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This paper introduces a method for linking technological improvement rates(i.e. Moore's Law) and technology adoption curves (i.e. S-Curves). There hasbeen considerable research surrounding Moore's Law and the generalized versionsapplied to the time dependence of performance for other technologies. The priorwork has culminated with methodology for quantitative estimation oftechnological improvement rates for nearly any technology. This paper examinesthe implications of such regular time dependence for performance upon thetiming of key events in the technological adoption process. We propose a simplecrossover point in performance which is based upon the technologicalimprovement rates and current level differences for target and replacementtechnologies. The timing for the cross-over is hypothesized as corresponding tothe first 'knee'? in the technology adoption "S-curve" and signals when themarket for a given technology will start to be rewarding for innovators. Thisis also when potential entrants are likely to intensely experiment withproduct-market fit and when the competition to achieve a dominant designbegins. This conceptual framework is then back-tested by examining twotechnological changes brought about by the internet, namely music and videotransmission. The uncertainty analysis around the cases highlight opportunitiesfor organizations to reduce future technological uncertainty. Overall, theresults from the case studies support the reliability and utility of theconceptual framework in strategic business decision-making with the caveat thatwhile technical uncertainty is reduced, it is not eliminated.

Data-Driven Investment Decision-Making: Applying Moore's Law and S-Curves to Business Strategies