Fall 2002

Tools for Looking Ahead

Being able to supply the right quantity of goods at the right time is crucial to success in manufacturing. If you can’t forecast demand, you run two risks: missed delivery deadlines on one hand and excess inventories on the other.

Forecasting is not an exact science, since customers often don’t know what they will want until they want it.

Sophisticated forecasting software programs can eliminate some of the uncertainty and can help you make the best use of information. Sales and operations planning programs, known as SOP, include a resource-leveling function to help fine-tune production targets with labor and supplies. But like all computer programs, forecasting systems are only as accurate as the information you feed them.

A Simple Plan

A simple forecasting plan can be built around order history. One basic technique is to compute a rolling forecast, built around the most recent three-month sales record, dropping the oldest monthly figure as each new month’s figure becomes available. The same pattern might be adapted to sales averages for six, nine, or 12 months — any period suitable to the product in question.

With appropriate software, it’s an easy matter to keep the rolling average sensitive to current conditions by adjusting computation of the average so that more recent figures have a greater weight. Figures for products sensitive to seasonal and cyclical demand patterns need to be followed over an appropriate time span.

General Data

Market research data and general economic information about changes in interest rates, housing starts, or employment levels may also have a bearing on forecasts for specific products. To be useful, such figures need to be updated frequently and analyzed in light of relevant historic data to reveal patterns that point to changed product demand.

Contingency Planning

Another approach, especially useful in high-value, low-volume capital goods manufacturing, is contingency analysis. Such planning prepares for the eventuality of inaccurate forecasts. For example, a producer might negotiate contingency agreements with suppliers for suddenly needed goods.

Time Frame

Forecasts can affect business decisions in different ways, depending on the forecast time frame:

· Long-term expectations take into account broad changes in the market, product line, or technology that require decisions about major capital assets and manpower changes affecting capacity.

· The outlook over the middle range generally affects plans about the work force and supplies.

· Variability in the short run requires flexibility in staffing capacities, perhaps involving overtime or outsourcing.

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The articles in this newsletter are general in nature and are not a substitute for accounting, legal, or other professional services. We assume no liability for the reader's reliance on this information. Before implementing any of the ideas contained in this publication, consult a professional advisor to determine whether they apply to your unique circumstances.

© 2002