A Heuristic Method for Scenario Projections
An exercise from the Graduate Planning program Global Issues and Futures Seminar.
In futures studies, scenarios are developed from a mix of verbal, empirical, theoretical, anecdotal information, fantasy, fact, and fiction. A scenario typically embodies a selection of variables, our understanding of their past trends and the interactions between them, and some assumptions about future changes. This information may be expressed in a combination of structured verbal and quantitative ways (such as cross-impact, Delphi, scenarios, and simulation). Generally the links between qualitative and quantitative information are quite vague and the methods advocated by futurists tend to polarize between quantitative modeling methods that focus on empirically measured variables (typically economic) and qualitative methods that make peripheral use of empirical data. Thus, one challenge in futures studies is to synthesize these various approaches in a more systematic manner in order to be able better to assess trends and alternatives.
With the heuristic method, described here, futures are developed from the assumed interactions between a selected set of issues. The term "heuristic" is not intended to mean "anything goes". While we could make an arbitrary selection of variables and plausible set of relationships between them, the idea is rather to help us to represent our ideas about important variables in a consistent fashion, to address the relationships between them systematically, and so to refine our ideas. The approach may be viewed as a variant of cross-impact analysis in that the key component is a table of showing the selected variables (or items) and the interactions (or cross-impacts) between them.
Total for Item 1
Total for Item 2
Total for Item 3
Total for Item 4
The aim is to fill the cross-impact table with ideas, explanations, and data consistent with a particular view of the world or scenario. We use this as an exercise to form opinions, share specialist knowledge, work as a group, and make connections between complex issues. We do this by confronting and bringing together major concerns, opinions, data, theories, and methods. This helps us to understand the possibilities and limits of knowledge, quantification, dealing with many variables simultaneously, establishing relationships between variables, and considering implications of uncertainty. We can explore possibilities for developing strategies, or even use the method as the basis for global development simulation "game'.
A recent class exercise began by asking what variables the students considered critical to an understanding of future global trends? The selected items were Conflict, Culture, Education, Poverty, Technology, Population, Economy, and Environment. Each of these items and their mutual inter-relationships was then considered. How to conceptualize and define key variables? Even with agreement on the importance of "culture", "environment", "conflict", and so on, there can be considerable diversity on what they are. For example, conflict could be defined as the number of deaths from wars, institutional violence, crime etc. but could also include psychological stress or a propensity to violence, including the size of the military or arms races. Similarly, environment may be conceptualized as an abundance of ecological diversity depleted by demographic and economic advance, but with some intrinsic capacity for regeneration, or simply as a remaining level of mineral resources.
The variables are systemically related in that change in the level of each variable comes from the positive and negative influences from all others, as well as change internal to each, e.g. births and deaths in the population, economic growth via investment etc. Assessing the cross-impacts involves discussing questions such as "does conflict polarize culture or destroy cultures", "does conflict create poverty", "does conflict stimulate technological change"? For the heuristic method such judgments have to be translated in quantitative terms - what is the current annual growth of the variable, and what is the contribution of the other variables to this growth? As an intermediate step here it can be useful to if the relative importance is attributed as small (S), negative (N), large positive (PPP), etc. This leads to one or more tables summarizing the discussion, as well as alternative opinions about the importance of the various items. The entries may reflect the opinions of a particular group, the results of a questionnaire, or an individual's judgments.
ISSUES Conflict Culture Education Poverty Technology Environment Economy Population Conflict PP NN S P P N N N Culture PP P S S P P S P Education N S P N P S S NN Poverty P S N P S N N N Technology P N P P PP S P P Environment NNN P S N NN P P P Economy NN S P N P N PP N Population P S S P N N P PPP Net Growth S N PP P PPP N PPP PP
These values may then be translated into the numerical contribution to annual growth rates. It is convenient to set the levels of each variable at unity for the base year (say 1990) so that the numbers in the table are simply the contributions to annual growth. For each variable , the year on year growth is given by a formula such as
Growth of Population = Contribution from Conflict + Contribution from Environment + Contribution from Economy + etc. + Self Contribution from Population
where the Contribution from Conflict = Level of Conflict x Impact of Conflict on Population, and so on, so that,
Next Year's Level = Current Level x (1 + Growth + Uncertainty)
The last term in this equation is a measure of the uncertainty associated with each growth rate. This may reflect an empirical uncertainty, the diversity of views across a group, or a "wild card" phenomenon reflecting poor understanding or serendipity, not least in conflict and environmental relationships.
Uncertainty NNN NN NN NN NN NN N N ISSUES Conflict Culture Education Poverty Technology Environment Economy Population
This procedure is readily programmed in a spreadsheet. A trend forwards and backwards in time from the base year may now be calculated. The forward forecasting exercise provides a hint of where our assumed worldview is taking us "should present trends continue". The backcasting exercise tests whether our assumed relationships fit with our understanding of the past (emphatically, not a necessary requirement in futures studies).
Typically, the initial forward projection serves us with various predictions of catastrophe. This may cause us to revise our estimates in the table, or provide clues as to how relationships might have to be changed in the forward projection (future) in order to avoid the foreseen catastrophe. This is the most intriguing and difficult part of any futures study. The following animation attempts to reduce the level of poverty and loss of culture and environmental resources by reallocating economic and educational resources so as to further these goals.
You can download a working version of the heuristic futures model and the data set used in the class exercise.
The intention is to develop an interactive web site through which survey participants can construct an interactions table based on their chosen variables and interrelationships, and to develop the corresponding projections and multiple scenarios and alternatives using the information received.
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