Just as the ability to devise simple but evocative models is the signature of the great scientist so overelaboration and overparameterization is often the mark of mediocrity.

Remember that all models are wrong the practical question is how wrong do they have to be to not be useful.

The business of the statistician is to catalyze the scientific learning process.

The only way to know how a complex system will behave-after you modify it-is to modify it and see how it behaves.

The benefits provided by worker participation are twofold. Quality is improved because of the finding and fixing of a very large number of problems, but also, and perhaps equally important, moral is improved.

One important idea is that science is a means whereby learning is achieved, not by mere theoretical speculation on the one hand, nor by the undirected accumulation of practical facts on the other, but rather by a motivated iteration between theory and practice.

Management must provide employees with tools that will enable them to do their jobs better, and with encouragement to use these tools. In particular, they must collect data.

All models are wrong, but some are useful.

The management system which makes only a pretense of valuing employee involvement and encouraging employee empowerment merely breeds cynicism.

Discovering the unexpected is more important than confirming the known.