Business leaders know that accurate forecasting is a critical organizational capability. Forecasting is predicting the future, and the list of what needs to be predicted to run a world-class organization and its supply chain is virtually endless. Forecasting goes well beyond simply predicting demand or sales. Accurate forecasts are essential for identifying new market opportunities, forecasting risks, events, supply chain disruptions, innovation, competition, market growth and trends. It also includes the ability to conduct a what-ifa analysis to understand the tradeoff implications of decisions. Over the past few years the ability to make accurate and useful forecasts has become particularly challenging due to a spike in the competitiveness of global markets coupled with a global economic recession. Customers are demanding increasingly shorter response times, improved quality, and greater product choice. Increased competition is exacerbated by a downward global economy and rising fuel prices, which increase uncertainty, risk, and operating costs. The result has been a sharp rise in the complexity of what needs to be forecasted. In an era of rapid change, historical data that are typically used to make forecasts can be of limited value. At the same time information technology has enabled forecasts to drive entire supply chains and enterprise resources planning systems. However, more technology and software, without an understanding of how they can most effectively be utilized, are not the answer to improving forecast accuracy

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.