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Forecasting

in

Indian scenarioGroup 1


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Agenda

What is forecasting, Why we do it?

End note

Forecasting in Petroleum Industry

Time horizons

Design and stepsTypes

Accuracy and issues

Forecasting in Retail Industry


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What is Forecasting ?

Forecasting is the estimation of future

trends by examining and analyzing available

information.

It is a scientifically calculated guess.

It is a very critical activity for strategic or

tactical production planning.


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To prepare for the future How much profit will a business make ?

How many workers will the company need ?

Determine demand for a product/service.

To take effective business decisions Determine cost to produce a product/service.

How much money should the companyborrow ?

When and how borrowed funds should be

repaid ?

Developing new product/service.

Why Forecasting ?


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Time horizon in forecasting

Short range (3 years)


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Less

than 3

months

3 months to

3 years

After 3 years


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Design of forecasting systems

Develop a forecasting logic by identifying the purpose,

data and models to be used

Establish control mechanisms to obtain reliable forecast

Incorporate managerial considerations in using the forecasting

system


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Developing the Forecasting Logic

Identify purpose

Purpose of forecast

Time horizon

Type of data needed

Identify a suitable technique

Collect/analyze past data

Select an appropriate model

Develop a forecasting logic

Establish model parameters

Build the model

Test model adequacy

Test using historical dataSatisfactory

Start

Stop

No

Yes


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Sources of data

Sales force estimates

Point of sales(POS) data systems

Forecasts from supply chain partners

Trade/industry association journals

B2B portals

Economic surveys and indicators

Subjective knowledge


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Elements of good forecasting

Meaningful Written

Accurate

Easy to use

Reliable

Timely


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Judgmental

Uses subjective inputs

Time series

Uses historical data assuming the future will be

like the past

Associative models

Uses ex lanator variables to redict the future

Types of forecasting


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Executive opinions

Sales force composite

Consumer surveys

Outside opinion

Opinions of managers and staff

(Delphi method)

Judgmental


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Trend

Long-term movement in data

Cyclical

Short term variation in data

Seasonality

C

aused by unusual circumstances

Time series

`


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Components of time series

Trend

Irregularvariation

Cycles

Seasonal variations

90

89

88

Business Cycle


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Moving average

Exponential

smoothening

Techniques of averaging


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Associative models

Regression

Technique for fitting a line to a set of points

Least squares line

Minimizes sum of squared deviations around the line


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Basic concept

Mean Error

Where,

FE = Forecast Error

Ai = The actual value in time period i

Fi = The forecast value in time period i

Mean Square Error

Where,

=

)]([1

1

!

!n

i

ii

nFE

2

1

)]([1 !

!n

i

iiFA

nMSE


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Mean Absolute Deviation

Where,

MAD = Mean Absolute Deviation

Ai = The actual value in time period i

Fi = The forecast value in time period i

Mean Absolute Percentage Error

Where,

MAPE = Mean Square Error

!

!n

i

iiFA

nMAD

1

1

A10011

v-

! !

n

i i

ii

A

FA

nMAPE

Ai = The actual value in time period iFi = The forecast value in time period i

Mean Absolute Percentage ErrorWhere,

MAPE = Mean Square ErrorAi = The actual value in time period iFi = The forecast value in time period i

Basic concept


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Tracking Signal

Where,

TS = Tracking signal

SFE = Sum of forecast error

MAD = Mean Absolute Deviation

MAD

SFETS !

Where,TS = Tracking signalSFE = Sum of forecast errorMAD = Mean Absolute DeviationBasic concept


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Issues while using forecasting

system


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outline text format

Second Outline

Level

Third Outline

Level

Fourth

Outline

Level

Fifth

Outline

How to get Started?Choice Of Model

Estimation Of Parameters

Key Inferences from

research/practice

Issues while using forecasting

systemCost

Time frame

Data Availability


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outline text format

Second Outline

Level

Third Outline

Level

Fourth

OutlineLevel

Fifth

Outline

Click to edit the outline text format

Second Outline Level

Third Outline Level

Fourth Outline Level

Fifth Outline Level

Issues in using the system:-

How to incorporate externalinformation

Stability Vs Responsiveness

New

Competitor

Sales

Promotion

Agency

reports


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When to change the system?

Parameter Re-estimation VsModel Change

Forecast

Reliability


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Forecasting in Retail sector


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After leading the IT bandwagon, India is poised to grow as a Retail hub

India have potential to consume ; given the power to spend

Key challenge areas for the retail growth

Escalating real estate cost

Scarcity of skilled workforce Structured supply of merchandise

Insights to the retail sector


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Values in Cr. Rs.

Source: TSMG Analysis

Future forecast of different categories in retail sector


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Primarily past two-three years of data and the

targeted growth in the particular good is used to

predict the volume of sales.

Taste and trend are subjective terms and hence

requires much more than just theoretical knowledge

hence more personal & judgmental involvement.

Forecasting - Retail sector


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Second Outline

Level

Third Outline

Level

Fourth OutlineLevel

Fifth

Outline

Level

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High brand retailers

use the forecasting

techniques of the

kind studied intheory & forecasting

is done for a longer

time duration andinvolves substantial

amounts of asset

cost.

Small scale retailersemploy qualitative

techniques on the

historical data andconsidering the

behavior trends in

the market.

Ex: Daily bazaar

Forecasting - Retail sector


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Forecasting is done on a six monthly basis in the

retail industry.

The production time is considered to be 60 days.

Hence orders usually placed at least 2 months inadvance.

Example :

For the Diwali season, the forecasting study is

started sometime in March.

For the summer season it is done in October.

Time Period for which forecasting is done?


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Forecasting in petrochemical

industry


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Steps - Petrochemical Industry

Assumptions about tariff structure, exchange rate fluctuation,

imported price, nature of competition & local price

Total market for polyethylene in the medium term of 18-36months is calculated

Analysis of supply demand position based on own &

competitors capacity and expansion plan

Series of forecasting techniques implemented

on past data and analysis done at various levels

Estimates derived at regional level are

aggregated & future demand is estimated


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Forecasting - Petrochemical

Industry Balancing capacity available to actual projected requirement. Detailed production planning for the next year by disintegrating available data

into specific products and scheduling plans.

Helps in establishing performance targets for various departments (production,

material, marketing) and setting up control system.


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Closure to foreign participation

Sellers market

Underdeveloped technology

Emphasis on getting appropriate permits to manufacture.

Previous Scenario

Limited use of forecasting methods. Industries

believed in Production concept

Result


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Globalization

Buyers Market

Advanced Technologies

Competition

Present Scenario

Indian market / business is now resorting to

forecasting models, opinion based methods

such as Delphi techniques and Consumer

Behavioral Surveys

Result


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Despite having a sophisticated forecasting system,

managers must use the forecasts obtained fromthe system in the context of

external information

I see that you willget an A in this term


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THANK YOU

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