SCENARIOS: LEARNING AND ACTING FROM THE FUTURE Part 3: Three Schools of Scenario Planning
In 1987 William Huss and Edward Honton published the paper “Scenario Planning — What style should you use?”, in which they distinguish three types of scenario development approaches, namely ‘Intuitive Logics’, ‘Trend-Impact Analysis’ and ‘Cross-Impact Analysis’.
In 2002, Heijden, Bradfield, Burt, and Wright (Heijden et al., 2002: 128–129; Bradfield, et al.: 805) stated that the categorization presented above had two problems: the first one relates to the omission of the “La Prospective” methodology which it is for these authors a true school of Scenario Planning; the second one relates to the fact that the “Trend Impact Analysis” and the “Cross Impact Analysis”, although being standalone techniques, share the same foundations, which are anchored in the mathematical improvement of extrapolated time series data. In this sense, these two techniques must be viewed as a coherent group of techniques which, for convenience, those authors called `probabilistic modified trends’ (PMT) methodology (Heijden, et al., 2002).
In this article we will present and characterize the three major schools or techniques of Scenario Planning identified by Bradfield et al. (20052): “Intuitive Logics”, the “Probabilistic Modified Trends” and the “La Prospective” methodologies.
The “Intuitive Logics” School
The “Intuitive-Logics” School (Huss, Honton, 1987, Heijden et al., 2002; Bradfield et al, 2005) or Anglo-Saxon school (Godet, 2000) has its major inspiration in the work of Herman Kahn, and “SRI International” and Royal Dutch/Shell its “pioneering” references. As mentioned above, Pierre Wack was the leader of the implementation process of the strategic planning by scenarios in Royal Dutch/Shell in the beginning of the 1970s (Wack, 1985a, 1985b).
This school of Scenario Planning presents some particular features which derive mainly from the fact that it was strongly stimulated and developed by the business sector. Initially by the Royal Dutch/Shell that adopted the strategic planning by scenarios as a permanent strategy in 1972/1973, and later developed with variations by other organizations as the GBN — Global Business Network (founded in 1987, GBN is a global Scenario Planning network, offering studies, consulting and training services), SRI International or Decision Strategies International (a consulting company founded by Paul Schoemaker, an author with several scientific articles published about Scenario Planning).
As mentioned above, Peter Schwartz was the successor of Wack in the Head of the Scenario Planning Department of Royal Group Dutch/Shell in London, having extended the amplitude of the scenarios beyond the energy questions. He was also professor in the Stanford University, the founder of the Stanford Research Institute (SRI International) and the Global Business Network.
The conceptual overview that Schwartz presents in his 1991 book forms the basis of the approach used by Global Business Network, which we can say is the most used framework or approach to develop and build scenarios worldwide.
According to Schwartz (1991), the first step of any Scenario Planning process is to identify a focal issue or decision. The objective of this first stage is to identify or uncover a decision, a strategy or a specific important question for the company. According to Schwartz, to make sure that the Scenario Planning exercise is relevant for the company, that decision or question must be really important or decisive for the company.
The second step is to identify the key forces in the micro or “transactional” environment. The purpose is to build a list of key factors that have the capability to influence the success or failure of the decision under analysis.
For companies, the so called micro-environment includes such factors usually addressed in a “sector analysis” or in a classic business plan (vd. structure of the industry, corporate activities, important decisions by suppliers, major clients, changing customer needs, type of market segmentation, etc.)
The third step is to identify or to brainstorm the driving forces in the so-called macro-environment. The purpose is to list and sort out the “Driving Forces” of the macro-environment influencing the “Key Factors” defined in the previous stage, trying to establish a “map” of interrelations between them.
According to Schwartz it’s important to conduct an analysis of social, economic, political and technological driving forces, trying to identify which of these forces of the macro-environment can be “hidden” behind the “Key Factors” of the micro-environment. We should also differentiate among these forces those that by their characteristics can be considered as “pre-determined” elements and those whose evolution is considered to be highly uncertain.
At this stage it is crucial to have a list of key trends and potential disruptions that could lead us to identify the “Crucial Uncertainties” in the macro-environment relevant to the subject of analysis, which constitute the “driving forces” of the Scenario Planning process.
This stage of the Scenario Planning process usually needs extensive research into markets, new technologies, political factors and economic forces.
Step four consists of ranking the key factors and the driving forces on the basis of two criteria: 1) the level of importance to the success of the decision or to clarify the central question of the process; 2) the uncertainty level associated to those drivers and trends. Schwartz defends that “Scenarios cannot differ over predetermined elements (…) because predetermined elements are bound to be the same in all scenarios” (Schwartz, 1991: 243).
The objective of this stage is to determine the two or three most important and relatively independent uncertainties that will form the two axes around which we will build the scenarios.
Step five is the development and selection of general scenario logics according to the matrix resulting from the two uncertainty axes. The Scenario logic allows us to give coherence and dynamism to the “plot” of each scenario.
In step six, “fleshing out the scenarios”, the objective is to complete the texture of the scenarios, including the Key-factors and the Driving Forces identified previously and also the scenario logic that was chosen, allowing the generation of the timeline for the story of each scenario. Schwartz argues that we should try to identify key events that can give consistency to scenarios.
Step seven explores the implications of the developed scenarios to the decision or major question. At this stage it is important to draw conclusions about the main decision or clarify the central issue, based on each of the scenarios built.
The final step is to select “leading indicators” that will allow us to know in advance which scenario is closer to happen in reality.
As mentioned above, Kees van der Heijden was also responsible for the Planning Group at Shell, regarding Scenario Planning as a tool or process to stimulate organizational strategic conversations. Heijden had a particularly important role in deepening the methodological framework of Scenario Planning, formalizing what Wack, and in particular Schwartz, developed and presented in a more intuitive way.
At the core of the Scenario Planning process, Kees van der Heijden (1996) identifies the concept of “business idea”. “The business idea is the organization’s mental model of the forces behind its current and future success” (Heijden, 1996) and according to this author this concept contributes to the “purposeful” level of a Scenario Planning process..
In the last two decades several variations of these “intuitive logics” Scenario Planning methods initially designed and implemented in Shell and later in the SRI and Global Business Network were developed and applied.
The “Probabilistic Modified Trends School”
Strongly influenced by the work of Helmer, Gordon, Dalkey and other researchers in Rand Corporation, this Scenario Planning school incorporates two distinct methodologies: The Trend Impact Analysis (TIA); and the Cross-Impact Analysis (CIA).
Trend Impact Analysis (TIA)
The Trend Impact Analysis (TIA) was developed in the beginning of the 1970s, and it’s strongly associated to the “Futures Group”, a company founded by Theodore Gordon settled in Connecticut (Heijden et al., 2002).
The TIA concept is relatively simple and it aims to modify simple extrapolation, involving basically four steps (Gordon, 1994):
the historical data relating to the issue being examined is collected;
an algorithm to select specific curve-fitting historical data and extrapolate this to generate ‘surprise-free’ future trends is used;
a list of unprecedented future events which could cause deviations from the extrapolated trend is developed; and
expert judgments to identify the probability of occurrence of these unprecedented events as a function of time and their expected impact, to produce adjusted extrapolations, are used.
It’s important to mention that the references in the literature to the use of TIA as a method to build and explore scenarios are relatively scarce (Heijden et al., 2002).
Cross-Impact Analysis (CIA)
The Cross-Impact Analysis (CIA) was developed by Gordon and Helmer in 1966 in RAND Corporation as a “forecasting game” to the Kaiser-Alumium company, having been later programmed by Gordon and Hayard (Heijden et al., 2002).
Since the pioneering work made by Gordon and Helmer were developed several causal and correlation cross-impact variants developed by other researchers, along with different proprietary methodologies including the following ones (Heijden et al., 2002):
IFS (Interactive Future Simulations — previously known as BASICS) developed by the Battele Memorial Institute (Millet, 2003);
INTERAX (Interactive Cross Impact Simulation) developed by Enzer in the California University;
SMIC (a French acronym for Cross Impact Systems and Matrices), developed by Duperrin and Godet (Godet, Duperrin, 1975, Godet, 1993);
Like TIA, the CIA methodology tries to evaluate the changes in the probability of occurrence of events which can cause deviations in the explorations of historical data. The basic process of the two methodologies is similar, but the CIA incorporates an additional layer of complexity in the sense that instead of accepting a priori the attached probabilities related to future events given by experts, it tries to determine the conditional or proportional probabilities of pairs of future events given that various events have or have not occurred, through crossed impacts calculations (Heijden et al., 2002).
These methodologies instead of generating a one point extrapolation based on historical data, allow the construction of alternative futures, and thus, when combined with judgments and narratives about events on those futures, they can be described as scenarios (Heijden et al., 2002).
The French School “La Prospective”
The French School of “La Prospective” has its foundational references in the French philosopher Gaston Berger, who founded the “Centre International de Prospective” in the 1950s. Berger also founded the magazine “Prospective” (published between 1958 and 1969), being considered by many authors as the “father” of the French school of “La Prospective” (Godet, 1993: 21).
The pioneering work of Berger was continued in the 1960s and 1970s by Pierre Massé and Bertrand de Jouvenel, among others.
Pierre Massé was the Director of the national economic planning in France in the 1960s (Commissariat Général du Plan) and introduced the use of the “Prospective” scenario approach in the development of the 4th French National Plan (1960–1965).
Bertrand de Jouvenel was one of the most influential figures in the history of “La Prospective”, having written “L’Art de la conjecture” in 1972. He was the founder of the “Projet Futuribles” (which became a catalyst in the development of the international futures movement) and the first president of World Futures Studies Federation (WFSF) (1973–74). Pioneer of “La Prospective”, he faced the future as a field of freedom and power, and he spoke insistently about the need to distinguish the notions of “future dominable” and “future dominante” and the importance of having a global and a long view (vision), in the decision making. The thrust of Jouvenel’s work therefore was the use of scenarios to construct positive images of the future or ‘scientific utopias’ and then specifying ways in which these could be brought about to improve the life of ordinary people (Jouvenel, 1967).
Another important reference in the French school of “La Prospective” is Jacques Lesourne who founded SEMA in 1958 and headed the company until 1975 (it was with SEMA that some of the first French Prospective studies were made). Lesourne was the Director of the Project Interfuturs in OCDE, and also professor at the CNAM — Conservatoire National des Arts et Métiers (1974–1998) and Director of the newspaper “Le Monde” (1991–1994). He was the author of the work “Face aux Futurs — Pour une maîtrise du vraisemblable et une gestion de l’imprévisible” (1979), and he was, with Christian Stoffaes, the coordinator of the work “La Prospective stratégique d’entreprise: concepts et études de cas.” (1996).
Hughes de Jouvenel heads the Group Futuribles since 1973, having been the creator of the magazine with the same name (proposed in 1974; first number published in 1975). As director of the Futuribles magazine, he defined two basic roles for the magazine: “To stimulate the politicians to take in consideration the long run in their decisions. And being a place for the creation of prospective visions, fighting the State monopoly in that domain and feeding the public debate on big issues as the environment, labour politics or the social protection system” (Mousli, Roels, 1995).
Michel Godet is considered the main international reference of the French school of “La Prospective”. In the mid-1970s Godet, then Head of the Department of Future Studies at SEMA (an active firm in the defence sector), began to develop scenarios for several French national institutions such as EdF and Elf. Although firmly rooted in the “La Prospective” methodology inspired by Berger, Godet began to develop his own largely mathematical and computer-based probabilistic approach to scenario development, which he suggests, “stands apart because of its more integrated approach and use of mixed systems analysis tools and procedures.”(Godet, 1993, Heijden et al., 2002)
Professor at CNAM and responsible for the “Chaire de Prospective Industrielle” at the LIPSOR (Godet created the “Chair de Prospective” at CNAM in 1982), Godet published important works, among others, “Crise de la Prévision, Essor de La Prospective” (1977), “Demain les Crises, de la Résignation à l’Antifatalité” (1980), “De l’Anticipation à l’Action” (1992), and the two volumes edited in 1997 “Manuel de Prospective Stratégique — Tome 1: Une Indiscipline Intellectuelle” and “Manuel de Prospective Stratégique — Tome 2: L’art et la Méthode”.
In 1992 Godet publishes the “Manuel de Prospective Stratégique — De l’Anticipation à l’Action” presenting the Scenarios Method, which is structured in an interconnected but modular set of Stages, some of which with specific software tools (vd. Software MICMAC for the Structural Analysis, the MACTOR for the analysis of the Actors Game or the MORPHOL for the Morphologic Analysis, and SMIC Prob Expert which was a new model based on the cross impact analysis developed by Godet and J.C. Duperrin in 1974).
Michel Godet presents a scenario methodology strongly anchored in a philosophical and conceptual background offered by authors like Berger and Jouvenel, and developed a modular and integrated approach to Scenario Planning. (Godet, 1997a: 18)
Figure 1: Integral Approach to “La Prospective Stratégique” (Scenarios Method: Stages 1, 3, 4 and 5)
Source: Translated and adapted from Godet, 1997a: 18.
A first phase of the Integrated Method, previous to the Structural Analysis and the use of MICMAC method consists in the accomplishment of a Diagnosis of the most important dynamics. This Diagnosis will have to include a delimitation of the system, an initial explanation about its functioning, and a brief reasoning about the causal and dependence relations between the identified elements (“variables”).
The second phase is dedicated to the Structural Analysis through the use of MICMAC method, having the following basic objectives:
• To reduce the complexity of the system;
• To detect the key-variables;
• To detect the actors at the origin of the evolution of the key-variables.
This last purpose makes the connection and it’s the starting point for the analysis of the actor’s strategies through the MACTOR method. Identified the relevant actors, the MACTOR implies a brief description of the actors projects and means of action, preparing an analysis about their positioning and relations of force between them.
Although presented in a linear and sequential way, the integrated Scenario Method developed by Michel Godet demands a permanent interaction between the different modules and enough flexibility to optimize the analysis around new data and information. In fact, it’s important to have in mind that the basic inputs of the Morphological Analysis that leads to the “structure” of the scenarios are possible/probable evolutions of the key variables and the challenges identified and analysed in the “structural analysis” and in the “actor’s game”.
One of the strengths of this method is its modularity and flexibility to multiple objects of analysis and its function as an aid to a working group allowing people to pose the right questions and structure a collective reasoning. Some of the limitations of the process are related to the time needed to its implementation (although its modular approach can be a solution) and some difficulties that can arise from the interconnection of its different modules.
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This paper is based on a chapter of the author’s PhD thesis “Scenarios as a tool to give context and sense to Weak Signals in a process of Competitive Intelligence”, Université Jean Moulin III, Lyon, November 2010.