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FORECASTING pankajchaudhary582@gmail.com
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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
7
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
13
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