Sales Management 8

1. Sales Management 8 Estimating Demand

2. Market Potential Sales Industry Forecast (Industry Forecast ≤ Market Potential) (Company Forecast ≤ Company Potential) Company Potential Company Forecast 0 Time

3. Key Terms • Market Potential: All possible ______ • Industry Forecast: Likely _________, all companies • Company Potential: All possible _________for one company • Company Sales Forecast: Likely company _________ NB: All figures are expressed for a period of ___.

4. So how do you estimate demand? • Determine WHO will use the product. • Which segment(s)?; Size? • Determine their RATE of use. • New/Replacement; Frequency. • WHO buys product? • Purchasing agent, parent, lover, uncle • WHAT is their motivation to purchase? • Life event, new business, new market, fun

5. Why Forecast Sales? • Allocate _________ • Control _________ • Project Cash Flow (Important!) • Capital/operating budgets • Production schedules & _________control • Hiring; collective _________ • Planning marketing and sales plans

6. Methods of Forecasting • Subjective • Users’ Expectations • Sales Force Composite • Jury of Executive Opinion • Delphi Technique

7. Users’ Expectations • Also called Buyers’ _________method • __________________ • _________ • Intention ≠ Behavior, but does correlate

8. Sales Force Composite • Salespeople are _________ • Close to customers, competitors • Fingers on the pulse of the market • Survey sales force, and add up estimates • Good starting point; need adjustment

9. Jury of Executive Opinion • Top/key _________, perhaps outside consultants, give best estimate • Not boundary spanners, but see “Big Picture” • May need discussion to reach an estimate that everyone can agree on

10. Delphi Technique • Similar to Executive Opinion • _________Process • _________

11. Methods of Forecasting • Objective • Market Test • Time Series Analysis • Moving Averages • Exponential Smoothing • Decomposition • Statistical Demand Analysis

12. Test Market • Pick “_________” city • Full marketing effort • _________results to rest of nation Disadvantages: • _________ • _________ • _________ • _________

13. Time Series Analysis • Use historical (not hysterical) data to predict future • Like driving by looking in the rear-view mirror • Estimate starts in “ballpark” (not the franks)

14. Moving Averages • Average last n (=2,4, whatever) years sales to predict the coming year 2000: 5,000 units 2001: 8,000 units 2002: 6,500 units estimated

15. Decomposition • Apply to monthly or quarterly data • Account for: • _________ • _________ • _________ • _________

16. Statistical Demand Analysis • Use regression or other techniques to determine relationship between sales and predictor factors. • Need good data and analytical skills. • Example: • Home heating oil demand = Function of temperature, sun, last fill, tank size, & history.

17. What do companies use? • They tend to rely more heavily on qualitative than quantitative. • Especially sales force composite and jury of executive opinion. • Easier, quicker, perhaps accurate enough

18. Sales Territories • Design territories • Need a market index to compare • Industrial Goods • Standard Industrial Classification • North American Industrial Classification System • Consumer goods • Buying Power Index = (5I + 2P + 3R)/10 • % disposable personal Income • % US Population • % total Retail sales