The Forecasting Perspective
Chapter 1 - Solution to 1.2
Step 1: Problem definition This would involve understanding the nature of the individual product lines to be forecast. For example, are they high-demand products or specialty biscuits produced for individual clients? It is also important to learn who requires the forecasts and how they will be used. Are the forecasts to be used in scheduling production, or in inventory management, or for budgetary planning? Will the forecasts be studied by senior management, or by the production manager, or someone else? Have there been stock shortages so that demand has gone unsatisfied in the recent past? If so, would it be better to try to forecast demand rather than sales so that we can try to prevent this happening again in the future? The forecaster will also need to learn whether the company requires one-off forecasts or whether the company is planning on introducing a new forecasting system. If the latter, are they intending it to be managed by their own employees and, if so, what software facilities do they have available and what forecasting expertise do they have in-house?
Step 2: Gathering information It will be necessary to collect historical data on each of the product lines we wish to forecast. The company may be interested in forecasting each of the product lines for individual selling points. If so, it is important to check that there are sufficient data to allow reasonable forecasts to be obtained. For each variable the company wishes to forecast, at least a few years of data will be needed.
There may be other variables which impact the biscuit sales, such as economic fluctuations, advertising campaigns, introduction of new product lines by a competitor, advertising campaigns of competitors, production difficulties. This information is best obtained by key personnel within the company. It will be necessary to conduct a range of discussions with relevant people to try to build an understanding of the market forces.
If there are any relevant explanatory variables, these will need to be collected.
Step 3: Preliminary (exploratory) analysis Each series of interest should be graphed and its features studied. Try to identify consistent patterns such as trend and seasonality. Check for outliers. Can they be explained? Do any of the explanatory variables appear to be strongly related to biscuit sales?
Step 4: Choosing and fitting models A range of models will be fitted. These models will be chosen on the basis of the analysis in Step 3.
Step 5: Using and evaluating a forecasting model Forecasts of each product line will be made using the best forecasting model identified in Step 4. These forecasts will be compared with expert in-house opinion and monitored over the period for which forecasts have been made.
There will be work to be done in explaining how the forecasting models work to company personnel. There may even be substantial resistance to the introduction of a mathematical approach to forecasting. Some people may feel threatened. A period of education will probably be necessary.
A review of the forecasting models should be planned.