Flynn, Michael (1991, ASQC) STAT-A-MATRIX, Inc., Edison, NJ
Although 80% of the American work force is engaged in service operations, the quality movement has not given the service industry the same attention it has given to manufacturing and production. This paper illustrates several applications for binomial probability paper (BIPP) analysis, a useful tool created by Mosteller and Tukey in 1949. BIPP analysis can be applied to such diverse data as EEO complaints, the error rates of clerical personnel, the on-time performance of different carriers in motor freight, and the pass completion rates of quarterbacks in the NFL.The author compares Shewhart's approach to variation and Deming's use of Common and Special causes. The paper defines four types of variation: (1) Interchangeability; (2) Homogeneity; (3) Consistency; and (4) Stability. The methods of collecting statistical data and tracking the variation down to one of these four types requires some creativity in the way data is sampled, stratified, charted, and analyzed.
Service quality data is, with few exceptions, attribute data. Attribute data lends itself to the Pareto chart, the p-chart, and the c-chart. BIPP, a technique that should not be overlooked, provides a simple method for plotting and comparing individual performers; it can also provide time series data in the form of Year-to-Date charts, which are useful to management.
Common causes,Equal Employment Opportunity (EEO) regulations,Shewhart, Walter A.,Statistics,Variation