3 Forecasting Market Demand

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FORECASTING MARKET

DEMAND



FORECASTING M ARKET DEMAND

1. When one is in a producers market there is lessof a need for forecasting as the market takes upall ones production; it is less a matter of sellingand more a matter of allowing customers topurchase.

2. However, in a buyers market, the consequenceof over-production is unsold stock which is costlyto finance from working capital borrowings.Conversely, under-production can be detrimental

as sales opportunities might be missed due tolong delivery times and business might pass to acompetitor that can offer quicker delivery.

3. Thus the purpose of the sales forecast is to planahead and go about achieving forecasted sales.



USES OF S ALES FORECASTS

1. A sales forecast is the estimated dollar or unit sales for a specific future time period based on a

proposed marketing plan and an assumedmarket environment.

2. In addition, the sales forecasting procedure must be taken seriously because from it stemsbusiness planning. If the forecast is flawed then

business plans will also be incorrect.



1. A sales forecast becomes a basis for setting and

maintaining a production schedule ± manufacturing.

2. It determines the quantity and timing of needs for labor,

equipment, tools, parts, and raw materials ± purchasing,

personnel.

3. It influences the amount of borrowed capital needed to

finance the production and the necessary cash flow to

operate the business ± controller.

4. It provides a basis for sales quota assignments to various

segments of the sales force ± sales management.

5. It is the overall base that determines the company¶s

business and marketing plans, which are further broken

down into specific goals ± marketing officer.

A sales forecast is important for at least five reasons:



Marketing Plan

Sales Forecasts Sales Force Budget

PLANNING/FORECASTING/BUDGETING SEQUENCE



THE FORECASTING PROCESS

The forecasting process refers to a series of procedures used to forecast.

The process starts with the determinationof forecast objective.

This may be an estimation of rupees sales,unit sales or number of salespeople to hirenext year.



A market factor is an item or element that

(1) exists in a market, (2) may be measured

quantitatively, and (3) is related to the

demand for a product or service.

A market index is simply a market factor

expressed as a percentage relative to some base figure.



Forecast

Objective Determine Dependent and

Independent Variables

Develop Forecast

Procedure

Select Forecast

Analysis Method

Total Forecast

Procedure

Gather and Analyze

Data

Present Assumptions

about Data

Make and Finalize

Forecast

Evaluate Results

versus Forecast

THE FORECASTING PROCESS



Categories of Forecasting

1. Breakdown2. Build-up



Basic Steps in Breakdown Method of Forecasting Sales

General Environment Forecast

Industry Sales Forecast

Company Sales PotentialCompany Sales Forecast

Product Lines

Individual Products for

Customers-Territories-Regions-Divisions-U.S.A.-World



Company sales potential is the maximum

estimated or potential sales the companymay reach in a defined time period under

given conditions.

The company¶s share of the estimated sales

for an entire industry is referred to as

market share.

Industry sales forecast, or market potential,

is the estimated sales for all sellers.



1. This method is reverse of breakdown method.

2. Individual forecasts are made by

groups and units with-in the firmand then combined to make broaderforecasts.

Build-up Method



SALES FORECASTING

METHODS

Survey methods are qualitative and includeexecutive opinion, sales force composite,and customer¶s intention surveys.

Mathematical methods are test markets,market factors, naïve models, trend analysis,and correlation analysis.

Two categories of sales forecasting methods exist:



Survey Methods

Executive

Opinion

User·s

Expectation

Sales Force

Composite

Build-to-

Order

Mathematical Methods

Test Market Regression

Naive Trend

Moving

Average

Exponential

Smoothing

THE MORE POPULAR OF MANY FORECASTING METHODS



SURVEY FORECASTING METHODS

Four basic survey methods are

Executive O pinion Sales Force Composite

User¶s Expectations

Build-to-Order



Executive Opinion

Is the original sales forecasting method

and is still the most widely used,

regardless of the company size.

1. By one seasoned individual (usually

in a small company).

2. By a group of individuals, sometimes

called a ³jury of executive opinion.´

Executive forecasting is done in two ways:



1. Key executives submit the independent

estimates without discussion, and these are

averaged into one forecast by the chief executive.

2. The group meets, each person presents

separate estimates, differences areresolved, and a consensus is reached.

The group approach uses two methods:



Delphi Method

Administering a series of questionnaires

to panels of experts.



Sales Force Composite

O btaining the opinions of sales

personnel concerning future sales.



User¶s Expectations

Consumer and industrial companiesoften poll their actual or potential

customers.



Build-to-Order

Companies build final products only after firm orders are placed.



MATHEMATICAL FORECASTING

METHODS

Test markets are a popular method of

measuring consumer acceptance of new

products.



Time Series Projections

Time series methods use chronologicallyordered raw data.

Historical data are used to predict future

events.



The trend component.

The seasonal component.

The cyclical component.

The erratic component.

Classical approach to time series analysis:



Naïve MethodAlso known as ratio method

NextYear¶s Sales = ThisYear¶s Sales XThisYear¶s SalesLastYear¶s Sales



Moving Average

Moving averages are used to allow for

marketplace factors changing at different

rates and at different times.

With this method distant past and distant

future have little value in forecasting.



PER IOD

SALES

VOLUME

SALES FOR

THREE-YEAR PER IOD

THREE-YEAR

MOVING AVER AGE

1 200

2 250

3 300 750

4 350 900 300

5 450 1100 ( 3) = 366.6

6 ?

Period 6 Forecast = 366.6

TABLE 5.1 EXAMPLE OF MOVING-AVERAGE FORECAST



Exponential Smoothing

Exponential smoothing is similar to the moving-

average forecasting method. It allows

consideration of all past data, but less weight is

placed on data as it ages.

It is weighted moving average method.

NextYear¶s Sales = a (ThisYear¶s Sales) + (1-a) (ThisYear¶s Forecast)



Trend Projections ± Least Squares

Eyeball fitting is simply a plot of the datawith a line drawn through them that the

forecaster feels most accurately fits the

linear trend of the data.



600

500

400

300

200

100

01984

Time

1985 1986 1987 1988 1989 1990

Observed Sales Forecast Sales

S a l e s

TrendLine

FIGURE 5.6 A TREND FORECAST OF SALES



R egression Analysis

R egression analysis is a statistical method used toincorporate independent factors that are thought toinfluence sales into the forecasting procedure.



Linear Relationship

Population

(A)

S

a l e s

0

Curvilinear Relationship

Population

(B)

S

a l e s

0

FIGURE 5.7 REGRESSION ANALYSIS



Have You Developed

a Good

Sales Forecasting

Process?

Market Decision Support System

BreakdownUse Multiple

Forecasting

Methods

Buildup

Questions to Answer to Improve Chances of Hitting the Forecasting Bulls-Eye

H a v e Y o u C o n s i d e r e d

t h e B a s i c s t o

I n c r e a s i n g A c c u r a c y

a n d S e l e c t i n g Y o u r

F o r e c a s t i n g M e t h o d ?

W h i c h F o r e c a s t ( s )

M e t h o d S h o u l d

Y o u U s e ?

C o u l d O

u t s i d e

S o u r c e s H e l p ?

C o

u l d t h e C o m p u t e r

a n d S o f t w a r e H

e l p ?

90%

80%

70%60%

140%

130%

120%

110%F

OR

E

C

A

S

T



GUIDE TO FORECASTING

FORCASTING

METHOD TIME SPAN

MATHEMATICAL

SOPHISTICATIO N

COMPUTER

NEED ACCUR ACY

Executive O pinion Short to medium Minimal Not essential Limited

Delphi Method Medium to long Minimal Not essential Limited; good in dynamic

conditions

Sales Force Composite Short to medium Minimal Not essential Accurate under dynamic conditions

User¶sE

xpectations Short to medium Minimal Not essential Limited

Test Markets Medium Needed Needed Accurate

Naïve Method Present to medium Minimal Not essential Limited

Moving Average Short to long Minimal Helpful Accurate under stable conditions

Exponential Smoothing Short to medium Minimal Helpful Accurate under stable conditions

Least Squares Short to long Needed Desirable Varies widely

R egression Analysis Short to Medium Needed Essential Accurate if variable relationships

stable

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