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Supply Chain Management (SCM) Forecasting 3

Dr. Husam Arman

4/10/2009

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Today’s Outline

Qualitative methods Economic indicators Market research Historical analogy Delphi method Sales force composites Scenario writing and analysis

Contemplations and conclusions

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Qualitative forecasting techniques

Often use data and models but with human interpretation/ judgment to form a view on the future

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Qualitative forecasting techniquesQualitative

Scenario writing

Sales force composites

Delphi Methods

Historical analogy

Market research

Economic indicators

More human

judgment

More models

and data

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Economic indicators 1

Originated in the US following the depression

Monthly, quarterly and annual series on prices, employment, production etc

Closely relates to observed economic activity and business cyclesUseful for interpretative, judgmental forecasting by many organizations

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Economic indicators 2

Economic indicator: an economic series from which a forecast is basedLeading indicators: advance warning of

probable change in economic activity Coincident indicators: reflect current

performance of economyLagging indicators: confirm changes

previously signaled Interpretation/impact depends on nature of the

forecast, sector, type of organization, location etc

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Market research 1

Extracts information form a sample of a target market and infers something about the populationUseful for information on product preferences

e.g. opinions on existing products, opinions on new products, opinions on competitors products and more general preferences

May provide sophisticated accurate forecasts on market potential

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Market research 2

Needs to be designed, executed and analyzed with care

Decisions on sample size and sample type Decisions on medium and method for information

gathering Prior selection methods for statistical inference

Many sources of expertiseMay be costly and time-consuming How do we do it?

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Historical analogy 1

Forecasting relation to new products, take up of new technologies where little or no previous market experienceLink the new products with an assumed analogous occurrence in the past1. Forecast for the demand for a product in a new

market might be made by analogy with the known demand for the same product in a mature market

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Historical analogy 2

2. Forecast demand for a new product by analogy with known demand for a related product

Analogy of mail order as a basis for predicting the development of e-shopping

If Ad-hoc method, many potential dangers

May aid understanding with qualitative information on the shape of the demand curve

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Delphi methods

DELPHI method attempts to systematically evaluate expert judgment on the likelihood of future events without expert or analyst interaction

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Delphi steps

1. Establish panel of expert2. Establish a questionnaire3. Evaluate responses by producing numerical

summary- Modal values and extreme values are highlighted

4. Controlled feedback- Make the extremists justify their position and

decide whether to include or exclude extreme values.5. Repeat (3) and (4) until a clear, not necessarily

unanimous, forecast emerges. Extremes may persist

6. Summaries the result

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Delphi

Difficulties• How many experts to use, how many rounds

are appropriate, when should extremes be eliminated?

• Time consuming and may be costlySuccessful in broad studies of issues that affect demand in many businesses in the longer term. e.g. future of the Common Agricultural growth in different tourist destinations

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Sales force composites

Utilizes knowledge and experience of sales-force to produce a forecastUseful whencomplex product mix, few customerswhere sales force have close contact with

customers, technical expertise, closely involved in negotiation, pricing and specification

but there are many problems / sources of error, like what ?

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Scenario writing and analysis 1

A scenario is a narrative description of future conditions and how a business and its competitors may react to those conditions Identifies the principal factors that affect the

future and explores a number of different future scenarios with some indications of the likelihood of each scenario occurring

Closely linked with corporate strategy and planning

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Scenario writing and analysis 2

Attempts to understand and plan for the future rather than producing ’blind’ forecastsAcknowledges that different scenarios may be plausible from a given starting pointNo generally accepted way of constructing scenariosSimulation approaches may be useful particularly System Dynamics

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Contemplation and Conclusions

Many ‘advanced’ time series extrapolation methods – little evidence that complex methods significantly outperform simpler approachesErrors made consistently in one direction imply bias, important to track errors and bias over timeAutomation of forecasting techniques for large scale inventory systems is difficult - challenging in ERP

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How much should we invest in forecasting?

Decreasing forecast errors

Increasing costs Cost of

operating a forecasting

process

Cost of forecasting

error

Naive models Sophisticated models

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Forecasting in SCM

Whatever techniques are employed, forecasts need to be embedded in the decision making processesFailure to forecast or act on forecasts may lead to implicit acceptance of a previous

outdated forecastsmay be an assumption that present conditions

will persist in the future result in lack of preparation for change

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Longer term/higher level forecasting

In operations we typically need longer term forecasts for:Strategy – decide if demand is sufficient to

entre a market• e.g. 3-10 years

Longer term capacity needs for facility design• e.g. exceeding 2 years

Medium term capacity and resource ‘flexing’• recruiting/shedding labor, balancing production

across multiple sites• supply chain ‘ramp’ up and down• e.g. 6 months to 2 years

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Selecting the appropriate forecasting techniques

What is the purpose of the forecast? How is it to be used?What are the dynamics of the system for which the forecast will be made?How important is the past in estimating the future?What about the different stages of the product life cycle? Can we use more than one technique?