable process.
The corrective action typically seeks to maintain the natural stability of a stable and capable process.
Histogram is the fourth tool of the seven basic quality control tools. Histogram is a special form of bar chart which describes the central tendency, dispersion, and shape of a statistical distribution.
A histogram summarizes data measured on a continuous scale, showing the frequency distribution of some quality characteristic (in statistical terms central tendency and dispersion of the data).
Unlike the control chart, the histogram does not consider the influence of time on the variation that exists within a distribution.
Scatter diagram is the fifth tool of the seven basic quality control tools. A scatter diagram is also known as correlation chart. These diagrams seek to explain a change in the dependent variable (Y) in relation to a change in the corresponding independent variable (X).
The direction of correlation may be proportional (positive correlation), inverse (negative correlation), or a pattern of correlation may not exist (zero correlation).
Flowchart is the sixth tool of the seven basic quality control tools. Process Maps or flow charts display the sequence of steps and the branching possibilities that exist for a process that transforms one or more inputs into one or more outputs. Flow charts show the activities, decision points, branching loops, parallel paths, and the overall order of processing. A flow chart maps the operational details of procedures that exists within a horizontal value chain. The figure below depicts one such value chain called Supplier Input Output Customer (SPIOC) model.
Moreover, flowcharts prove useful in understanding and estimating the cost of quality in a process. Information is obtained by using the workflow branching logic and associated relative frequencies to estimate expected monetary value for the conformance and non-conformance work required to deliver the expected conforming output.
Additionally, process flow diagrams or process diagrams are flowcharts that represent steps in a process. Therefore, a process flow diagrams can help to identify where quality defects can occur or where to incorporate quality checks. Moreover, process diagrams also facilitate in identifying process improvements activities.
Finally, the seventh tool of the seven basic quality control tools is a pareto diagram / chart . Pareto diagrams exists as special forms of vertical bar chart. A pareto chart consists of bars and line graphs. Bars in descending order in a pareto chart represent individual values. The line in pareto diagram represents cumulative value.
A pareto chart helps to identify the vital few sources that are responsible for causing most of a problem’s effects. According to Pareto principle 80% of the effects comes from 20% of the causes. This is also popularly known as the 80 / 20 rule.
The categories shown on the horizontal axis exist as a valid probability distribution that accounts for 100% of the possible observations. The relative frequencies of each specified cause listed on the horizontal axis decrease in magnitude until the default source named “other” accounts for any non-specified causes.
Typically, the Pareto diagram is organized into categories that measure either frequencies or consequences.
The most important fact is that PMBOK 6th edition does not have any mention of pareto chart.
For detailed explanation of the four control quality data representation tools like cause-and-effect diagrams, control charts, histogram, and scatter diagram refer to the following post.