Date post: | 07-Apr-2018 |
Category: |
Documents |
Upload: | pankaj-dhanore |
View: | 224 times |
Download: | 1 times |
8/6/2019 Sales Forecasting Vruhali
http://slidepdf.com/reader/full/sales-forecasting-vruhali 1/19
Sales forecasting
Presented byVrushali Dhanore
8/6/2019 Sales Forecasting Vruhali
http://slidepdf.com/reader/full/sales-forecasting-vruhali 2/19
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
8/6/2019 Sales Forecasting Vruhali
http://slidepdf.com/reader/full/sales-forecasting-vruhali 3/19
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
8/6/2019 Sales Forecasting Vruhali
http://slidepdf.com/reader/full/sales-forecasting-vruhali 4/19
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
8/6/2019 Sales Forecasting Vruhali
http://slidepdf.com/reader/full/sales-forecasting-vruhali 5/19
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
8/6/2019 Sales Forecasting Vruhali
http://slidepdf.com/reader/full/sales-forecasting-vruhali 6/19
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
8/6/2019 Sales Forecasting Vruhali
http://slidepdf.com/reader/full/sales-forecasting-vruhali 7/19
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
8/6/2019 Sales Forecasting Vruhali
http://slidepdf.com/reader/full/sales-forecasting-vruhali 8/19
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
8/6/2019 Sales Forecasting Vruhali
http://slidepdf.com/reader/full/sales-forecasting-vruhali 9/19
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
8/6/2019 Sales Forecasting Vruhali
http://slidepdf.com/reader/full/sales-forecasting-vruhali 10/19
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
8/6/2019 Sales Forecasting Vruhali
http://slidepdf.com/reader/full/sales-forecasting-vruhali 11/19
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
8/6/2019 Sales Forecasting Vruhali
http://slidepdf.com/reader/full/sales-forecasting-vruhali 12/19
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
8/6/2019 Sales Forecasting Vruhali
http://slidepdf.com/reader/full/sales-forecasting-vruhali 13/19
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
8/6/2019 Sales Forecasting Vruhali
http://slidepdf.com/reader/full/sales-forecasting-vruhali 14/19
*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
8/6/2019 Sales Forecasting Vruhali
http://slidepdf.com/reader/full/sales-forecasting-vruhali 15/19
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
8/6/2019 Sales Forecasting Vruhali
http://slidepdf.com/reader/full/sales-forecasting-vruhali 16/19
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
8/6/2019 Sales Forecasting Vruhali
http://slidepdf.com/reader/full/sales-forecasting-vruhali 17/19
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
8/6/2019 Sales Forecasting Vruhali
http://slidepdf.com/reader/full/sales-forecasting-vruhali 18/19
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
8/6/2019 Sales Forecasting Vruhali
http://slidepdf.com/reader/full/sales-forecasting-vruhali 19/19
THANK YOU!!!!!!!!!!