Most decisions and plans in a firm require a forecast. Not matching supply with demand can make or break any business, and that's why forecasting is so invaluable. Forecasting can appear as a frightening topic with many arcane equations to master. For this reason, the authors start out from the very basics and provide a non-technical overview of common forecasting techniques as well as organizational aspects of creating a robust forecasting process. The book also discusses how to measure forecast accuracy to hold people accountable and guide continuous improvement. This book does not require prior knowledge of higher mathematics, statistics, or operations research. It is designed to serve as a first introduction to the non-expert, such as a manager overseeing a forecasting group, or an MBA student who needs to be familiar with the broad outlines of forecasting without specializing in it. Annotation Every plan needs a forecast - a reasonable prediction of the future. No business plan can be implemented without one. But the academic literature on forecasting is vast and spans disciplines such as statistics, economics, operations management and informed judgment and decision making. Recommendations from this literature have been implemented in a vast array of commercial software, and almost all modern companies have access to some decision support models that provide demand forecasts. In the long run, the demand forecast shapes decisions to build or close down plants, add or remove products from a portfolio, and bolster or challenge investor confidence in the stock price. In the short run forecasting software greatly aids managers in making functional decisions (how much are we going to sell next month, next year, or 5 years from now?) but without a proper understanding of the basics of forecasting, such software appears as a black-box, and the output from this software garners little trust within an organization. The intention of this book is to underscore the importance of demand forecasting and to demonstrate what an executive should know about it. It discusses the value of forecasting, presents both basic and advanced forecasting models, introduces the subject of time series and the technique of exponential smoothing (critical for accurate forecasts), examines the role that human judgment plays in interpreting the numbers and identifying forecasting errors. Finally, the book offers an organizational context by creating a rational framework that shows how forecasting is an integral part of business planning and demonstrates how to use forecasts within an organization Provides a non-technical overview of common forecasting techniques as well as organizational aspects of creating a robust forecasting process. The book also discusses how to measure forecast accuracy to hold people accountable and guide continuous improvement.
