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By Root 3017 0

Thus, it is almost useless and definitely misleading. The vast majority of management reports contain only the column of the forecast, namely the average predicted forecast. The forecasting error, the equivalent of the standard deviation, is not mentioned in those reports. The basic misunderstanding is even more destructive when people, mainly from Sales, are required to give their “forecast” for the next period. What kind of single number does management hope to get? The average? Do they really get a fair assessment of the average from the salespeople? Could it be that a typical salesperson provides his intuition regarding what he hopes to sell, rather than his or her estimation of the average? The salesperson wants to be sure he would have available all the quantity he might sell. On the other hand, the salesperson may want to give his estimation on what he is sure he can sell and not be caught failing to meet his forecast. The point is that for an unclear question, people get answers to whatever interpretation the person answering the question has in mind.

Is the “average” forecast the required information for a decision regarding how much to produce for stock? Let’s consider the following example.

The forecast for next month sales is 1000 units. We should have in stock, at the start of next month, 300 units (also “on average” depending on the sales until then). Assuming the policy is to produce the whole monthly requirement in one batch (usually an unwise policy, but that is not the point right now), should we produce 700 units?

Well, if that is the only information we have, then we are led to make a faulty decision. A proper forecast should also contain, at least, an indication of the forecasting error. Suppose the forecasting error is 500 units. The hidden meaning is that it is perfectly possible that the real demand next month would be 1500 units. Even 2000 is still a valid possibility. Of course, it also means you might sell only 500 units. Managers are required to make sound decisions even when living in such an imperfect world. A much better decision than to produce 700 units would be to produce 1700 units to cover for the valid possibility of having demand for 2000 units. Another sound decision could be to produce only 200 units when the concern of being left with unsold products is more severe than being short of products. In other words, any sound decision has to take into account the damage of producing too much versus the damage of producing too little and the larger damage should dictate whether to produce more than the average or less than the average. In most cases, the decision to produce according to the “average” prediction (based on a single average forecast number) is a truly bad decision because the element of risk is not brought into the picture. Suppose that the plan is to produce more than the average. However, without any indication of the possible spread, how should one make up his mind regarding how much more to produce?

Misunderstanding of the forecast has more aspects to it. Forecasting the sales of just one item in the coming month might be too “erratic”; thus, the idea is to forecast the sales of the whole product family. This should yield a much better forecast, shouldn’t it?

Well, usually the term “better forecast” means a relatively smaller forecasting error, while the term “erratic forecast” means a very large forecast error. The problem is you cannot use that “better forecast” for a better decision on the level of the individual item. Suppose it is “known” that the sales of a certain item are approximately 10 percent of the sales of the total family. Do we get a “better forecast” for that item when we take the forecast for the sales of the family as a whole and then take 10 percent of it as the forecast for that individual item? No, you do not get a better forecast for the individual item this way. You have a gross estimation of the average, but the possible spread of the results for different units in the product family is pretty high and you cannot reduce the spread of the sales