Ssm lecture-17 & 18 (sales forecasting-extended)

07/06/10 1
By :
Prof. Amit Kumar

07/06/10 2
“A student pursuing management education from IILM-
Graduate School of Management, for example may find
himself or herself placed in a firm as a Sales Manager.
Our goal is to prepare the student for the exciting
challenges related to leading sales organizations in
today’s hyper-competitive global economy”.
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Importance of this course
Selling & Sales Management

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IILM-GSM
Selling & Sales Management

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Contents
• Forecasting & Application of Forecasting
• Sales Forecasting
• Forecasting Market Demand/ Potential
• Marketing Decision Support System
• Forecasting Process
• Popular Methods of Forecasting
1. Judgment based- Qualitative
2. Sales extrapolation- Quantitative
3. Customer based
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Selling & Sales Management Sales Forecasting

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Forecasting
• Forecasting is the process of making statements about
events whose actual outcomes (typically) have not yet
been observed. A commonplace example might be
estimation of the expected value for some variable of
interest at some specified future date.
• Prediction is a similar, but more general term.
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Application of Forecasting
Forecasting has application in many situations:
1. Supply chain management - to make sure that the right product is at the
right place at the right time. Accurate forecasting will help retailers reduce
excess inventory and therefore increase profit margin. Accurate
forecasting will also help them meet consumer demand.
2. Weather forecasting, Flood forecasting
3. Transportation forecasting
4. Economic forecasting
5. Technology forecasting
6. Earthquake prediction
7. Product forecasting
8. Player and team performance in sports
9. Political Forecasting
10. Sales Forecasting
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Sales Forecasting
Sales forecasting is estimating what a company's
future sales are likely to be based on sales records
as well as market research.
• Information used for sales forecasting must be well
organized and may include information on the
competition and statistics that affect the businesses'
customer base.
• Companies conduct sales forecasting in hopes of
identifying patterns so that revenue and cash flow can
be maximized.
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Reason for Undertaking Sales Forecasting
Businesses are forced to look well ahead in order to planBusinesses are forced to look well ahead in order to plan
their investments, launch new products, decide when totheir investments, launch new products, decide when to
close or withdraw products and so on. The salesclose or withdraw products and so on. The sales
forecasting process is a critical one for most businesses.forecasting process is a critical one for most businesses.
Key decisions derived from sales forecasting include:
• Employment levels required
• Promotional mix
• Investment in production capacity
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Sales Forecasting
• Before the forecasting process begins, marketing, sales,
or other managers should determine how far ahead the
forecast should be done.
• Short-term forecasting is a maximum of three months
and is often effective for analyzing budgets and markets.
• Intermediate sales forecasting is between a period of
three months and two years and may be used for
schedules, inventory and production.
• Long term forecasting is for a minimum of two years
and is good for dealing with growth into new markets or
new products.
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Purposes for Short-Term Forecasting
• Appropriate production scheduling
• Reducing cost of purchasing R/M
• Determining appropriate price policy
• Setting sales targets and establishing controls and
incentives
• Evolving a suitable promotional program
• Forecasting short-term financial requirements
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Purposes for Long-Term Forecasting
• Planning of a new unit or expansion of an existing unit
• Planning of long-term financial requirements
• Planning of man-power requirements
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Sales Forecasting
• Basically, sales forecasting is analyzing all parts of a
business from total inventory to the strengths and
weaknesses of salespeople.
• Managers must think about changes in customer sales
or other changes that could affect forecasting figures.
• They must be competitive when assessing the
competition and how they can surpass the competition
to better meet the needs of the target market.
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Stages in Sales Forecasting
1.1. Stage One in the forecast is to estimate Market DemandStage One in the forecast is to estimate Market Demand
2.2. Stage Two in the forecast is to estimate CompanyStage Two in the forecast is to estimate Company
DemandDemand
3.3. Stage Three is then to develop the Sales ForecastStage Three is then to develop the Sales Forecast
( Forecasting Process)( Forecasting Process)
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Stage One in the forecast is to estimateStage One in the forecast is to estimate
Market DemandMarket Demand
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The First stage in creating the sales forecast is to estimateThe First stage in creating the sales forecast is to estimate
Market Demand.Market Demand.
Definition:Definition:
Market Demand for a product is the total volumeMarket Demand for a product is the total volume
that would be bought by a defined customerthat would be bought by a defined customer
group, in a defined geographical area, in agroup, in a defined geographical area, in a
defined time period, in a given marketingdefined time period, in a given marketing
environment. This is sometimes referred to asenvironment. This is sometimes referred to as
the Market Demand Curve.the Market Demand Curve.

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Consider the UK Overseas Mass MarketConsider the UK Overseas Mass Market
Package Holiday IndustryPackage Holiday Industry
What is Market Demand?What is Market Demand?
Using the definition above, market demand can be definedUsing the definition above, market demand can be defined
as:as:
Defined Customer GroupDefined Customer Group:: Customers Who Buy an Air-Customers Who Buy an Air-
Inclusive Package Holiday.Inclusive Package Holiday.
Defined Geographical AreaDefined Geographical Area:: Customers in the UKCustomers in the UK
Defined Time PeriodDefined Time Period: A calendar year: A calendar year
Defined Marketing EnvironmentDefined Marketing Environment:: Strong consumerStrong consumer
spending in the UK but overseas holidays affected byspending in the UK but overseas holidays affected by
concerns over international terrorism.concerns over international terrorism.
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Recent data for the UK Overseas Mass MarketRecent data for the UK Overseas Mass Market
Package Holiday market suggests that marketPackage Holiday market suggests that market
demand can be calculated as follows:demand can be calculated as follows:
Number of Customers in the UKNumber of Customers in the UK:: 17.5 million17.5 million
per calendar yearper calendar year
Average Selling Price per HolidayAverage Selling Price per Holiday:: £450£450
Estimate of market demandEstimate of market demand: £7.9 billion: £7.9 billion
(customers x average price)(customers x average price)
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Stage Two in the forecast is to estimateStage Two in the forecast is to estimate
Company DemandCompany Demand
Company demand is the company’s share of marketCompany demand is the company’s share of market
demand. This can be expressed as a formula:demand. This can be expressed as a formula:
Company Demand = Market Demand V/s Company’sCompany Demand = Market Demand V/s Company’s
Market ShareMarket Share
For example, taking our package holiday market example;For example, taking our package holiday market example;
the company demand for First Choice Holidays in thisthe company demand for First Choice Holidays in this
market can be calculated as follows:market can be calculated as follows:
First Choice Holidays Demand = £7.9 billion x 15%First Choice Holidays Demand = £7.9 billion x 15%
Market Share = £1.2 billionMarket Share = £1.2 billion
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Stage Two in the forecast is to estimateStage Two in the forecast is to estimate
Company DemandCompany Demand
Company Demand = Market Demand V/s Company’sCompany Demand = Market Demand V/s Company’s
Market ShareMarket Share
A company’s share of market demand depends onA company’s share of market demand depends on
how its products, services, prices, brands and so onhow its products, services, prices, brands and so on
are perceived relative to the competitors. All otherare perceived relative to the competitors. All other
things being equal, the company’s market share willthings being equal, the company’s market share will
depend on the size and effectiveness of itsdepend on the size and effectiveness of its
marketing spending relative to competitors.marketing spending relative to competitors.
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Stage Three is then to develop theStage Three is then to develop the
Sales ForecastSales Forecast
The Sales Forecast is the expected level of company salesThe Sales Forecast is the expected level of company sales
based on a chosen marketing plan and an assumedbased on a chosen marketing plan and an assumed
marketing environment.marketing environment.
Note that the Sales Forecast is not necessarily theNote that the Sales Forecast is not necessarily the
same as a “sales target” or a “sales budget”.same as a “sales target” or a “sales budget”.
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Stage Three is then to develop theStage Three is then to develop the
Sales ForecastSales Forecast
A sales targetA sales target (or goal) is set for the sales force as a way(or goal) is set for the sales force as a way
of defining and encouraging sales effort. Sales targetsof defining and encouraging sales effort. Sales targets
are often set some way higher than estimated sales toare often set some way higher than estimated sales to
“stretch” the efforts of the sales force.“stretch” the efforts of the sales force.
A sales budgetA sales budget is a more conservative estimate of theis a more conservative estimate of the
expected volume of sales. It is primarily used for makingexpected volume of sales. It is primarily used for making
current purchasing, production and cash-flow decisions.current purchasing, production and cash-flow decisions.
Sales budgets need to take into account the risksSales budgets need to take into account the risks
involved in sales forecasting. They are, therefore,involved in sales forecasting. They are, therefore,
generally set lower than the sales forecast.generally set lower than the sales forecast.
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Forecasting Process
The forecasting process is defined as the series of decisions
and actions taken by a business organization in:
 Identifying the forecasting objectives
 Determining the independent and dependent variables
 Developing a forecasting procedure
 Using the available data in the selected method to estimate the
sales in future
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Develop forecasting
procedure
Forecasting Process
contd.
Select forecasting
analysis method
Comprehend total
forecasting procedure
Collect, collate,
gather and analyze
data
Determine
independent and
dependent variables
Present all the
assumptions about
data
Forecast objectives
Evaluate performance
results against the
forecasts
Make and finalize
the forecast
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Forecasting Market Demand
It is the estimated rupee or unit sales for a specific future time
period based on the company’s marketing plan and an assumed
marketing environment.
Price/
Unit
Price /
Unit
Price/
Unit
Price/
Unit
Price/
Unit
Price /
Unit
Qty per Unit
(E)
Qty per Unit
(F)
Qty per Unit
(C)
Qty per Unit
(B)
Qty per Unit
(A)
Qty per Unit
(D)
Total
Market
demand
P1
P2
Q1
Q2
D D1
D D2
D D1
D D2
Market demand curve
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Market Demand Function
P- Price of the product
I- Consumer Income
T- Consumer preference
P0 Price of other goods & services
QD = B + aP P + a1I + a0P0 + aTT
aP,, aI, a0, aT represents the one unit
change in quantity associated
with the variables.
QD = B + aP P
Linear form of the demand equation
B represents the combined influence
of all the other determinants of the
demand
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QD = F (P, I, P0, T)

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• Marketing Decision Support System
an MDSS is an ongoing future-oriented information structure
designed to collect, collate, categorize, edit, store, and retrieve
information on demand to aid decision making in an
organization’s sales and marketing programme
Marketing Decision Support System
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MDSS
TRANSACTIONAL SYSTEMS USERS
Marketing Decision Support System
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Selecting Types of Forecasting Depends On
• The degree of accuracy required
• The availability of data and information
• The time horizon that the sales forecast is intended to
cover
• The position of the product in its life cycle
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Methods of Forecasting
1. Judgment based (Qualitative Methods)
• Jury of expert opinion (most common)
• Delphi method (2nd
most common)
• Sales force composite (3rd
most common)
1. Sales extrapolation (Quantitative Methods)
• Naïve Method (Simplest trend projection)
• Free Hand or Graphic Method
• Method of Semi-Average
1. Customer based
• Market Testing
• Market Surveys
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Judgment-based Forecasting: Qualitative
Jury of expert opinion (most common)
• In the Jury of executive opinion method of Sales
Forecasting, appropriate managers within the organization
assemble to discuss their opinions on what will happen to
sales in the future.
• Since these discussion sessions usually resolve around
hunches or experienced guesses, the resulting forecast is a
blend of informed opinions.
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Delphi Method (most common)
• A similar, forecasting method, which has been developed
recently is called the DELPHI Method. 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.
• The Delphi Method has the following steps:
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Delphi Method (most common)- It has the following steps:
STEP 1 – In this method, A group of experts and A Delphi Coordinator will be
selected. (from the group of experts)
STEP 2 – Various Experts are asked to answer, independently and in writing,
a series of questions about the future of sales. A summary of all the
answers is then prepared. No expert knows, how other answered.
STEP 3 – Copies of summary are given to the Delphi Coordinator. (Individual
experts with the request to Coordinator that they modify their original
answers if they think it necessary.)
STEP 4 – The coordinator processes, compiles, and refers them back to the panel
members for revision, if any.
STEP 5 – This is a to-and-fro process continues for several rounds. (usually three).
The forecast is generated from all of the opinions and justifications.
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The Delphi forecasts will be primarily median forecasts.

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Sales Force Composite (3rd
most common)
• The Sales Force Method is 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.
• As with the jury of executive opinion method, the resulting forecast
normally is a blend of the informed views of the group.
• The sales force estimation method is considered very valuable
management tool and is commonly used in business and industry
throughout the world.
• This method can be further improved by providing sales people with
sufficient time to forecast and offering incentives for accurate
forecasts.
• Companies can make their sales people better forecasters, by
training them to better interpret their interactions with the customers.
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Sales Extrapolation: Quantitative
Trend Projections: Assumes future will follow on past
– Appropriate for mature, static industry
• Naïve Method (Simplest trend projection is Naïve method)
• Free Hand or Graphic Method
• Method of Semi-Average
• Method of Moving average (common quantitative method)
• Exponential smoothing
– Alternative method to smooth data
• Regression analysis (next most common in U.S.)
– Forecast sales = a intercept + b slope (time)
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Observed sales Forecasted sales
Trend
line
Time
Sales
Trend Forecast of Sales
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Naïve Method
The following formula shows how to adjust the naïve method to
account for a change in rate of sales levels. The formula is stated
this way:
Next Year’s Sales = This Year’s Sales X This Year’s Sales
Last Year’s Sales
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Assume, for example, that sales for period 6 is to be forecasted.
Also assume that this year’s sales, period 5, equaled Rs. 5,50,000
and that last year’s sales, period 4, were worth Rs. 4,00,000. Thus
the nest year’s sales forecast equals Rs. 7,56,250.
Method is applicable if trends are stable or are changing in a
relatively consistent manner.

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Free Hand or Graphic Method
Free Hand Graphic Method
0
5
10
15
20
25
30
1 2 3 4 5 6 7 8 9 10
Years
Sales Series1
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Year Sales
1 20
2 22
3 24
4 21
5 23
6 25
7 23
8 26
9 25

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Method of Semi-Averages
In this method available data are divided into two parts, usually with
equal number of years on both the parts
Year Sales
1993 102
1994 105
1995 114
1996 110
1997 108
1998 116
1999 112
The average of the first three years will be:
102+105+114 321
----------- = -------- = 107
3 3
Similarly, for the last three years,
108 + 116 + 112 336
---------------------- = --------- = 112
3 3
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The 3-yearly moving average can be computed with the
following formula:
a+b+c b+c+d c+d+e d+e+f
--------- , ----------- , ---------- , --------- , ………….
3 3 3 3
Method of Moving Averages
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Exponential Smoothing Method
• It is similar to the moving- average forecasting method.
• The forecaster is allowed to vary the weights assigned to
past data points.
• It allows consideration of all past data, but less weight is
placed on data as it ages, e.g. previous year’s data has greater
weight than five-year old data.
• Exponential smoothing is basically a weighted moving
average of all past data
• The method is used to forecast only one period in the future.
• Exponential smoothing techniques vary in terms of how
they address trend, seasonality, cyclical and irregular influences.
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Exponential Smoothing Method contd.
Next Year’s Sales = a (This Year’s Sales) + (1 – a) (This Year’s
Forecast)
While using this method, a probability-weighting factor, or
smoothing constant, is selected arbitrarily. This factor is usually
between 0.1 to 0.5. This value determines how sensitive the
forecasting values will be to recent changes in sales.
The forecasting equation is:
If sales change consistently, the smoothing constant would be small
to retain the effect of earlier data. Rapid changes call for a large a.
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Correlation Analysis
• a correlation is basically the degree of linear association
between two variables where one variable is treated as
independent variable and sales as the dependent variable
• sales managers look for variables that correlate with or
relate to sales
• correlation analysis involves the determination of whether
a relation exists, and if it does, then measuring it, testing
whether it is significant, and establishing the cause and
effect relation
• the degree of relationships between the variables is called
co-efficient of correlation
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Regression Analysis
• Regression analysis is another form of correlation technique
• reveals average relationship between two variables and
this makes possible estimation or prediction
• a statistical method used to incorporate independent factors
that are thought to influence sales into forecasting procedures
Regression equation of X on Y is expressed as: X = a + b (Y)
Population
Sales
Population
Sales
(Liner Relationship) (Curvilinear Relationship)
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Customer-based Forecasting Methods
• Does not assume future will follow on past
– Appropriate for dynamic markets / new products
• Market Testing
• Market Surveys
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Market Testing
• Test marketing is one of the popular methods for
measuring acceptance of new products.
One market is called a ‘test market’ where the product is
marketed without any promotional campaign. A similar
market is selected as ‘control market’ where the product
is sold with promotional campaign.
The difference in sales between both the market is a measure
of the effectiveness of the sales promotion campaign.
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• Result from a test market are extrapolated to make
prediction about future sales.

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Market Survey
• Market survey of buyer’s expectations.
• The survey of buying intensions involve the selection of a
sample of potential buyers and getting information from
them on their likely purchase of the product in future.
• Generally in B2B market, forecasting depends on the
demand pattern of their B2B buyers.
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Sales Forecast Versus Plan
THE SALES FORECAST IS A PROJECTION INTO THE
FUTURE OF EXPECTED SALES, GIVEN A STATED
SET OF ENVIRONMENTAL CONDITIONS.
THE SALES PLAN IS A SET OF SPECIFIED
MANAGERIAL ACTIONS TO BE UNDERTAKEN TO
MEET OR EXCEED THE SALES FORECAST
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Conclusions
• Forecasting is necessary, but difficult
• All methods have plusses and minuses
– All are based on prior experience
– Will generally miss the turning points
• Best to come up with different scenarios
– Have expected, best and worst forecasts for each
• Be prepared!
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Ssm lecture-17 & 18 (sales forecasting-extended)

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