Demand Forecasting and Aggregate Planning in Supply Chains

Business forecasting, by professional and business man alike, is too frequently a guessing game. Even when forecasters agree, they are apt to reach their common conclusion by different methods and for different reasons. And when they happen to be right, they are frequently right because of reasons or conditions they did not anticipate. These critical observations are written with no disparaging or pharisaical implications. These difficulties are inherent in the art and beset everyone who attempts to move ahead of time and to pierce the veil that shrouds the future. There is no infallible forecasting system.

Unorganized business forecasting is usually the product of personal judgment or intuition or, sometimes, only a subconscious feeling for the course of future events. It is more art than science, and it will remain in this unsatisfactory state until its methods can be brought into the realm of the rational and can be based on logical relationships that govern business behaviour and can be stated in measurable terms. General progress in forecasting will come only with the wider understanding and application of the common-sense economic principles that govern the fluctuations of aggregate national income, production, and prices.

This wider understanding is one of the objectives of this volume. It is hoped that this study will bring to the businessman and to other students of forecasting an understanding of some of these principles and their application to business forecasting. In order to fulfil this task, more pages will be devoted to theory than the reader may, at first thought, be prepared to welcome. However, it is necessary discipline, and it is hoped the reader will be prepared by this warning and will not be too impatient (Pindyck, & Rubinfield, 1998).

Notwithstanding the unsatisfactory state of forecasting as usually practiced in business, forecasting, by some method or other, is necessary and is as inescapable in business life as breathing and digestion are in physical life. Characteristics of forecasts Every successful business concern–Big Steel or the corner grocery–must anticipate the needs of its customers, the demand for its products, the prices it must pay, and the prices it will be able to collect. Business forecasting of these involuntary kind needs no advocate, requires no justification, and like other arts permits of few generalizations.

Its successful practitioners develop a sixth sense of impending events, a feel of the market drawn from day-to-day experience. A few forecasters of this psychic type may be highly successful, but why they are successful or how they reach their conclusions they can explain no more than they explain the involuntary processes of their healthy digestions. But this subconscious psychic kind of forecasting is scarcely possible for the vast majority of businessmen. If men lacking this sixth sense depend upon it, forecasting becomes less than an art, is practiced without organized knowledge and with little personal skill.

It degenerates into a feeling, a hunch, a guess without reason or the possibility of explanation, although the forecaster likes to think of his conclusion as a considered opinion based on good judgment and mature experience (Gunther, & Schoemaker, 2002). The point that should be mentally underscored is that the businessman will forecast in one way or another; he cannot escape forecasting while he remains responsible for a business enterprise. The question every executive faces is not whether he will forecast but, rather, how he will forecast.

The businessman can forecast by hunch or by intuition or by judgment (if he prefers to call it so), or he can bring the forecasting activities of his enterprise within the more definite and tangible boundaries of an organized management function and with as solid a foundation of scientific principle and method as the status of this difficult art permits. His forecasting can be without plan and without organization, or it can be made a recognized function of scientific management. How good should forecasting be to be acceptable?

Some top business executives believe in holding out for the impossible standard of completely correct forecasts–for 100 per cent hits–without really expecting any such performance. Actually no other single figure which places a maximum limit on error is reasonable because permissible limits of error should change with the conditions under which the forecast is made. Two or three per cent error may represent poor forecasting in a stable industry in times of high personal income and customer demand.

Ten per cent error may be good forecasting in an industry which fluctuates widely, and when customer demand is declining. High per cent accuracy is easier to attain in sellers’ markets than in buyers’ markets (Gunther, & Schoemaker, 2002). Then in some situations a qualitative forecast is all that is needed. The prediction of the direction of business trend–up or down or level-may meets the requirements of the business executive. The broad test for good forecasting is whether or not it leads to correct management decisions. Components of a forecast and forecasting methods

Forecasters may also go too far in the use of elaborate mathematical and statistical procedures that are not justified by the inexactness of the data that forecasters frequently are compelled to use. There is a golden common-sense mean between pure guessing and too much mathematics. Even though many business executives do not think too highly of forecasting as it is usually performed, there are at least two reasons why they should take the practice of forecasting seriously. In the first place, forecasting is a part of business management from which there is no escape, as has been pointed out.

Forecasting will be done in one way or another. If it is not approached as a management function to be organized along scientific lines to the extent that the scientific approach can be used, then the unavoidable forecasting will be done by guess and by feel. The second reason why businessmen should tackle forecasting seriously is that, except for the rare forecasting genius, any organized plan is better than no plan. No matter how simple and elementary an organized forecasting plan may be, it is better than 100 per cent judgment or hunch or guesswork.

However inadequate and disappointing the results from organized forecasting may seem, they are still better than the usual results of unorganized guessing (Morris, & Siegel, 1993). It is the part of wisdom to recognize the inadequacies of available forecasting procedures and results. It is also wise for management to recognize the importance of forecasting as a function of management and to do what can be done to increase understanding of its underlying principles, to organize pertinent information concerning past experience and current events, and to improve forecasting procedures.

There are a number of fairly obvious reasons why good forecasting is an important part of good management. There can be no intelligent or effective planning for a business enterprise without the preliminary step of forecasting. The planned objectives of management can be realized only when there is a reasonably accurate forecast of the trend of general business and of the sales income of the specific company. The businessman cannot act on the spur of the moment.

Successful management requires that the businessman look ahead and make plans. In short, he must plan, and he must forecast in order that he can plan. Successful budgeting of expenses, costs, and profits depends on good forecasting of sales income. Some well-conceived and executed budget plans have failed and have been discarded because they were not backed up by good sales forecasts. A forecast of annual sales and prices is the necessary foundation of the control of a business through a budgetary program (Siegel, & Shim, 1991).

Successful forecasting reduces the area of avoidable risk. Forecasting will seldom, if ever, be without some error, but forecasting can limit the area in which assumption and judgment must be the only guide. Good forecasting can help stabilize production and employment over the year by ironing out variations caused by seasonal fluctuations of sales. Steady employment can mean better labour and community relations, lower employee turnover, and lower labour costs.

Better forecasting will be needed by managements to deal successfully with the growing rigidities of labour costs and other problems brought about by the demand by organized labour and by public opinion for greater security of employment in manufacturing industries. Guaranteed annual wages, employee seniority, transferable pension rights, and severance pay may so increase the costs of high employee turnover–of hiring and firing–that it will become necessary for management to plan future expansions more carefully (Siegel, & Shim, 1991).

No management in a volatile, feast-or-famine industry can handle this explosive problem unless the management has developed a dependable sales-forecasting procedure–a procedure that will provide correct trends of sales and employment not only for one year but for several years. The satisfactory and safe solution of this important problem of job security awaits the attainment of more dependable results in forecasting and planning long-term company growth.

Satisfactory control of inventories of all kinds–raw materials, component parts, semifinished materials, work in process, and finished goods–is dependent on satisfactory forecasts of future sales, of raw-material and parts requirements, of raw-material and parts prices. The traditional methods of inventory control, which are based on past activity alone, inevitably lead to losses. Control based only on past activity leads to loss of possible sales and competitive position when market demand increases unexpectedly and to direct money loss when market demand suddenly declines.

Successful planning of long-term investment programs of new mills and other facilities and of corresponding new capital requirements depends on reasonably accurate long-term forecasting of sales. An even rate of investment expenditures, as will be shown, is the first step in the stabilization of aggregate employment over the business cycle. The successful use of standard cost systems for cost and expense control and for satisfactory pricing of products depends on good long-term forecasting of sales and production volume.

The successful use of standard costs depends on the selection of a good normal volume of production that is neither too high nor too low. The setting of a high normal volume results in consistently unabsorbed expense, high variances, low standard costs, and the danger of establishing market prices that are below real costs. A low normal results in over-absorption of expense, high standard costs, and market prices that may be unnecessarily high (Smaghi, Lorenzo, & Casini, 2000). Basic approach to demand forecasting

These are some of the ways by which better forecasting can help produce successful planning and control of operations and contribute to better over-all management. Good planning depends on good forecasting. There would be no difficulty in convincing business executives of the importance of forecasting as an organized management function if direct dependable answers to the executives’ problems in this field were always forthcoming. Unfortunately in this world there is no way to see clearly and with certainty what lies ahead.

The best that can be managed is an indirect approach: to attempt to understand the causes of impending events and to anticipate their coming or to analyze past experience and behaviour so that it can be safely projected some little way beyond the present (Press, 1996). The first of these approaches requires the understanding of various economic principles and relationships that affect business behaviour and the direct measurement of the factors and forces that determine business activity, such as the size of customer demand and the availability of funds to make that demand effective.

It is completely scientific and rational in that it depends on the development and understanding of general principles and on the measurement of necessary data. This approach fails in being a complete solution only because we are dealing, in considerable measure, with human behaviour which may not be rational and because we cannot determine or measure all the necessary factors. The second of these approaches supplements the first and attempts to bridge over its deficiencies. This method of organizing past experience and projecting it into the future assumes that all other conditions of the past remain the same in the future.

It is a safe method only to the extent that this rash assumption may be true. This general approach includes the determination and extension of trend lines of growth, of seasonal fluctuations, and of longer cyclical movements of the business cycle. It also includes the determination of past empirical relationships or correlations between the quantity being forecasted and other quantities that are more readily measured or estimated such as the relationship that exists between department-store sales (or of any single product) and total available consumer income.

This method of analyzing past behaviour and relationships and of assuming that this past experience can be usefully projected into the future is frequently frowned upon; nevertheless it is quite generally used. The method can be used safely and successfully if it is used with intelligence and with good judgment. But it has been used frequently and on notable occasions without good judgment and with too little experience.

The possible improvement of forecasting methods and the increase in accuracy and dependability of forecasts lie very largely in these two directions: in the discovery and scientific use of general principles and factual measurement and in the systematic analysis, organization, and projection of past experience (Heilbroner, Thurow, 1994). Forecasting in practice It is true and should be recognized that forecasting organized as a separate management function is not equally necessary in all industries or in all companies.

The difficulties of achieving good forecasting and the benefits to be derived from it vary widely with different businesses. Each company has a unique problem which only the management of the company can solve satisfactorily. There is no universal plan. There are, for example, many small business enterprises that may not need organized forecasting. A concern small enough, or with operations simple enough, so that its operations can be planned and controlled by one chief executive will usually depend on this one man’s foresight and ability for its success.

Forecasting in such a concern is likely to be the intuitive or subconscious kind. But as a business grows in size and complexity beyond the physical and mental powers of one man, then organized forecasting should become a separately organized function of management. Organized forecasting becomes more necessary and pays larger dividends as a company increases in size, in the variety of products it handles, in the number of different markets it supplies, and in the extent of its decentralization of management (Smaghi, Lorenzo, & Casini, 2000).

Some processors of staple foods, for example, are affected only to a minor extent by fluctuations in general business. Consumption of food per person remains much the same from year to year, and the growth of a specific company depends mainly on the energy and skill of its management and more directly on the skillful, aggressive sales promotion of its products. In other industries of the feast-or-famine kind, sales volume from one year to the next may be determined by general business conditions, regardless of sales-promotion campaigns.

Companies that deal with new and rapidly growing products and whose major sales problems are the creation of markets for new products, usually have little interest in the state of general business. Their sales may be made to increase by creative selling against the general business trend. Such company managements are prone to underestimate the importance of general business conditions and to exaggerate their own independence of these conditions. They are apt to be right in their ability to control their sales volume until their new product grows in importance and becomes an established product with substantial market acceptance.

Success under these circumstances is the forerunner of trouble. A company manufacturing mechanical refrigerators, for example, could not be convinced that its sales volume in 1938 would be lower than sales in 1937 even though general business had started to decline in the fall of 1937. Mechanical refrigerators were a new product during the early 1930’s, and sales had increased each year all through the depression. But by 1937 the market for refriger ators had become sufficiently saturated so that it fluctuated with other established industries and durable products (Heilbroner, Thurow, 1994).

Organized forecasting takes on added importance to industries and companies with long production processes and where raw materials are subject to wide fluctuations in price. The risks of doing business increase with the length of the cycle from commitment of funds for raw materials to the sale of the finished product. Tire manufacturers, because of the raw rubber situation, and soap manufacturers, because of their use of imported fats and oils, have to hold large inventories of these raw materials. They are vitally interested in following supply and demand factors affecting the prices of these materials.

Meatpacking companies’ major interest in forecasting is also in the prospective supplies and prices of their raw materials–cattle, sheep, and hogs. Companies that are important users of copper, such as the larger electrical manufacturing companies, find it advisable to study supply and demand conditions and their probable effect on the future price of copper. It is necessary only to remember the many uses of forecasting and the close ties between forecasting and planning to realize the extensive ramifications of forecasting throughout the operations of a large corporation.

Good forecasting requires team play, the best possible coordination among many departments: general business research and market research, sales, accounting, treasury, production planning (another coordinating activity), and line production. Good forecasting and planning will not come if each of these several departments works independently. Poor results are sometimes the result of too much emphasis on a departmental objective instead of a wiser emphasis on a company objective (Spiegel, 1994).

Organized forecasting, where it is justified by the conditions, should lead to the development of a logical structure of forecasts and budgets. The foundation of this structure is the forecast of general business conditions wherever the volume of the single company sales is strongly affected by general business conditions. On this foundation the company sales forecast is erected. The sales forecast, in turn, becomes the support of the complete superstructure of financial forecasts and budgets and also of production forecasts and schedules with their array of employment, purchasing, and inventory plans and schedules.

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