DECISION MODELING WITH DECISION MODELING WITH MICROSOFT EXCELMICROSOFT EXCEL

Chapter 13Chapter 13

Copyright 2001Copyright 2001Prentice HallPrentice Hall

Part 3Part 3

Historical data play a critical role in the Historical data play a critical role in the construction and testing of forecasting construction and testing of forecasting models.models.Whether a causal model or time-series Whether a causal model or time-series quantitative model is used, the parameters quantitative model is used, the parameters of the model must be selected. For of the model must be selected. For example, example, 1.1. In a causal model using a linear In a causal model using a linear

forecasting function, forecasting function, yy = a + b = a + bxx, the , the values of values of aa and and bb must be specified. must be specified.

2.2. In a time series model using a In a time series model using a weighted weighted nn-period moving average, -period moving average, yytt+1+1 = = 00yytt + + 11yytt-1-1 + … + + … + nn-1-1yytt--nn+1+1, the number of , the number of terms, terms, nn, and the values for the , and the values for the weights, weights, 00, , 11, …, , …, nn-1-1, must be , must be specified.specified.

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3.3. In a time-series model using In a time-series model using exponential smoothing, exponential smoothing, yytt+1+1 = = yytt + (1- + (1-))yytt , the value of must be , the value of must be specified.specified.

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In order to specify the parameter values for In order to specify the parameter values for any of these models, one typically must any of these models, one typically must make use of historical data.make use of historical data.It is often a useful practice to use part of It is often a useful practice to use part of the data to estimate the parameters and the data to estimate the parameters and the rest of the data to test the model.the rest of the data to test the model.With real data, it is also important to With real data, it is also important to “clean” the data.“clean” the data.In other words, examine the data for In other words, examine the data for irregularities, missing information, or irregularities, missing information, or special circumstances, and adjust them special circumstances, and adjust them accordingly.accordingly.

For example, suppose a firm has weekly For example, suppose a firm has weekly sales data on a particular product for the sales data on a particular product for the last two years (last two years (104104 observations) and plans observations) and plans to use an exponential smoothing model to to use an exponential smoothing model to forecast sales for this product.forecast sales for this product.

The firm might use the following procedure:The firm might use the following procedure:

1.1. Pick a particular value of Pick a particular value of , and , and compare the values of compare the values of yytt+1+1 to to yytt+1+1 for for tt = 25= 25 and and 7575..

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The first The first 2424 values are not compared, values are not compared, so as to negate any initial or so as to negate any initial or “startup” effect (so as to nullify the “startup” effect (so as to nullify the influence of the initial guess, influence of the initial guess, yy11).).^̂

The manager would continue to select The manager would continue to select different values of different values of until the model until the model produces a satisfactory fit during the produces a satisfactory fit during the period period tt = 25 = 25 to to 7575..

2.2. Test the model derived in step Test the model derived in step 11 on on the remaining the remaining 2929 pieces of data. pieces of data.

If the model does a good job of forecasting If the model does a good job of forecasting values for the last part of the historical values for the last part of the historical data, there is some reason to believe that it data, there is some reason to believe that it will also do a good job with the future.will also do a good job with the future.

That is, using the best value of That is, using the best value of from from step step 11, compare the values of , compare the values of yytt+1+1 to to yytt+1+1 for for tt = 76 = 76 to to 104104..

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On the other hand, if by using the data from On the other hand, if by using the data from weeks weeks 11 - - 7575, the model cannot perform well , the model cannot perform well in predicting the demand in weeks in predicting the demand in weeks 7676 - - 104104, , then another forecasting technique might then another forecasting technique might be applied. be applied. The same type of divide-and-conquer The same type of divide-and-conquer strategy can be used with any of the strategy can be used with any of the forecasting techniques presented in this forecasting techniques presented in this chapter.chapter.This popular approach amounts to This popular approach amounts to stimulatingstimulating the model’s performance on the model’s performance on past data.past data.It should be stressed, however, that this It should be stressed, however, that this procedure represents what is termed a procedure represents what is termed a null null testtest. . If the model fails on historical data, the If the model fails on historical data, the model probably is not appropriate.model probably is not appropriate.If the model succeeds on historical data, If the model succeeds on historical data, one cannot be sure that it will work in the one cannot be sure that it will work in the futurefuture..

Many important forecasts are not based on Many important forecasts are not based on formal models.formal models.

EXPERT JUDGMENTEXPERT JUDGMENT

For example, during the high-interest-rate For example, during the high-interest-rate period of 1980 and 1981, the most period of 1980 and 1981, the most influential forecasters of interest rates were influential forecasters of interest rates were Henry Kaufman of Salomon Brothers and Henry Kaufman of Salomon Brothers and Albert Wojnilower of First Boston.Albert Wojnilower of First Boston.These gentlemen combined relevant factors These gentlemen combined relevant factors such as the money supply and such as the money supply and unemployment, as well as results from unemployment, as well as results from quantitative models, in their own intuitive quantitative models, in their own intuitive way to produce forecasts that had way to produce forecasts that had widespread credibility and impact on the widespread credibility and impact on the financial community.financial community.

Qualitative forecasts can be an important Qualitative forecasts can be an important source of information.source of information.Managers must consider a wide variety of Managers must consider a wide variety of sources of data before coming to a decision.sources of data before coming to a decision.

Expert opinion should not be ignored.Expert opinion should not be ignored.A sobering and useful measure of A sobering and useful measure of allall forecasts is a record of past performance.forecasts is a record of past performance.

Managers should listen to experts Managers should listen to experts cautiously and hold them to a standard of cautiously and hold them to a standard of performance.performance.There is, however, more to qualitative There is, however, more to qualitative forecasting than selecting “the right” forecasting than selecting “the right” expert.expert.

The The Delphi MethodDelphi Method confronts the problem of confronts the problem of obtaining a combined forecast from a group obtaining a combined forecast from a group of experts.of experts.

THE DELPHI METHOD THE DELPHI METHOD AND CONSENSUS PANELAND CONSENSUS PANEL

The The consensus panelconsensus panel approach is to bring approach is to bring the experts together in a room and let them the experts together in a room and let them discuss an event until a consensus emerges.discuss an event until a consensus emerges.However, due to group dynamics, one However, due to group dynamics, one person with a strong personality can have person with a strong personality can have an enormous effect on the forecast. an enormous effect on the forecast. The Delphi Method was developed by the The Delphi Method was developed by the Rand Corporation to retain the strength of a Rand Corporation to retain the strength of a joint forecast, while removing the effects of joint forecast, while removing the effects of group dynamics.group dynamics.

The method uses a coordinated set of The method uses a coordinated set of experts.experts.No expert knows who else is in the group. No expert knows who else is in the group. All communication is through the All communication is through the coordinator.coordinator.

Coordinator requests forecastsCoordinator requests forecasts

Coordinator receives Coordinator receives Individual forecastsIndividual forecasts

Coordinator determinesCoordinator determines(a)(a) Median responseMedian response(b)(b) Range of middle Range of middle

50% of answers50% of answers

Coordinator Coordinator requests requests

explanations from explanations from any expert whose any expert whose estimate is not in estimate is not in the middle 50%the middle 50%

Coordinator sends to all Coordinator sends to all expertsexperts

(a)(a) Median responseMedian response(b)(b) Range of middle 50%Range of middle 50%

(c)(c) ExplanationsExplanations

The process is as follows:The process is as follows:

After three or four passes through this After three or four passes through this process, a consensus forecast typically process, a consensus forecast typically emerges.emerges.The forecast may be near the original The forecast may be near the original median, but if a forecast that is an outlier in median, but if a forecast that is an outlier in round round 11 is supported by strong analysis, the is supported by strong analysis, the extreme forecast in round extreme forecast in round 11 may be the may be the group forecast after three or four rounds.group forecast after three or four rounds.

GRASSROOTS FORECASTING GRASSROOTS FORECASTING AND MARKET RESEARCHAND MARKET RESEARCH

Other qualitative techniques are based on Other qualitative techniques are based on the concept of asking either those who are the concept of asking either those who are close to the eventual consumer, such as close to the eventual consumer, such as salespeople, or consumers themselves, salespeople, or consumers themselves, about a product or their purchasing plans.about a product or their purchasing plans.

Consulting SalesmenConsulting Salesmen In In grassroots grassroots forecastingforecasting, salespeople are asked to , salespeople are asked to forecast demand in their districts. forecast demand in their districts. In the simplest situations, these forecasts In the simplest situations, these forecasts are added together to get a total demand are added together to get a total demand forecast.forecast.In more sophisticated systems individual In more sophisticated systems individual forecasts or the total may be adjusted on forecasts or the total may be adjusted on the basis of the historical correlation the basis of the historical correlation between the salesperson’s forecasts and between the salesperson’s forecasts and the actual sales.the actual sales.Such a procedure makes it possible to Such a procedure makes it possible to adjust for an actual occurrence of the adjust for an actual occurrence of the stereotyped salesperson’s optimism.stereotyped salesperson’s optimism.

With Grassroots forecasts, the individual With Grassroots forecasts, the individual salesperson should be able to provide salesperson should be able to provide better forecasts than more aggregate better forecasts than more aggregate models.models.There are, however, several problems:There are, however, several problems:

1.1. High costHigh cost: The time salespeople : The time salespeople spend forecasting is not spent selling.spend forecasting is not spent selling.Some view this opportunity cost of Some view this opportunity cost of grassroots forecasting as its major grassroots forecasting as its major disadvantage.disadvantage.

2.2. Potential conflict of interestPotential conflict of interest: Sales : Sales forecasts may well turn into forecasts may well turn into marketing goals that can affect a marketing goals that can affect a salesperson’s compensation in an salesperson’s compensation in an important way. important way. Such considerations exert a Such considerations exert a downward bias in individual forecasts.downward bias in individual forecasts.

1.1. Product schizophrenia (i.e., Product schizophrenia (i.e., stereotyped salesperson’s optimism)stereotyped salesperson’s optimism): : It is important for salespeople to be It is important for salespeople to be enthusiastic about their product and enthusiastic about their product and its potential uses.its potential uses.It is not clear that this enthusiasm is It is not clear that this enthusiasm is consistent with a cold-eyed appraisal consistent with a cold-eyed appraisal of its market potential.of its market potential.

In summary, grassroots forecasting may not In summary, grassroots forecasting may not fit well with other organization objectives fit well with other organization objectives and thus may not be effective in an overall and thus may not be effective in an overall sense.sense.Consulting ConsumersConsulting Consumers Market researchMarket research is a is a large and important topic which includes a large and important topic which includes a variety of techniques, from consumer variety of techniques, from consumer panels through consumer surveys and on to panels through consumer surveys and on to test marketing.test marketing.

The goal of market research is to make The goal of market research is to make predictions about the size and structure of predictions about the size and structure of the market for specific goods and/or the market for specific goods and/or services.services.These predictions (forecasts) are usually These predictions (forecasts) are usually based on small samples and are qualitative based on small samples and are qualitative in the sense that the original data typically in the sense that the original data typically consist of subjective evaluations of consist of subjective evaluations of consumers.consumers.A large menu of quantitative techniques A large menu of quantitative techniques exist to aid in determining how to gather exist to aid in determining how to gather the data and how to analyze them.the data and how to analyze them.Market research is an important activity in Market research is an important activity in most consumer product firms. It also plays most consumer product firms. It also plays an increasingly important role in the an increasingly important role in the political and electoral process.political and electoral process.