Forecasting
- process of predicting a future event based on
historical data
- Educated guessing
- Underlying basis of all business decisions:
Production, Inventory, Personnel, and Facilities
Besided demand, service providers are also
interested in forecast of population, of their
demographic variable
Types of Forecasts by Time Horizon
-
In general, forecasts are almost always wrong.
So,
Throughout the day we forecast very different
things such as weather, traffic, stock market,
state of the company from different
perspective.
Virtually every business attempt is based on
forecasting. Not all of them are derived from
sophisticated methods. However, best educated
guesses about future are more valuable for
purpose of Planning no forecasts and hence no
planning.
Importance of Forecasting in OM
Departments throughout the organization
depend on forecasts to formulate and execute
their plans
Finance needs forecasts to project cash flows
and capital requirements
Human resources need forecasts to anticipate
hiring needs
Short-range forecast – usually < 3
months
Medium-range forecast – 3 months to 2
years
Long-range forecast – 2 years
Qualitative Forecasting Methods
1. Executive Judgment – Opinion of a
group of high level experts or managers
is pooled
2. Sales Force Composite – Each regional
salesperson provides his/her sales
estimates. Those forecasts are then
reviewed to make sure they are
realistic.
3. Market Research – Solicits input from
customers pertaining to their future
purchasing plans. It involves the use of
questions
4. Delphi method – As opposed to regular
panels where the individuals involved
are in direct communication
Quantitative Forecasting Methods
1.
2.
Time series models
Naïve
Moving Average
Exponential smoothing
Regression Models
Time series models
Demand is not the only variable of interest to
forecasters
Manufacturers also forecast worker
absenteeism, machine availability, material
costs, transportation and production lead times,
etc.
-
Try to predict the future based on past
data
1. Naïve approach
Demand in next period is the same as
demand in most recent period
- May Sales = 46 -> June forecast = 48
- Usually not good
2. Simple Moving Average
Assumes an average is a good estimator
of future behavior
- Used if little or no trend
- Used for smoothing
- 3 previous months only
3. Weighted moving average (WMA)
Gives more emphasis to recent data
- Weights
- Weighted moving average: 3/6, 2/6, 1/6
Month
Sales
WMA
1
4 x 1/6
2
6 x 2/6
3
5 x 3/6
4
?
5
?
4. Exponential Smoothing
Week
Demand
1
820
2
775
3
680
4
655
5
750
6
802
7
798
8
680
9
775
10