This post will focus on a third analytical challenge at the core of the foresight and warning process, the fact that actors and “factors”, or rather variables, are often mixed together. Using the example of the unfolding crisis in Ukraine, the first post of the series explained how to map a strategic foresight and warning question, notably how to move from factors to variables and the second underlined the importance to define and name the actors relevant to the question as objectively as possible and suggested ways to do it.

The “black box” actor

As we recall from the last post, during the first steps of a mapping for the future evolution of the crisis in Ukraine, both factors or rather variables and actors would have been identified as influencing the situation (see here for the map).

US flagYet, as seen in the first post, what we are looking for are variables, i.e. elements that can take values or attributes, which must be at once exhaustive and mutually exclusive. However, actors are not variables. If we identify “the U.S.” or “Russia” as an actor and include it in our map, then, if we do not specify further our label, we cannot attribute to the actors “the U.S.” or “Russia” different values. We have not made explicit what we try to describe when using the name of actors. 

actors, Russia, strategic foresight and warning

Are we talking about various foreign policy options, about strength of influence towards another actor or group of actors, about military options, about domestic policies, about economic prospects, etc?

The scope of what is covered is so broad that it is actually useless in terms of specifically identifying the dynamics at work for an issue. Furthermore, it opens the doors to many biases and misunderstandings as what one person will imply by using the name “the U.S.” will be different from what another person thinks. Consequently, actors, if they remain as such, cannot be indicators for warning, as we would not know what to monitor specifically. 200px-BlackboxThe way actors are used here is similar to the black box approach and we thus have a mapping that is less useful than it could or should be.*

Mixing actors and factors as if both were variables and using shorthand names for actors does not reflect an erroneous cognitive process, but the initial steps of a genuine attempt at considering all “things” that influence an issue, and both actors and factors are indeed operative for any question. When writing a classical analysis, mixing actors and factors does not appear to create any specific problem. What we often do is to try ordering our analysis according to paragraphs: one paragraph (or part) will deal with the economy and economic factors, another with foreign policy and related factors, and the next with this or that actor. We tend to instinctively separate “factors” and “actors” thus showing their difference in nature.

Should we thus abandon the approach through mapping and revert to a “more simple” classical analysis? The drawback of a classical analysis is that the simple fact to sort out and separate various factors and actors tends to make us forget how those could interact in the future, which is a serious problem for SF&W.  Without the mapping process we may only rely on the power of the implicit cognitive models we have, with all the biases and dangers this implies. Furthermore, it is extremely difficult, without the support of a tool, to make sure that, somewhere, we do not forget an element, that we have indeed considered all impacts, etc. Considering our highly complex world, this is all the harder. Thus, relying solely on a classical analysis, sorting out actors and factors thus enhancing the odds to forget connections between them would also increase the risks to obtain results that would fail to consider potential situations, thus to surprise, i.e. what we were seeking to avoid.

How are we thus to proceed if we want both to use the methodology that allows to consider complex questions for SF&W and to properly consider actors?

The imperfect, easy solution

This is the solution that is most of the time taken during workshops that are under time pressure to deliver scenarios – or at least outline of scenarios – within a very short timeframe, or that tend to put a premium on the participatory process of a workshop over the analytical result itself (even though a participatory process leading to unsatisfactory results would disappoint participants and thus be counter-productive). Variables (assuming factors have been transformed into them at all) and actors are left as such and links of influence are drawn among them. The most important variables and actors are selected and then values are attributed to them, or alternatively, attributes are given to all variables and factors before the selection of the most important of them. It is at this stage, when values or attributes are specified that, most often, the real breach of science happens.

2014-04-15._Протесты_в_Донецке_012Following on our case study, what type of values could be attributed to “Eastern Ukraine” (assuming that we consider “Eastern Ukraine” as an actor and not a complex variable as seen with the last post) for example, or to “Germany” (the example below is adapted from real-life situations on other issues)? In the first case, participants might decide to attribute as values: “protests against Kiev”, “protests against Kiev with violence”, “wants autonomy”, “wants to secede and join Russia”, “accepts Kiev power and rule of law”.  As this example shows, it is particularly difficult to specify mutually exclusive attributes, and to cover the whole possible range of values. Here I have attributed values that were dependent upon an implicit international concern. However, we could very well attribute values such as “increasingly acts in a united way” and “shows rising disunity and disparities”.

If we take the other example of “Germany”, the type of values that could be attributed are also near endless, from the relationships between Mrs Merkel and Mr Putin, to Germany’s power within the E.U., to trade relationships with Russia, Ukraine or the U.S., without forgetting energy dependency.

If we choose the easy, quick and simple solution, then the overall process, especially in a workshop setting, flows much more quickly and smoothly and can easily be accelerated to reach scenarios or outlines of scenarios. However, areas that would determinate plausible futures will remain obscure, and non accounted for. In terms of participatory process, difficult discussions will have been put aside. In terms of analysis, we shall have seriously limited our foresight results and thus our policy options. Then, because each actor is only summarily considered, the map will be useless in terms of warning. Indeed, most analysts would not use it, nor even refer to it and would, instead, use their own inner cognitive map, with all the risks this implies in terms of bias.

The ideal solution

Each time an actor is identified, it must be unpacked adequately and transformed into variables, each with its proper values or attributes.

Pro Donestk Rep protests 6 April
6 April 2014, Donetsk: Pro-Donetsk Republic and pro-Russia protests by Andrew Butko [GFDL or CC-BY-SA-3.0 via Wikimedia Commons
pro Ukraine protest 17 april Donetsk
17 April 2014, Donetsk: Pro-Ukraine protest tweeted by @_DuncanC

We can try to find the best representative variable for the question at hand. For example, instead of “Eastern Ukraine”, we could choose “likelihood that Eastern Ukraine will fall into civil war over autonomy demands” or, as we suggested last week, “likelihood that Eastern Ukraine follows on Crimea and acts to obtain re-attachment to Russia”. However, as become obvious with those two examples, the variable that is substituted to the actor covers many elements: escalation towards civil war, motivation for protest and struggle, influence of the example of Crimea, decision or not to act, ultimate goal. Each proposition is different from the other, and the choice of one over the other will impact the result of our analysis.

Thus, a better solution is to detail further through a string of variables what we meant by referring to this actor, as is best according to both the issue and the resources available (including in terms of time). This will be a relatively slow and complicated process, but it will ensure that the mapping is correct, thus can lead to adequate foresight, and resulting policy options. Furthermore, it will enhance the odds to see it becoming useful to analysts for their future monitoring of the issue.  

What should direct us, in general, when substituting variables to an actor is that the aim, as always when making a mapping for an issue, is to be able to describe at best in an explanatory way the dynamics of the situation. We gave an example of the string of variables that could be used for “Eastern Ukraine” when addressing the labelling of actors. This shows that when trying to overcome the problem linked to the labelling of actors and the biases involved, then one automatically finds a solution to the challenge of improperly mixing variables and actors. Thus, with a single rigorous process we can solve two challenges facing SF&W analysis. 

It will be up to the analyst or group facilitator to find the right balance between not enough details and too many. The importance of this cluster of variables for the overall SF&W question may also guide us in deciding upon the desirable level of details we need to achieve.  In the case of “Eastern Ukraine” and “Western Ukraine”, as they are central to the overall SF&W question, it is obvious that we should pay attention to detail as much as possible the variables involved.

On 16 April 2014, Ukrainian soldiers sent by Kiev would have defected when arriving in Kramatorsk after having discussed with local people. from Youtube video posted by Kobi Michael https://www.youtube.com/watch?v=4iOcAfFPH0E
On 16 April 2014, Ukrainian soldiers sent by the interim government would have decided instead to side with protestors when arriving in Kramatorsk from Youtube video posted by Kobi Michael

Proceeding in such a way will also help us overcoming the bias according to which human cognitive processes tend to overestimate centralized direction and planning, as shown by Heuer (Psychology of Intelligence Analysis, pp. 131-132). This bias is currently most probably at work in the willingness to accuse, according to case, “Russia”, “the U.S.”, “the E.U.”, etc. for events that answer also, if not first and foremost,  to political dynamics including people and domestic movements (for interested readers, watch the Youtube (apparently) independent video showing “the armored column taking the side of the people” – duration: 11:16).

This is not to say that attempts at manipulation and subversion, that covert operations and propaganda do not exist, because they do, but that all of them exist within a specific setting that must be considered (as indeed their success depends on understanding these conditions). This is not to say either that there are no interactions between the domestic and international levels as indeed feedbacks exist between both, as show, for example, the emerging new U.S. Cold War vision (see The Weekly 148 and Baker, NYT 20 April 2014). Yet, considering all forces at work properly, notably remembering the importance of indigenous movements’ and people’s will and their capacity to mobilize and act will be essential for the success or failure of the implementation of the 17 April Geneva agreement (Download the pdf EEAS official Geneva statement140417_01_en).

We are, or were if Geneva succeeds, which appears as increasingly difficult, in a typical escalation process (see How to analyze future security threats (5): scenarios and crises), which might have been recognized by the major actors, hence the fact that Geneva was convened, that everyone went and that, finally, an agreement was reached (see for the timeline of the negotiations’ day Derek Scally,  18 April 2014, The Irish Times). Unfortunately, the various declarations made at Geneva ended with the shooting that took place in Slaviansk, when three protestors were killed on 20 April at a roadblock they held, and the immediate – absurd – blame laid on Russia for it (AFP 21 April 2014, Kramer, SMH, 21 April 2014). It shows that stabilization has not yet occurred and that some are looking to spoil the hope for peace, despite also “encouraging signs” as stressed by Pyatt, the U.S. ambassador to Ukraine (Payne, CNN, 21 April 2014).

There is also a quite large advantage to the “unpacking actors” approach, which is insufficiently – if ever – considered: we could prepare in advance parts of mappings, as well as reuse them for different issues. What will be understood for actors such as, for example, “Russia”, “Germany”, or “the U.S.”, will, most of the time, be operative each time Russia, Germany, or the `U.S. are involved in an issue. Thus, participants to a workshop and analysts will not have to redo all the work, but only to check that the existing graph for this or that actor is adequate, complete it if need be, and add the links between the variables previously identified and those of the “imported” map for this or that actor. This approach, however, will ask from participants and analysts new skills, notably to be able to read and check an already constituted network, without being frightened by its potential complexity. 

——–

*What we see here somehow enacted is an instance of the difficulty to conciliate both structure and agency to explain human phenomena, which led, in social science, to the famous structure versus agency debate.

Featured image: Protests in Donetsk, 7 April 2014 – This photograph was created by Andrew Butko. Contact information – e-mail: abutko@gmail.com. Do not copy this image illegally by ignoring the terms of the СС-BY-SA or GNU FDL licenses, as it is not in the public domain. Other photos see here.