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ISSN 1995-459X print
E-ISSN 2312-9972 online
ISSN 2500-2597 online English

Leonid Gokhberg


Jonathan Calof1,2, Gregory Richards 2, Jack Smith 2
  • 1 National Research University Higher School of Economics, 20 Myasnitskaya Str., Moscow, 101000, Russian Federation
  • 2 Telfer School of Management, University of Ottawa, 55 Laurier Avenue East, Ottawa, ON K1N 6N5, Canada

Foresight, Competitive Intelligence and Business Analytics — Tools for Making Industrial Programmes More Efficient

2015. Vol. 9. No. 1. P. 68–81 [issue contents]

Creating industrial programmes, especially in technology, is fraught with high levels of uncertainty. These programmes target the development of products that will not be sold for several years; therefore, one of the risks is that the products will no longer be in demand due to the emergence of more advanced technologies. The paper proposes an integrated approach involving the complementary functions of foresight, intelligence and business analytics. The tools of foresight and intelligence are focused on the external environment and enable industry and researchers to, among other things, understand the direction in which markets and technologies are evolving, and profile local industries to determine which policy instruments may be effective in these industries. Signals picked up today through externally focused intelligence studies can be used to confirm conclusions from longer term foresight initiatives such as scenarios, roadmaps and scans, thereby providing the information needed to establish the long-term industrial policy that science and technology related industries require. 

The authors propose a dashboard for monitoring an industrial programme’s use so that any problems can be corrected early on. The dashboard relies on both information available in open sources and that accessible to a government. Combining foresight, intelligence and business analytics is believed to not

only decrease uncertainty and risk but also make it more likely that the policy is implemented by its intended audience and  that industry opportunities are identified at an early stage. To illustrate how this approach works in practice, the paper discusses a hypothetical case of a state programme to develop the nutraceuticals industry in Canada.

Citation: Calof J., Richards G., Smith J. (2015) Foresight, Competitive Intelligence and Business Analytics — Tools for Making Industrial Programmes More Efficient.  Foresight-Russia , vol. 9, no 1, pp. 68–81. DOI: 10.17323/1995-459X.2015.1.68.81
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