This gallery contains 8 photos.
Maps are both necessary tools for analysis and crucial delivery visuals for foresight and warning products. They constitute a very powerful type of delivery form, as they change both the world and the mind. The pivotal importance of maps and … Continue reading
This gallery contains 7 photos.
(Updated 28 November 2012) Here we shall present maps (list, details and sample of maps below) related to global water security that are useful for both analysis and delivery of products. As new maps are created and found, they will … Continue reading
Check the embedded Pearltree below for automatically updated map – The featured image for this post is a snapshot of a map done with Pearltrees.
This page is about presenting ways to follow and access the series of posts constituting The Chronicles of Everstate, beyond the usual linear menus or the detailed outline in the website footer.
This idea, mapping the very posts of The Chronicles of Everstate, is a direct result of the interactive quality of this foresight experiment. One faithful reader, indeed, underlined that, as the number of posts increased, reading and understanding was becoming more complex, notably for newcomers. He suggested that a map would be very helpful to allow users and readers to navigate among posts. We then discussed various ways to implement this idea. Here are the results of this idea. From May onwards, only the navigating map using Pearltree will be updated, as it is the only one to allow doing so automatically. The previous maps are kept as example of what can be done.
Click on the image to access the interactive map of the posts on Pearltrees, or below see the embedded Pearltree. There, the various links between posts are displayed, although it is impossible to have multiple parents for a same post, unfortunately. The trick, which can be used, is to duplicate children nodes. However, it seems to me that all the other advantages, as shall be explained in detail in a dedicated post, including the possibility to embed the tree in a blog post, far outweigh the inconvenient.
Click on the image to access the interactive map of the posts on Webbrain. There, the various links between posts are displayed, and each post can be accessed by clicking on the hyperlink displayed in the window at the bottom of the page. Hyperlink access in indicated by a favicon before the label of the idea, which is also the title of the post.
The violet nodes correspond to categories and menus (that may include other posts). The dark blue nodes correspond to posts of The Chronicles of Everstate and the grey nodes either to parts of posts or to a topic subdivided in two or more posts.
The red nodes indicate either the first scenario, Mamominarch that has been narrated already or the second one that shall be told starting May 13. The last scenario (in green) is forthcoming. Turquoise nodes are forthcoming posts.
Once variables (also called factors and drivers according to authors) have been identified – and in our case mapped, most foresight methodologies aim at reducing their number, i.e. keeping only a few of those variables.
Indeed, considering cognitive limitations, as well as finite resources, one tries obtaining a number of variables that can be easily and relatively quickly combined by the human brain.
Furthermore, considering also the potential adverse reactions of practitioners to complex models, being able to present a properly simplified or reduced model (however remaining faithful to the initial one) is most often necessary.
When the foresight methodology does not include links between variables, thus if we don’t have a graph or a map, then the way to select variables is by ranking them according to specific criteria. Among the criteria most used, one finds likelihood and impact, or impact and uncertainty (i.e. one does not know how the variables will evolve). However, in a complex world, which includes feedback loops and where ripple effects exit, not linking variables is a serious handicap.
When variables are linked (as here), the method most commonly used is to identify the most influential variables – influence analysis – and then to reduce the foresight analysis to those variables. Hence, scenarios will be constructed around those influential variables. There are different ways to proceed.
Some systems, such as Parmenides Eidos™ and all similar approaches, e.g. Singapore RAHS 1.6 (watch the technological demonstration video, especially from 3:32mn onwards), use what graph and network theory call indegree and outdegree centrality measures. The indegree of a node (our variable) is the number of head endpoints adjacent to the node, i.e. how many edges (arrows) arrive to this node. It represents the number of variables that influence this node. The larger the indegree, the more influenced the variable is.
The outdegree of a node is the number of tail endpoints adjacent to the node, i.e. how many edges (arrows) leave from this node. It represents the number of variables that are influenced by this node. The larger the outdegree, the more influential the variable is.
However, as underlined by Arcade, Godet et al. (Structural Analysis with the MICMAC Method, 2009), this method only considers direct influence. What happens if one variable exerts only a single influence on one group of variables, but if this group of variable exerts a strong influence on the whole system? The importance of the initial variable would be downplayed if we were considering only direct influence.
In graph and network theory, various measurements – centrality measures – exist that allow identifying various types of importance of a node in relation to the whole network or graph. However, those measurements were created initially with social analysis in mind, not for foresight analysis.
After having tested them against the direct influence idea and with foresight in mind, the measure that is chosen here to determine the initial set of criteria is the Eigenvector centrality. Again, using Gephi allows for easy and instantaneous calculation of all centrality measures.
We should however underline that we lose here the information differentiating between influenced and influential nodes. This is why graph and network analysis use an array of measurement and not a single one, and why we used here Eigenvector centrality measures against indegree and outdegree when selecting Eigenvector centrality measures.
Further tests should be designed to refine the choice of measurement for this revisited influence analysis.
Once influence (or degree centrality in graph and network theory) is measured, the variables are positioned on a graph, the “influence graph,” with as abscissa (x axis) dependency or influence received, and as ordinate (y axis) influence.
This can be easily done with Gephi by choosing the layout called “Geo Layout” and entering, in the case of the degree measurements, “indegree” for longitude and “outdegree” for latitude.
The location of variables on the graph expresses their type of influence and they are labelled accordingly:
Influence graph (degree) with Eigenvector centrality (size of the node) for the entire graph
Once variables have been sorted out according to influence, then the variables that are seen as most important are usually selected and used to proceed to the next step. For example, on may redraw a map using only the drivers, pivots and outcomes and then move to creating foresight scenarios or to Morphological Analysis with those selected variables.
However, as seen, foresight methods usually start from an explicitly limited number of variables, which allow them to select at the end of the influence analysis between 2 and 10 variables. Here, on the contrary we use as many variables as needed for the map to be a good enough model, and thus the influence analysis, whatever the measurement chosen, does not lead to the easy selection of this very limited number of variables.
Furthermore, the selection of only those variables, if it can seem helpful initially, becomes a disadvantage when we move to the creation of scenarios. Experience shows that it is practically impossible to construct a serious narrative with only those selected variables. When constructing narratives, one automatically and unconsciously reintroduces other variables that had been previously eliminated. As those variables are now reintroduced unsystematically and without guidelines, the door is opened for any kind of mistake and biases can easily creep in.
Finally, it is scientifically absurd and wrong to dispense with one variable, when we know it is there. It could lead to erroneous foresight and then warning. Furthermore, in the case of warning, ignoring variables could deprive us of crucial indicators and thus impede the overall warning on the issue at hand.
Hence, in the methodology used here, we shall do otherwise. We shall NOT reduce the number of variables but use a method that could be called propagation and is made possible by the existence of ego networks in social network analysis.
Does it mean that we can fully dispense with influence analysis? The answer is evidently no – or this post would not have been written – but we shall use it for a different purpose.
We shall use influence analysis to set the initial criteria that will give us the point of departure for constructing the narrative of our scenarios.
According to cases, between 5 and 10 variables can be chosen as initial criteria. The rule of thumb is to try to determine variables truly standing out. Visualization is here very helpful. If the software used is Gephi, then one will also be able to choose various features such as filters allowing selecting various ranges of variables according to measurement. As no variable has been suppressed, fixing the number of initial variables is not a crucial problem and cannot lead to major mistakes. It is more a matter of convenience to be able to start telling the stories of the future (narrating the scenarios).
Cite as Helene Lavoix, (2011), “Revisiting influence analysis,” The Chronicles of Everstate, Red (Team) Analysis, http://wp.me/p1S3g8-50.
Arcade, Jacques, Godet, Michel, Meunier, Francis, and Roubelat, Fabrice, “Structural Analysis with the MICMAC Method & Actors’ Strategy with MACTOR Method,” The Millennium Project: Futures Research Methodology, Version 3.0, Ed. Jerome C. Glenn and Theodore J. 2009, Ch 11.
Glenn, Jerome C. and The Futures Group International, “Scenarios,” The Millennium Project: Futures Research Methodology, Version 3.0, Ed. Jerome C. Glenn and Theodore J. 2009, Ch 19.
Hanneman, Robert A. and Mark Riddle. 2005. Introduction to social network methods. Riverside, CA: University of California, Riverside ( published in digital form at http://faculty.ucr.edu/~hanneman/ )
Ritchey, Tom; “Morphological analysis,” The Millennium Project: Futures Research Methodology, Version 3.0, Ed. Jerome C. Glenn and Theodore J. 2009, Ch 1.
Once an initial question is defined – in our case, what will be the future of the modern nation-state for the next twenty years – most strategic foresight and warning methods start with building a model that will describe and explain the issue or question at hand. In other words, we construct our underlying model for understanding. As Epstein underlines, making explicit models is nothing else than explicating the hidden model we, as human beings, are using when thinking. Furthermore, in terms of analysis and more specifically intelligence analysis, making the model explicit will help first identifying various unconscious biases, thus allowing minimising them. It will then help defining areas of uncertain understanding, which can then be marked for further research.
Most futures or foresight methods start looking for variables (also called factors or drivers) that are part of their model. A variable is a symbol or symbolic name that stands for a value that may vary. Some methodologies then link those variables. The link between two variables represents an influence (A influence B), most often causality. For example, in a model on demographics, one might have as variables birth rate and total population, and a link from birth rate to total population.
Whatever the question at hand, the construction of the model must be grounded in science, i.e. accumulated knowledge and understanding. Brainstorming sessions are crucial but should not dispense with using what others have understood beforehand, even if debates exist. Ideally the model should also be regularly updated to consider new findings.
One may see such maps, for example, in the British foresight product, Dimensions of Uncertainty done by the Foresight department of the Government Office for Science (2010?), notably Annex A.
Actually, maps are nothing else than graphs or networks – in our case directed graphs - and thus will benefit from the long scientific history that is attached to them, from Graph Theory, as graphs started being studied in mathematics with Euler in 1735 to the more recent Network Science. The development of the field has seen the emergence of new tools, such as network visualization software that greatly facilitate working with and on networks. Gephi, open source software, has been used here for the development of the underlying model, considering both its ease, its flexibility and yet its power.
Once the model is built, it is used to develop the scenarios that will constitute the history of Everstate, notably thanks to ego networks as will be explained in a few weeks. It will also give the indicators that are necessary for warning. Were capabilities available, it could be a step towards developing proper simulations that could then be mixed with the narratives.
The map itself, if it is seen as a whole by neophytes, may appear as complicated and difficult to use. It is however not so. It is just a tool and as all tools it demands understanding and training. Computers or mobile phones are far from being simple and yet they are now almost universally used. Once mastered, working with networks greatly facilitates the task of the analyst. It can be used as reference and give support to analytical conclusion, as statistics, trends or indications do. It is indeed one of the purposes of the Chronicles of Everstate to show how simple using a map for strategic foresight and warning is.
In terms of analytical management, a map is an investment. Indeed, once a graph has been properly built for a specific issue, it will most likely remain valid for a large period of time, especially if it is regularly updated with scientific findings. It can thus be used again each time the issue it covers comes into play. For example, if one wanted to do some foresight and warning on pandemics, the future of nuclear energy, of weapons of massive destruction (WMD), or cybersecurity, then at one stage or another the dynamics linked to state and government would have to be introduced and thus the map constructed here for the future of the state could and should be used again.
Rather than attempting to build from scratch the overall graph in all its complexity, it is easier to start building a minimalist core ideal-type model. This core graph will allow understanding the fundamental dynamics at work and then will be used as basis for developing the full model.
In the case of the future of the nation-state, I have started from Weber’s ideal-type, which gives the following graph.
This approach to understanding politics, which, obviously must include the population, a variable so often forgotten, would have helped understanding the 2011 uprisings in North Africa and the Middle East as well as the more recent protests in Europe and the Americas. We may only assume, with hindsight, that, had it been applied to classical F&W countries’ analysis, the likelihood to have been able to foresee the events would have been greatly heightened.
As the graph shows, s0 (“step 0”) and s1 (“step 1”) have been added to variables, so as to include a dynamic dimension. Indeed as the model was being constructed, tested and revised, it appeared that using uniquely broad static conceptual variables was inadequate. The system constituted by the polity evolves; each action has consequences; the aggregation of all actions, reactions and consequences, as well as creativity, lead to evolution and change…. Read more next post.
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Image: The Seven Bridges of Königsberg, by Bogdan Giuşcă (Public domain (PD), based on the image, GFDL or CC-BY-SA-3.0, via Wikimedia Commons
As the graph shows, s0 (“step 0”) and s1 (“step 1”) have been added to variables, so as to include a dynamic dimension. Indeed as the model was being constructed, tested and revised, it appeared that using uniquely broad static conceptual variables was inadequate. The system constituted by the polity evolves; each action has consequences; the aggregation of all actions, reactions and consequences, as well as creativity, lead to evolution and change.]
Actually, any SF&W model as it primarily deals with time should be a dynamic network. How can we expect obtaining any potential outline for the future if our model for understanding is static?
Our map thus aims at representing the potential dynamics of polities. We shall notably use Ertman’s work on past state-building, but making it adaptable to present and future conditions.
Steps s0 and s1 will be used for the initial, simpler model. Then, what happens during s0 and s1 leads to the “evolution of society,” which thus starts the second step, s2. The hypothesis here is that we have a successful political organisation that provides the necessary security to the people. As a result, various developments take place, notably involving creativity, innovations, etc. The variable “evolution of society” (in red in the graph) is thus a cluster variable for all those developments that are not included in the graph. With s2, we shall build a more advanced model, representing the modern state. However, s2 will not display potential domestic escalation and stabilization. The underlying hypothesis for s2 is that at the end of s2 the overall socio-political model has not changed but starts showing signs of increasing inadequacies.
For s3 (step 3), we shall have the same model as for s2, but here we shall include variables related to potential domestic escalation or stabilization. Indeed, if the existing socio-political organization finally proves itself to be adequate or if it is changed in a timely fashion, then it will be possible to stop escalation, solutions can be found and finally there are possibilities to stabilize the situation.
Finally, s4 will focus on a potential failure of the s2s3 type of socio-political organisation. Actually, with s4 we shall also change scale as not all variables existing in s2 and s3 are replicated, for the sake of simplicity and clarity.
Ideally, if we had a simulation in mind, or if we wished to insert agent based modelling inside our larger conceptual framework, then n steps should be included and all variables used for each step.
Furthermore, network software give us the possibility to add a time component to a graph, as time can be attributed to each link between two variables.
The possibility to work in this direction is a very promising way forward to improve SF&W analysis and sufficient interest and funding should be made available to allow including this component. However, social science in general, international relations and political science in particular have not focused upon time. Effort should thus be made here, explicating the time factor when it is there, complementing existing findings when it has not been considered to allow for the proper, scientific inclusion of the time factor.
Having now our core fundamental model on the one hand and our broad dynamic structure on the other, we must progressively add the variables or groups of variables that are missing. For example, the core interactions take place within a milieu and against a normative backdrop that must both be considered. We now obtain the following graph, which is still considerably simple, with the nodes representing the milieu in green and the normative variables in violet.
One may also realise that some variables are actually generic and represent cluster of variables. For example, the variable “ruler,” which was indeed very convenient when starting our model, needed to be developed to be representative of our current polities. Thus for s2 and s3, to be as accurate as possible, the ruler was replaced with its corresponding nodes, using notably Susan E. Scarrow’s work, which gave the following subgraph.
There is no best or easiest way to add nodes, sub-graphs or develop a cluster: variables existing in both core graph and subgraph will serve as pivot and care will be taken not to have twice the same variable, then all links and dynamics must be rechecked.
Decision to detail or not a node will remain with the foresight analyst and depend upon the question as well as upon the resources available. A map that is too simplistic will lead to erroneous foresight and thus should not be favoured. A map that would take too long to construct would also deny foresight. Thus a middle ground must be found.
It is now time to envision what might happen to the ideal-type model of polity with time, and why, as this is the purpose of foresight.
Scientific historical knowledge tells us that war and the timing of its onset were some of the major causes for changes that led to state-building and, if we take the case of the fall of the Roman Empire, to collapse. However, political history, international relations and security studies have generally tended to focus on external military threats, while as a pendent, in the state security apparatus, security has by and large be seen as equal to external military threats.
Now, if we want to be able to envision the future as well as possible, we need to consider not only conventional variables but also unconventional ones. To be able to determine those supplementary variables, we need first to understand what they cover. Here, starting from the importance of war and its onset for prompting change, we may deduce that any type of pressure threatening the security of the polity will be cause for change, as, indeed, the society and its political authorities must adapt to face those pressures. Capability to adapt or not, which will vary according conditions, will lead to one or another type of outcome or plausible future. Using imagination, research, horizon scanning and, in a collaborative setting, brainstorming, will allow identifying various types of pressures that will then be included in the graph as new nodes. For example, the variable “evolution of society,” which starts s2, as seen previously, is a first intrinsic cause of pressure on the polity, as new phenomena must be integrated. The pressure is increased because evolution goes in the direction of an increasing complexity that political authorities must learn to harness. Each pressure identified is a cluster variable or group node that could – and ideally should – become a graph. Here, as our focus is the nation-state, we shall leave them as such.
Now, we also need to introduce the possibility for the appearance of new variables. For example, if we consider complexity theory, we know that complex systems generate emerging properties. Something that did not exist in the past emerges. For example, if we follow the modernist school of thoughts on nation and nationalism, as is done here, nationalism and nations in their current acceptance are a modern phenomenon that did not exist previously.
Such novelties correspond to a change of structure for a map. If the possibility for such new variables were not included, then the map created would most probably fail to envision some plausible futures. Only changes happening while the structure is fixed could be foreseen. For example, any foresight done during the Cold War – a stable period structurally – which would have focused only on Cold War related variables would have been unable to foresee the end of the Cold war and potential post Cold War futures. Indeed, if it had not included those “new variables” and processes, then it would have been unable to foresee changes once the structure changed. This is why it is much easier to practice foresight – and warning – when the structure is stable than when it is in transition as now.
How can we introduce the possibility for structural changes? One way is to add a node labelled along the line of “other types of,” then to explain the type of variable one refers to, and to fully include it within the map, with all necessary linkages. This generic variable may then be refined and divided into various more specific variables, still always allowing for something we did not think of at the time of the design of the graph and that may appear later, in one day, one month or one year, or that may be found somewhere else in the world.
In our case, we thus have a model that evolves under different kinds of pressures: previous pressures, cumulated and acting from a global level, new external military threats, new unconventional threats (those direct threats that have already been identified, such as cyber threats or bio weapons of mass destruction), cumulated/global unconventional threats (those unconventional threats that act at a global level), other kinds of pressure for survival (direct potential pressures that are generally not yet accepted or even identified). Known pressures such as peak oil (the end of cheap oil), global warming, biodiversity loss, etc. are covered by the cluster nodes. If need be, they can be detailed as subgraphs and the linkages previously identified for the initial cluster node will help integrating the subgraph into the overall map.
The potential for various changes of structure must be permanently kept in mind when constructing the map.
The overall dynamic map that is progressively constructed is the foundation for the entire strategic foresight and warning analysis and conditions the success of the next steps, and the quality of the various products that will be delivered.
In our case, the dynamic map looks as follows, and we shall see with the next posts how to work with it.
Epstein, Joshua M. “Why Model?” Santa Fe Institute Working Papers, 2008
Ertman, Thomas. Birth of the Leviathan : Building States and Regimes in Medieval and Early Modern Europe. Cambridge, UK ; New York: Cambridge University Press, 1997.
Zellman, Ariel Review: Birth of the Leviathan by Thomas Ertman, 2008.
Scarrow, Susan E. “The nineteenth-century origins of Modern Political Parties: The Unwanted Emergence of Party Based Politics,” in Richard S. Katz, William Crotty (eds), Handbook of Party Politics, London, Sage, 2006.
To exist, foresight products as well as warnings must be delivered to those who must act upon them, the customers, clients or users. Furthermore, they must be provided in a timely fashion. This criterion of timeliness is extremely important. It means that customers or users will have enough time to decide and then implement any necessary course of action as warranted by foresight.
Timely reflections (Image by Stanley Howe – CC-BY-SA-2.0, via Wikimedia Commons)
Most often, the challenge of timeliness is thus understood as stemming from the need to conciliate on the one hand the dynamics which are specific to the issue, object of anticipation, and on the other the related decision and coordination of the response.
Let us take the example of Peak Oil, i.e. the date when “world oil production will reach a maximum – a peak – after which production will decline” (Hirsch, 2005, 11) which implies the end of a widespread availability of cheap (conventional crude) oil. The phenomenon is now well documented and relatively widely recognized, from scientists’ reports, associations, institutions and books (see, for example, the creation of the Association for the Study of Peak Oil & Gas in 2000 , Robert Hirsch report (2005), the Institut Français du Pétrole (IFP), Thomas Homer Dixon, Michael Klare or Jeff Rubin), to web resources such as The Oil Drum or Energy Bulletin to finally the International Energy Agency (IEA – it recognised the peaking of Peak Oil in 2010, e.g. Staniford, 2010), despite still some resistance by a shrinking number of actors.
By azrainman http://flickr.com/photos/azrainman/991225765/ – CC-BY-2.0, via Wikimedia Commons
Notwithstanding other impacts, Hirsch estimates that 20 years of a “mitigation crash program before peaking” would have allowed avoiding “a world liquid fuels shortfall” (Hirsch, 2005). Assuming that oil peaked in 2006, as evaluated by the IEA, if we had wanted to have an energy mix of replacement for the now gone cheap oil, then we should have decided implementing and then coordinating a response… back in 1986. Thus SF&W on this issue should have been delivered some time before 1986.
Obviously, this did not happen, even if one starts finding rare articles regarding Peak Oil earlier (e.g. the 1974 miscalculated warning for a global Peak Oil happening in 1995 by M. King Hubbert (Wikipedia ‘Predicting the timing of Peak Oil’) and much later Colin J. Campbell and Jean H. Laherrere, “The end of cheap oil,” Scientific American, March 1998). Why?
Jack Davis, writing on strategic warning in the case of US national security, hints at the importance of another criterion linked to timeliness, credibility:
“Analysts must issue a strategic warning far enough in advance of the feared event for US officials to have an opportunity to take protective action, yet with the credibility to motivate them to do so. No mean feat. Waiting for evidence the enemy is at the gate usually fails the timeliness test; prediction of potential crises without hard evidence can fail the credibility test. When analysts are too cautious in estimative judgments on threats, they brook blame for failure to warn. When too aggressive in issuing warnings, they brook criticism for “crying wolf.”
For Davis, credibility is the provision of “hard evidence” to back up foresight. Of course, as we deal with the future, hard evidence will consist in understanding of processes and their dynamics (the model used, preferably an explicit model) added to facts indicating that events are more or less likely to unfold according to this understanding.
Credibility is, however, also something more than hard evidence. To obtain credibility, people must believe you. Hence, biases of the customers, clients or users must be overcome. Thus, whatever the validity of the hard evidence in the eyes of the analyst, it must also be seen as such by others. The various biases that can be an obstacle to this credibility have started being largely documented (e.g. Heuer). Actually, explaining the model used and providing indications, or describing plausible scenarios are ways to overcome some of the biases, notably out-dated cognitive models. Yet, relying only on this scientific logic is insufficient, as shown by Craig Anderson, Mark Lepper, and Lee Ross in their paper “Perseverance of Social Theories: The Role of Explanation in the Persistence of Discredited Information.” Thus, other ways to minimize biases must be imagined and included, that will most probably involve time. The possibility to deliver the SF&W product will be accordingly delayed.
Credibility and more broadly overcoming biases are so important that I would go further than Davis and incorporate them within the very idea of timeliness. This would be much closer to the definition of timely, according to which something is “done or occurring at a favourable or useful time; opportune” (Google dictionary result for timely). Indeed there cannot be timely SF&W if those who must act cannot hear it.
If the SF&W product is delivered at the wrong time, then it will be neither heard nor considered, decisions will not be taken nor actions implemented.
More difficult, biases also affect the very capability of analysts to think the world and thus to even start analysing issues. We are there faced with cases of partial or full collective blindness, when timeliness cannot be achieved because SF&W analysis cannot even start in the specific sectors of society where this analysis is meant to be done.
This is most probably what happened for our example of Peak Oil. If a model existed, created by M. King Hubbert, the initial miscalculation led to some loss of credibility as those denying peak oil underlined and still emphasize, even though King Hubbert model was not wrong. Analysts in SF&W in the early 1980s were more preoccupied with the Cold War than concerned by anything else. Afterwards, the system that had won against the Communist world could not even be thought not being perfect. Such highly disturbing threats that could question the prevalent worldview could not be envisioned. Had they been, they would most probably have been discarded first by policy makers then by political leaders. Furthermore, a host of actors had interest in a permanence of the ideological setting, which would have made the possibility to see a very early foresight work on peak oil develop very remote indeed (I am emphasizing here unconscious reactions and “deafness,” not hidden maneuvers).
Thus, to summarize timeliness is best seen as the intersection of three dynamics:
To understand each dynamic is, in itself, a challenge. Even more difficult, each dynamic acts upon the others, making it impossible to truly hope to achieve timeliness if the impact of one dynamic on the others is ignored.
For example, if we continue with our initial case of Peak Oil, having been unable to even think the possibility of Peak oil in the early 1980s has dramatically changed the current possible dynamics of the response, while both the cognitive delay and the absence of previous decisions and actions have orientated the dynamics of the issue towards some paths, while others are definitely closed. Any SF&W delivered on this issue now is quite different from what would have been delivered 20 years ago, assuming it could have been heard.
To acknowledge the difficulty of finding the timely moment, and the impossibility to ever practice an ideal SF&W in an imagined world where everyone – at individual and collective level – would have perfect cognition is not to negate SF&W. Answering this challenge with a “what is the point to do it now as we did not do it when things were easy/easier” is childish. On the contrary, fully acknowledging hurdles is to have a more mature attitude regarding who we are as human beings, accepting our shortcomings but also trusting in our creativity and capacity to work to overcome the most difficult challenges. It is to open the door to the possibility to develop strategies and related tools to improve the timeliness of SF&W, thus making it more actionable and efficient:
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Anderson, Craig A., Mark R. Lepper, and Lee Ross, “Perseverance of Social Theories: The Role of Explanation in the Persistence of Discredited Information,” Journal of Personality and Social Psychology 1980, Vol. 39, No.6, 1037-1049.
Campbell, Colin J. and Jean H. Laherrere, “The end of cheap oil,” Scientific American, March 1998.
Davis, Jack, “Improving CIA Analytic Performance: Strategic Warning,” The Sherman Kent Center for Intelligence Analysis Occasional Papers: Volume 1, Number 1, accessed September 12, 2011.
Dixon, Thomas Homer, The Upside of Down: Catastrophe, Creativity and the Renewal of civilization, (Knopf, 2006).
Elias, Norbert, Time: An Essay, (Oxford: Blackwell, 1992)
Hirsch, Robert L., SAIC, Project Leader, Roger Bezdek, MISI, Robert Wendling, MISI Peaking of World Oil Production: Impacts, Mitigation & Risk Management, For the U.S. DOE, February 2005.
International Energy Agency (IEA), World Energy Outlook 2010.
Klare, Michael, Blood and Oil: The Dangers and Consequences of America’s Growing Dependency on Imported Petroleum, (New York: Metropolitan Books, 2004; paperback, Owl Books, 2005).
Klare, Michael, Rising Powers, Shrinking Planet: The New Geopolitics of Energy (Henry Holt & Company, Incorporated, 2008).
Rubin, Jeff, Why Your World is About to Get a Whole Lot Smaller: Oil and the End of Globalization, Random House, 2009.
Staniford, Stuart, “IEA acknowledges peak oil,” Published Nov 10 2010, Energy Bulletin.
As Cynthia Grabo underlines, a warning does not exist if it is not delivered. Similarly, a foresight product – or risk assessment or horizon scan – has to be delivered. Furthermore, if foresight and warning are to be actionable, then clients or customers – those to whom the product has been delivered – must pay heed to the foresight, or warning. What they decide to do with those is another story, but from the point of view of SF&W, they must receive them, know they have received them and as much as possible consider them.
by Philip Devere, FAL, via Wikimedia Commons
Strategic foresight and futures’ efforts, as well as related literature, with a few exceptions, have rarely focused explicitly on this specific part of the overall process. Yet, it is crucial. As a first step, it has much to learn from the warning part of the activity. Then, both strategic foresight and warning may also have much to learn from the mobile and social networking approach that is being constantly imagined and re-imagined.
In a nutshell, the – ideal – approach that strategic actionable foresight must learn from warning underlines that:
If those steps are followed then we have improved the likelihood to see our customers paying heed to foresight and warning products. Many challenges, however, are lurking behind those apparently simple steps, potentially hindering the best completion of each of them. First and foremost, the various biases, as summarized by Heuer, that alter the understanding of any human being, will be at work. They will affect not only customer but also analyst and officer in their relationship to customers, as astutely pointed out by Woocher.
Without entering into the specifics of each bias and each challenge, which is more than a blog post can do, I would like here to suggest that the social and mobile web could help us with this specific phase of the SF&W process. It could not only by give us new capabilities but also, and primarily, a new philosophy.
Usually, chains of command and hierarchical structures define who gets SF&W products. They have been established over time, exist and are necessary as such. Yet, as far as those traditional existing “customers” or “clients” are concerned, most usually policy-makers and decision-makers, could it be worthwhile to change our mind-set, not seeing them anymore as “customers,” but, instead, as is done by the mobile and social web, considering them as users? Customers are those to whom one sells products or services, if we pursue the analogy (with all the potential biases this imply, as for example studied by Nolan, MacEachin, and Tockman).
Meteorologist at work at the Storm Prediction Centre de Norman, Oklahoma Source: NOAA
Users refer to a different universe. It imply that we provide them with tools (concrete or immaterial), instruments that are first and foremost useful and of value to them; devices that are needed to construct, to act, that will be helpful in the accomplishment of their mission. The emphasis moves from something that can be useless, that can been thrown away or disregarded and that is separated from the person who must buy it, to a long-term relationship, to the consideration of the other and its needs first – or rather the needs of its mission. This would be somehow adopting the first core principle of Google’s philosophy.
If we adopt the user’s approach, then we can start our process of identification again, with a fresh mind:
Those questions are more difficult than it appears for polities as they also touch upon democracy on the one hand, and power on the other.
First, in a representative democracy, policy-makers are those who are elected, and decision to act (or not act) should remain in their hands. Thus, care will be taken when or if new users are outside the nexus of elected representatives to see the democratic process respected.
Second, SF&W is (or should be) an essential tool of power, of might (the German Macht – verb machen = do) in its meaning of doing something. Thus, identifying new users may potentially lead to power struggles and care should be taken in advance to mitigate such drawback.
Currently, once all the policy-makers and decision-makers are known, then the most advanced practitioners design specific format and delivery – seen as a unified process – for the product, according to clients. The form and the delivery must be adapted to customers and will achieve the aim to get their attention and raise their awareness.
By National Weather Service Aviation Weather Center (http://aviationweather.gov/products/swm/), Public domain, via Wikimedia Commons
If we move to users, then product becomes tool, the emphasis on delivery can switch to reception, and then one should also think about the use of the tool. An overall strategy, centered on the actionable use of SF&W can thus be imagined, designed and implemented. One will have to ask questions such as
Once we switch to the users’ approach, then the capabilities of the social and mobile web can be fully integrated and adapted to SF&W. We shall examine specific ideas in future posts.
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Grabo, Cynthia M., and Jan Goldman. Anticipating Surprise: Analysis for Strategic Warning. [Washington, D.C.?]: Center for Strategic Intelligence Research, Joint Military Intelligence College, 2002.
Heuer, Richards J. Jr., Psychology of Intelligence Analysis, Center for the Study of Intelligence, Central Intelligence Agency, 1999.
Nolan, Janne E., and MacEachin, Douglas, with Kristine Tockman, Discourse, Dissent and Strategic Surprise Formulating U.S. Security Policy in an Age of Uncertainty. Washington, D.C.: Georgetown University, Institute for the Study of Diplomacy, 2007.
Woocher, Lawrence, “The Effects of Cognitive Biases on Early Warning,” Presented at the International Studies Association Annual Convention (2008).