Statistical Thinking to Improve Quality

The Customer-Complaint-Process Example illustrated two types of variation, i.e., special and common cause.   The example, taken from Britz, Emerling, et (2000, p. 29), in this post illustrates four types of variation, i.e.,

·        Off-target

·        Common Cause

·        Special Cause

Off-target variation occurs when the process average does not meet the organization’s desired target.  Structural variation occurs when causes occur in a predictable manner.    For example, the waiting line for a table at a restaurant might be longer on Saturday evenings than on other days.

Distribution Center On-Time Delivery Example

Shawn was perplexed when she examined Figure 1 showing a plot of weekly on-time deliver percentages at her distribution center.  The corporation’s goal was to deliver 97.5% of orders each week in a timely manner.  During the past quarter, the center had only met that goal twice.   In addition, a review to the center’s activities during the two satisfactory weeks did not reveal any unusual behavior.

The overall average of weekly on-time delivery percentages was 94% which was significantly below the corporate goal of 97.5%.    The average of weekly on-time percentages must be greater than 97.5% in order for the center to consistently meet its goal of 97.5%.   If the average of all weekly on-time delivery percentages exactly equaled 97.5% then about half of the weeks would have on-time delivery percentages less than the goal of 97.5%.   Assume that a target of 99% on-time deliveries would permit the center to consistently meet the goal of 97.5% for each week.   This gap between the target (99%) and the weekly averages of 94% is Off-target variation.

Figure 1

Figure 2 suggests that the variation in on-time delivery percentages is due to common-cause variation.   One reason is that all of the plotted points are less than the Upper Control Limit (UCL) and greater than the Lower Control Limit (LCL).   Factors contributing to Common-Cause Variation are:

·        Number and complexity of orders in each week

·        Truck schedules

·        Personnel availability

The conclusion is that an analysis of the actions during the two weeks where the center met the goal of 97.5% would be an inefficient approach to improving the system.   Analyzing all of the weeks where the same common-causes are active would be more effective in identifying process improvements.

The next post will illustrate special-cause and structural variation.

Figure 2

1.     Britz, G. C., D. W. Emerling, et al. (2000). Improving Performance Through Statistical Thinking. Milwaukee, WI, ASQ Quality Press.