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Forecasting McGraw-Hill/Irwin Copyright © 2012 by The McGraw-Hill Companies, Inc. All rights reserved.

Forecasting McGraw-Hill/Irwin Copyright © 2012 by The McGraw-Hill Companies, Inc. All rights reserved

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Page 1: Forecasting McGraw-Hill/Irwin Copyright © 2012 by The McGraw-Hill Companies, Inc. All rights reserved

Forecasting

McGraw-Hill/Irwin Copyright © 2012 by The McGraw-Hill Companies, Inc. All rights reserved.

Page 2: Forecasting McGraw-Hill/Irwin Copyright © 2012 by The McGraw-Hill Companies, Inc. All rights reserved

You should be able to:1. List the elements of a good forecast2. Outline the steps in the forecasting process3. Describe at least three qualitative forecasting

techniques and the advantages and disadvantages of each

4. Compare and contrast qualitative and quantitative approaches to forecasting

5. Describe averaging techniques, trend and seasonal techniques, and regression analysis, and solve typical problems

6. Explain three measures of forecast accuracy7. Compare two ways of evaluating and controlling

forecasts8. Assess the major factors and trade-offs to consider when

choosing a forecasting technique

3-2Student Slides

Page 3: Forecasting McGraw-Hill/Irwin Copyright © 2012 by The McGraw-Hill Companies, Inc. All rights reserved

Forecast – a statement about the future value of a variable of interestWe make forecasts about such things as

weather, demand, and resource availabilityForecasts are an important element in making

informed decisions

3-3Student Slides

Page 4: Forecasting McGraw-Hill/Irwin Copyright © 2012 by The McGraw-Hill Companies, Inc. All rights reserved

n

100

Actual

ForecastActual

MAPE t

tt

n

tt ForecastActualMAD

2

tt

1

ForecastActualMSE

n

MAD weights all errors evenly

MSE weights errors according to their squared values

MAPE weights errors according to relative error

3-4Student Slides

Page 5: Forecasting McGraw-Hill/Irwin Copyright © 2012 by The McGraw-Hill Companies, Inc. All rights reserved

Forecasts that project patterns identified in recent time-series observationsTime-series - a time-ordered sequence of

observations taken at regular time intervalsAssume that future values of the time-series

can be estimated from past values of the time-series

3-5Student Slides

Page 6: Forecasting McGraw-Hill/Irwin Copyright © 2012 by The McGraw-Hill Companies, Inc. All rights reserved

These Techniques work best when a series tends to vary about an averageAveraging techniques smooth variations in the

dataThey can handle step changes or gradual

changes in the level of a seriesTechniques

1. Moving average2. Weighted moving average3. Exponential smoothing

3-6Student Slides

Page 7: Forecasting McGraw-Hill/Irwin Copyright © 2012 by The McGraw-Hill Companies, Inc. All rights reserved

Technique that averages a number of the most recent actual values in generating a forecast

average moving in the periods ofNumber

1 periodin valueActual

average moving period MA

period for timeForecast

where

MA

1

1

n

tA

n

tF

n

AF

t

n

t

n

iit

nt

3-7Student Slides

Page 8: Forecasting McGraw-Hill/Irwin Copyright © 2012 by The McGraw-Hill Companies, Inc. All rights reserved

The most recent values in a time series are given more weight in computing a forecastThe choice of weights, w, is somewhat

arbitrary and involves some trial and error

etc. ,1 periodfor valueactual the , periodfor valueactual the

etc. ,1 periodfor weight , periodfor weight

where

)(...)()(

1

1

11

tAtA

twtw

AwAwAwF

tt

tt

ntntttttt

3-8Student Slides

Page 9: Forecasting McGraw-Hill/Irwin Copyright © 2012 by The McGraw-Hill Companies, Inc. All rights reserved

A weighted averaging method that is based on the previous forecast plus a percentage of the forecast error

period previous thefrom salesor demand Actual

constant Smoothing=

period previous for theForecast

periodfor Forecast

where

)(

1

1

111

t

t

t

tttt

A

F

tF

FAFF

3-9Student Slides

Page 10: Forecasting McGraw-Hill/Irwin Copyright © 2012 by The McGraw-Hill Companies, Inc. All rights reserved

A simple data plot can reveal the existence and nature of a trend

Linear trend equation

Ft a btwhere

Ft Forecast for period t

aValue of Ft at t 0

bSlope of the line

t Specified number of time periods from t 0

3-10Student Slides

Page 11: Forecasting McGraw-Hill/Irwin Copyright © 2012 by The McGraw-Hill Companies, Inc. All rights reserved

Slope and intercept can be estimated from historical data

bn ty t yn t 2 t

2

ay b tn

or y bt

where

n Number of periods

y Value of the time series

3-11Student Slides

Page 12: Forecasting McGraw-Hill/Irwin Copyright © 2012 by The McGraw-Hill Companies, Inc. All rights reserved

The trend adjusted forecast consists of two componentsSmoothed errorTrend factor

TAFt+1 St Ttwhere

St Previous forecast plus smoothed error

Tt Current trend estimate

3-12Student Slides

Page 13: Forecasting McGraw-Hill/Irwin Copyright © 2012 by The McGraw-Hill Companies, Inc. All rights reserved

Alpha and beta are smoothing constantsTrend-adjusted exponential smoothing has

the ability to respond to changes in trend

TAFt+1 St Tt St TAFt + At TAFt Tt Tt 1 TAFt TAFt 1 Tt 1

3-13Student Slides

Page 14: Forecasting McGraw-Hill/Irwin Copyright © 2012 by The McGraw-Hill Companies, Inc. All rights reserved

Regression - a technique for fitting a line to a set of data pointsSimple linear regression - the simplest form of

regression that involves a linear relationship between two variablesThe object of simple linear regression is to obtain

an equation of a straight line that minimizes the sum of squared vertical deviations from the line (i.e., the least squares criterion)

3-14Student Slides

Page 15: Forecasting McGraw-Hill/Irwin Copyright © 2012 by The McGraw-Hill Companies, Inc. All rights reserved

The better forecasts are, the more able organizations will be to take advantage of future opportunities and reduce potential risks A worthwhile strategy is to work to improve short-term

forecastsAccurate up-to-date information can have a

significant effect on forecast accuracy:PricesDemandOther important variables

Reduce the time horizon forecasts have to cover Sharing forecasts or demand data through the

supply chain can improve forecast quality

3-15Student Slides