FUTURIST SKILLS, 
TOOLS, & INFORMATION

TREND FORECASTING

by Earl C. Joseph, Walden University Professor
A publication of the Minnesota Futurists

Trend forecasting is one of the most used methods of forecasting. It is often the starting point for forecasters who after doing a trend analysis, modify the future trends discovered using various other methods and information to arrive at a ãbetterä forecast.

Trend analysis forecasting philosophies, assumptions, and method:
 

ð Trend analysis identifies and maps past and present experience along the path of change traveled over time and, when extended (called extrapolated), forecasts a likely heading for the future.

ð Trend forecasts are based upon the assumption that the future will unfold at about the same rate of change, direction, and magnitude of growth or decline as it did in past.

ð Trend forecasts provide the most likely path for the short-range future they prophesy (because of the flywheel impact of recent decisions and actions).

ð Trend forecasts most often give a least likely prediction for the long-range future they depict (because other factors and other forces also steer future change).

ð Trend forecasting can be quantitative and qualitative.
 

Trend forecasts provide a ãyardstick of changeä for measuring future change (better than taking a ãsnapshot of today ã as the extrapolated yardstick) for steering our intuition and decision-making efforts relative to the future.

Trends are not just straight lines extended into the future from the past. Trend forecasts can take on many different curve paths into the future.  Some common trend curves are:
 

ð J-curve - the trend curve grows along a path like the letter J depicting exponential change;

ð S-curve - the trend curve grows along a path simulating the letter S depicting the trend reaching a limit;

ð Step function curve - the trend follows a curve path like steps going in or out of a building;

ð Life cycle curve - the trend follows a curve path similar to the normal curve in statistics;

ð Cyclic curve - the trend curve follows approximately a repeated set of transitions, each with a similar shape but differing magnitudes;

ð Breakthrough trend curve - a current or new generation of change breaks though its past trend;

ð Bumpy trend curve - much like a stockâs price changes over time.

The farther one attempts to extend past trends into the future, the fuzzier the result is, relative to the actual future to result. Trend forecasting attempts to measure the expected path that a particular area under study will follow into its future. The ãcurvilinearä shape of the trend is important and more easily forecast than the actual timing of curving transitions. Thus, a trend is more qualitative rather than quantitative.

Other ways to approach or do qualitative trend forecasting involve:

ð Forecasting generational transitions - involves product or technology improvements per generation; requires also forecasting (or stating as an assumption), for example, how technology will advance, market acceptance of changes, how a new human generation will react to past/present life style trends, etc.

ð Envelope trend forecasting - involves plotting and extending a tangent curve over multi-generational change in a particular area.  By extending envelope past trends with the upper and lower bound of expectation, the wider the differences grow the farther into the future the trends are extrapolated. Therefore, a fan-shaped area of trend possibilities results.

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