Future-Oriented Technology Analysis Strategic Intelligence for an In
The application of foresight to address the challenges of uncertainty and rapid change has grown dramatically in the past decade. In that period, the techniques have been greatly refined and the scope has been broadened to encompass future-oriented techno
- PDF / 86,871 Bytes
- 14 Pages / 439.37 x 666.142 pts Page_size
- 70 Downloads / 135 Views
Strategic Intelligence in Decision Making P. De Smedt
7.1
Introduction
There are many reasons why strategic intelligence is required to support policy decisions. These primarily stem from the nature of today’s knowledge society with two contrasting trends. On one hand, there is a trend of increasing human intelligence in the economic, social and political systems (Hughes 2007). On the other hand, there is a trend towards dissolving certainties about the problems and solutions of today’s society (Hoijer et al. 2006). Clearly, more information does not always imply more certainties on how to act and even the same facts are often interpreted in markedly different ways. The same policy relevant information can and often does result in conflicting framing of a problem by different stakeholders. This is rather because of competing assumptions than because of inconsistent facts (Dunn 2004). Therefore, it is not surprising us that policy-makers are demanding for strategic intelligence to support their understanding of today’s challenges, including the relevant aspects and impact of science and technology and their possible future developments. Strategic Intelligence (SI) applications – such as forecast, impact assessment and foresight exercises – have been developed to support decision-making. Examples demonstrating the diversity and broad application of SI, can be found in a wide range of scientific literature, in project reports and occasionally in policy documents. Still, limited information can be found on the impact, limitations and effectiveness of SI applications. This chapter on strategic intelligence in decision-making reflects on policy analysis concepts, such as the evidence-based approach and the rational decisionmaking model, and explores the core problems concerning the effectiveness of SI applications to support decision-making. The hypothesis is that SI applications need to be better institutional embedded in terms of opportunity, purpose and legitimacy, so that SI applications do not become meaningless and useless for the decision-makers. The first part (Sects. 7.2–7.4) looks at different concepts of decision-making, including evidence for policies, the role of politicians and policy change. The first section lists witch types of evidence for policy can be distinguished, who can provide
C. Cagnin et al. (eds.) Future-Oriented Technology Analysis, doi:10.1007/978-3-540-68811-2, © Springer-Verlag Berlin Heidelberg 2008
89
90
P. De Smedt
the knowledge, and how the best evidence can be mobilised. The second section describes the different positions a politician can take in the policy process and also looks in at decision failure. The third section defines policy as a process and explores the nature of policies and the dynamics of policy change. In the second part (Sects. 7.5 and 7.6) three complementary perspectives are proposed to analyse the effectiveness of SI applications in decision-making. The three complementary perspectives – window of opportunity, clarity of purpose, and legitimacy of evidenc
Data Loading...
