Sales Forecasting Vruhali

8/6/2019 Sales Forecasting Vruhali

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Sales forecasting

Presented byVrushali Dhanore



Definition

� Sales forecasting is the process of estimating what yourbusiness sales are going to be in the future

� Estimate of the number of sales on rupees or physicalunits, in a future period under a particular marketing

program and an assumed set of economic conditions andother external factor

� Purpose to provide information to make importantdecisions

� Helps marketer

to develop marketing budget

Allocate market resources

Monitor the competition



Steps involved

1. Determine the use of forecast- what objective are wetrying to obtain?

2. Select the items or quantities that are to be forecasted

3. Determine the time limit?

4. Select the forecasting model or models

5. Gather the data needed to make the forecast

6. Validate the forecasting model

7. Make the forecast

8. Implement the result



Uses of forecasting

1) Production department - for production planning andcoordination with the sales team

2) Purchase department - to plan its purchases in advance

3) HR department - for its manpower planning

4) The accounting department - to plan for future cash flow

well as for new equipment needed

5) R&D - to make innovations in advance

6) Marketers - to plan their activity accordingly incoordination with the sales team



Techniques of of sales

forecastingQualitative

1. Jury of executive

opinion

2. Customer / channel

/user survey

3. Executive opinion

4. Delphi

Quantitative

Time Series

1. Moving averages2. Exponential smoothing

Causal

1. Regression analysis

2. Multiple Regression



Jury of executive opinion

Jury of Executive OpinionThere are two steps in this method:

i. High ranking executives estimate probable sales

ii. 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

� Q uick 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

� The panel of experts responds

to a sequence of questionnaires

in which the responses to onequestionnaire are used to

produce the next questionnaire

� Thus information disseminated

to all, enabling all to base their

final forecasts on ³all available´

information



Sales force estimation

� By analyzing the opinion of the sales people as a

group

� Interaction with the customers

� Can be improved by providing sufficient time to

the sales people



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 growthrates are relatively stable

Next years sale= This years sales/ Last years sales



Time- series analysis

� A statistical procedure for studying historical sales data.Ithas four components

� Trends(T) is the gradual upward or downward movement of the data over time

� Seasonality(s) is a pattern of the demand fluctuation aboveor below the trend line

� Cycles (c) are patterns in annual data occur every severalyears

� Random variation (R) blips in data caused by change andunusual 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

Month Actual Sales Three month moving average

January 10 (10+12+13)/3=11.67

February 12 (12+13+16)/3=13.67

March 13

April 16



Weighted moving average

� Weights are used to give more values to recent

values

� This makes the techniques more responsive tochanges because latter periods may be more

heavily waited



*Sales three month ago

Sum of the weights

Weights Applied period

3 Last month ago

2

1 Three month ago

Two month ago

13 *sales last month + 2 *Sales Two month ago +

6

Month Actual sales Three month moving average

January 10

February 12

March 13

April 16 (3*13)+(2*12)+(10)/6=12.17



Exponential smoothing

� Exponential smoothing: A statistical technique for short-

range sales forecasting

Next years sale= a(this years sale)+ (1-a) (this years

forecast)

a- smoothing constant and is set between 0.0 and 1.0

Determine value of a is difficult as a should be small to retain

the effect of earlier observation



Regression Analysis

� Regression Analysis is a statistical process and, as used in

sales forecasting, determines and measures the association

between company sales and other variables

� It involves fitting an equation to explain sales fluctuationsin terms of related and presumably causal variables,

substituting for these variables values considered likely

during the period to be forecasted, and solving for sales



Continue«

There are three major steps in forecasting sales

through regression analysis:

1. Identify variables causally related to company sales

2. Determine or estimate the values of these variables

related to sales

3. Derive the sales forecast from these estimates



Evaluation of sales forecast

� Before submitting forecasts to higher management, sales

executives evaluate them caref ully

� Every forecast contains elements of uncertainty

� All are based on assumptions so a first step in evaluating asales forecast is to examine the assumptions

� Sales executives should evaluate the accuracy and economic

value of the forecast as the forecast period advances

� Forecasts should be checked against actual results, differencesexplained, and indicated adjustments made for the remainder of

the period



THANK YOU!!!!!!!!!!

Sales Forecasting Vruhali

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