Statistical Thinking to Improve Quality

This posting gives an example of an Interrelationship Digraph which is a tool for use in the seventh step, Study Cause and Effect, of the Hoerl-Snee Process Improvement Strategy.   The quality issue is the potential causes or factors contributing to late deliveries.   We take our example from Benbow and Kubiak (2005).   The interrelationship digraph appears below.

After constructing the interrelationship digraph we want to interpret its meaning.   What are the key factors or causes to investigate and improve?   Recall that we called the entries in the digraph concerns.  A concern with a high number of output arrows is a driver or key cause.  A key cause affects a large number of other items.  The above diagram shows the following key causes:

1. ‘Poor scheduling practices’ (6 outgoing arrows),
   
2. ‘Late order from customer’ (5 outgoing arrows), and
   
3. ‘Equipment breakdown (3 outgoing arrows).
   

A concern with a large number of input arrows is affected by a large number of other concerns.  Thus, it could be a source of a quality or performance metric.   ‘Poor scheduling of the trucker’ has 4 input arrows.   A measure of poor scheduling performance of the trucker could indicate the magnitude of system problems causing late delivery.

References:

1. Benbow, D. W. and T. M. Kubiak (2005). The Certified Six Sigma Black Belt Handbook. Milwaukee, Wisconsin, ASQ Quality Press.