2. C HAPTER 5 F ORECASTING M ARKET D EMAND AND S ALES B UDGETS

4. M ANAGING S ALES I NFORMATION “Our charge is to design, build, and implement decision support systems that help our field and marketing managers make business decisions.” Dan McKee Marketing decision support systems manager for Marion Merrell Dow, Inc.

5. F ORECASTING M ARKET D EMAND A marketing decision support system (MDSS) is an ongoing, future-oriented structure designed to generate, process, store, and later retrieve information to aid decision making in an organization’s marketing program. It involves problem-solving technology composed of people, knowledge, software, and hardware “wired” into the sales management process.

6. U SES OF S ALES F ORECASTS A sales forecast is the estimated dollar or unit sales for a specific future time period based on a proposed marketing plan and an assumed market environment.

8. FIGURE 5.1 PLANNING/FORECASTING/BUDGETING SEQUENCE

9. T HE F ORECASTING P ROCESS The forecasting process refers to a series of procedures used to forecast.

10. A market factor is an item or element that (1) exists in a market, (2) may be measured quantitatively, and (3) is related to the demand for a product or service. A market index is simply a market factor expressed as a percentage relative to some base figure.

11. FIGURE 5.2 THE FORECASTING PROCESS

12. FIGURE 5.3 BASIC STEPS IN BREAKDOWN METHOD OF FORECASTING SALES

13. Company sales potential is the maximum estimated or potential sales the company may reach in a defined time period under given conditions. The company’s share of the estimated sales for an entire industry is referred to as market share. Industry sales forecast, or market potential, is the estimated sales for all sellers.

15. FIGURE 5.4 THE MORE POPULAR OF MANY FORECASTING METHODS

19. Delphi Method Administering a series of questionnaires to panels of experts.

20. Sales Force Composite Obtaining the opinions of sales personnel concerning future sales.

21. User’s Expectations Consumer and industrial companies often poll their actual or potential customers.

22. Build-to-Order Companies build final products only after firm orders are placed.

23. M ATHEMATICAL F ORECASTING M ETHODS Test markets are a popular method of measuring consumer acceptance of new products.

24. FIGURE 5.5 CITIES COMMONLY USED AS TEST MARKETS – RESIDENTS ARE MOST LIKELY TO SEE NEW PRODUCTS .

25. Time Series Projections Time series methods use chronologically ordered raw data.

27. Naïve Method Next Year’s Sales = This Year’s Sales X This Year’s Sales Last Year’s Sales

28. Moving Average Moving averages are used to allow for marketplace factors changing at different rates and at different times.

29. TABLE 5.1 EXAMPLE OF MOVING-AVERAGE FORECAST Period 6 Forecast = 366.6 ? 6 366.6 1100 ( 3) = 450 5 300 900 350 4 750 300 3 250 2 200 1 T HREE- Y EAR M OVING A VERAGE S ALES FOR THREE- Y EAR P ERIOD S ALES V OLUME P ERIOD

30. E xponential S moothing Exponential smoothing is similar to the moving-average forecasting method. It allows consideration of all past data, but less weight is placed on data as it ages. Next Year’s Sales = a (This Year’s Sales) + (1- a ) (This Year’s Forecast)

31. Trend Projections – Least Squares Eyeball fitting is simply a plot of the data with a line drawn through them that the forecaster feels most accurately fits the linear trend of the data.

32. FIGURE 5.6 A TREND FORECAST OF SALES

33. Regression Analysis Regression analysis is a statistical method used to incorporate independent factors that are thought to influence sales into the forecasting procedure.

34. FIGURE 5.7 REGRESSION ANALYSIS

35. FIGURE 5.8 QUESTIONS TO ANSWER TO IMPROVE CHANCES OF HITTING THE FORECASTING BULL’S-EYE

36. TABLE 5.2 GUIDE TO FORECASTING Accurate if variable relationships stable Essential Needed Short to Medium Regression Analysis Varies widely Desirable Needed Short to long Least Squares Accurate under stable conditions Helpful Minimal Short to medium Exponential Smoothing Accurate under stable conditions Helpful Minimal Short to long Moving Average Limited Not essential Minimal Present to medium Naïve Method Accurate Needed Needed Medium Test Markets Limited Not essential Minimal Short to medium User’s Expectations Accurate under dynamic conditions Not essential Minimal Short to medium Sales Force Composite Limited; good in dynamic conditions Not essential Minimal Medium to long Delphi Method Limited Not essential Minimal Short to medium Executive Opinion A CCURACY C OMPUTER N EED M ATHEMATICAL S OPHISTICATION T IME S PAN F ORCASTING M ETHOD

37. T HE S ALES M ANGAGER’S B UDGET The sales force budget is the amount of money available or assigned for a definite period, usually one year.

39. TABLE 5.3 SALES FORCE OPERATING COSTS d. Hospitalization c. Stock options 10. Travel b. Retirement plan 9. Entertainment a. Social Security 8. Transportation expenses 3. Other compensation 7. Selling aids 2. Commissions 6. Product samples b. Salespeople 5. Office expenses a. Management 4. Special incentives 1. Base salaries

40. B UDGETS S HOULD BE F LEXIBLE Sales, costs, prices, or the competition’s marketing efforts are some factors that may be higher or lower than expected.

41. T HE B OTTOM L INE Because of the growing trend in business to centralize data collections, the job of forecasting has become an integral part of a firm’s marketing decision support system (MDSS). A sales forecast is the estimated dollar or unit sales for a specific future period based on a proposed marketing plan and an assumed market environment. Firms know sales forecasting is never 100 percent correct. Two categories of sales forecasting methods are survey methods and mathematical methods. Because the sales forecast has a major impact on the company, the top executives give final approval. To create a sales forecast, sales managers should know how to use a computer.