Strategic Intelligence

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Project Visions and Visioning
File:Vision.jpg This article is developed within the scope of the Project Visions and Visioning, an effort to enhance Foresight learning through collaborative work.



Strategic intelligence (SI) can be defined as "the set of actions to search, process, diffuse and protect information in order to make it available to the right person at the right time in order to make a decision".


Strategic intelligence applications have been developed to support decision-making. These applications are:

  • forecast
  • impact assessment
  • foresight exercises

The following forms of strategic intelligence are prospective or forward looking and targeted on policy decisions:

  • Technology forecasting - consists of a continuous monitoring of technological developments and their conditions, leading to an early identification of promising future applications and an assessment of their potential.
  • Technology assessment - consists of an analysis of social, economic and environmental potentials of new scientific and technological developments in order to obtain results that support the decision-making process on technology and to develop options for better exploiting opportunities arising from new technologies. It can be:
    • technology-driven - with focus on a specific technology
    • problem-driven - with focus on societal problems arising from the application of technology
  • Technology foresight - is based on a much broader concept that implies a wide range of themes and stakeholders in order to examine the social, economic and environmental aspects of new technologies. This form of strategic intelligence is frequently used to support policy-related decision-making at the national or supra-national level.

As background to the innovation-based knowledge-economy, the speed of technological development and its role for the society and the economy leave less time for political decision-making. This is the more true in rapidly advancing fields and with respect to technological breakthroughs and "unpredictable" developments. Strategic Policy Intelligence includes tools that support the anticipation of breakthroughs, assigning it a kind of "early-warning" function.

Strategic Policy Intelligence offers a variety of methodologies to meet the demands of policy-making. This variety is a strength of the concept, creating flexibility and promoting independence.

Concepts of decision-making

Evidence-based policy

A policy is a deliberate plan of action, guiding decisions and achieving rational outcomes. From a strategic perspective, the role of a policy is to resolve contradictions between the organisation and its environment. Broadly, policies are typically instituted in order to seek positive benefit and to avoid negative effects. The purpose is not simply to provide a basis for making efficient decisions, but also to provide knowledge needed to improve the organisational, political and social systems. The notion of evidence-based policy fits well with a rational decision-making model (Davies et al. 2000). The solution of a complex social problem requires not only better evidence of what works in terms of policy intervention, but also requires more rational decision-making in which such evidence can play a stronger role (Sanderson 2004). Colebatch (2006) describes three types of policy knowledge (based on Tenbensel 2006):

  • Epistemic knowledge - the universal knowledge produces by analytic rationality. It is the type that establishes causal links and chains and is the knowledge aspired to by mainstream rationalist policy analysts in their search for the likely consequences of the different policy alternatives they evaluate.
  • Tacit knowledge - the practical-technical knowledge derived from experience and skill. This is not simply the practical applications of epistemic knowledge. The tacit knowledge rests very much in implicit personal or institutional practices often associated with craft like skills, awareness of reputations, hands on techniques, etc. It is the knowledge which cannot be explicitly codified.
  • Phronetic knowledge - this is a sense of the ethical. It is based on practical value rationality. ‘Where are we going?’, ‘Is this desirable?’, and ‘What should be done?’ are phronetic questions. This type of knowledge is important because it is often needed to underpin the definition of a policy problem.

The point here is that policy arguments are likely to involve all of these sorts of knowledge, but that participants are unlikely to be equally skilled in all of them. The reason for this is because each type of knowledge asks a different question. Episteme asks ‘what is true?’; tacit knowledge asks ‘what works?; and phronetic asks ‘what should be done?’ Good policy argument rests on a foundation of all three types of knowledge (Colebatch 2006). In many policy areas participation of actors from society has become common practice. Participation can take place in different forms and at different levels. A general definition of public participation is the practice of involving members of the public in the agenda setting, decision-making, and policy forming activities of organizations responsible for policy development (Rowe and Freyer 2005). The stakeholders are members of the public who own the problem under discussion and having a stake in the future. Stakeholders can be individuals, informal groups or well established organisations. The number of stakeholders involved in a certain issue is not necessarily fixed but might change over time. As the policy process evolves, new stakeholders will enter the scene and others will leave. Stakeholder participation is considered to be a key driver behind improving evidence for policy (Enserink 2003). Decisions will be better in two respects: first, they will command greater respect from the stakeholders involved and hence carry more legitimacy; and second, they will benefit from the insights and knowledge brought by the different stakeholders (Burton et al. 2006).

The Decision Makers

There are inherent tensions between traditional, more pluralist forms of public participation and new deliberative democratic processes. These innovative processes are challenging existing roles of the decision-makers in society. But the appreciation of these processes depends largely on the ingoing position taken towards the role of politicians in general. Hendriks (2002) makes an abstraction of a politician’s role by describing two opposite positions: on one side a centralised and top-down steering approach, and on the other side a facilitating and networking approach. For each of these two opposite approaches he also describes a hard and soft approach.

  • Centralised: proponents of powerful politics are in favour of the classic notion of representative democracy. Politicians are elected representing the public interest and take precedence. The hard variant stands for a strong centralised leadership with a strong concentration of the decision power, while the soft variant tolerates more interactive consultation.
  • Decentralised: proponents of the modest role of politics are in favour of a facilitating role for politicians in decision-making. The hard variant stands for politicians who only steer and intervene when and if necessary, but who otherwise remain on the sidelines. The soft variant is more managerial oriented and in favour of politicians who are limiting their selves to network management: politicians as a creator of preconditions and rules of game, as a process facilitator.

The conceptual difference between stakeholders and decision-makers is clear. The former has a stake and can have an influence to the decision-makers. The latter has the responsibility and power to make the decisions. In practice policy decisions are often shrouded in uncertainty. It is not always clear that a decision has been taken. It is sometimes unclear what the decision is and who has taken it (Burton et al. 2006). In reality the role of a politician is dynamic and deviates depending on internal and external developments such as the actual political agenda setting, temporally coalitions, discontinuities and so one. The boundaries between stakeholders and decisionmakers are less fixed and literature often includes also others non-politicians who are demonstrating political support to the process. Also agencies or government departments who are playing a role in the development of programs or in the allocation of funding can be seen as part of the decision-making, although this is sometimes contested

The Risk of Decision Failure

Decision failure is more common than people often tend or wish to believe. Some decision-makers always expect good results ignoring the possibility that outcomes of a good decision may change. If a decision-maker gets caught up in decision failure, most often they reveal as little as possible. Additional it is also difficult to separate good decisions with bad outcomes from bad decisions with good outcomes. Anyhow, research on decision errors in organisations reveals high levels of failure, even up to fifty percent, in day to day decision-making (Nutt 2004). Decision failures occur in two overarching categories:

  • simple explainable errors or mistakes - the possibility that the decision-maker was unable to make the decision. This category of inevitable errors denotes the statistical necessity that some random error will occur.
  • unexplainable or unexpected decision errors - decision failures that occur in this category are more important because there is seemingly no logical explanation for the decision failure. The unexpected happened and the mental model turned out not to be robust enough (Chermack 2004).

There are four potential contributors, each independently or combined contributing to decision failures, as follows:

  • Bounded rationality - people cannot effectively cope with all of the available information and alternatives
  • Neglecting internal change - people have a tendency to believe that all internal processes are well being recognised
  • Stickiness and friction of information and knowledge - there are cost and limitations in the transfer of information and knowledge between people
  • Mental models - people are often selective and include and exclude information based on their mental model

Policy change

Perspectives to analyse the effectiveness of SI applications in decision-making:

  • window of opportunity
  • clarity of purpose
  • legitimacy of evidence

Reference - Strategic Policy Intelligence: Current trends, the State of Play and Perspectives, S&T Intelligence for Policy-making Processes, Executive Summary, by Alexander Tubke (JRC-IPTS)

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