Trend impact analysis

A forecasting method that permits extrapolations of historical trends to be modified in view of expectations about future events. This method permits an analyst interested in forecasting a particular trend or variable, to include and systematically examine the effects of possible future events that are believed important to the future course of that trend or variable. The events can include technological, political, social, economic, value-oriented changes and other kinds of developments. TIA is a method for analyzing consequences of such future developments on the trend or variable One of its most important Applications of this technique is to specify what events will make a difference in the future. This analysis produces a range of outcomes rather than just a single value. It begins with an extrapolation of a time series. This is taken to be "baseline forecast" that is the future of the variable if there were no future trend-changing developments. Next a list of developments is prepared using a literature search, Delphi, or any other technique. These developments might include unique technology, societal changes, political actions or any other change that my affect the futures course of the variable. Each development on the list is expressed in terms of its expected probability of occurrence over the future time interval of concern, and were it to occur, its impact on the variable or trend under study. TIA "´plays out" all possible combinations of the events and their effect on the variable (Monte Carlo), adjusting the baseline forecast in the process. In this simulation, a single run consists of deciding, at each point in the forecasted time range, whether or not each event "occurs" and adjusting the baseline forecast accordingly to account for its impact. The result of each simulation is essentially a mini-scenario documenting which developments have “occurred” over time. Ideally, 1,000 runs or more of this sort must be made, playing out the various combinations of events and their impacts. The mini-scenarios are then viewed as a set and reviewed to find the median and quartiles, and the TIA results are generally presented as a "fan" of outcomes, spread according to their probability.