In virtually every decision they make, executives today consider
some kind of forecast. Sound predictions of demands and trends are no
longer luxury items, but a necessity, if managers are to cope with
seasonality, sudden changes in demand levels, price-cutting maneuvers of
the competition, strikes, and large swings of the economy. Forecasting
can help them deal with these troubles; but it can help them more, the
more they know about the general principles of forecasting, what it can
and cannot do for them currently, and which techniques are suited to
their needs of the moment. Here the authors try to explain the potential
of forecasting to managers, focusing special attention on sales
forecasting for products of Corning Glass Works as these have matured
through the product life cycle. Also included is a rundown of
To handle the increasing variety and complexity of managerial
forecasting problems, many forecasting techniques have been developed in
recent years. Each has its special use, and care must be taken to
select the correct technique for a particular application. The manager
as well as the forecaster has a role to play in technique selection; and
the better they understand the range of forecasting possibilities, the
more likely it is that a company’s forecasting efforts will bear fruit.
The selection of a method depends on many factors—the context of the
forecast, the relevance and availability of historical data, the degree
of accuracy desirable, the time period to be forecast, the cost/ benefit
(or value) of the forecast to the company, and the time available for making the analysis.
These factors must be weighed constantly, and on a variety of levels.
In general, for example, the forecaster should choose a technique that
makes the best use of available data. If the forecaster can readily
apply one technique of acceptable accuracy, he or she should not try to
“gold plate” by using a more advanced technique that offers potentially
greater accuracy but that requires nonexistent information or
information that is costly to obtain. This kind of trade-off is
relatively easy to make, but others, as we shall see, require
considerably more thought.
Furthermore, where a company wishes to forecast with reference to a particular product, it must consider the stage of the product’s life cycle for which it is making the forecast.
The availability of data and the possibility of establishing
relationships between the factors depend directly on the maturity of a
product, and hence the life-cycle stage is a prime determinant of the
forecasting method to be used.
Our purpose here is to present an overview of this field by
discussing the way a company ought to approach a forecasting problem,
describing the methods available, and explaining how to match method to
problem. We shall illustrate the use of the various techniques from our
experience with them at Corning, and then close with our own forecast
for the future of forecasting.
Although we believe forecasting is still an art, we think that some
of the principles which we have learned through experience may be
helpful to others.
A manager generally assumes that when asking a forecaster to prepare a
specific projection, the request itself provides sufficient information
for the forecaster to go to work and do the job. This is almost never
Successful forecasting begins with a collaboration between the
manager and the forecaster, in which they work out answers to the
1. What is the purpose of the forecast—how is it to be used?
This determines the accuracy and power required of the techniques, and
hence governs selection. Deciding whether to enter a business may
require only a rather gross estimate of the size of the market, whereas a
forecast made for budgeting purposes should be quite accurate. The
appropriate techniques differ accordingly.
Again, if the forecast is to set a “standard” against which to
evaluate performance, the forecasting method should not take into
account special actions, such as promotions and other marketing devices,
since these are meant to change historical patterns and relationships
and hence form part of the “performance” to be evaluated.
Forecasts that simply sketch what the future will be like if a
company makes no significant changes in tactics and strategy are usually
not good enough for planning purposes. On the other hand, if management
wants a forecast of the effect that a certain marketing strategy under
debate will have on sales growth, then the technique must be
sophisticated enough to take explicit account of the special actions and
events the strategy entails.
Techniques vary in their costs, as well as in scope and accuracy. The
manager must fix the level of inaccuracy he or she can tolerate—in
other words, decide how his or her decision will vary, depending on the
range of accuracy of the forecast. This allows the forecaster to trade
off cost against the value of accuracy in choosing a technique.
For example, in production and inventory control, increased accuracy
is likely to lead to lower safety stocks. Here the manager and
forecaster must weigh the cost of a more sophisticated and more
expensive technique against potential savings in inventory costs.
Exhibit I shows how cost and accuracy increase with sophistication
and charts this against the corresponding cost of forecasting errors,
given some general assumptions. The most sophisticated technique that
can be economically justified is one that falls in the region where the
sum of the two costs is minimal.
Exhibit I Cost of Forecasting Versus Cost of Inaccuracy For a Medium-Range Forecast, Given Data Availability
Once the manager has defined the purpose of the forecast, the
forecaster can advise the manager on how often it could usefully be
produced. From a strategic point of view, they should discuss whether
the decision to be made on the basis of the forecast can be changed
later, if they find the forecast was inaccurate. If it can be
changed, they should then discuss the usefulness of installing a system
to track the accuracy of the forecast and the kind of tracking system
that is appropriate.