1. Alternatives to Sales Budgeting Process

2. Impact of Sales Forecasts on Budgeting Sales forecasts Sales budget Production budget Direct labor materials and overhead budgets Cost of goods sold budget Budgeted profit and loss statement Sales and administrative expense budget Revenue budget

3. Figure 7-2: Comparing Trend Forecasting Methods 1 2 3 4 5 0 10 20 30 40 50 Percent rate of change forecast Unit rate of change forecast Naïve forecast Moving average forecast Time Period Sales

4. Fitting a Trend Regression to Seasonally Adjusted Sales Data 0 1 2 3 4 5 6 50 60 70 80 90 63.9 3.6 Y = 63.9 + 3.5 X Sales Time Period

5. Forecasting with Moving Averages 123456 Actual sales4977907957 98 Seasonally adjusted sales6768788178 87 Two-period moving average forecast seasonally corrected78.370.158.0 89.8 Three-period moving average forecast seasonally corrected68.955.2 89.3 Two-period moving average forecastThree-period moving average forecast F 3 = ( S 1 + S 2 ) x I 3 F 4 = ( S 1 + S 2 + S 3 ) x I 4 2 3 = ( 67 + 68 ) x 1.16 = 78.3 = ( 67 + 68 + 78 ) x 0.97 = 68.9 2 3 Time Periods

6. 1 2 3 4 5 6 7 8 9 10 11 12 Relations Among Market Potential, Industry Sales, and Company Sales Company forecast Actual Forecast Custom time period Industry forecast Industry Sales Market potential Company potential Basic demand gap Company demand gap

7. Percentage Percentage of of FirmsPercentage of Firms that That Use Firms No MethodsUse Regularly Occasionally Longer Used Subjective Sales force composite 44.8% 17.2% 13.4% Jury of executive opinion 37.3 22.4 8.2 Intention to buy survey 16.4 10.4 18.7 Extrapolation Naïve 30.6 20.1 9.0 Moving Average 20.9 10.4 15.7 Percent rate of change 19.4 13.4 14.2 Leading indicators 18.7 17.2 11.2 Unit rate of change 15.7 9.7 18.7 Exponential smoothing 11.2 11.9 19.4 Line extension 6.0 13.4 20.9 Quantitative Multiple regressing 12.7 9.0 20.9 Econometric 11.9 9.0 19.4 Simple regression 6.0 13.4 20.1 Box-Jenkins 3.7 5.2 26.9 Utilization of Sales Forecasting Methods of 134 Firms

8. 2001 Effective2001 Total Buying IncomeRetail Sales Total Population Percentage Percentage Percentage Buying Amount of United Amount of United Amount of United Power ($000,000) States ($000,000) States (000) States Index Total United States $4,436,178 100.0% $2,241,319 100.0% 262,313 100.0% 100.0 Sacramento Metro 25,5720.5764% 12,414 0.5538% 1,482 0.5653% 0.5674 Data Used to Calculate Buying Power Index

9. (1) (2) Production Number of Machines Market NAIC Employees Used per 1000 Potential Code Industry (1000) Workers (1 x 2) 204 Grain milling 2.3 8 18.4 205 Bakery Products 11.9 10 119.0 208 Beverages 1.9 2 3.8 141.2 Estimating the Market Potential for Food Machinery in North Carolina

10. Calculating a Seasonal Index from Historical Sales Data Four-year Quarterly Seasonal Quarter 1 2 3 4 Average Index 149575373 58.0 0.73 2779885100 90.0 1.13 390899298 92.3 1.16 479628878 76.8 0.97 Four-year sales of 1268/16 = 79.25 average quarterly sales Year