SYSTEM DYNAMICS IN BUSINESS

FORECASTING

A CASE STUDY OF THE COMMERCIAL JET

AIRCRAFT INDUSTRY

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INTRODUCTION

•Use of Forecasts in Decision-Making

•The Case Example - Worldwide Commercial Jet Aircraft &

Parts Industry

•System dynamics models

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DECISION-MAKING

Forecasting is essential for many business decisions, such as:

•How much to produce;

•How much capacity and other resources will be required;

• What products should be developed; and

• How much financing will be needed by the business.

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ARE FORECASTS RELIABLE ?

Although models of forecasting widely used, they may not

be always reliable.

•Forecasts are likely to be wrong. (Inaccuracies may occur.)

•Forecasts can contribute to problematic behaviour.

(Forecasts are a part of a system’s decision structure)

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ADDING VALUES OF SYSTEM DYNAMICS MODELS

The proper use of system dynamics models for “forecasting”

can add value to clients.

•More reliable forecasts of short-term to mid-term trends

than statistical models

•Detecting changes in industry Structure

•Determining key sensitivities

•Determination of appropriate buffers and contingencies

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THE CASE EXAMPLE – WORLDWIDE COMMERCIAL JET AIRCRAFT & PARTS INDUSTRY

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MORE RELIABLE FORECASTS IN DYNAMIC MODELS

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MORE RELIABLE FORECASTS IN DYNAMIC MODELS

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MEANS OF DETECTING CHANGES IN INDUSTRY

•If a well calibrated model is capable of providing a very

good short to mid mid-term forecasts, that model becomes a

means of detecting changes in industry structure.

•As new data and other information become available, they

are compared to the model’s forecast.

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MEANS OF DEVELOPING MORE CAREFULLY AMD ROBUST SENSITIVITIES

•Determine those

uncertainties to which

the forecast is more

sensitive – real risks

•Provide better ranges

for the “forecast” and

scenarios, given the

key uncertainties.

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DETERMINATION OF APPROPRIATE BUFFERS AND CONTINGENCIES

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PERFORMANCE IMPROVEMENT “FORECASTING”

In investments

In worse-better-before situations

For early warning-learning systems

Properly calibrated models, can provide forecast of the expected

change in performance resulting from the selected initiative.

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CONCLUSION

System dynamics models for forecasting allows managers to :

•get an early warning of industry structural changes

•identify key sensitivities and scenarios

•determine appropriate buffers and contingencies for forecast

inaccuracies.

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THANK YOU FOR

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