This document discusses sales forecasting techniques. It begins with an introduction to sales forecasting and its importance for setting sales quotas and budgets. It then covers qualitative and quantitative forecasting methods. Qualitative methods include jury of executive opinion, Delphi technique, sales force composite, and buyer surveys. Quantitative methods include continuity extrapolation, time series analysis, exponential smoothing, regression analysis, and econometric models. The document emphasizes that both qualitative and quantitative methods are useful for sales forecasting. It concludes that proper demand forecasting enables better business planning and decision making.

1. SALES
FORECASTING
Presented By
Nirmal Morya
M.Pharm. (Pharmaceutics)
(Dept. Pharmaceutical Science )
BBAU Lucknow
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2. CONTENT
 INTRODUCTION TO SALES FORECASTING
 IMPORTANCE OF SALES FORECASTING
 SALES FORECASTING CONCEPT
 PRODUCT LIFE CYCLE
 METHOD OF SALES FORECASTING
 EVALUATION OF SALES FORECASTING
 CONCLUSION
 REFERENCE
QUALITATIVE METHOD
QUANTITATIVE METHOD
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3. Sales Forecasting
• Estimate of company sales for a specified
future period…
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4. • Sales forecasting is an important aspect of
sales management.
• These forecasts are the result of painstaking
efforts by a number of individuals and
departments in the firm.
• Forecasts aids sales managers in improving
decision making.
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5. Importance Of Sales Forecasting
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6. Sales Quotas and Budgets
• Two of the most vital managerial uses of the
sales forecasts are the setting of sales
quotas and the developing of sales budget.
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7. • The forecast is the company’s actual
prediction of what sales will be in a
forthcoming time period.
• If sales quotas are realistic, they are the best
and fairest method for setting sales budget.
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8. Sales Budgets
• Another important evaluative technique.
• Sales Budget is a management plan for
expenditures to accomplish sales goals.
• It’s a blueprint for sales force action.
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9. Sales Forecasting Concepts
 There are 3 levels of concern in sales
forecasting…
•Market Potential
•Sales Potential
•Market Share
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10. Market Potential
 Highest possible expected industry sales of
a good or service in a market for a given time
period…
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11. Market Share
• Percentage of a market controlled by a
company or product…
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12. Sales Potential
• Individual Firm’s share of the market
potential…
 it can be expressed as:
Sales Potential = Percentage of market
potential based on market share
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13. The Product Life Cycle
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14. The Product Life cycle
• Is an important sales planning and control
tool, since it projects the changes in a
product’s sales and profits that will occur
overtime.
• When estimating market and sales potential,
sales managers must also take into account
the stage, the product has reached in its life
cycle.
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15. The Product Life cycle
• It provides a conceptual framework for
developing sales objectives and strategies for
different stages of a product’s life.
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16. The Product Life cycle
• The most difficult stage of the product life
cycle to forecast is the INTRODUCTION.
• There is no historical sales record, and new
products have a high failure rate.
• It is important for the sales forecaster to
prepare a realistic estimate of potential sales
so that management can assess the risks of
introducing the new item.
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17. The Product Life cycle
• Most firms use marketing research
techniques such as focus groups, surveys,
and test marketing to project sales of new
products.
• If a new product gains market acceptance
and enters the GROWTH STAGE, traditional
sales forecasting methods can be used.
• The forecaster must be aware of the adoption
rate for the new product, and of the potential
impact of competitive products. 17

18. The Product Life cycle
• During the MATURITY and DECLINE stage,
traditional forecasting techniques are
appropriate.
• Historical data can be analyzed statistically to
project sales.
• The sales forecaster must be alert to other
factors, such as new uses for the product,
that may suggest significant changesin the
sales trend.
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19. Sales Forecasting
Procedures
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20. • Qualitative Methods rely upon subjective,
but informed, opinions or judgments.
• Quantitative Forecasting applies
mathematical and statistical techniques.
• Both are useful in sales forecasting function.
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21. QUALITATIVE METHODS
• Jury of Executive opinion
• Delphi Technique
• Sales force Composite
• Survey of Buyer’s Intentions
• Factor Listing
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22. Jury of Executive Opinion
• The jury of executive opinion is probably the
oldest approach to forecasting, and is used by
many firms.
• Managers from sales, marketing research,
accounting, production & advertising
assemble to discuss their opinions on what
will happen to sales in future.
• These forecasts are usually made for only the
most aggregate of the sales categories such
as districts, product groups, or customer
classes. 22

23. Delphi Technique
• A similar, forecasting method, which has
been developed recently is called the
DELPHI Method.
• Its is used to make long-range projections by
group of experts.
• Delphi Method also gathers, evaluates, and
summarizes expert opinions as the basis for
a forecast, but the procedure is more formal
than that for the jury of executive opinion
method.
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24. Sales Force Composite
• A sales forecasting technique that predicts
future sales by analyzing the opinions of
sales people as a group.
• Salespeople continually interact with
customers, and from this interaction they
usually develop a knack for predicting future
sales.
• It is considered very valuable management
tool and is commonly used in business and
industry throughout the world.
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25. Survey of Buyer’s Intentions
• Applicable to situations in which potential
purchasers are well defined and limited in
number, such as industrial markets.
• Forecast survey of a limited and well-defined
group of buyers.
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26. QUANTITATIVE METHODS
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27. QUANTITATIVE METHODS
• Quantitative methods of sales forecasting
have the advantage of impartial objectivity
not possible with the qualitative methods.
• The basic disadvantages and limitations of
quantitative methods concern the nature and
the validity of the assumptions used, the lack
of data, and the fact that mathematical
forecasting techniques tend to generalize on
the basis of past experience.
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28. Methods
• Continuity Extrapolation
• Time series Analysis
• Exponential Smoothing
• Regression & Correlation Analysis
• Multiple regression analysis
• Leading indicators
• Econometric models
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29. 1.Continuity Extrapolation
• Projection of the last increment of sales
change into the future.
• Continuity extrapolation can be done on
either an absolute basis or percentage basis.
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30. 2.Time Series Analysis
• Projection of the average increment of sales
change into the future.
• Time series analysis is best used for long-
term company forecast and industry sales
projections.
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31. • A time data series is determined by four basic
elements of sales variations: trends, or long-
run changes (T), cyclical changes ©,
seasonal variations (S), and irregular or
unexpected factors (I).
• The analysis is based on the assumptions
that these elements are combined in the
following relationships:
Sales = T x C x S x I
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32. 3.Exponential Smoothing
• A weighted-average time series analysis
technique.
• Exponential smoothing is best suited to short-
term forecasting in relatively stable markets.
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33. 4.Regression and Correlation
Analysis
• Simple Regression: Forecasting technique
using only one independent variable.
• Multiple Regression: forecasting technique
using two or more independent variables.
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34. 5.Leading Indicators
• Time series of an economic activity whose
movement leads changes in sales volume.
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35. 6.Econometric Models
• Input-Output Models: models showing that
the output (sales) of one industry is the input
(purchases) of another industry.
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36. Evaluation of Sales Forecasts
• The sales manager is often given the
responsibilty for periodically evaluating the
sales forecast.
• In other cases, higher-level management is
charged with this duty.
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37.  Three objective criteria can be employed for
assessing the accuracy of sales forecasts:
1. Comparison with total sales.
2. Comparison with actual change in total
sales.
3. Comparison with other forecasting
techniques.
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38. 1.Comparison with total sales.
• This approach matches sales performance
forecasts with actual sales performance.
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39. 2.Comaprison with actual
change in total sales.
• Here, the forecast’s anticipated change is
compared with the actual change.
• For example, if sales are expected to
increase from $200 million to $230 million,
but only go upto $215 million, then the sales
forecast has failed to predict 50% of the real
change.
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40. 3.Comparison with other
forecasting techniques.
• Another evaluating approach is to compare a
firm’s actual sales forecast with the results
obtained through some naïve method of
estimating future sales such as extrapolating
the last increment of change in sales.
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41. CONCLUSION
• Proper demand forecasting enables better
planning and utilization of resources for
business to be competitive.
• Forecasting is an integral part of demand
management since it provides an estimate of
the future demand and the basis for planning
and making business decisions.
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42. REFERENCE
• Siriram, R and Snaddon, D.R. “Forecasting New Product
Sales” South African Journal of Industrial Engineering , Vol 21
Issue 1; page no 123-125
• Kumar , M and Patel N.R. “Using Clustering to improve Sales
Forecast in Retail Merchandising”, Ann Oper Res, Vol 174;
P.33-46
• Kotler. P. And Armstrong , G. Principle of Marketing Appendix
2, 11th
edition Pearson Edcation New Jersey, 2006
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43. Thank You…
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