Great book. The book contains some great ideas which are presented in an easy to read manner. The central idea is actually quit simple, but you'd never think of it. This book changed the way I approached performance management systems.

This book provides an amazingly convincing explanation for why employee incentive programs often do more harm than good. It's often because knowledge work is too complicated to benefit from any simple measures.

The core argument of the book uses some mathematical reasoning that will be accessible to anyone who stayed awake through Economics 101. This is illuminating enough, but then Austin continues to add on additional insights.

I've placed this book on my shelf next to The Logic of Failure (Doerner) and Normal Accidents (Perrow). All of these books provide solid scientific arguments for the limits of management.

As a software tester, the most obvious application of the book is as an explanation of exactly when counting defects (found by testers, or introduced by programmers) is likely to lead to trouble.

This book is not - a light read - long - mathematical - about software specific issues and the arcana of that discipline - a cookbook for deciding what to measure, how to measure, how to analyze, how to report

This book describes - the uses of measurement, informational vs motivational - a (increasingly elaborated) measurement model - an objective definition of dysfunction and how it arises because of measurement - a model of "supervision" and how measurement supports (or interferes with) various kinds of supervision - a suggestion about organizational incentives - some strengths & weaknesses of well known assessement systems; e.g., ISO, SEI - the interview method and answers applying the model with 8 well-known writers on software and software management issues.

The messages I got - setting up measurement systems is not easy. There are many pitfalls - picking the goal(s) that the measures will support is critical - picking the measures. Some things are too expensive to measure - deciding how much to spend - deciding what to report to whom - (to my own chagrin) that I had personnally and fully encountered most pitfalls - it's easy for those measured to subvert the measuring - partial measurement may make things worse - informational measurement (measuring and results stay with those measured) is less likely to be subverted - purely economic models are not fully adequate explanations of employee-employer relationships.