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Technology Futures

Beyond the time scale of Roadmaps (usually a few product cycles) the capability for directing strategic technology investments is dramatically improved by characterizing sustained trends of enabling technologies and identifying potentially disruptive innovations. For example, in computers and communications, long-term advances in semiconductors and optics have allowed far more accurate forecasts of technology innovations compared to fields where trends were not recognized or did not exist. Accurate forecasting of technology innovations requires characterizing technology advances, connecting key enabling technologies to potential applications, and quantitative assessment of driving forces.

Our capabilities:
  • Identify and assess the implications of technology trends and disruptions, and develop priorities for investment.
  • Develop quantitative technology forecasts using market and technology experience curves, learning curves, and technology adoption analytics.

Science and Technology Roadmaps

About S&T Roadmaps : The elements and a framework for Science and Technology Roadmaps.

Roadmaps for Converging Technologies . Plotting the course of emerging technologies of nanotechnology, biotechnology, information technology and cognitive science presents complex future scenarios that roadmapping can help identify and clarify.

Past Forecasts provide key lessons for technology forecasting:

A review of Herman Kahn and Anthony Wiener’s One hundred technical innovations very likely in the last third of the twentieth century, published in their 1967 book, "The Year 2000, A Framework for Speculation on the Next Thirty-Three Years" found that fewer than 50% were judged good and timely, having occurred in the twentieth century. However, when the forecasts were grouped into nine broad technological fields there were wide variations in the judged accuracy of the forecasts. Forecasts in computers and communication stood out as about 80% correct, while forecasts in all other fields were judged to be less than about 50% correct. Sustained trends of increasing capabilities and declining costs of technologies used for computers and communication applications were apparent in 1967 and enabled accurate long term forecasts. To improve our current forecasts, we should look for sustained and continuing trends in underlying technologies, where increasing capabilities enable more complex applications and declining costs drive a positive innovation loop, lowering the cost of innovation and enabling wider learning and contributions from more people, thus sustaining the technology trends.
The complete review: What Can Past Technology Forecasts Tell Us About the Future? , Technological Forecasting and Social Change, Vol. 69 No. 5, pgs. 443 – 464, June, 2002.

Experience Curves for short term forecasts
A valuable tool for forecasting short term cost requirements is the experience curve. The example below shows the declining cost per unit versus cumulative volume over time. The trend is often a straight line in log-log space, helping product teams to set industry based cost targets.

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