FLEXIBILITY IN DESIGN - Title Page - MIT

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de Neufville + Scholtes D R A F T September 30, 2009size of oil reservoirs, when faced with a new site we have just begun to explore. In all cases, weshould ask: what is the best information we can have about the size and range of uncertainties?[Figures 2.5 and 2.6 here]Where possible, we need to characterize the distribution of the uncertainties. We will beable to weigh the relative value of different designs more accurately to the extent we can estimatethe probability of different outcomes. In some cases, we might be able to do this easily. Forexample, we can derive the occurrence of earthquakes, and other natural hazards unaffected byman, from historical records with some accuracy. More generally, we must use sophisticatedstatistical analyses to estimate the exact nature of the uncertainties (see Appendix D onForecasting.)Shift forecasting emphasis. To develop a realistic view of forecasts requires a double shift in theforecasting process. Most obviously, it is desirable to spend effort on the process of recognizingthe uncertainties, defining their ranges, and estimating the probabilities of the outcomes. Thisimplies a shift in emphasis, away from standard efforts to identify the most likely or best forecastsand point estimates, and toward spending more time and money thinking about the range ofpossibilities. Managers and users wanting the most realistic – and thus most useful – forecastsrequire the forecasters to identify and characterize the uncertainties.The shift in emphasis involves a shift in mindset and expectations. To the extent thatforecasters realistically accept the evidence that trend-breakers and other factors disrupt even themost sophisticated estimates of the future, they must also recognize that it is not useful to try todevelop very detailed point forecasts. This will mean also that they can generally forego the verydetailed kinds of analyses on which they currently spend so much effort. It is desirable not only tospend more effort on understanding the nature of the uncertainties, but also to spend less ontrying to get best estimates of most likely forecasts.Track developments. All the above implies that we need to track developments and readjust ourestimates of the future accordingly. This is the logical consequence, once we recognize thatforecasts done at any time are unlikely to be reliable due to trend-breakers and other changes inthe environment. To develop designs that will be able to meet the current and future needs mosteffectively, system managers need to be on top of these needs. They cannot rely on forecastsmade long ago to be the proper basis for design, even if some administrative process approvedthese forecasts. Official approval does not define reality!To track developments most effectively, the forecasting process can identify leadingindicators of change. These are factors that are most likely to signal changes in trends. Forexample, the developers of the Iridium satellite telephone system might have identified “sales ofcell phones” as a leading indicator of the success of their prospective competition. If they hadPart 1: Chapters 1 to 3 <strong>Page</strong> 32 of 69
de Neufville + Scholtes D R A F T September 30, 2009done so early enough, they might have redesigned their system and avoided much of its financialfailure. System managers can then track these factors over time, to obtain early warning of trendbreakersand other developments that might affect the design. They should reallocate theirforecasting efforts not just from point forecasts to understanding distributions, but also from aone-shot effort to a continuous process.Take-awayOverall, system owners, designers and managers need to change their approach to forecasting.They should avoid asking for the “right forecast” or a narrow range of possible futures. If theyrequest and pay for such a result, they will surely get it. However, it will be almost meaningless.Forecasts are “always wrong” in that the future that actually occurs routinely differs from whatsomeone predicted.Users of forecasts need to recognize the inevitable uncertainties. They should thus ask for arealistic understanding of the range of possible scenarios. Specifically, they can tailor theirrequests for forecasts to:• De-emphasize the development of precise best estimates – such point estimates aredemonstrably unreliable, generally very expensive, and thus a waste of money;• Develop a realistic assessment of both the range of uncertainties around the forecastsand the possible asymmetry of any distribution;• Estimate, to the extent possible, the probabilities associated with possible outcomes; and• Track developments over time to keep abreast of the situation and adjust designs andplans accordingly.Part 1: Chapters 1 to 3 <strong>Page</strong> 33 of 69
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