3-1
Forecasting
CHAPTER
3
Operations Management
Forecasting
3-2
Forecasting
FORECAST:

A statement about the future value of a variable of
interest such as demand.

Forecasts affect decisions and activities throughout
an organization
 Accounting, finance
 Human resources
 Marketing
 MIS
 Operations
 Product / service design
3-3
Forecasting
Uses of Forecasts
Accounting
Cost/profit estimates
Finance
Cash flow and funding
Human Resources
Hiring/recruiting/training
Marketing
Pricing, promotion, strategy
MIS
IT/IS systems, services
Operations
Schedules, MRP, workloads
Product/service design
New products and services
3-4
Forecasting
Characteristics

Assumes causal system
past ==> future

Forecasts rarely perfect because of
randomness

Forecasts more accurate for
groups vs. individuals

Forecast accuracy decreases
as time horizon increases
I see that you will
get an A in this semester.
3-5
Forecasting
Elements of a Good Forecast
Timely
Reliable
Accurate
Written
3-6
Forecasting
Steps in the Forecasting Process
“The forecast”
Step 6 Monitor the forecast
Step 5 Prepare the forecast
Step 4 Gather and analyze data
Step 3 Select a forecasting technique
Step 2 Establish a time horizon
Step 1 Determine purpose of forecast
3-7
Forecasting
Types of Forecasts

Judgmental - uses subjective inputs

Time series - uses historical data
assuming the future will be like the past

Associative models - uses explanatory
variables to predict the future
3-8
Forecasting
Judgmental Forecasts

Executive opinions

Sales force opinions

Consumer surveys

Outside opinion
 Delphi
method

Opinions of managers and staff

Achieves a consensus forecast
3-9
Forecasting
Time Series Forecasts
Time Series is a time ordered sequence of observations
taken at regular intervals over time.

Trend - long-term movement in data
 Seasonality - short-term regular variations in data
 Cycle – wavelike variations of more than one year’s
duration
 Irregular variations - caused by unusual
circumstances
 Random variations - caused by chance
3-10 Forecasting
Forecast Variations
Irregular
variation
Trend
Cycles
90
89
88
Seasonal variations
3-11 Forecasting
Naive Forecasts
Uh, give me a minute....
We sold 250 wheels last
week.... Now, next week
we should sell....
The forecast for any period equals
the previous period’s actual value.
3-12 Forecasting

Naïve Forecasts
Simple to use
 Virtually no cost
 Quick and easy to prepare
 Data analysis is nonexistent
 Easily understandable
 Cannot provide high accuracy
 Can be a standard for accuracy
3-13 Forecasting

Stable time series data


F(t) = A(t-1)
Seasonal variations


Uses for Naïve Forecasts
F(t) = A(t-n)
Data with trends

F(t) = A(t-1) + (A(t-1) – A(t-2))
3-14 Forecasting
Techniques for Averaging

Moving average

Weighted moving average

Exponential smoothing
3-15 Forecasting

Moving Averages
Moving average – A technique that averages a
number of recent actual values, updated as new
values become available.
n
MAn =
 Ai
i=1
n
3-16 Forecasting
Example
Period
Actual
1
2
3
4
5
6
7
8
9
10
11
12
42
40
43
40
41
39
46
44
45
38
40
3-17 Forecasting
Simple Moving Average
Actual
MA5
47
45
43
41
39
37
35
MA3
1
2
3
4
5
6
7
8
n
MAn =
9
 Ai
i=1
n
10
11
12
3-18 Forecasting

Moving Averages
Weighted moving average – More recent values in a
series are given more weight in computing the
forecast.
• Premise--The most recent observations might
have the highest predictive value. Therefore,
we should give more weight to the more recent
time periods when forecasting.
3-19 Forecasting
Exponential Smoothing
Ft = Ft-1 + (At-1 - Ft-1)
3-20 Forecasting
Example - Exponential Smoothing
Period
Actual
1
2
3
4
5
6
7
8
9
10
11
12
Alpha = 0.1 Error
42
40
43
40
41
39
46
44
45
38
40
42
41.8
41.92
41.73
41.66
41.39
41.85
42.07
42.36
41.92
41.73
Alpha = 0.4 Error
-2.00
1.20
-1.92
-0.73
-2.66
4.61
2.15
2.93
-4.36
-1.92
42
41.2
41.92
41.15
41.09
40.25
42.55
43.13
43.88
41.53
40.92
-2
1.8
-1.92
-0.15
-2.09
5.75
1.45
1.87
-5.88
-1.53
3-21 Forecasting
Picking a Smoothing Constant
Actual
Demand
50
  .4
45
  .1
40
35
1
2
3
4
5
6
7
Period
8
9 10 11 12
3-22 Forecasting

Controlling the Forecast
Control chart

A visual tool for monitoring forecast errors
 Used to detect non-randomness in errors
 Forecast is under control if all errors are within
the control limits
3-23 Forecasting
Sources of Forecast errors

Model may be inadequate
 Irregular variations
 Incorrect use of forecasting technique
3-24 Forecasting
Choosing a Forecasting Technique

No single technique works in every situation
 Two most important factors

Cost
 Accuracy

Other factors include the availability of:

Historical data
 Computers
 Time needed to gather and analyze the data
 Forecast horizon