The greatest loss of time is delay and expectation, which depend upon the future. We let go the present, which we have in our power, and look forward to that which depends upon chance, and so relinquish a certainty for an uncertainty
Some time ago I outlined the basic principles of managing a complex system and promised to use them to explore a range of management issues. It’s been longer than I intended, partly because it’s starting to look as if each of these requires a minor essay, or possibly (dare I say it) a book chapter. My first subject is scenario planning, although I am thinking of that in a wider strategic context that the generation of a series of structured narratives about possible and credible futures. The conclusion of all of this will link back to the Seneca quote above; I will be arguing that we should be finding ways to better describe the current situation, in order to manage the emergent possibilities of the present; further that we need to find ways to create a process of thinking about scenarios that is highly dynamic, engages large populations in evaluation and speculation. In particular I want to talk about moving from anticipation to a state of anticipatory awareness.
Given the time since I first introduced this topic (I planned a couple of weeks, but its panned out as the best part of half a year) I’d suggest a quick read of the original post, which concluded with three necessary, although not necessarily sufficient conditions for any strategy based on complexity theory. The three were: (i) distributed cognition, (ii) using fine granularity objects and (iii) disintermediation (connecting decision makers with raw data in real time). A final warning before you read on – this posting has not been fully proof read and will be modified with additional material over the next week or so. Consider it an invitation to participate in a work in progress.
Each of these posts will have a common form. The lede (that spelling proves I spend too much time editing the Wikipedia) will always start with a quotation, a Melbourne Art Museum photograph and the series title to mark them out. After that I attempt a summary of the field in question, followed by a discourse on issues and limitations before moving on to some of the new tools and techniques emerging from our work in Cognitive Edge as well as other people working in complexity theory and narrative. As they progress I will convert the posts into papers with additional material based on the comments received (if any!)
What is it?
The origins of scenario planning, like many other management practices lie in a military environment and the first real formalisation of the techniques can be found in Prussian Army from the mid 19th Century. Military plans are almost inevitable based on scenarios and they are frequently tested through war games that are intended to prevent complacency (although there are some famous cases where the “enemy” won the war game, but the original plan was maintained with inevitable consequences). That aside a military scenario tends to be bounded (a campaign, or a battle) over a relatively short term planning period and also assumes an intelligent human opponent.
Non-military use is normally traced back to the work of Pierre Wack and one of the defining papers is his 1985 HBR paper Scenarios: Uncharted Waters Ahead. There is also a body of work in the 60s and 70s focused on forecasting and the management of expert groups whose collective acts of judgement were used to inform strategy with the intention of more effectively managing risk. In terms of our current understanding however it all goes back to Shell and much of the anecdotal evidence (there is as far as I can see only anecdotal evidence by the way) comes from the use of scenarios to handle the oil crisis of the time and the CEO’s claim that Shells comparative success over oil companies was due to the power of their scenario planning. Shell remain one of the few companies with a major investment in a professional scenario planning group and many a member of that group has gone on to create their own consultancy business based on that initial Shell success.
There are many variations on the basic scenario planning process that range from the pragmatic to the esoteric (using clairvoyant dreamers being advocated by one Washington Think Tank with more money than sense). However in essence it boils down to a three/four stage process with a variant. The illustration is a high level representation of this.
My job here is not to write a text book on scenario planning so I am not pretending the above is comprehensive, but I wanted to create a broad brush summary for those not familiar with the process as a whole. Some of the better approaches I have seen are linked to SRI (Stanford Research International) and I worked with them on DARPA programmes around a decade ago and have stayed in touch. It takes high quality facilitation to create a good set of scenario plans. Too frequently I have seen pre-determined outcomes imposed on a group to ensure an easy to produce outcome for the consultancy group involved. One of the worst ever in which I had to participate was led by one of the leading practitioners, in which all activity was in small groups with facilitators/reporters from the firm engaged. Their reports of the sessions appeared to most of us, to confirm with the sample outcomes we had been shown rather than the spirited and diverse discussions we had engaged in. However run well, the process is engaging for the participants, expands the range of options they are prepared to consider and can often create new and exciting options and possibilities. Along with Shell, one of the other examples used frequently in anecdotal support of the technique is the use of scenario planning to vision futures in post-apartheid South Africa; mind you spiral dynamics makes claims there as well, expert an attack blog before too much longer, turquoise was always my least favourite colour.
Issues & boundaries
One of the key distinctions between military and commercial/government scenario planning is that in the latter case there is no enemy, or rather the enemy is the wider environment. Also the time period is often longer and less focused than a campaign or a battle. Many of the control methods that are an inherent part of the military process are not there in a civilian environment. Over the years I have done a lot of work with military groups and found them much more rewarding than their equivalents in industry. They tend to take exercises seriously as its the only opportunity they have to practice, before unfolding events end up killing people (including possibly themselves). If you run a programme with the military, even if they are uncertain of why you are doing something they will still engage and thus learn. Their officers also tend to be more favourably inclined to sound theory than many an industrialist or government official. In those environments if people are uncomfortable they often withdraw.
Its also worth noting that the evidence for the success of scenario planning is largely anecdotal, and the anecdotes are from restricted sources in the main Shell. One quote you see a lot is supposedly from a Shell Executive: the Scenario team were bright and their work was of a very high intellectual level. However neither the high level “Group Scenarios” nor the country level scenarios produced with operating companies really made much difference when key decisions were being made. This type of comment is far from uncommon, and you would expect scenario planning to inform operational decision making. The fact that it doesn’t does not make it useless but it does bound it. My evidence (also anecdotal) over multiple strategic exercises as a General Manager before my days in IBM was that the process of creating the scenarios was valuable for the participants, but the impact on operational decision making, even over the next budget planning horizon was limited. This matches work by Arie de Geus and others which shows the value of the process for participants in terms of reported behaviour changes and expanded thinking. However there is no real or substantive evidence of any impact on decision making, and limited academic studies which you would expect after thirty years.
The diversity of participants in the process is also an issue and there are inherent dangers of pattern entrainment in workshop processes. An idea can capture the imagination (especially if it comes from a powerful player). The structure (route one) or the clustering and culling (route two) runs the danger of premature convergence on a limited set of outcomes. Once a scenario or scenarios are committed then the danger is that unforeseen events are filtered out of organisational scanning, weak signals are missed. Individual groups or factions may start to use the scenarios to gain short term strategic advantage for their pet goals. Future scenarios start to assume the status of a new religion with heaven, hell purgatory and limbo. Even Dante thought in two by two matrices and I couldn’t resist the illustration. This paragraph is all about limitations associated with cognitive issues around people and people engagement in process.
So used well Scenario provides a means to imagine different alternatives and enthral people in a new way of thinking about the world, either by way of an aspirational goal or a to be avoided at all costs negative future. Used badly it is an attempt to reduce uncertainty in the future by mapping out a range of future possibilities. Now this may seem a contradictory or at best a paradoxical statement, surely we want to reduce uncertainty?Well yes we do, but only if it is genuinely possible to do so. If it is not then we are in fact increasing risk; better to embrace the uncertainty and learn to live in the present in knowledge of that uncertainty. We can reduce risk, and we can increase our state of anticipatory awareness which is preferable to inauthentic attempts at anticipation. We need to think about resilience and rapid reaction rather than RRRRR. This I think is the essence of the Seneca quote.
Now I want to make one thing very clear. I am not arguing against scenario planning per se, but about some of the more common applications of scenario planning. I have seen excellent cases where a scenario planning session can open people up to new possibilities, sensing that a different future is possible from the current imaginings of fear that can haunt people in difficult circumstances. Such processes can allow people to seek out new goals and ambitions, to sense unimagined possibilities. I have seen national scenarios in Singapore and elsewhere that enlighten and inform policy. However all the other objections stand, and the general failure to translate into operation processes (after thirty years) along with the reduction of professional scenario planning departments (Shell remains an exception) in times of economic stress all indicate a useful but bounded technique.
In Cynefin terms scenario planning (and its no accident that it is often combined with systems dynamics) is a complicated technique not a complex one. So what else can we do?
Thinking anew, acting anew
One of the key points I have made over the years is that complexity based approaches are inherently messy in nature, we are dealing with non-linear problems and we need multiple methods and tools operating in different ways from which patterns can emerge that allow us to think strategically. In the area of scenario planning one of the key needs is to radically increase the number of participants and the diversity of perspective. To do this we need technology. Now while some of the posts in this series will be method based, this is one that links with SenseMaker™. Managing future uncertainties was fundamental to its design. Where I am making reference to SenseMaker™ modules I indicate them in a different font and colour, like this. Some of the software listed is currently in alpha or beta test by the way (just to set expectations). Firstly, this is not a linear process it is a series of activities that combine to create an ecology of present possibilities.
Now all of the above points relate to capturing and interpreting material in significantly large volumes than has been envisaged in scenario planning todate. The volume of material and the number of perspectives radically reduces some of the issues on bias identified above. We are also now starting to focus on using metadata rather than the micro scenarios. This means that we can look at various ways in which we can interpret the material. At its simplest we can look for formal mathematical correlations in the way that different groups index material, we can take normed data sets representing specific perspectives and use those to test incoming data for similar or different patterns. The ultimate representation is a landscape which I illustrate here. This is from a government related project and the metadata (signifier) labels used are show with their ranges. Here the valleys or hollows in the landscape represent stabilities where change is unlikely other than under catastrophic circumstances. On the other hand, what I have called the Lumpy bits represent areas where change can happen quickly. Now remember that these representations are not drawn from the limited output of a series of workshops, but from the mass participation of large numbers of people.
The degree of volatility in the models gives us a measure of risk. We can draft scenarios (the traditional method) around the possibility that a proto-attractors (small hollows in the lumpy bits)may develop and suck energy away from the current dominant ones. We can start to look at conditions under which a phase shift (a radical disruption of the model) can take place and create monitor systems for those events. As more data continuously feeds the system we can sense subtle changes (otherwise know as weak signals) early and not by examination of the raw content (pattern entrainment and various forms of bias would creep in) but by a quantitative assessment of metadata. When we want to know more we mouse click on the model and then we look at the content which has been signified, we now know that it is significant. The landscapes for me sum up the Seneca quote with which this post started: they represent the emergent possibilities of the present in such a way that decision makers can navigate the future.
Of course this is one representation. Within SenseMaker™ three modules interpret the data. Explorer handles statistical relationships, Wanderer handles database search and representation and Classifier ( a non-trivial service) allows for automation of expert knowledge within the system. The idea here is to present different groups of people within the organisation tools to allow them direct access to the raw data and metadata patterns. Rather than a high priesthood of specialist researchers, statisticians or even scenario planners, we distribute sense-making into networks to increase our capacity to handle uncertainty. All of these analysis tools, if an interesting pattern is discovered can be turned into Monitors. Instead of a multi-threaded flow chart of turning points which will ever cover the field, we can have large libraries of monitors created on the fly, stored and forgotten until at an unexpected point in the future they suddenly trigger an alert. It means that anyone can create a monitor (including the mavericks who after the event everyone wishes they had listened to) which if they trigger a threshold level will gain senior management attention.
Now traditional scenario planning on implementation tends to produce turning points and agreed signals to monitor for. As identified above the danger here is that we can only consider a limited number of possibilities. Now we have made a significant set of changes. We have distributed cognition, without having to delegate power to broad populations. We are working with fragmented fine granularity material which has not been synthesised or summarised (with inevitable loss. We have removed the mediating layers between decision makers and the raw data from their markets and staff which is key to effective decision making.
This is a big subject, and although long this is a short summary! One of the key things to realise is that the above approach moves us from attempting to anticipate or predict future events (which as Seneca says is a waste of time) to creating a sensor network that encompasses the organisation and its environment. As such we move from anticipation, to a state of anticipatory awareness. We move from planning for scenarios, to true scenario planning.
Summary: applying the three principles
|Distributed Cognition||Fine Granularity Objects||Disintermediation|
|Engaging large numbers of people from different backgrounds in creating and signifying material, including the same material from different perspectives.||Use of multiple sources of material, both open source intelligence, generated material and normal data feeds to be used without summarisation (and loss)||Absence of interpretative structures, decision makers moves directly from abstraction of the total field to the raw data.|
|Creating the ability to carry out mass consultation of pre-prepared lists on aspects of a current or prospective situation||Interpretation of multiple fragments through blending of different perspectives and material allowing novel solutions to emerge in context.||Executives able to initiate new questions and queries on aspects of a problem without the need to brief analysts, agencies & departments|
|Creating multiple monitors over time, not trying to pre-determine which are right, allowing multiple trigger methods within a sensor network||Generation of fragmented scenarios rather than fully structured stories including assessments of current situation||Making the mavericks and front line people with strategic vision visible to senior decision makers, removing middle management filtering.|