bump. But what if that show is being moved to October next year? A good forecast would plan for the show-induced increase in sales to happen earlier. Your understanding of your business is what would tell the forecast model to incorporate that change. Develop a relevant forecasting process. Forecasting cannot be an event; it must be a process. To get forecasts that will help you make informed decisions, you must define steps to ensure you are using the right data, that the forecast models used make sense, and that the forecast is used in the way it was intended. You need to define responsibilities and timing requirements . It is less important where the responsibilities lie, and more important that they are defined, accepted, and executed within the timing rules of your process. Ignoring these issues makes a good forecast is a matter of luck, not planning. As an example of "right data," consider this: Some of you use shipment or billing history as a basis to forecast the future. Ask yourself, does that data really reflect what and when the customer wanted? If you have a history of late deliveries or product substitutions, then customer order data could better reflect what the customer wanted. If you are going to use the past to predict the future, make sure the history data you use reflects the assumptions you want to make about the future. Understand how the forecast will be used. "Please have a forecast on my desk at 8:00