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This article aims to focus on how to ensure that Future‐Oriented Technology Assessment (FTA) activities have an impact on decision‐making. On the basis of the extensive experience of the authors, this article seeks to offer suggestions regarding the factors that may help policy makers, academics, consultants, and others involved in FTA projects, to produce useful and meaningful contributions to decision‐making processes.

The methodology deployed for this article is empirical. It is based on the lessons extracted and evidence produced by the authors' hundreds of diverse global consulting engagements as well as their analytical work on the subject. Added together the authors of this paper have engaged in over 80 years of professional practice. The article summarizes the results of presentations given by the authors and the ensuing discussion that occurred at the conference: Futures Oriented Technology Analysis 2011, held at the Institute for Prospective Technological Studies (IPTS) in Seville on 13 May.

Impactful FTA starts with the selection of the appropriate methodologies and skills for the specific anticipatory task. Arguing on the basis of experience, the authors point out that the effective impact of FTA projects on decision‐making depends on a strong grasp of the principles of foresight and project design, an educated client with clear expectations and a strong commitment, well‐developed communication efforts throughout, and considerable managerial capacity both on the demand and supply sides of the process.

By bringing the evidence of experience to bear, this article adds value to existing academic and practitioner discussions of the effectiveness of FTA for decision‐making. The article provides an original vantage point on key questions being posed by both users and suppliers of forward‐looking activities.

The paper seeks to explore competitive intelligence as a complex business construct and as a precedent for marketing strategy formulation.

In total, 1,025 executives were surveyed about their companies' usage of competitive intelligence collection, analysis, and dissemination as well as their perception concerning certain organizational characteristics.

This research develops and tests intelligence as a precedent to marketing strategy formulation, revealing multiple phases and contributing aspects within the process. It also discovers that the practice of competitive intelligence, while strong in the area of information collection, is weak from a process and analytical perspective.

While the sample was indeed a census of Canadian technology firms, care must be taken in generalizing the study beyond this industry, and certainly beyond the Canadian borders. Also, the questionnaire used only dichotomous variables (yes/no answers), which limited the testing that could be done.

Using these results, competitive intelligence departments and professionals can improve efficacy within their approach and execution strategies.

The contribution of this paper is two‐fold. It reveals many of the “state‐of‐the‐art” levels of practice within current competitive intelligence efforts, and it proposes a model of the intelligence process.

The article traces the origins of the competitive intelligence fields and identifies both the practitioner, academic and inter‐disciplinary views on CI practice. An examination of the literature relating to the field is presented, including the identification of the linear relationship which CI has with marketing and strategic planning activities.

Bibliometric assessment of the discipline. Findings reveal the representation of cross disciplinary literature which emphasises the multi‐faceted role which competitive intelligence plays in a modern organization.

The analysis supports the view of competitive intelligence being an activity consisting dominantly of environmental scanning and strategic management literature. New fields of study and activity are rapidly becoming part of the competitive intelligence framework.

The analysis only uses ABI Inform as the primary sources for literature alongside Society of Competitive Intelligence Professionals (SCIP) and Competitive Intelligence Foundation (CIF) publications, particularly the Journal of Competitive Intelligence and Management. A more comprehensive bibliometric analysis might reveal additional insights. Simple counts were used for analytical purposes rather than co‐citation analysis.

Attention is drawn to the need for the integration of additional, complementary fields of study and competitive intelligence practice. It is clear that today's competitive intelligence practitioner cannot afford to rely on what they learned 20 years ago in order to ensure the continued competitive advantage of their firm. A keen understanding of all business functions, especially marketing and planning is advocated.

While there have been bibliographies of competitive intelligence literature there have been few attempts to relate this to the three distinct areas of practice. This article is of use to scholars in assisting them to disentangle the various aspect of competitive intelligence and also to managers who wish to gain an appreciation of the potential which competitive intelligence can bring to marking and business success.

Seeks to examine three empirical studies carried out in Canada, the UK and Europe with comparisons drawn on their approach and findings.

The studies were compared using a framework, developed by the authors, along four central elements and two influencing drivers.

Little measurement consistency or output value was evident. The current focus on isolated studies, carried out at a macro level, is discouraged.

Future studies need greater rigour, and consequently might be of more value to academics and practitioners.

The lack of research consistency is highlighted. Recommendations are made for stronger adhesion with other disciplines to develop a robust research agenda.

The objective of this paper is to contribute to improved practice and impact of foresight through the development and testing of a Foresight Impact Evaluation Schema. The schema is designed to guide foresight practitioners in the more effective design and conduct of foresight exercises to optimise impact.

The development of the schema is based on the significant previous work in this field, and the author's experience of designing and managing more than 100 foresight projects. It also takes into account accumulated experience with heuristics developed to guide foresight design and management, and with various approaches to evaluating the impact of social science knowledge on policy‐ and decision‐making.

A range of impacts identified from major foresight projects have been characterised according to four categories of impact ‐ awareness raising, informing policy, enabling greater capacity to address uncertainty, and influencing policy, strategy, investment, program delivery and public attitudes.

The schema needs to be tested against a variety of foresight projects to further refine its usefulness.

With the rapid growth of the application of foresight, it has become essential to guide practitioners in the appropriate design and management of all the processes associated with foresight to achieve maximum impact, and to demonstrate the value of the investment in foresight to consequent policy and planning.

This paper builds on earlier and contemporary work to develop a more refined and applicable schema to guide foresight impact evaluation.

The paper seeks to examine the relationship between the number of competitive intelligence (CI) information topics used by small Canadian firms and their innovation performance, measured by the number of newly launched products, processes and services.

A CI information framework was applied including 42 information topics classified into four groups, i.e. industry, competitors, customers and firm. The 45 firms in the sample were classified into three types, i.e. new technology‐based, specialized supplier, and service firms. Statistical analysis was used to analyze the relationship between CI information and innovation.

Analysis of the results suggested that there was a clear relationship between the CI information firms used and their innovation performance, specialized suppliers firms were the most efficient users of CI information, information about industry and competitors was the least used but highly relevant for firms' innovation performance, and information about customers was found to be highly used and relevant for the innovation of all firms.

The methodological validation of the CI information framework could help executive managers in the development of analytical tools enhancing the role of CI for new product/process/service launch.

The results demonstrate the need for using appropriate firm classifications and in depth statistical analysis when studying the relationship between CI information and innovation.

This paper is intended to enable competitive intelligence practitioners using an important method for everyday work when confronted with conditional uncertainties: the Bayes' theorem.

The paper shows how the mathematical concept of the Bayes theorem applies to competitive intelligence problems. The main approach is to illustrate the concepts by a near‐real world example. The paper also provides background for further reading, especially for psychological problems connected with Bayes' theorem.

The main finding is that conditional uncertainties represent a common problem in competitive intelligence. They should be computed explicitly rather than estimated intuitively. Otherwise, serious misinterpretations and complete project failures might follow.

In psychological literature it is a known fact that conditional uncertainties sometimes cannot be handled correctly. Conditional uncertainties seem to be handled well when they are about human properties. This should be verified or falsified in the competitive intelligence context.

In general, the application of Bayes' theorem should be seen as one of the foundations of competitive intelligence education. Especially, when it is clear in which intelligence research situations conditional uncertainties can or cannot be handled intuitively, competitive intelligence education and practice should be adapted to these findings.

CI practitioners can underestimate the value of Bayes' theorem in practice as they are often unaware of the (psychological) problems around handling conditional uncertainties intuitively. The article demonstrates how to take a computational approach to conditional uncertainties in CI projects. Thus, it can be used as part of appropriate CI training material.

Foresight often encompasses participative approaches for decision making. This paper aims to give a first overview of the authors’ research on immediate learning and networking in the context of foresight. The paper seeks to introduce a practical concept for an accompanying social research of a participatory foresight process for empirically identifying and mapping impacts; and to present empirical results from the study of a specific foresight process.

The authors apply three approaches to analyze impacts. Accordingly data were gathered in moderated workshops for process analysis; structured telephone interviews for qualitative analysis; and surveys for social network analysis.

The accompanying social research produced direct insights on experiences and knowledge acquisition of participants in a large, complex foresight process, as well as a measurable increase of personal ties in this process. This research shows that the perception of the wider spectrum of actors in a social system, as well as their rationales and approaches, are one identifiable and crucial achievement of participative foresight processes.

This research focuses on immediate learning impacts, while additional impacts of mid‐ or longer‐term scales were not captured in this study. Accompanying social research (e.g. longitudinal studies) of broader scale would be beneficial to foresight research and process design.

The authors use a specific foresight process to analyze its immediate impacts. They introduce and demonstrate ways forward to use practical concepts for impact description, empirical data acquisition, and how it relates to underlying process design. The results are relevant for foresight project managers, process counselors and accompanying social research.

The paper seeks to show how the increasingly popular use of data and information acquired from open sources (OS) impacts competitive and marketing intelligence (C/MI). It describes the current state of the art in analysis efforts of open source intelligence (OSINT) in business/commercial enterprises, examines the planning and execution challenges organizations are experiencing associated with effectively using and fusing OSINT in C/MI decision‐making processes, and provides guidelines associated with the successful use of OSINT.

This is a descriptive, conceptual paper that utilizes and develops arguments based on the search of three unclassified bodies of literature in competitive and marketing intelligence, intelligence processing and marketing analysis.

Open sources are useful in marketing analyses because they can be easily accessible, inexpensive, quickly accessed and voluminous in availability. There are several conceptual and practical challenges the analyst faces in employing them. These can be addressed through awareness of these issues as well as a willingness to invest resources into studying how to improve the data gathering/analysis interface.

Marketing analysts increasingly rely on open sources of data in developing plans, strategy and tactics. This article provides a description of the challenges they face in utilizing this data, as well as provides a discussion of the effective practices that some organizations have demonstrated in applying and fusing open sources in their C/MI analysis process.

There are very few papers published focusing on applying OSINT in enterprises for competitive and marketing intelligence purposes. More uniquely, this paper is written from the perspective of the marketing analyst and how they use open source data in the competitive and marketing sense‐making process and not the perspective of individuals specialized in gathering these data.

The paper seeks to address the viability of planning and executing the integration of four often independent marketing information management techniques, i.e. competitive intelligence (CI), customer relationship management (CRM), data mining (DM) and market research (MR).

The research presented is a longitudinal, exploratory and descriptive case study, covering a three‐year period during a critical development phase of a medium‐size, national employer association which sought to improve the quality of marketing‐based insights to its strategic planning capability as well as improve economic outcomes.

It is possible to achieve profitable and capability enhancing integration of diverse marketing information management techniques. Successful integration and the use of a highly focused cross‐functional team generated better market strategies and bottom line benefits.

The need to generate greater insight from popular marketing information management and planning techniques is routinely experienced by marketing and other executive decision makers. This article provides a multi‐year roadmap of the successful execution of technique integration, including identifying barriers that arose as well as suggesting solutions for achieving progress.

There are very few case studies published that demonstrate the successful evolution and integration of CI, CRM, DM and MR into the enterprise's strategy‐making process. The unique element of this example is that it was achieved within the context of a medium‐sized, national, not‐for‐profit employer association.