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 Sales forecasting Presented by VrushaliDhanore
Definition  Sales forecasting is the process of estimating  what your business sales are going to be in the future  Estimate of the number of sales on rupees or physical units, in a future period under a particular marketing program and an assumed set of economic conditions and other external factor Purpose –to provide information to make important decisions Helps marketer ,[object Object]
Allocate market resources
Monitor  the competition,[object Object]
Uses of forecasting Production department -  for production planning and coordination with the sales team Purchase department - to plan its purchases in advance HR department - for its manpower planning The accounting department - to plan for future cash flow well as for new equipment needed R&D  - to make innovations in advance Marketers  - to plan their activity accordingly in coordination with the sales team
Techniques of sales forecasting Qualitative Jury of executive opinion Customer / channel /user survey Executive opinion Delphi Test marketing Quantitative Time Series Moving averages Exponential smoothing Causal Regression analysis Multiple Regression
Jury of executive opinion  Jury of Executive Opinion  There are two steps in this method: High ranking executives estimate probable sales An average estimate  The assumption is that the executives are well informed about the industry outlook and the company’s market position, capabilities and marketing program
Benefits  of Jury of executive opinion  Quick and easy method Pools opinion of experienced, well informed people For a young company, it may be the only way When statistics are missing, there can be no other option
Delphi Method ,[object Object]
Thus information disseminated to all, enabling all to base their final forecasts on “all available” information,[object Object]
Projection of past sales  Set the sales forecast as per past growth trend; which can be the previous year or to a moving average It would be more appropriate for industries where growth rates are relatively stable Next year’s sale= This year’s sales/ Last year’s sales
Time- series analysis ,[object Object]
Trends(T) is the gradual upward or downward movement of the data over time
Seasonality(s) is a pattern of the demand fluctuation above or below the trend line
Cycles (c) are patterns in annual data occur every several years
Random variation (R) “blips” in data caused by change and unusual situations    multiplicative model    Demand=T*S*C*R     Additive model            Demand=T+S+C+R
Moving averages technique Moving averages are useful if we can assume that market demands will stay fairly steady over time    moving average forecast= sum of demands in previous n periods / n
Weighted moving average Weights are used to give more values to recent values This makes the techniques more responsive to changes because latter  periods may be more heavily waited
Weights Applied period 3 Last month ago 2 Two month ago Three month ago 1 1 3 2 *Sales three month ago *sales last month + *Sales Two month ago + 6 Sum of the weights

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Sales Forecasting Vrushali

  • 1. Sales forecasting Presented by VrushaliDhanore
  • 2.
  • 4.
  • 5. Uses of forecasting Production department - for production planning and coordination with the sales team Purchase department - to plan its purchases in advance HR department - for its manpower planning The accounting department - to plan for future cash flow well as for new equipment needed R&D - to make innovations in advance Marketers - to plan their activity accordingly in coordination with the sales team
  • 6. Techniques of sales forecasting Qualitative Jury of executive opinion Customer / channel /user survey Executive opinion Delphi Test marketing Quantitative Time Series Moving averages Exponential smoothing Causal Regression analysis Multiple Regression
  • 7. Jury of executive opinion Jury of Executive Opinion There are two steps in this method: High ranking executives estimate probable sales An average estimate The assumption is that the executives are well informed about the industry outlook and the company’s market position, capabilities and marketing program
  • 8. Benefits of Jury of executive opinion Quick and easy method Pools opinion of experienced, well informed people For a young company, it may be the only way When statistics are missing, there can be no other option
  • 9.
  • 10.
  • 11. Projection of past sales Set the sales forecast as per past growth trend; which can be the previous year or to a moving average It would be more appropriate for industries where growth rates are relatively stable Next year’s sale= This year’s sales/ Last year’s sales
  • 12.
  • 13. Trends(T) is the gradual upward or downward movement of the data over time
  • 14. Seasonality(s) is a pattern of the demand fluctuation above or below the trend line
  • 15. Cycles (c) are patterns in annual data occur every several years
  • 16. Random variation (R) “blips” in data caused by change and unusual situations multiplicative model Demand=T*S*C*R Additive model Demand=T+S+C+R
  • 17. Moving averages technique Moving averages are useful if we can assume that market demands will stay fairly steady over time moving average forecast= sum of demands in previous n periods / n
  • 18. Weighted moving average Weights are used to give more values to recent values This makes the techniques more responsive to changes because latter periods may be more heavily waited
  • 19. Weights Applied period 3 Last month ago 2 Two month ago Three month ago 1 1 3 2 *Sales three month ago *sales last month + *Sales Two month ago + 6 Sum of the weights
  • 20.
  • 21.
  • 22.
  • 23.
  • 24. Every forecast contains elements of uncertainty
  • 25. All are based on assumptions so a first step in evaluating a sales forecast is to examine the assumptions
  • 26. Sales executives should evaluate the accuracy and economic value of the forecast as the forecast period advances
  • 27.