If you are successful, your audience will come away with the same conviction you have in implementing the solutions. In addition to this, the decision makers will have useful information they understand, allowing them to determine what solutions should be implemented, in what order and when, and by which group.

As we move more fully into anticipating change, which is a gentler term for forecasting, predictive analysis, and capacity planning, be very cautious. The concepts and techniques I have presented in this book so far, and what remains, are not meant for deep predictive analysis. As I continue to state, our objective is to anticipate the impact of solutions. Use general and imprecise words and numbers to convey change, movement, and direction.

The main reason the forecasting techniques presented in this book are not up to predictive analytics snuff is because they are not validated and may be based on a single sample. The math is fine, but I have purposely not brought you through the steps to create a robust forecast model and then to validate the model so you can understand its precision and usefulness. For our objectives, which are very general and imprecise, the increased precision and complexity are not necessary. If you desire more precision, a number of technical papers, books, and some training opportunities are available.11