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Sales Forecasting

Sales Forecasting. Professor Lawrence Feick University of Pittsburgh. Forecasting . Forecasting is difficult, especially about the future. Victor Borge I know of no way of judging of the future but by the past. Patrick Henry

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Sales Forecasting

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  1. Sales Forecasting Professor Lawrence Feick University of Pittsburgh

  2. Forecasting • Forecasting is difficult, especially about the future. Victor Borge • I know of no way of judging of the future but by the past. Patrick Henry • Forecasting is like trying to drive a car blindfolded and following directions given by a person who is looking out the back window. Anonymous

  3. Outline • Sales forecasting: what and why? • Tools for sales forecasting • judgmental methods • market methods • quantitative methods

  4. Sales forecasting: what and why? • Estimating future sales • Important for planning about: • production • marketing and sales • financing • human resources • support • etc.

  5. Tools for sales forecasting • Judgmental methods • expert opinion: executives, analysts, sales force • Market methods • customer opinion (surveys) • customer behavior (test markets) • Quantitative • trend projection • explanatory models

  6. Judgmental methods for forecasting • Rely on knowledgeable individuals to provide estimate • Often uses firm’s executives and salespeople or industry analysts • Opinions combined with Delphi or other techniques

  7. Judgmental methods for forecasting • Rely on knowledgeable individuals to provide estimate • Often uses firm’s executives and salespeople or industry analysts • Opinions combined with Delphi or other techniques

  8. Market methods for forecasting • Surveys of customers/potential customers • interest in product concept • intention to buy • Test markets • marketing of product in limited geographic area

  9. Quantitative methods for forecasting: trend projection • Use sales history and time period to predict future sales • Example model • Ft+1 = St + b(St - St-1 ) + c (St-1 - St-2 ) +...

  10. Trend projection:Example 1

  11. Trend projection:Example 2

  12. Trend projection: issues • Change in trend: weight more recent sales more heavily to account for recent history (e.g., exponential smoothing) • Systematic variation: build seasonal variation or business cycle variation into model

  13. Quantitative forecasting:explanatory models • Develop a model with predictors of sales • Find past relationship of sales to predictors, usually using multiple regression • Use expected future values of predictors to compute expected sales • Example: forecasting year-to-year Pirates attendance

  14. Pirates forecasting: year to year • Example predictors of attendance: • winning percentage during the year • winning percentage in previous year • number of all stars on team • others? • Use regression to estimate historical relationship of predictors to attendance

  15. Questions • Predictors in forecasting Pirates attendance game-to-game? • Predictors in forecasting sales of Coke month-to-month?

  16. Explanatory models: issues • Choice of predictors: • must make sense given the time period being forecast (day, month, quarter, year) • must be strongly related to product sales to have reliable forecasts • Future values of predictors: • results depend on good estimates of future values of predictor variables

  17. Summary • Judgmental methods • Market methods • Quantitative methods

  18. The bottom line • Forecasting is a critical tool • Forecasting is an art and science • Most companies use multiple techniques

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