Better Business and Technology Evolution Forecasting Using Systematic Innovation Methods

It often seems that the only sure thing about any form of technology forecast produced by any of the currently known techniques is that they will be wrong. The biggest single cause why they are wrong is that they assume the world to be mappable using linear models. Prevailing logic dictates that non-linearities are fundamentally non-predictable. While this may be true in certain instances, in the large majority of cases, research on systematic innovation methods has demonstrated that non-linear disruptions can be reliably and accurately predicted. The basis for this – perhaps difficult to believe – claim emerges through a programme of research built from the analysis of over 3 million patents and scientific advances. This research – part of the biggest study of creativity ever conducted – has demonstrated that systems evolve through a number of distinct and predictable stages. Thus far, 35 known trends of evolution have been uncovered. The paper demonstrates how these trends could have been used to predict disruptive technology shifts like the digital camera, ultrasound-based washing machines, and many others, and, more importantly, how leading companies are beginning to use them to systematically identify new disruption opportunities. The uncovered trends offer a very clear picture of the ‘what’s ’ of disruptive innovation. Using these trends as the foundation, the paper then proceeds to examine how they can be used in conjunction with business and market trends in order to also predict the ‘when’s’. In discussing the subject of innovation timing, the paper defines the tension between market pull and technology push as the principle disruption driver. With regard to ‘market pull’, the paper further demonstrates that even when those market forces are hidden (as was the case with the digital camera), disruptions can still be uncovered in a systematic and reproducible manner