Learning from the future

Scenario analysis

Frank Romeike [Editor in Chief]30.01.2015, 10:38

The following quotation is attributed to the US strategist, cyberneticist and futurologist: "Anyone can learn from the past. What we need to today is learn from the future." Kahn is one of the pioneers of modern concepts of preparation for the future. He became known for his strategy of imaging a world after a nuclear war. His approach is to think the unthinkable.

The optimum method is scenarios and - in more general terms - simulations. They enable alternative futures to be made transparent and tangible. In turn, this facilitates preventive preparation for the future. As a result these methods are of interest to every decision-maker in a company, but particularly in banks. In practice, there are at least two kinds of people who can use them - the strategists whose job it is to lead a company into a future that will be as successful as possible, and the risk managers who are aiming to prevent any kind of negative future and stress scenarios.

Thinking in terms of (future) scenarios helps us to shift our focus from the past to the future. But what exactly do we mean by a scenario? The term originally referred to the sequence of scenes in a drama and, from the 18th Century onwards, was also used for the director's overview of a play. The military origins of scenario analysis go back to the Prussian General Carl Philipp Gottlieb von Clausewitz (1780 – 1831) and the Prussian Field Marshall Helmuth Karl Bernhard von Moltke (1800 – 1891), who used scenarios to anticipate enemy tactics and implement their own counter-measures [see Romeike/Spitzner 2013, p. 16].

The modern scenario concept was expanded and precisely defined by the US strategist, cyberneticist and futurologist Herman Kahn. In his 1967 study "The Year 2000. A Framework for Speculations on the next Thirty-Three Years" [see Kahn 1967] he provided key impetus for today's scenario techniques. Kahn defined a scenario as follows: "Scenarios describe hypothetically a succession of events with the objective of drawing attention to causal relationships and working towards decisions“ [see Kahn 1976].

From the 1970s onwards, scenario analysis techniques increasingly gained a foothold in companies' strategic planning, as a response to the growing dynamism and complexity of the situations they were facing. In particular, the report "The Limits to Growth" to the Club of Rome provided key impetus for the practical use of scenario analysis in the 1970s [see Meadows/Meadows/Randers/Behrens 1972]. His central thesis was that the absolute limit of the earth's growth will be reached during the next hundred years if humanity does not succeed in reducing its ecological footprint.

This was a true revolution and made the book a global bestseller. As a basis for their study, Donella and Dennis L. Meadows and their colleagues at the Jay W. Forrester Institute for System Dynamics at the Massachusetts Institute of Technology conducted a system analysis and ran computer simulations on selected scenarios. The "World3" model of the world used studied five scenarios or issues with a global impact: industrialisation, population growth, malnutrition, exploitation of raw material reserves and destruction of habitats.

The modern scenario concept can be illustrated very effectively using the following definition [see Götze 1993, p. 38f.]: "A scenario

  • represents a hypothetical picture of the future in a socioeconomic area and the development path to this picture of the future;
  • combines with other scenarios to define the scope for possible future development in the area studied;
  • is created systematically and transparently, taking into account the developments of several factors and the interrelationships between them, and is therefore plausible and free of contradictions;
  • includes both quantitative and qualitative statements that form a completely developed text;
  • provides a guide to future developments and/or assists in preparing for decisions."

Underdeveloped use of scenario analyses in practice

Forecasts are becoming increasingly difficult and vague. With this in mind, companies should no longer rely on deterministic planning instruments. Instead, they need to concentrate on managing uncertainties. The required methods already exist in the form of simulation tools. However, many companies shrink from using them. In terms of the reasons for failure to use simulations, the results of a study carried out by the RiskNET competence portal in conjunction with the Technical University of Hamburg-Harburg and C21 Consulting GmbH show that simulation methods are generally tarnished by the reputation of being too complex. In addition, many decision-makers have little experience of simulations. As a result, they make even greater use of familiar and supposedly more simple methods. This lack of experience with simulations is a very common reason for not using them [see Meyer/Romeike/Spitzner 2012]. The complexity of simulation models and availability of data are cited as the key challenges involved in using them.

Procedure for scenario analysis

In a business context, scenario analysis is a method used as an instrument for preparing and supporting decision-making, particularly in the areas of strategy and business development. It is predominantly used for issues relating to the future, but can also provide effective support in selecting an alternative option for an imminent decision. The basis idea is to describe an alternative situation and to then use this description to derive possible consequences for the issue being studied. The information obtained is generally used as a basis for developing actual recommendations for action.

Different procedural models exist depending on the author and the methodological school [see Romeike/Spitzner 2013, Götze 1993 and von Reibnitz 1992], but they all follow the three main steps of analysis phase, extrapolation and scenario creation, and evaluation and transfer of findings. Here, we will present and briefly describe a procedural model consisting of eight steps, see Figure 01 [the following explanations are based on Romeike/Spitzner 2013, p. 95 onwards].

Figure 01: Possible procedural model of scenario analysis [Source: Romeike/Spitzner 2013, p. 95]

Figure 01: Possible procedural model of scenario analysis [Source: Romeike/Spitzner 2013, p. 95]

The first step, definition of the issue to be studied, has two key aspects: Achieving clarity on what exactly is to be studied and establishing a shared understanding of it in the team. The second aspect involves finding a shared language, which in an interdisciplinary or even inter-sectoral or international team is not easy but is extremely important. A shared understanding is the only way to endure that the team is pulling in the same direction in the subsequent analysis.

Influencing factors describe relevant situations relating to the issue to be studied (2nd step). They are characterised by being changeable and that this change is important in terms of the issue. Identification of influencing factors frequently begins as an internal analysis using creativity techniques. If necessary, defined structures - such as the classic political, economic, social, technological and ecological - can help when collecting potential influencing factors. Based on these results, in-depth literature research and expert interviews can help to verify and supplement the influencing factors identified. As a result of this step there should be a shared understanding of the influencing factors, while duplicates, generic terms and sub-topics should be eliminated. To avoid misinterpretation in the subsequent analysis, influencing factors should be described neutrally.

The third step is to prioritize the influencing factors based on their important in respect of the issue. The aim is to concentrate on the most important influencing factors in the subsequent analysis. As a rule of thumb, no more than twenty influencing factors should be left after this process. This reduces the complexity of the subsequent analysis. Without this prioritization, there is a risk of falling into the complexity trap and that the analysis will fail. The instruments that can be used here are influencing factor analysis, also known as a networking matrix or Vester's paper computer, or an influence uncertainty analysis. It should be noted that in this step there is always a risk that relevant areas will be eliminated from the subsequent analysis. Regular monitoring of whether influencing factors were accidentally and incorrectly discarded here, is therefore essential later in the process.

In the fourth step the manifestations of each influencing factor that appear realistic are defined for the following scenario analysis. This definition can be based on studies, expert interviews, extrapolations, group discussions and intuition.

The fifth step involves creating possible scenarios by combining different manifestations of the influencing factors. This includes a study of whether they are as consistent as possible in themselves (6th step), which means whether the manifestations of the influencing factors contradict one another. This can be done by analysis in pairs or using a consistency matrix. From the consistent scenarios, those to be studied in detail are then selected.

The seventh step is to analyse the selected scenarios in terms of the issue to be studied and to derive the resulting consequences of them. It is often advisable to include disturbances such as external shocks or trend reversals in this analysis to obtain a feeling for the sensitivity or stability of the scenarios. However, this sensitivity analysis should exclude changes at the level of a disaster, as they frequently involve a change in the entire structure, in order words the assumptions made and the interdependencies taken into account may no longer apply. Based on the consequences identified, the eighth step is to gather possible actions and study them in terms of their impact. This results in specific recommendations for the issue under analysis. Particularly for negative scenarios, it is also advisable to identify indicators that signal the occurrence of the scenario. All of these results are combined into what is known as a scenario profile.

Challenges in practical use

Because the potential uses of scenario analysis are so broad and flexible, the challenges frequently vary according to the specific area in which it is used. Nevertheless, there are certain crucial elements that need to be taken into account in most situations [the following explanations are based on Romeike/Spitzner 2013, p. 100 onwards]:

  • Composition of analysis team: To obtain the broadest possible perspective of the issue to be studied during the discussion process for the scenario analysis, an interdisciplinary analysis team is recommended. It is essential to find a common language to reduce the risk of misunderstandings. To counter the problems of opposing interests from different areas, open communication is an essential recommendation as this is the only way to ensure acceptance of the contributions of all individual team members.
  • Shared understanding of the issue to be studied and the initial situation: The issue to be analysed should first be clearly delineated and then fixed. Otherwise, it is frequently the case that a lack of clarity about the issue leads to increasing complexity as a whole range of aspects are always included in the discussion "to be on the safe side". A shared understanding of the initial situation is also absolutely essential - this is the only way in which the starting point for the scenario funnel can actually be defined. All influencing factors considered in the scenario analysis should also be described for the initial situation.
  • Gradually increasing complexity: The more different manifestations of influencing factors are studied, the more complex the entire analysis becomes. The individual influencing factors should be verified for mutual influences and the consistency of their manifestations.  The former increases potentially, the latter exponentially. To effectively counter the complexity trap, the number of influencing factors - or at least the number of influencing factors with changing manifestations - can be gradually increased.
  • Manageable number of scenarios: If it is difficult to agree on the manifestations of the influencing factors, there appears to be a certain tendency to look at more scenarios. The strength of the simulation method in emphasising individual developments and thus providing a feel for the possible range of developments is then quickly lost. Based on experience, concentrating on a manageable number of scenarios rather than breaking down the analysis more and more is recommended.
A scenario analysis allows qualitative and quantitative data to be incorporated into the analysis and promotes thinking in terms of alternatives.Among other things, the quality of the scenarios depends on the expertise, imagination, creativity, team skills, communication skills and enthusiasm of the people involved; there is plenty of scope for failure here.
Considering situations from different perspectives frequently reveals relationships that are not apparent at first glance, while the usual interdisciplinary cooperation extends the perspective of the analysis team.Depending on the level of subjective influence from the participants, the results of the analysis may not be neutral and therefore the findings are not definitive and are always subject to attack.
Scenario analysis can easily be combined with other methods of obtaining information, such as forecasts, surveys or Delphi methods.Using the method takes time and is labour-intensive, which means that it is generally associated with high costs.

Table 01: Advantages and limits of scenario analyses


What makes companies successful is their ability to simultaneously seize opportunities and avoid risks. In some cases, this may happen by chance. However, in the long term systematically addressing the future using simulations or potential scenarios is essential. Perhaps taking the first step takes a bit of courage - using new and innovative methods and leaving behind familiar decision-making processes is not easy. Table 01 summarises the key advantages and limits of scenario analyses. Using scenario analyses opens up exciting prospects for companies, just as the French writer Victor-Marie Hugo said: "The future has many names. For the weak it is the unattainable, for the fearful the unknown, for the brave an opportunity."


  • Götze, Uwe (1993): Szenario-Technik in der strategischen Unternehmensplanung [Scenario Techniques in Strategic Business Planning], 2nd updated edition, Deutscher Universitätsverlag, Wiesbaden 1993.
  • Kahn, Herman (1976): The next 200 years: A scenario for America and the world, Morrow, New York 1976.
  • Kahn, Herman (1972): Things to Come: Thinking About the Seventies and Eighties, MacMillan Publishing Company, New York 1972.
  • Meadows, Donella H./Meadows, Dennis L./Randers, Jørgen/Behrens III, William W. (1972): The Limits to Growth, Universe Books, New York 1972.
  • Meyer, Matthias/Romeike, Frank/Spitzner, Jan (2012): Simulationen in der Unternehmenssteuerung [Simulations in Business Management]; empirical study in conjunction with TU Hamburg-Harburg, RiskNET and C21 Consulting, RiskNET GmbH, Brannenburg 2012.
  • Romeike, Frank/Spitzner, Jan (2013): Von Szenarioanalyse bis Wargaming – Betriebswirtschaftliche Simulationen im Praxiseinsatz [From Scenario Analysis To War Games - Practical Use Of Business Simulations], Wiley Verlag, Weinheim 2013.
  • von Reibnitz, Ute (1992): Szenario-Technik. Instrumente für die unternehmerische und persönliche Erfolgsplanung [Scenario Techniques. Instruments For Planning Business And Personal Success], Gabler Verlag, Wiesbaden 1992.
  • Weber, Jürgen/Kandel, Olaf/Spitzner, Jan/Vinkemeier, Rainer (2005): Unternehmenssteuerung mit Szenarien und Simulationen. Wie erfolgreiche Unternehmenslenker von der Zukunft lernen [Business Management Using Scenarios and Simulations. How Successful Managers Learn From The Future], Wiley Verlag, Weinheim 2005.


Frank Romeike, Managing Partner of RiskNET GmbH, board member and chairman of the Society of Risk Management and Regulation and editor in chief of RISIKO MANAGER magazine.

[ Source of images: © Argus - ]

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