FUTURES & FORESIGHT SCIENCE最新文献

This piece is a personal reflection on the work and impact of Kees van der Heijden as part of the retrospective book review by Rowland and Spaniol (2021).

October 9, 2021

The “it depends on the client” mantra highlighted by Matt Spaniol in this essay about Kees van der Heijden's approach to scenario planning brought me back to an experience, from 1986 to 1991, when Kees and the late Jaap Leemhuis were the clients with whom Richard Normann and I worked in the so-called “Shell Manufacturing Reorientation Project”.

The way Jaap and Kees acted as clients, with Richard and I as advisors, taught me a lot about how clients and advisors can collaborate effectively and work together in scenario planning and beyond.

My recollection of this intervention benefits from its having been written up already twice. The first write-up of that experience was by Peter Checkland and Scholes (1999). I find it fascinating how Checkland, who was a consultant to Shell alongside Normann and Ramirez, saw “the same” engagement so differently from how I remember seeing it. This difference is reminiscent of Gareth Morgan's excellent 1983 book “Beyond Method” (Morgan, 1983), where he contrasted 20 well-accepted methods in the social sciences with which to consider organizational phenomena, and where he showed how a given situation is seen uniquely with the lens of one method, while it is inescapably to be seen very differently with the lens of another. Importantly, for efforts in scenario planning to mix methods and to attempt to produce “hybrid” methods, Morgan found that as there is no meta-method providing a “neutral” (meta-)stance from which to assess different methods. Instead, he found that any comparison among methods must inevitably be from the stance of one single method. The one method whose stance is used to assess the other methods frames all of them, and this perspective in effect entails a “hostile” takeover of the other methods which are compared from its own specific stance. Morgan's conclusion was that all we can do is see a situation from the individual points of view afforded by different methods, and then seek to learn about the situation we are examining from and with these differences. Not coincidentally, this is also what scenario planning seeks to help its users to do—to see the here and now from the point of view of different and contrasting stances in the conceptual future.

My experience of this intervention was also about how difficult it is to work with soft systems and scenario planning concurrently (cf., Lang & Allen, 2008). But if anyone has the intelligence, skill, nuance, and patience to do so, Kees certainly would come top of mind as someone who can succeed—and indeed he adapted the CATWOE mnemonic from soft systems methodology in the second edition of his book, repurposing it into the VOCATE analysis as part of contracting with a client. My colleague Trudi Lang tells me that this emerged after a strategic conversation organized at Curtin Business School in Perth in which Kees and Peter were hosted to explore the two met

Rowland and Spaniol's (2021) in-depth piece on Kees van der Heijden's seminal text, Scenarios, cued several memories for me, sparked a bit of self-reflection on my learning journey as a scenario planner, and encouraged me to reconsider Scenarios in the context of Open Strategy.

I first met Kees in 2008. I was working on my PhD in foresight. George Burt recommended I take a well-known scenario planning course, noting that this would be the last time Kees van der Heijden would offer it. I do not recall if this actually was the case, but it, along with a modest PhD discount, convinced me to join this training in Glasgow, where Kees van der Heijden and George Burt were delivering the lessons as a team.

Of course, by then van der Heijden's work had already influenced my PhD research on foresight. Those descriptions of scenario planning practices at Shell (Schoemaker, 1993; Schoemaker & Heijden, 1992; Schwartz, 2004, 2012; van der Heijden, 1996) were not only essential for my research but, at that time, also for establishing credibility in the/my German context vis-à-vis the field of foresight—a context in which scenario planning had not been even modestly institutionalized.

While I was grateful to have attended this particular scenario planning training program, in retrospect, I now realize that I had not yet truly connected to many aspects of the training and will note that I was not actually able to apply the training for the next several years.

My journey with scenario planning did not start until some 2 years after the training. By then, I had completed my PhD and joined the strategy department in the global headquarters of an insurance company, Allianz, in Munich, Germany. At Allianz, I was asked to establish foresight processes. After several discussions, we collectively decided to conduct a scenario planning exercise, focusing on current trends in the organization.

This was the moment when I returned to my training materials, specifically, to Scenarios: The Art of Strategic Conversation and The Sixth Sense (van der Heijden, 1996; van der Heijden et al., 2002). At this point, my applied learning journey began by applying scenario planning in Allianz and, subsequently, in other organizations, something that I have now been doing for more than 10 years. This included also working for Paul Schoemaker's consulting firm Decision Strategies International (DSI, later acquired by Heidrick and Struggles) and later with Felix Werle, a former member of the Shell Scenario Planning team, and his consulting firm the Institute for Innovation and Change Methodologies. Throughout the course of this ongoing learning journey, I have continued, without exception, to apply the practice of scenario planning in a manner that closely reflects the work of Kees van der Heijden.

While my first encoun

Kees van der Heijden is an icon in the futures and foresight academic and practitioner community. Educated at the Technische Universiteit Delft, his work at Royal Dutch Shell, the Global Business Network, the Strathclyde Business School at University of Strathclyde, the Saïd Business School and the Templeton College at University of Oxford, and the Netherlands Business School at Nijenrode University has shaped the scholarly field of futures studies as well as the practical world of scenario facilitation. This article is a 25-year reflective and retrospective book review of Kees van der Heijden's seminal text Scenarios: The Art of Strategic Conversation. The authors conducted interviews with colleagues, coworkers, collaborators, students, and friends of Kees van der Heijden to add depth and dimension to this retrospective work. To bring van der Heijden's work into scholarly conversation with the extant literature, we also situated this return to Scenarios in the context of related works and other reviews of both editions of the book.

Cross-impact analysis is widely employed to inform management and policy decisions based on the formulation of scenarios, defined as combinations of outcomes of relevant uncertainty factors. In this paper, we argue that the use of nonprobabilistic variants of cross-impact analysis is problematic in the context of risk assessment where the usual aim is to produce conservative risk estimates which may exceed but are not smaller than the actual risk level. Then, building on the characterization of probabilistic dependencies, we develop an approach to probabilistic cross-impact analysis which (i) admits several kinds of probabilistic statements about the outcomes of relevant uncertainty factors and their dependencies; (ii) maps such statements into constraints on the joint probability distribution over all possible scenarios; (iii) provides support for preserving the consistency of elicited statements; and (iv) uses mathematical optimization to compute lower and upper bounds on the overall risk level. This approach—which is illustrated with an example from the context of nuclear waste repositories—is useful in that it retains the informativeness of cross-impact statements while ensuring that these statements are interpreted within the coherent framework of probability theory.

Organizations increasingly adopt technologies and logistics measures to improve their social sustainability, reduce transportation-related carbon emissions, or even design their supply chains carbon negative. However, the speed at which this adoption is progressing is not fast enough to address the sustainability challenges of the world today. To gain deeper knowledge about the adoption process of sustainability-related measures in road freight transportation, this paper examines barriers currently hindering a broader market penetration and derives expected timeframes when mass adoption of 14 relevant technologies will occur. Furthermore, the technologies' impacts on the economic, environmental, and social dimensions of sustainability are discussed providing recommendations, on which technologies the respective stakeholders might focus on in the future. Since we want to examines a long-term technology perspective of the next 25 years, we rely on systematic foresight methodology. More specifically, we collect empirical data by use of a real-time Delphi survey, which particularly suits complex and uncertain environments. Our global panel includes 116 experts from 25 different countries. The assessments are grouped into short-term, midterm, midterm to long-term, and long-term developments. The categories shed light on potential drivers and barriers to the implementation of the surveyed technologies. The findings emphasize the need to systematically select suitable measures and promote those that are expected to deliver short-term sustainability improvements to address current deficits in a timely manner. The article further outlines the crucial role of politics in developing necessary regulative frameworks to drive sustainability in road freight transportation.

This paper outlines new perspectives for data-supported foresight by combining participatory expert-based futures dialogues with the power of artificial intelligence (AI) in what we call the hybrid AI-expert-based foresight approach. To this end, we present a framework of five typical steps in a fully fledged foresight process ranging from scoping to strategizing and show how AI can be integrated into each of the steps to enable the hybrid AI-expert foresight approach. Building on this, we present experiences gained from two recent research projects of TNO and Fraunhofer ISI that deal with aspects of the hybrid AI-expert foresight approach and give insights into the opportunities and challenges of the new perspectives for data-supported foresight that this approach enables. Finally, we summarize open questions and challenges for future research.

Forecasting plays a vital role in intelligence assessment and contributes to national security decision-making by improving strategic foresight. Remarkably, most intelligence organizations do not proactively track their forecasting accuracy and, therefore, do not know how accurate their forecasts are or what types of biases intelligence analysts (or organizations) might exhibit. We review research on geopolitical forecasting and a roughly decade-long program of research to assess the accuracy of strategic intelligence forecasts produced by and for the Government of Canada. This research is described in three phases corresponding to previously published research, following which novel analyses (drawing from the data used in the earlier phases) are reported. The findings reveal a high degree of forecasting accuracy as well as significant underconfidence. These results were evident regardless of whether analysts assigned numeric probabilities to their forecasts. However, the novel analyses clarified that there is a substantial cost to accuracy if end-users rely on their own interpretations of verbal probability terms used in the forecasts. We recommend that intelligence organizations proactively track forecasting accuracy as a means of supporting accountability and organizational learning. We further recommend that intelligence organizations use numeric probabilities in their forecasts to support better comprehension of these estimates by end-users.