Development projects for radical innovations are typically long in duration and, therefore, surrounded by a high level of technological , market, organizational and resource uncertainties. Various techniques have been developed in order to manage the uncertainties due to unpredictable future and to support managers in their strategic decision making during the innovation development process. Typically such techniques give support for decision making only in a particular phase or element of the innovation process. Systematic strategic support throughout the innovation process under high level of future uncertainty, from the first evaluation of ideas of new business opportunities through design and development stages to commercialization and launch, is usually highly insufficient or missing. This paper describes a systematic framework to support strategic decision making in innovation development that attempts to put appropriate amounts of planning resource into the process at different stages. It is constructed to make use of qualitative evaluation techniques, based on risk management methodology, early in the process when faster, less expensive methods are preferred to more accurate quantitative techniques. It is also constructed to make use of a small number of reusable process building blocks, including a simple process for approximating expert consensus without requiring face-to-face meetings of experts. It makes use of modern contingency planning techniques in order reduce wasteful investment in ideas that will eventually be discarded during the innovation process. The starting point of the paper was a large interview study about innovation management practices in major Finnish organizations. The study identified management of future uncertainty as one of the main challenges of corporate executives, which initiated the present research for the development of practical techniques to support strategic decision making at multiple critical decision points of innovation development under high level of uncertain information. The work is a joint study involving IBM Research and VTT Technical Research Centre of Finland. As a result, separately developed techniques were integrated to produce a more systematic, more comprehensive, but highly efficient innovation management framework.
We present systematic decision support for innovation management. At the core of our system is a dynamically evolving risk taxonomy that we map to either qualitative or quantitative decision processes. We describe several experiments that could advance the science behind innovation management. In the context of a portfolio of potential and actual service offerings, we discuss how to spread, hedge, or mitigate risk, and how these activities constitute enterprise innovation management.
Building on state-of-the-art techniques for forecasting future developments in technology, business, economics, and other areas of human endeavor, we describe a novel methodology for adaptive contingency planning at the strategic initiative level. Complementing normal business planning that uses a schedule based on predictions tied to dates in the future, we use a new kind of early warning signal called a signpost to trigger the execution of corresponding new recommended actions
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