Data Stratification

Six Sigma is a fact and data based approach to problem solving.  After we have defined a gap in performance and have collected data about the performance of a process, we need to analyze the data to find the root cause or causes of the problem.  Data stratification is a tool that we can use to organize the data for analysis.  The time to think about data stratification is before the data is collected, not after.  We must make sure that the data are collected in such a fashion that they are useful for analysis.

Data are typically stratified in four different ways.  The four factors are Who, What, Where and When.  Here is an example that was submitted recently by one of our Green Belt students in response to an assignment on this subject.  The purpose of the data analysis is to determine why employees are late for work.  Data might be collected and analyzed as follows to try and uncover patterns that would lead us in the direction of root causes.

For the Who factor, data could be stratified by the class or group that the employees belong to.  Examples are Executives, Managers, Engineers, Machinists and Assembly Workers.

For the What factor, data could be stratified by what type of transportation is used to get to work.  Examples are alone by automobile, by carpool, by bus, by train and by walking.

For the Where factor, data could be stratified by the physical location where the employees report to work.  Examples might be a main office building, a factory location, and a warehouse location.

For the When factor, we need to stratify by some dimension of time.  Examples in this case could be by shift, or by day of week.

In all cases we would be looking for patterns where there is a difference in performance from one stratum to another.  For example, the data may show that the type of transportation that is used has a significant impact on whether or not an employee is late.  Or, the data might show that employees who work in the warehouse are late more often than employees who work in other locations.  When such a pattern is noted, we would continue asking “why” until a correctable root cause was identified.

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About the author:  Mr. Roger C. Ellis is an industrial engineer by training and profession.  He is a Six Sigma Master Black Belt with over 45 years of business experience in a wide range of fields.  Mr. Ellis develops and instructs Six Sigma professional certification courses for Key Performance LLC.   For a more detailed biography, please refer to