[1] It uses the iterative, independent questioning of a panel of experts to assess the timing, probability, significance and implications of factors, trends and events in the relation to the problem being considered.
The application of the Delphi method requires a great deal of attention to the selection of participating experts and the questionnaires have to be scrupulously prepared and tested in advance.
Unlike panel sessions, the iterative Delphi method allows the forecasting and assessment to be done without the effect of strong personalities or reputations influencing other panelists and also overcomes the difficulty of getting all experts together in a single time and place.
CLA is based on the assumption that the way in which a problem is formulated changes the policy solutions and the actors in charge of initiating transformations.
Causal layered analysis increases the range and richness of scenarios; leads to inclusion of different ways of knowing among participants in workshops; appeals to wider range of individuals through incorporation of non-textual and artistic elements; extends the discussion beyond the obvious to the deeper and marginal; and leads to the policy actions that can be educated by alternative layers of analysis.
It aims at broad exploration of all major trends, issues, advancements, events and ideas across a wide range of activities.
Information is collected from many different sources, such as newspapers, magazines, Internet, television, conferences, reports, and also science-fiction books.
An example is the widely used FUTURE structure developed by futurist Patrick Dixon described in his book Futurewise - F(ast), U(rban), T(ribal), U(niversal), R(adical), E(thical).
Four types of indicators can be examined in the process of environmental scanning: Morphological analysis is a technique developed by Fritz Zwicky (1966, 1969) for exploring all the possible solutions to a multi-dimensional, non-quantified problem complex.
The term scenario was introduced into planning and decision-making by Herman Kahn in connection with military and strategic studies done by RAND in the 1950s.
It can be defined as a rich and detailed portrait of a plausible future world, one sufficiently vivid that a planner can clearly see and comprehend the problems, challenges and opportunities that such an environment would present.
They assist in selection of strategies, identification of possible futures, making people aware of uncertainties and opening up their imagination and initiating learning processes.
Such 'messages' can be found in books, journals, newspapers, private letters, publications of political parties, reports, surveys, interviews, television, Internet and so on.
Back-view mirror analysis allows dealing with the fears related to the future by creating a new perspective that looks to the past instead of starting the process in the present.
The method was developed by Theodore Gordon and Olaf Helmer in 1966 in an attempt to answer a question whether perceptions of how future events may interact with each other can be used in forecasting.
The technique can be used by individuals and groups at an elementary qualitative level as well as it can be employed to perform more complicated and intensive quantitative analysis.
FMEA helps select remedial actions that reduce cumulative impacts of life cycle consequences (risks) from a systems failure (fault).
The method is a form of structured brainstorming that aims at identifying and packaging secondary and tertiary consequences of trends and events.
A trend or event is placed in the middle of a piece of paper and then small spokes are drawn wheel-like from the centre.
It is a powerful technique that helps to ensure that a given problem or issue is broken into comprehensive detail and that important connections among the elements considered are presented in both current and potential situations.
The main purpose of simulation is to discern what would really happen in the real world if certain conditions, imitated by the model, developed.
The visioning process is based on the assumption that images of the future lead peoples' present behaviours, guide choices and influence decisions.
It involves analysis of two groups of trends: quantitative, mainly based on statistical data, and qualitative, these are at large concerned with social, institutional, organisational and political patterns.
This form of simple trend extrapolation helps to direct attention towards the forces, which can change the projected pattern.
A more elaborated curve that uses times series analysis can often reveal surprising historical and current data patterns.
ALL-WinWin collaborative efforts require group decision support systems (GDSS) that enable the knowledge management community of practice to assure sustainable mutually-beneficial results.