Collaborative Forecasting: An Intra-Company Perspective

Describes who should own forecasts, key elements of a successful collaborative forecasting process and how to determine whether or not an organization has a collaborative forecasting process in place ... collaborative forecasting not only enhances the quality of forecasts but also improves the allocation of resources. Over the past thirty years, the inherent capabilities of statistical forecasting models, market and economic data, and forecasting software have exploded. Yet, overall forecast accuracy has not kept pace with it. While practitioners are looking for ways to increase forecast accuracy, management is concerned whether the forecaster truly understands the nature and realities of the marketplace. Collaborative forecasting plays an important role in forecast accuracy. In this article, we discuss the intra-company aspect of collaborative forecasting as practiced in corporate America, and how it can be used to improve forecast accuracy and, consequently, the bottom line. Collaborative forecasting is a process that has grown in importance and moved to a place of prominence in corporate America. Once it is properly put in place, it adds significant value to the organization. It not only enhances forecast accuracy, but also increases the efficiency of reaching a consensus on forecasts. COLLABORATIVE FORECASTING DEFINED Stated in simple terms, collaborative forecasting is a way of getting people to talk to each other and work together to improve forecast accuracy. Below are statements from four senior forecasters, which may give some idea what collaborative forecasting is all about. 1. It is away to bring together all corporate resources and collective knowledge across functional areas internally and externally through strategic partnerships. 2. It is a forecasting process based on teamwork, free exchange of information, and knowledge sharing. 3. It is a communication-based approach to forecasting, based on the premise that two heads are better than one. 4. It is a way to combine industry and product knowledge about competitive intelligence, marketing plans, and statistical models to produce superior forecasts. In nutshell, it is aprocess that combines people with data, knowledge, and experience for the purpose of improving forecast accuracy. WHY COLLABORATIVE FORECASTING? In an ideal world, the forecaster would have a complete customer and market knowledge. Everyone would understand and appreciate forecasting. Management would have complete trust in the forecaster. The forecasts would be consistently right on target. But in the real world things are different. People who are in the forefront of forecasting have little or no understanding what forecasting is all about. They are ignorant about sound forecasting practices and processes. There is confusion about who owns the forecast. Many business decisions are politically motivated. In such a business environment, collaborative forecasting is needed more than ever because: 1. Often, the forecaster is unable to determine the true causal factors that influence the forecasts. In a collaborative setting, the forecaster is more likely to come up with the right factors. 2. It is extremely difficult to prepare forecasts for new products because there is no history. But there are people within an organization who have experience in launching similar products. The collaborative setting enables the forecaster to tap into their experience. 3. In case of existing products, judgment plays an important part because not all information is incorporated into statistical models. Elements such as changes in market dynamics, production or supply chain considerations, sales and promotional activities and competitive intelligence have a bearing on the forecast but are not fully factored into a model. Therefore, to improve forecasts an overlay of informed judgment on statistical forecasts is needed. …