The problem of intermittent demand interferes with efficient production and inventory control activities in US manufacturing firms. While the key role of accurate and timely demand forecasting in planning production, inventories and work force, and economic lot sizing has received considerable attention, the vast majority of forecasting research, and nearly all commercial forecasting software, assume that demand is "smooth" rather than intermittent. Results of the Phase I Small Business Innovation Research (SBIR) study establish the technical basis for a new software tool that can be used to forecast intermittent demand and that is suitable for use on a desktop computer. The objectives of the Phase II research focus on (1) gathering and analysis of more real-world intermittent time-series data; (2) implementation of a single-series method of Croston's for forecasting intermittent demand, including its extension to trending and seasonal data; (3) development of a new multi- series forecasting approach based on stochastic process models that "borrow strength" across the items in a product line; (4) determination of the most effective use of sales-force judgments of intermittent demand, including their combination with statistical forecasts' and (5) integration of the forecasting methods developed in Phase II, culminating in their implementation in a software prototype running on desktop computers. The project will provide a computerized state-of-the-art solution to the intermittent demand forecasting problem. A large percentage of US manufacturing firms stand to benefit from more efficient production made possible by such demand forecasting.
