What you will learn in this chapter of the book is to let data drive problem solving. However, to interpret data, you need to make a judgment as to whether unusual results were due to random cause, like someone who flips a coin and gets an excessive number of heads by chance, or due to an assignable cause, like the coin having two heads. A knowledge of probability helps you make this determination with a minimum number of samples.
Much Six Sigma work can't be done without some understanding of probability statistics. Probability can be used in all the steps of DMAIC. You will be able to use these techniques to solve many problems in the work-place without using additional tools.
NOTE
Probability
Manufacturing On any production line with multiple heads, compare defect levels from each head to see if they are significantly different. Compare two or more similar production lines, shifts, defects on different days of the week, etc. Often you will see significant differences that can be addressed at little cost.
Sales Compare salespeople. The criteria could include new customers, lost sales, etc. Cross training between the best and worst performers can often improve both! Also, through these careful comparisons, compensation can be made more equitable.
Marketing Check if sales increased significantly in multiple markets after a marketing campaign.
Accounting and Software Development Compare error incidence to check for significant difference between groups.
Receivables Check the effect of increased or decreased monitoring of overdue receivables.
Insurance Compare the complaints at similar-sized treatment centers. The criteria could include patient care, billing errors, etc.
The above case study is typical in that the initial conclusion that the problem was caused by the raw materials was made without carefully analyzing data. In contrast, the engineer used specific data and an elementary knowledge of probability to reach his conclusions, since he knew that defects caused by raw materials would have been random and not specific to one of the sets of tools on a line. Although the other production lines did not have the identical problems, the same kind of careful analysis based on detailed data resolved the production problems.
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