At Royal Dutch Shell for example, scenario planning has been described as changing mindsets about the exogenous part of the world prior to formulating specific strategies.
[5][6] Scenario planning may involve aspects of systems thinking, specifically the recognition that many factors may combine in complex ways to create sometimes surprising futures (due to non-linear feedback loops).
The method also allows the inclusion of factors that are difficult to formalize, such as novel insights about the future, deep shifts in values, and unprecedented regulations or inventions.
Critics of using a subjective and heuristic methodology to deal with uncertainty and complexity argue that the technique has not been examined rigorously, nor influenced sufficiently by scientific evidence.
Scenarios usually include plausible, but unexpectedly important, situations and problems that exist in some nascent form in the present day.
When anticipated years in advance, those weaknesses can be avoided or their impacts reduced more effectively than when similar real-life problems are considered under the duress of an emergency.
For example, a company may discover that it needs to change contractual terms to protect against a new class of risks, or collect cash reserves to purchase anticipated technologies or equipment.
Flexible business continuity plans with "PREsponse protocols" can help cope with similar operational problems and deliver measurable future value.
This chief value of scenario planning is that it allows policy-makers to make and learn from mistakes without risking career-limiting failures in real life.
Further, policymakers can make these mistakes in a safe, unthreatening, game-like environment, while responding to a wide variety of concretely presented situations based on facts.
[5] These simplistic guesses are surprisingly good most of the time, but fail to consider qualitative social changes that can affect a business or government.
During the mid-1960s various authors from the French and American institutions began to publish scenario planning concepts such as 'La Prospective' by Berger in 1964[23] and 'The Next Thirty-Three Years' by Kahn and Wiener in 1967.
Several large companies also began to embrace scenario planning including DHL Express, Dutch Royal Shell and General Electric.
[19][21][25][26] Possibly as a result of these very sophisticated approaches, and of the difficult techniques they employed (which usually demanded the resources of a central planning staff), scenarios earned a reputation for difficulty (and cost) in use.
Even so, the theoretical importance of the use of alternative scenarios, to help address the uncertainty implicit in long-range forecasts, was dramatically underlined by the widespread confusion which followed the Oil Shock of 1973.
[27] Practical development of scenario forecasting, to guide strategy rather than for the more limited academic uses which had previously been the case, was started by Pierre Wack in 1971 at the Royal Dutch Shell group of companies – and it, too, was given impetus by the Oil Shock two years later.
In addition, with so few organisations making consistent use of them – and with the timescales involved reaching into decades – it is unlikely that any definitive supporting evidenced will be forthcoming in the foreseeable future.
As derived from the approach most commonly used by Shell,[29] it follows six steps:[30] The first stage is to examine the results of environmental analysis to determine which are the most important factors that will decide the nature of the future environment within which the organisation operates.
When, however, they are asked to consider timescales in excess of ten years they almost all seem to accept the logic of the scenario planning process, and no longer fall back on that of extrapolation.
A very simple technique which is especially useful at this – brainstorming – stage, and in general for handling scenario planning debates is derived from use in Shell where this type of approach is often used.
At the start of the meeting itself, any topics which have already been identified during the environmental analysis stage are written (preferably with a thick magic marker, so they can be read from a distance) on separate Post-It Notes.
It is where managers' 'intuition' – their ability to make sense of complex patterns of 'soft' data which more rigorous analysis would be unable to handle – plays an important role.
This is, however, a potentially difficult concept to grasp, where managers are used to looking for opposites; a good and a bad scenario, say, or an optimistic one versus a pessimistic one – and indeed this is the approach (for small businesses) advocated by Foster.
Some, though use an expanded series of lists and some enliven their reports by adding some fictional 'character' to the material – perhaps taking literally the idea that they are stories about the future – though they are still clearly intended to be factual.
The final stage of the process is to examine these scenarios to determine what are the most critical outcomes; the 'branching points' relating to the 'issues' which will have the greatest impact (potentially generating 'crises') on the future of the organisation.
During the past 5 years, computer supported Morphological Analysis has been employed as aid in scenario development by the Swedish Defence Research Agency in Stockholm.
It is a judgmental forecasting procedure in the form of an anonymous, written, multi-stage survey process, where feedback of group opinion is provided after each round.
The author comes to the conclusion that the Delphi technique has instrumental value in providing different alternative futures and the argumentation of scenarios.
Further benefits lie in the simplification of the scenario writing process and the deep understanding of the interrelations between the forecast items and social factors.
In traditional prediction, given the data used to model the problem, with a reasoned specification and technique, an analyst can state, within a certain percentage of statistical error, the likelihood of a coefficient being within a certain numerical bound.