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Abstract
This book is about pragmatic, management-oriented sales forecasting for entrepreneurs, small business owners, and middle managers faced with the kind of practical management problems that forecasting can help prevent. Its main focus is the real-world sales forecast done almost every day, not using technical analysis or sophisticated forecasting techniques, but rather common sense, experience, and industry knowledge. This is forecasting that respects the educated guess.
The book is written for entrepreneurs and managers to help with practical and commonplace management issues. The sales forecast is a vital tool for management, even though it’s likely to be wrong. It becomes the foundation of the expense budgets and, through that, cash management.
It begins by setting forecasting into management context. It isn’t about guessing the future correctly; instead, it’s about setting reasonable assumptions, getting them organized into a forecast, and then tracking and following up so that the difference between original forecast and actual results can be tracked and managed. A good forecast continues, every month, with regular review and course corrections. And that leads to better management. The process is something like steering, which is a matter of making regular corrections.
The bulk of the book is instruction by example. It presents actual cases, with step-by-step details, of sample sales forecasts. These include new products and new businesses and existing businesses. They also include top-down (called trees from the forest) forecasts from the larger market trends, and bottom-up (forest from the trees) forecasts looking at details by customer, channel, or product. These case examples are annotated with tips and traps and explanation of the underlying thinking and, where relevant, market research—and lots of spreadsheet specifics to empower the manager.
As it progresses, it does cover some of the more common sophisticated forecasting techniques, including an innovative strategic interactive model, several examples of data smoothing and weighting, and a simple regression analysis.
In the final chapter, it gathers spreadsheet forecasting tips from throughout the book to put them together where they can be most useful to real managers.

Genres for this book