Estimating the Market Demand

Michael R. Czinkota (), Masaaki Kotabe (), Demetris Vrontis () and S. M. Riad Shams ()
Additional contact information
Michael R. Czinkota: Georgetown University
Masaaki Kotabe: Waseda University
Demetris Vrontis: University of Nicosia
S. M. Riad Shams: Northumbria University

Chapter 6 in Marketing Management, 2021, pp 237-281 from Springer

Abstract: Abstract Forecasts predict what may happen, all other things being equal. Budgets go beyond these forecasts to incorporate the effects of an organization’s planned actions. Both may be Short term—For capacity loading, information transmission, and control Medium term—For the traditional annual planning process Long term—For strategic planning, resource planning, and communication Forecasts need to be dynamic. In other words, changes in the environment require modification of forecasts. From them, budgets may be derived at the sales, production, and profit levels. Forecasting is based on, and derived from, some other data sources; and it is conducted at three different levels. Macroforecasts look at total markets and may be derived from national or global data available from the OECD or the US government. However, the most important aggregate forecast for business is at the market or industry level. Microforecasts build on the predictions of individual or group (customer) behavior. Product forecasts may then be split into forecasts by product type and over time. There are both qualitative and quantitative forecasting methods. Qualitative forecasting is normally employed for long-term forecasts. Techniques include expert opinion, expert panel method, technological forecasting, Delphi technique, decision tree, and scenario. Quantitative forecasting techniques for the short and medium term typically try to isolate the trend, cyclical, seasonal, and random fluctuations. The specific techniques used may be period actuals and percent changes, exponential smoothing, time-series analyses, multiple regression analysis, and more complex econometric modeling. Various leading indicators are also readily available from government sources to forecast the short- to medium-term conditions of the market. Although most forecasting techniques ignore the competitors’ possible reaction to one company’s competitive move, game theory has been gaining popularity in recent years to address the likely impact of the competitors’ moves in forecasting. With the widespread use of personal computers, spreadsheets have become a useful forecasting tool to model many hypothetical “what if” scenarios. By developing many scenarios, you can determine which factors are sensitive to changes in the conditions under investigation. The primary role of forecasting is risk reduction. You should note that risk can also be reduced by purchasing insurance against unfavorable events, diversifying into a portfolio of different products and markets, or adopting flexible manufacturing to better cope with unexpected changes in the market. Finally, thanks to internet use, many companies, emphasizing the needs of customers with an ability to satisfy and serve them quickly and efficiently, have begun to adopt the “build to order” model of sales fulfillment with no forecasting error rather than the traditional “build to forecast” model.

Date: 2021
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DOI: 10.1007/978-3-030-66916-4_6

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