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The Seven (or so) Basic Quality Tools

The Seven (or so) Basic Quality Tools. Presented by Mike La Dolcetta ASQ Sr. Member, CQM, CSSGB. History and Introduction.

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The Seven (or so) Basic Quality Tools

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  1. The Seven (or so) Basic Quality Tools Presented by Mike La Dolcetta ASQ Sr. Member, CQM, CSSGB

  2. History and Introduction • Although the Seven Basic Quality Tools were developed independently of each other, it was Dr. Kaoru Ishikawa of the University of Tokyo who popularized their use in the Quality Circles of Japan during their Quality Revolution. The original seven tools as published by JUSE in Ishikawa’s acclaimed Guide to Quality Control (1968) are: • Check Sheets • Histograms • Pareto Diagrams • Scatter Diagrams • Cause and Effect diagrams (aka “Ishikawa” or Fishbone Diagrams) • Graphs (particularly Run Charts) • Control Charts. Kaoru Ishikawa 1915 - 1989 Two popular additions that will be discussed are Stratification and Process Flow Diagrams.

  3. Check Sheets Check sheets can serve several functions and are typically tailored to specific needs. One of the most important is providing an organized way to collect data that lends to effective analysis. While check sheets have their roots in paper forms, the computer form shown here is a great example of a modern check sheet. This form collects quality data from the efforts of QA analysts monitoring sales reps who sell over the phone (Telesales). The QA analysts use recordings of the phone conversation between the sales rep and the customer, complete with synchronized video of the rep’s computer use during the call, to assess the sales rep’s performance on the various attributes. The results are analyzed for coaching and development of the sales force, and other endeavors.

  4. Histograms A histogram is just a special type of column graph that displays frequencies or counts of something, enabling us to see how the data is distributed. The histogram below shows the distribution of QA scores for all sales reps during a specific month. A red dashed line representing the minimum passing score has been added to help us judge performance. We notice almost half of the scores are below the minimum. In fact, some reps scored zero.

  5. Stratification Stratification, or the separation of data into different levels for analysis (in this case “tenure”), reveals that recently hired reps are struggling most with the QA process.

  6. Pareto Diagrams (Charts) Italian economist Vilfredo Pareto stated that 80% of the wealth is controlled by 20% of the population. However it was Dr. Juran (aka the Father of Modern Quality Management) who applied this concept to quality, and designed a chart to effectively display the phenomenon that relatively few defect types typically comprise the bulk of the defectives (Juran, SP7518). The Pareto chart below reveals which QA attributes new reps failed most often, and we see that the top 3 drove over 60% of the attribute failures. Vilfredo Pareto 1848 - 1923 Joe Juran 1904 - 2008

  7. Scatter Plots Scatter plots are typically used to check for relationships between factors. The pattern of the plotted data, as well as some calculated statistics, can expose possible cause and effect relationships. However, care should be taken to validate such relationships (for example, using designed experiments) less we be misled by undiscovered factors truly driving the results. Statistics that are often used to measure the linear strength of relationships between variables include the Pearson Product-Moment correlation and Spearman Rank correlation. Below is plotted data for average sales revenue and average points achieved for the QA form’s sales attributes. Charles Spearman 1863 - 1945 Karl Pearson 1857 - 1936

  8. Run Charts The basic idea behind a Run Chart is to display the trend in some attribute count or variable measure over time. Peaks are drops are readily visible on Run Charts, and can then be investigated. Below, we see historical trending of sales attribute pass rates for new reps. While stable for almost two years, performance dropped sharply for the most recent graduating class.

  9. Ishikawa Diagrams Ishikawa’s Fishbone diagram helps us to brainstorm (typically in groups) the causes that result in the effect we are trying to understand. Major group categories along the “bones” such as Employees and Systems, etc. assist in organizing ideas for possible causal factors leading to the outcome at the “head” of the fish. Below is an example diagram for the poor sales QA scores. With possible root causes agreed upon, improvement teams can collect specific data to validate, then investigate and apply solutions. Kaoru Ishikawa 1915 - 1989

  10. Process Flow Diagrams Thought to have originated at Princeton University in the late 1940s to aid software development, flowcharts help us understand how processes work by using symbols and directional connecting lines to visually represent different process steps. Often when a group flowcharts an existing process, key discoveries are made and improvement opportunities are identified. The flowchart below assists in selecting the proper control chart to use based on the data involved. Source: WHICH CONTROL CHART DO I USE? By William J. Latzko, Ph.D. www.asq.org/articles/aqc-proceedings/public_proceedings/57_2003/19375.pdf

  11. Control Charts Walter Shewhart (aka The Father of Modern Quality Control) introduced Control Charts in 1924s, while at Western Electric. Dr. Deming preached and popularized their use throughout both the manufacturing and services industries. The basic premise is to use statistical testing based on variation probability theory to separate process variation signal and noise (aka common cause and special cause variation) over time for process behavior monitoring and control. Different types are used depending on the nature of the data (see Which Control Chart Do I Useon asq.org). Below is a p-chart used to monitor new hire failure rate after applying solutions identified by an improvement team working the root causes identified on the Fishbone. Walter Shewhart 1891 - 1967 W. Edwards Deming 1900 - 1993

  12. Summary Hopefully these examples have provided some insights to what the Seven (or so) Quality Tools are and how they can be used for data analysis, quality improvement and quality control. Further information can be found obtained via the resources identified on the next slide. You are encouraged to think creatively to identify opportunities where you can apply these tools. And remember to share your knowledge… that’s what we’re about! “ASQC” 1951 Exhibit- 5th National Convention Photo from ASQ Archives: http://web.library.uiuc.edu/ahx/asq/

  13. References and Further Reading Click on the hyperlinked titles to go to a web page for details (Internet connection required) Seven Basic Quality Tools webpage on asq.org (free!) The Certified Quality Process Analyst Handbook – Christensen, Betz, & Stein The Quality Improvement Handbook – Bauer, Duffy, & Westcott Juran’s Quality Handbook – Joseph M. Juran Guide to Quality Control – Kaoru Ishikawa Economic Control of Quality of Manufactured Product – Walter Shewhart

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