Quality Assurance

360 Quality Assurance

information from people who do the work (operators) and are more familiar

with details of the problem. Frequently, these people have essential informa-

tion that they may not recognize as signicant.

Test each theory against each discrete set of IS/IS NOTs listed in the prob-

lem description (Step 2) for every element of what, where, when, and how big.

Specically, ask, “Does this ‘change-how’ theory completely explain both the

IS and IS NOT?” With this question, the team is asking, “If this theory is the

cause of the effect, do the factual data in the problem description explain

fully why the effect manifests itself in the IS dimension but never manifests

itself in the IS NOT dimension?” There are three possible outcomes ...