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Sales Forecasts
 

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Companies large and small engage in forecasting their sales in order to decide with the greatest accuracy possible what and how much to build or what and how much to buy. Sales forecasts support operational planning and supply chain management—not marketing or sales efforts. To be sure, sometimes accurate sales forecasts can also lead to intensified selling or its reverse: sales forces fanning out to dampen buyer enthusiasm because the company cannot actually supply the demand foreseen. But such efforts are not central to forecasting. Forecasts are made to project the business into the future accurately in order to avoid costly mistakes.

A classical example of sales forecasting is the determination of "the build." This phrase is used in industries where production falls into one season and sales into another. Thus snowmobiles are manufactured in the summer and sold in late fall and winter. How many sleds to build, how many of the low end and how many of the expensive models—"the build," in other words—must be decided long before the winter season actually arrives, before likely snowfall is predictable, before economic conditions influencing sales then can be known with certainty now. In "bad snow years" demand tends to drop, in "good snow years" it spikes. Snowmobiles are big-ticket items. Overbuilding can hurt the company and its dealer structure for longer than one season; under building leaves substantial money on the table and may lead to a loss of market share if the competitor made a better forecast. Builders of boats and similar "water toys" have the reverse problem: they build in the winter for spring and summer sales. Boat builders, like snowmobile manufacturers, require positive economic times in that they sell high-end recreational products users can do without. Both are influenced by weather. Boat sellers can also be hurt by high prices for fuels.

"The build" serves as an easy illustration of the need for good sales forecasts, but every producer and every merchant faces exactly the same problem in looking ahead. In every case more or less irreversible actions must be taken in advance of actual sales; in every case multiple factors influence future demand which may change in response to yet other factors; in every case bad forecasts may mean being saddled by large inventories or having to turn customers away. Not surprisingly, every business, even the smallest, engages in some kind of sales forecasting. It may be quite instinctive and informal—a gut feel by the owner that more or less should be purchased or made, based simply on experience leading up to the purchasing decision. Sales forecasting is often a process involving contact with the sales channel. In many large companies producing for mass markets, sales forecasting is a very complex, formal, and highly structured activity involving expensive surveys, computer modeling, and statistical analyses.

BASIC TECHNIQUES

Fundamental approaches to forecasting sales rely on 1) looking at the company's own history (internal numbers), on 2) looking at the product's or category's market history (external numbers), 3) soliciting external opinion (channel surveys), and 4) examining other sources of information which indirectly influence the future.

In the first case the company will look at its own past sales and determine a trend, ideally based on units rather than on dollars to eliminate the effect of price changes. If the item is growing at 2 percent a year, the company may feel safe in increasing its production/purchasing by 2 percent for the next period. Such a forecast is typically just the start of a process of review. The company may wish to eliminate the product because its margin is low and decreasing, its warranty service requirements are too great, etc. Alternatively, the company may wish to increase its growth in the category by additional promotional, discount, and sales efforts—and, betting on success, may order above its historical trend projection. Quite complicated formulas are sometimes applied. An example is production of replacement parts for outdated models of a product—in which the forecast is dated on an estimate of the models still remaining "out there" in active use—with the production reduced each year.

The second case, looking at the total market for the item, requires access to data on such sales. If these are available, the company can compare its own performance against the product's growth/decline as a whole and make adjustments accordingly. Suppose the category, e.g., a certain type of garden tool, has been declining as a whole in the gardening field while the company's own sales of that product have been increasing at 5 percent a year. This may mean that the company may have become the last active supplier of a product in its locality thus drawing a segment of the public that still wants the product. Such a finding may lead to energetic stocking up. Conversely, if the company's sales are poor but the product as a whole is making waves, adjustments in price, promotion, display, and the like may justify much more ambitious stocking. In practice it is often very difficult to get objective data on the performance of a specific item for comparison. Similarly, even if overall sales data can be found, it may be very difficult for a merchant to discover why he or she is selling more or less of an item. The merchant's location, clientele, region of operation, and many other factors may influence the result. The small business typically lacks the time and money to go deeply into such a subject unless the product is rather expensive and central, e.g., the business sells farm equipment.

Many small manufacturers make heavy use of the third basic technique (along with the others): asking the channel what it expects to purchase in the coming planning period (quarter, year). Companies typically survey their distributors, dealers, or major customers at regular intervals to get a feel for what they plan on buying. In many fields such surveys are routine—the buyers as anxious as the sellers in getting the production numbers right so that, in the future, shortages on the one hand and pressure to buy on the other can be avoided. These types of surveys are usually conducted outside the usual "selling" context—the channel made to understand that these estimates are intended for planning production. To be sure, the channel will nevertheless feel a certain pressure. Unless there is a known shortage in a field, buyers will thus typically somewhat understate their buying intentions; they don't want to have the numbers misunderstood as commitments to buy; they hedge in the lower direction; producers in turn typically plan on slightly higher production rates, all else being equal.

The fourth technique of developing forecasts—eye-balling indirect forces—is often the most tricky and occasionally the most important. This, in the snowmobile business, for instance, is guessing at the weather, but it takes innumerable other forms. Indicators of the economy are the most closely watched: almost all businesses are affected by rising or declining economies. Hot economies lift costs of supplies and of labor—and also lift sales. Consumer durables turn sluggish in times of decline—as do capital goods bought by industry. Interest rates powerfully influence new home construction—as does the demographic phenomenon of new family for-mation—which, in turn, depends on the age structure of the population and the average age of marriage, etc. Energy and fuel prices influence virtually every sector—and these, in turn, are influenced by international events. Sociological trends are more subtle and difficult to exploit effectively. In the mid-2000s a certain and very important trend is the aging of the baby boom generation, for example, but this generation is very large and pin-pointing its immediate influence on a small business during a brief period, like the next fiscal year, is not exactly simple. The small business that at least attempts consciously to look for and to analyze such trends—using the broadly available statistical sources as well as its own experience with the public—will outperform a company that simply looks at past sales and uses these to predict future sales.

FORECASTS, OUTCOMES, AND LIMITATIONS

Well-conducted sales forecasting programs have an impact on every aspect of the business—on financial performance first of all, of course, but also on market share, channel relations, and consumer satisfaction. An accurate forecast buys the company time—and time is money. If the market is projected to experience a sharp decline and the forecast is correct, the company can scale back its production and purchases early, will have more time to adjust to these changes—and will be able to retain its place in the market with a properly priced product. The downward adjustment will be no less painful when taken early rather than later—but if taken later, it will be more costly: the company will be sitting on and required to finance a large inventory; it will have to move goods at large discounts, eroding its margins; at the same time it will bear high costs of severance from layoffs. Companies, however, are rarely able to get themselves to shrink deliberately in advance of facts clear and evident on the ground. For this reason, even very effective managements will compromise and simply scale back a little. But even that will be more adaptive than projecting lasts year's sales with a small increase.

Companies, similarly, are rarely able to believe a forecast that predicts a sudden surge in sales. Such things are rare and therefore too good to be true. But the company that has a decent sales forecasting program and dares to act on it, at least up to a point, will find itself with product in the channel when everyone else is out. It will thus garner new buyers and, if the new customers are pleased, it will gain market share as well as channel loyalties.

These two cases illustrate the benefits as well as limitations of sales forecasting. The technique works best when projected changes are relatively small. Both sharp down and up adjustments from a company's or a market's history will tend to be resisted. But those with the best techniques, combining every major approach, are likely to go farthest in the right direction and will ultimately emerge as the winners.

BIBLIOGRAPHY

Burton, James E., and Steven M. Bragg. Sales and Operations for Your Small Business. John Wiley & Sons, 2001.

Crosby, John V. Cycles, Trends, and Turning Points: Practical Marketing and Sales Forecasting Techniques. NTC Publishing, 2000.

Evans, Michael. Practical Business Forecasting. Blackwell, 2003.

Forgang, William G. Strategy-Specific Decision Making. M.E. Sharpe, 2004.

Mentzer, John T., and Mark A. Moon. Sales Forecasting Management: A Demand Management Approach. Sage Publications, 2005.

Wallace, Thomas F., and Robert A. Stahl. Master Scheduling in the 21st Century. T.F. Wallace, 2003.





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