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Forecasts are either short- to mid-range, or long-range. Short-range (to mid-range) forecasts are typically for daily, weekly, or monthly sales demand for up to approximately two years into the future, depending on the company and the type of industry. They are primarily used to determine production and delivery schedules and to establish inventory levels. At Hewlett-Packard monthly forecasts for printers are constructed from 12 to 18 months into the future, while at Levi Strauss weekly forecasts for jeans are prepared for five years into the future.

A long-range forecast is usually for a period longer than two years into the future. A long-range forecast is normally used for strategic planning—to establish long-term goals, plan new products for changing markets, enter new markets, develop new facilities, develop technology, design the supply chain, and implement strategic programs. At Unisys, long-range strategic forecasts project three years into the future; Hewlett-Packard’s long-term forecasts are developed for years 2 through 6; and at Fiat, the Italian automaker, strategic plans for new and continuing products go 10 years into the future.

These classifications are generalizations. The line between short- and long-range forecasts is not always distinct. For some companies a short-range forecast can be several years, and for other firms a long-range forecast can be in terms of months. The length of a forecast depends a lot on how rapidly the product market changes and how susceptible the market is to technological changes.

Demand sometimes behaves in a random, irregular way. At other times it exhibits predictable behavior, with trends or repetitive patterns, which the forecast may reflect. The three types of demand behavior are trends, cycles, and seasonal patterns.

A trend is a gradual, long-term up or down movement of demand. For example, the demand for houses has followed an upward trend during the past few decades, without any sustained downward movement in the market. Trends are often the starting points for developing forecasts. Figure 12.2 (a) illustrates a demand trend in which there is a general upward movement, or increase. Notice that Figure 12.2(a) also includes several random movements up and down. Random variations are movements that are not predictable and follow no pattern (and thus are virtually unpredictable). They are routine variations that have no “assignable” cause.

A cycle is an up-and-down movement in demand that repeats itself over a lengthy time span (i.e., more than a year). For example, new housing starts and, thus, construction-related products tend to follow cycles in the economy. Automobile sales also tend to follow cycles. The demand for winter sports equipment increases every four years before and after the Winter Olympics.Figure 12.2(b) shows the behavior of a demand cycle.

A seasonal pattern is an oscillating movement in demand that occurs periodically (in the short run) and is repetitive. Seasonality is often weather-related. For example, every winter the demand for snowblowers and skis increases, and retail sales in general increase during the holiday season. However, a seasonal pattern can occur on a daily or weekly basis. For example, some restaurants are busier at lunch than at dinner, and shopping mall stores and theaters tend to have higher demand on weekends. At FedEx seasonalities include the month of the year, day of the week, and day of the month, as well as various holidays. Figure 12.2c illustrates a seasonal pattern in which the same demand behavior is repeated each year at the same time.

Demand behavior frequently displays several of these characteristics simultaneously. Although housing starts display cyclical behavior, there has been an upward trend in new house construction over the years. Demand for skis is seasonal; however, there has been an upward trend in the demand for winter sports equipment during the past two decades. Figure 12.2d displays the combination of two demand patterns, a trend with a seasonal pattern.

Instances when demand behavior exhibits no pattern are referred to as irregular movements, or variations. For example, a local flood might cause a momentary increase in carpet demand, or a competitor’s promotional campaign might cause a company’s product demand to drop for a time. Although this behavior has a cause and, thus, is not totally random, it still does not follow a pattern that can be reflected in a forecast.

The factors discussed previously in this section determine to a certain extent the type of forecasting method that can or should be used. In this chapter we are going to discuss three basic types of forecasting: time series methods, regression methods, andqualitative methods.

Types of methods: time series, causal, and qualitative.

Time series methods are statistical techniques that use historical demand data to predict future demand. Regression (or causal)forecasting methods attempt to develop a mathematical relationship (in the form of a regression model) between demand and factors that cause it to behave the way it does. Most of the remainder of this chapter will be about time series and regression forecasting methods. In this section we will focus our discussion on qualitative forecasting.

Qualitative (or judgmental) methods use management judgment, expertise, and opinion to make forecasts. Often called “the jury of executive opinion,” they are the most common type of forecasting method for the long-term strategic planning process. There are normally individuals or groups within an organization whose judgments and opinions regarding the future are as valid or more valid than those of outside experts or other structured approaches. Top managers are the key group involved in the development of forecasts for strategic plans. They are generally most familiar with their firms’ own capabilities and resources and the markets for their products.

Management, marketing and purchasing, and engineering are sources for internal qualitative forecasts.

The sales force of a company represents a direct point of contact with the consumer. This contact provides an awareness of consumer expectations in the future that others may not possess. Engineering personnel have an innate understanding of the technological aspects of the type of products that might be feasible and likely in the future.

Consumer, or market, research is an organized approach using surveys and other research techniques to determine what products and services customers want and will purchase, and to identify new markets and sources of customers. Consumer and market research is normally conducted by the marketing department within an organization, by industry organizations and groups, and by private marketing or consulting firms. Although market research can provide accurate and useful forecasts of product demand, it must be skillfully and correctly conducted, and it can be expensive.

The Delphi method is a procedure for acquiring informed judgments and opinions from knowledgeable individuals using a series of questionnaires to develop a consensus forecast about what will occur in the future. It was developed at the Rand Corporation shortly after World War II to forecast the impact of a hypothetical nuclear attack on the United States. Although the Delphi method has been used for a variety of applications, forecasting has been one of its primary uses. It has been especially useful for forecasting technological change and advances.

Technological forecasting has become increasingly crucial to compete in the modern international business environment. New enhanced computer technology, new production methods, and advanced machinery and equipment are constantly being made available to companies. These advances enable them to introduce more new products into the marketplace faster than ever before. The companies that succeed manage to get a “technological” jump on their competitors byaccurately predicting what technology will be available in the future and how it can be exploited. What new products and services will be technologically feasible, when they can be introduced, and what their demand will be are questions about the future for which answers cannot be predicted from historical data. Instead, the informed opinion and judgment of experts are necessary to make these types of single, long-term forecasts.

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