The Gartner Group produces a large range of technology trends and predictions, based on a so-called Hype Cycle model. (The term Hype Cycle implies that things come round again. But the model is not cyclic, so it is more accurate to refer to it as a Hype Curve model.) I have just been looking at a Gartner document that includes curves for 1995 and 2005.
Here are some clues about the degree of rigour and empirical support underpinning Gartner's analysis.
Clue Number One: All technologies appear to have the same eventual outcome.
Clue Number Two: All the points are perfectly on the line. To a scientific mind, this indicates that the coordinates are not based on any real objective measurement, and that the curve itself is not subject to scientific investigation or calibration. The curve itself is based on a standard engineering pattern.
Clue Number Three: The shape of the line has not altered (or accelerated) in ten years. But all the evidence points to a shifting (shrinking) curve. For one thing, technology studies suggest that the half-life of new technologies is getting shorter. (This is sometimes known as the Red Queen Effect.) Furthermore, we might expect the quantity of attention received by each technology to be affected by the number of technologies competing for attention - and since this is increasing, the quantity and/or duration of hype might be reduced - in other words the hype curve getting steeper. (Surely technologies used to remain at the top of the hype curve for longer than they do today?)
Rather than just 1995 and 2005, it would be useful to see the whole series - so we can pick out those technologies that have gone faster or slower than Gartner had expected. Interesting that Gartner has chosen not to include this information in the self-congratulatory document I have seen.
The Aye Conference has a good discussion on the Hype Curve (September 2003). I have some comments on the implications for the software industry on my Software Industry Analysis blog.
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