The art of forecasting the future is often fun. But it is fraught with peril. Perils of forecasting that I have often encountered are: disbelief and anger. Here is an example.
It was in the mid- to late-1980s. Selma Holo, the director of the Fisher Gallery at the University of Southern California, asked me to give a talk. The subject was possible future trends in art galleries. The occasion was an art museum curators’ conference held at the Fisher. That sounds innocuous doesn’t it?
Continue reading Perils of forecasting: disbelief and anger
Much of futures research focuses on identifying trends of one sort or another and defining the key events that might alter the course of the trends. For example, much of my work in forecasting trends in telework deals with defining and quantifying the major factors that influence the growth (or decline) in its acceptance. For the most part forecasting such trends involves estimating (guessing) the parameters in logistic curves. Logistic curves are seen in most growth forecasts such as this one for teleworkers around the world. Often, as in forecasts of the future of microchip performance following Moore’s Law, the growth can be seen as a series of logistic curves, each of which grows to a peak then declines in use. Of course the day-to-day details of growth and decline are much noisier than those smooth curves. The primary factors in such curves are the growth rate, the peak value and the subsequent decline rate. Are you still awake?
The preceding covers the business as usual part of forecasting. As Gordon Moore discovered it’s a fairly straightforward job to estimate technological trends. Also, such trends make it fairly easy to plan for the respective future events. The task can become much more difficult when we inject human actions or those of what we call nature into the mix. Then we can have severe examples of discontinuities. Take some recent history.
Continue reading Big bangs: the futurist’s dilemma