A

PRESENTATION

ON

“FORECASTING”

UNDER THE SUPERVISION OF: PRESENTED BY:

Dr. A.K BHARDWAJ RANJANA SINGH

PID NO. 14MTEEPS016

DEPARTMENT OF ELECTRICAL ENGINEERING

SAM HIGGINBOTTOM INSTITUTE OF AGRICULTURE, TECHNOLOGY & SCIENCES

ALLAHABAD

1

Forecasting

Forecasting is the process of making statements about events whose actual outcomes have not yet been observed.

Educated Guessing

Underlying basis of all business decisions

Production

Inventory

Personnel

Facilities

??

2

Types of Forecasts

Economic forecasts

Address business cycle – inflation rate, money

supply, housing starts, etc.

Technological forecasts

Predict rate of technological progress

Impacts development of new products

Demand forecasts

Predict sales of existing product

3

Forecasting Approaches

Used when situation is vague and little data exist

New products

New technology

Involves intuition, experience

e.g., forecasting sales on Internet

Qualitative Methods

4

Forecasting Approaches

Used when situation is ‘stable’ and historical data exist

Existing products

Current technology

Involves mathematical techniques

e.g., forecasting sales of color televisions

Quantitative Methods

5

Short-range forecast

Usually < 3 months

Job scheduling, worker assignments

Medium-range forecast

3 months to 2 years

Sales/production planning

Long-range forecast

> 2 years

New product planning

Types of Forecasts by Time Horizon

6

Collect historical data

Select a model

Selections should produce a good forecast

To Use a Forecasting Method

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A Good Forecast

Has a small error Forecast Error = Demand – Forecast

= Actual value at time t

= Forecast value at time t

= Number of periods to be averaged

tA

tF

n 8

n

1=t

tt F-A

=FE

Measures of Forecast Error

MSE = Mean Squared Error

n

F-A

=MSE

n

1=t

2

tt

n

F-A

=MAD

n

1=t

tt

Ideal values =0 (i.e., no forecasting error)

MSE =RMSE

RMSE = Root Mean Squared Error

MAD = Mean Absolute Deviation

9

FE/MAD Example

Month Sales (At) Forecast(Ft)

1 220 n/a

2 250 255

3 210 205

4 300 320

5 325 315

MAD =

A - F

n

t tt=1

n

5

5

20

10

|At – Ft|

= 40= 40

4=10

FE=

n = 4

10

MSE/RMSE Example

Month Sales(At) Forecast(Ft)

1 220 n/a

2 250 255

3 210 205

4 300 320

5 325 315

5

5

20

10

|At – Ft|

= 550

4=137.5

(At – Ft)2

25

25

400

100

= 550

n

F-A

=MSE

n

1=t

2

tt

=√137.5 =11.73

n = 4

MSE =RMSE

11

Supply Chain Management

Inventory Control

Personal Investment

Application

12

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