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Archive for the ‘Chaos’ Category

This is the text of an article in the Washington Post by Dominic Basulto about last week’s events in the financial markets. Great stuff.

When news first broke Thursday that JPMorgan’s credit derivatives portfolio had sustained a loss of $2 billion, and potentially as much as $5 billion, on trades gone awry, there was an immediate call for greater regulatory oversight over banks’ high-risk trading activities. The message was clear: “If you’re going to be a bank, then you can’t play at the casino,” as the Post’s Ezra Klein writes. At the same time that the market was lopping off billions of dollars in shareholder value, JPMorgan was purging top executives responsible for the bungled trades and facing awkward questions about its public stance in favor self-regulation. If banks can’t regulate themselves, though, who can?

Inevitably, the answer to that question depends on whether you view the financial markets as complicated or complex. If the financial markets are merely complicated, traditional approaches to regulation can be effective: regulators can turn their attention to individual actors within the market and systematically make the requisite changes to restore the market to equilibrium. In a complex system, however, traditional approaches to regulation can be woefully inadequate — small changes may end up having outsized effects, while big changes may end up having little or no effect. In a complex system, you need to focus on the interactions between each of the participants as much as the condition of individual actors.

The trading screens of Wall Street are, if nothing else, the perfect example of how computers are able to mask the complexity of an underlying system by being able to reduce the real world into 1’s and 0’s. There is no shortage of algorithms, formulas, sophisticated risk management models and quantitative trading models promising to reduce complex financial market interactions to something that can be studied, adjusted and tweaked. In theory, regulators should be able to look at a few numbers, compare them to a few benchmarks, and suggest the necessary adjustments.

But it is rarely that easy.

There is a big difference between complicated and complex. In a classic example, an automobile is complicated, but a transportation system with human drivers is complex. Ultimately, you can fix an automobile by lifting up the hood and checking that everything is working properly, no matter how sophisticated the parts. You can only fix a transportation system, though, by understanding how each of the drivers interacts with each other and understanding the distributions of dynamic traffic patterns.

One of the most innovative areas of public policy, in fact, involves the intersection of complexity theory with regulatory policy. Complexity theory, which has been used to model complex systems ranging from ant colonies to climate change, has also been applied to financial regulation. Practitioners within the financial markets are well-versed with complexity theory and its cousin: chaos theory. One of the entities consistently singled out in the academic literature is the CDC (Center for Disease Control), which is held up as a role model for how to deal with complex systems. For example, using complexity theory, the CDC was able to suggest that — contrary to what you might see in movies like “Contagion”restricting air travel would have little or no impact on stopping the SARS outbreak. As the CDC recognizes, you simply can’t regulate away diseases. You need to deal with them with in real-time as they appear and find the right levers to stop them. Most importantly, you need to be able to spot potential flare-ups before they occur and understand the emergent behaviors that lead to outbreaks.

Certainly, the types of events that we observe in the financial markets, such as “flash crashes” and billion-dollar Black Swan events in derivative markets, are reminiscent of complex systems behaviors where small changes lead to unimaginable consequences. While the Volcker Rule, which would keep banks from engaging in risky trading behavior, could be effective in the short-term in avoiding certain types of adverse market effects, it may not be as effective in dealing with the full range of market fluctuations in the long-term. Implicitly, we recognize the complexity of financial markets by ceding power to computers and algorithms to price financial instruments properly. Now, we need to recognize that this complexity also has important consequences for the way that we think about regulating these markets.

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Humanitarian coordination has been described in a new ODI paper as a ‘wicked problem’ which demands new and radical solutions. This post explores the  longstanding incentive issues underlying the lack of effective coordination and suggests possible ways forward.

In a paper published last yearMichael Barnett and I argued that the humanitarian system was stuck in much the same kind of bizarre loop as Bill Murray’s character in the film Groundhog Day: that it was ’condemned to repeat’. Each major disaster highlights pretty much the same problems and flaws, from Rwanda to the Tsunami to Haiti. This is despite a lot of work to try and improve the quality and accountability of aid between these events. Although some remarkable innovations have improved specific aspects of humanitarian aid, system-wide performance remains a major issue.

Drawing on the game theoretical work of Professor Elinor Ostrom and other leading political scientists, we argued that at the heart of this repetition was the issue of incentives.

The humanitarian system has few incentives for collective action, which are seen by many as key to effective coordination. Few of the humanitarian reform initiatives which have been launched over the past 15 years have attempted to understand or address the incentives that underlie and reinforce existing behaviours. This is because few if any agencies have been willing to sacrifice delivering quickly against their individual mandates for the benefit of the wider response.

This  ‘me first’ mentality is apparent throughout the interactions that make up the system - not just between international actors, but also in interactions with national and local actors, with ‘non-traditional’ actors such as the private sector and the military. It is also painfully evident in interactions with disaster-affected populations themselves.

Michael and I argued that without serious effort to examine and strengthen the incentives to cooperate versus those to ‘go it alone’, the coordination of humanitarian aid is likely to continue see a Groundhog Day-style repetition of below-par performance characterised by this ‘me-first’ mentality.

Haiti is the tragic exemplar for our times. Despite the complexity and scale of the post-earthquake response, the mechanisms set up to coordinate international efforts – sector-specific clusters in health, shelter, and so on – had no formal decision-making mechanisms or mandates. Remarkably, given their nominally central role in ensuring the coherence, effectiveness and efficiency of the response, the success of the cluster operations by and large came down to the personality or leadership skills of a single individual.

An ODI roundtable last month on the workings of the humanitarian system concluded that:

The recent humanitarian experience in Haiti is a tale of exclusion. The humanitarian system, with all its resources and coordination and information-sharing mechanisms, succeeded in by-passing many of the spontaneous, ad hoc or informal indigenous humanitarian responses. [agencies] actively excluded others, often without good reason.

None of this is new, of course. A UNOCHA-commissioned study published ten years ago revealed

…a ‘system’ that shows determined resistance to cede authority to anyone or any structure… Despite the urgency of the task, and the potential impact on human lives of poorly coordinated humanitarian responses, [key leaders] at the field level are all denied the ability to direct or manage humanitarian responses. Instead, all have to work on the basis of coordination by consensus. In the face of the obstacles, this is an uphill struggle…”

The Rwanda evaluation, published five years earlier in 1996, noted that the international system had ‘a hollow core’. It would seem that the latest solutions to this problem are also somewhat hollow.

And this is increasingly being recognised by disaster-affected states. Those that can afford to are turning down or strictly limiting international assistance. When Australia’s foreign minister Kevin Rudd was interviewed after the recent floods affecting his country, he argued that that one of the worst things they could have done was to have “a whole lot of uncoordinated delivery of stuff from around the globe plonked on [our] doorstep”. There are numerous ongoing debates in the context of the Japanese earthquake response which are also pertinent to this issue.

How can we deal with the Groundhog Day problem in system-wide humanitarian performance? There are numerous ideas bubbling around at the moment, from strict regulation to nationalisation to partial privatisation. But unless these new efforts tackle the incentives that arise at the point of disaster, they are unlikely to lead to significant and lasting change.

An important focus for anyone reflecting on how to improve system-wide performance is to explore ways to change the pay-offs, so that the longer-term incentives for mutual cooperation in the interests of disaster-affected people outweigh the short-term incentives for going it alone.

Without this issue being put front and centre so as to address the ‘hollow core’, any new reform to improve system-wide performance will sit on top of these issues instead of resolving them. Agencies will continue to deliver against their narrow, short-term organisationally-defined objectives, to the detriment of their own longer-term benefits, overall system-wide performance, and most importantly of all, the communities they purportedly seek to help.

Of course, such self-examination is not an easy thing to do, nor is it easy act upon. As the write-up of the ODI event notes, humanitarian coordination is a good example of a “wicked problem“: “difficult and fluid problems with no clear solutions, to which any response typically creates additional problems… the more closely they are examined or the better they are understood, the more complex and insoluble they may seem.” It continues:

Collective strategic action in the face of these problems may be continually frustrated; more effective responses may depend on developing and strengthening decentralised, diverse, non-linear and non-hierarchical approaches to problem-solving across the humanitarian sector.”

One radical suggestion for changing the pay-offs by along these line scomes from Yaneer Bar-Yam, president of the New England Complex Systems Institute. He suggests that the shortcomings of the humanitarian-response system in Haiti have a lot to do with a principle of systems thinking known as requisite variety. This states that an effective system has to have as many different states of response as conditions that are presented by its environment – or more simply, that internal diversity has to match external diversity.

This implies that we need to be seeing a lot more creativity and innovation in coordination efforts, in ways that are appropriate and tailored to different emergency contexts. The ‘one-size-fits-all’ model of the clusters, together with their lack of coordination ‘teeth’, may well be hindering more than helping performance.

There are also serious questions to address about who gets to judge the performance of agencies. According to a Slade interview with Bar-Yam, one example of such an improved model would be:

…one that understands that duplication and competition among NGOs is not a bad thing, so long as organizations are rewarded with donor money for delivering effective solutions.  And those solutions can only be determined by Haitians themselves…”  (emphasis added)

This idea seems to have some resonance with “cash on delivery” – an innovation from the development side of the system. Of course any attempt to apply this principle to humanitarian aid needs a lot more thought – and it is just one suggestion – but it is certainly an intriguing one. There are no doubt more such ideas to consider. What does seem clear is that this kind of incentives-focused thinking needs to play a central role in the current round of efforts on humanitarian performance and reform, if we are serious about change.

In Groundhog Day, Bill Murray’s character was only able to end his continuous loop of the same day when he started putting his own interests to one side. He ended the cycle when he stopped being arrogant and duplicitous, stopped trying to ‘win’, and started acting in the interests of the greater good in a simple and honest way.

Groundhog Day is a fable, of course, and to many it may appear a rather sentimental one. But it also contains a lesson that international humanitarian actors would do well to heed.

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A fascinating 7 minute TED talk by Sean Gourley.

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…Because of our urgency to end poverty, we act as if development is a construction, a matter of planning and engineering, rather the complex and often opaque set of interactions that we know it to be…

This is a excerpt from a recent interview I gave to Dennis Whittle (former CEO of Global Giving).

Click here to read the interview in full.

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“Why is geometry often described as cold and dry? One reason lies in its inability to describe the shape of a cloud, a mountain, a coastline or a tree.”  

Benoit Mandelbrot, 1924-2010

Benoit Mandelbrot, one of the most influential and original mathematicians of the past century, died last Thursday aged 85. Mandelbrot’s contribution to science was to try to describe natural phenomena as they actually are, as opposed to using idealised shapes such as circles, spheres, squares and straight lines common to Euclidian geometry. As one thinker put it, ‘[before Mandelbrot] geometry was concerned with abstract perfection almost non-existent in the real world.’

But how exactly did he give scientific validity to the famous words of Gertrude Stein: ‘There is no straight line in nature’?

In the 1960s Mandelbrot, then a research fellow with IBM, undertook mathematical analysis of electronic “noise” which caused interference with electronic transmissions of signals. It was here that he first discovered one of the core properties of fractals which he would go on to identify in a wide range of other phenomena. 

Although the nature of [electronic transmission] errors was not understood, IBM scientists noted that the blips occurred in clusters; a period of no errors would be followed by a period with many. Examining these clusters, Mandelbrot noticed that they formed a pattern and that the closer they were examined, the more complex the pattern seemed to become. An hour might pass with no errors, while the next hour might pass with several errors. However, if one of the hours that contained errors was divided into 20-minute sections, there would be 20 minutes with no errors, then 20 minutes with many errors. On any scale of magnification, Mandelbrot found, the proportion of error-free transmission to error-ridden transmission remained constant. In other words the electronic interference exhibited “self-similarity” at every scale of magnification: each small part, when magnified, reproduced exactly the larger portion.

The same phenomena of “self similarity” was also present in other phenomena. Mandelbrot’s now-famous analysis of cotton prices showed that while “daily, monthly and yearly pricing of cotton was random, the curves of daily monthly and yearly price changes were identical.”  Such phenomena could not be explained using existing tools, leading Mandelbrot to develop ‘fractal geometry’ as a means by which to systematically explore self-similar phenomena. He argued that  most traditional mathematical and classical geometric models were ill-suited to natural forms and processes. In his own words: 

Clouds are not spheres, mountains are not cones, coastlines are not circles, and bark is not smooth, nor does lightning travel in a straight line”

All of these phenomena and many others – stock market prices, earthquakes, planetary motion, blood vessels, even inequality (as Bill Easterly recently argued) – could be modelled using fractals. You can see more examples in Mandelbrot’s popular TED 2010 talk: 

Mandelbrot’s own view of his contribution is short and sweet:

In the whole of science, the whole of mathematics, smoothness was everything… What I did was open up roughness for investigation.”

In the last 40 or so years, Mandelbrot’s work on roughness has left a mark on fields as diverse as statistical physics, cosmology, meteorology, hydrology, geomorphology, anatomy, taxonomy, neurology, linguistics, information technology, computer graphics, and mathematics itself.
His most recent book, The Misbehaviour of Markets, which was published some five years ago and updated after the financial crisis, looks in detail at the fractal nature of risk and reward in financial markets. Co-authored with the Europe editor of the Wall Street Journal, the central message of the book is that modern financial theory is deeply flawed.
Finance, they argue, is built on assumptions of predictability and normal distribution of events (hm, reminiscent of any other sectors?) and as a result financiers vastly underestimate the likelihood of major crises and catastrophes.
Overall, the authors concur with the opinion of Wassily Leontief, a Harvard economist and 1973 Nobel Prize winner: “In no field of empirical enquiry has so massive and sophisticated a statistical machinery been used with such indifferent results.”
This takes on a whole new resonance on this side of the biggest crisis since the 1930s. As Mandelbrot presciently put it in the first edition, in 2005:

the financiers and investors of the world are, at the moment, like mariners who heed no weather warnings…. it is frightening because there are so many people of great brilliance and extraordinary greed who work there. They don’t understand the market, but they understand the numbers… “

And an interview he gave at that time reinforced the point:

A stockbroker wrote me a very plaintive letter asking why I was giving stockbrokers such a hard time. His argument was that what he did was right 98 percent of the time. Why bother about the events that occur in the rest of the time? The answer is that those events are the ones that really count… It is quite clear that some portfolios that were declared to be free of risk turned out not to be. They are very good for 90 percent or more of the time, but at the critical moment, they fail. They are just dreadful. Given the inter-connectedness of things, they may lead to very, very embarrassing complications for the whole world.”

Mandelbrot also gave a fascinating interview to the FT last year, where he takes his axe to the efficient market hypothesis:

It is perhaps unsurprising that the 2008 bestseller The Black Swan, on the importance of low frequency, high impact events in shaping the course of world history, was dedicated to Mandelbrot. (Nassim Nicholas Taleb also wrote an excellent essay on the Misbehaviour of Markets that can be downloaded here.)

To get a bit more into Mandelbrot’s way of thinking, it’s really worth taking a look at the transcript of this 2008 interview with PBS, A Radical Mind.

 This contains one of Aid on the Edge’s favourite quips, which gives us some insight into the nature of the man: “I abandon problems when a constituency gets created around them.

A true maverick to the end.

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The most interesting story this week for anyone interested in complexity and aid  issues is the news that Bill Frej, head of the United States Agency for International Development’s mission to Afghanistan from May 2009 until June 2010, will be the first ‘development diplomat in residence’ at the Santa Fe Institute, the leading global think-tank on complexity science.

Bill will be collaborating with a range of SFI experts on ways to establish evidence-based standards for US foreign policy and aid programs in Afghanistan and Pakistan.

Here is a radio interview he gave to Craig Barnes of KSFR and below are excerpts from another recent interview in which Bill “outlined his plans to apply SFI-style thinking to the complex adaptive system of Afghanistan”.

Q: What prompted this Santa Fe ‘development diplomat in residence’ experiment?

Bill: President Barack Obama appointed Rajiv Shah, a young medical doctor, as the USAID administrator. Shah is coming from a science background. He worked for the Gates Foundation on HIV-AIDS research and program development. He went on to become Undersecretary of Science and Research at the U.S. Department of Agriculture. Obama and Shah bring to international development a new approach. One of their major foci is using evidence-based, scientific research to help better inform foreign policy. It is applying scientific rigor to the question of how you define success in conflict countries such as Afghanistan.

I was really planning on retiring after Afghanistan. Shah came to visit. We got involved in a lot of discussions about science, the importance of research, where he’s taking the agency, his interest in employing a new science and technology director who will work as one of his chief advisers.

Q: Why the Santa Fe Institute?

Bill: Raj knew the Santa Fe Institute. I said I was going to Santa Fe, and I wanted to stay connected to the Foreign Service. I was talking to Jeremy Sabloff. I put together a proposal, and they liked it… my overall interest is conflict. There is a great conflict team here at SFI… but not in the social-policy arena. Paula Sabloff, (Jeremy Sabloff’s wife), one of the leading cultural anthropologists, has a real background and interest in tribes. The issue of tribes, how they live, and work and operate in Afghanistan, has never really been taken into consideration in our formulation of policy direction. Tribes do have and will continue to play a significant role. The tribal dynamics, how decisions are made within tribes, how tribal elders respond to issues in local-level justice — we really are not thinking enough about these issues.

Q: What’s different about this approach compared to what’s already in place for determining if programs are successful?

Bill: We’ve had many performance-monitoring systems in place over the years. Evaluation is a very important part of what we do at the country level. But we’re always looking at outputs, you know, x number of kids, x number of teachers, as the metric that defines success or failure. We now have to broaden that.

We have to look at the evolution of the relationship between metrics and systems. We have to look at how do we really move countries from poverty to prosperity. It’s not going to be purely output based. I think this is a new approach that Shah is bringing to the agency. He’s taking performance-based modeling seriously and looking at it in a completely different way.

Q: What will you be doing as ‘development diplomat in residence’ in the next year?

Bill: I’ll be working to develop two workshops. The first workshop we’ll focus on is looking at the relationship between short-term stabilization programs transitioning to sustainable development. We’re using Afghanistan and Pakistan as the two countries we’ll focus on. I’ve outlined a number of questions we’ll try to answer. 

Q: What are you looking for with a new monitoring and measurement system?

Bill: I think we’re looking at a whole new set of metrics to better define success. Is success the complete dismemberment and destruction of al-Qaida? Or is it more than that? I think the president would agree it is more. Foreign policy, USAID metrics right now are not really based on much science whatsoever. We’re spending billions of dollars in aid in 85 countries around the world. I think we need to be able to articulate what success is better than we have been.

Aid on the Edge has been in touch with Santa Fe and hopes to be speaking to Bill shortly about his work, so watch this space for more on this intriguing initiative.

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Earlier this year, renowned historian Niall Ferguson authored a piece in Foreign Affairs which presented human civilisations as complex adaptive systems, in contrast with the traditional view of civilisations as moving through a gradual cyclical of growth and decline.

As Ferguson argues, the cyclical model of civilisations has been long shared by historians, political theorists, anthropologists, and the public at large. Writers as diverse as Vico, Hegel, Marx and Toynbee shared a common belief and assumption that the history of humanity had some kind of natural rhythm to it. There is a rather standard theory underlying all of this – that all societies will inevitably move through a number of stages, a kind of grand narrative of rise and fall.

“Rome” – the archetypal ‘rise and fall of civilisation’ story (in the West at any rate)

Different disciplines have their own distinctive take on this rise and fall, but with some strong underlying resonances. So, for example, economic historians such as Paul Kennedy suggest that great powers rise and fall “according to the growth rates of their industrial bases and the costs of their imperial commitments relative to their GDPs.” By contrast, ecological historians such as Jared Diamond argue something like this: “population[s] grew larger than their fragile and inefficient agricultural system could support. More people meant more cultivation, but more cultivation meant deforestation, erosion, drought, and soil exhaustion. The result was civil war over dwindling resources and, finally, collapse.”

Easter Island, one of the civilisations described by Jared Diamond in Collapse

However, alternatives theories are available, which are based on a more realistic understanding of how change actually happens. As Ferguson asks:

What if history is not cyclical and slow moving but arrhythmic — at times almost stationary, but also capable of accelerating suddenly, like a sports car? What if collapse does not arrive over a number of centuries but comes suddenly, like a thief in the night?”

Ferguson argues that great powers and empires can be characterised as complex systems, made up of a very large number of interacting components, that “more resembles a termite hill than an Egyptian pyramid.” As such, they operate between order and disorder, on “the edge of chaos”, and while they may appear to be stable and in equilibrium for long stretches, they are in fact constantly adapting to maintain the overall sense of stability.

But there comes a moment when complex systems “go critical.” A very small trigger can set off a “phase transition” from a benign equilibrium to a crisis.”

Bond Trader, London, 2008

This so-called sandpile effect is, according to Ferguson, all too often misunderstood and misrepresented by those who seek to explain past events.  The fundamental problem is that analysts who analyse such crises tend to explain low-frequency, high-impact moments – wars, crashes, collapses – by misunderstanding complexity and how it works.

Instead of looking at the interconnectedness of the events and the prevailing context, most analysts try to explain crises in terms of linear, long-term causes. This is the ‘narrative fallacy’ identified in popular works such as the Black Swan by Nassim Nicholas Taleb, and this gives rise to a much more cyclical, and perhaps more comprehensible, model of change.

As Ferguson suggests:

Drawing casual inferences about causation is an age-old habit. Take World War I. A huge war breaks out in the summer of 1914, to the great surprise of nearly everyone. Before long, historians have devised a story line commensurate with the disaster: a treaty governing the neutrality of Belgium that was signed in 1839, the waning of Ottoman power in the Balkans dating back to the 1870s, and malevolent Germans and the navy they began building in 1897. A contemporary version of this fallacy traces the 9/11 attacks back to the Egyptian government’s 1966 execution of Sayyid Qutb, the Islamist writer who inspired the Muslim Brotherhood.

In reality, according to Ferguson, the proximate triggers of a crisis are often sufficient to explain the sudden shift from a good equilibrium to a bad mess. So, from his perspective:

World War I was actually caused by a series of diplomatic miscalculations in the summer of 1914, the real origins of 9/11 lie in the politics of US and Saudi Arabia in the 1990s… Most of the fat-tail phenomena that historians study are not the climaxes of prolonged and deterministic story lines; instead, they represent perturbations, and sometimes the complete breakdowns, of complex systems.

 

Ferguson concludes that “an understanding of how complex systems function is an essential part of any strategy to anticipate and delay their failure…” On the other hand, according to Taleb, the profound misunderstanding of the causal chains between policy and actions – what he terms ‘aggressive ignorance’ – can lead to triggering a multitude of Black Swans: “like a child playing with a chemistry kit”.

There is a lot of uncertainty in the application of ideas in complexity to social, economic and political problems (see for example the debates kicked off by Bill Easterly using fractals to describe inequality last week on Aid Watch). What is clear, however, is that establishing the kind of understanding Ferguson and Taleb call for is far from straightforward:

causal relationships are often nonlinear, which means that traditional methods of generalizing through observation (such as trend analysis and sampling) are of little use… Some theorists of complexity would go so far as to say that complex systems are wholly nondeterministic, meaning that it is impossible to make predictions about their future behavior based on existing data.”

As argued in a previous aid on the edge of chaos post, the biggest challenges to the wider take-up of such complexity-inspired suggestions is that, if they stay both sensible and true to the principles of complexity, they tend not to provide recipes which can be followed. Rather, complex adaptive systems theory:

  • provides a set of lenses with which to look at the world,
  • helps pose questions which can help better understand the dynamics of real world systems, and
  • helps generate insights as to how these dynamics can be ‘sensed’ and ‘navigated’

There is much of relevance here for thinking about development and humanitarian work. As a recent interviewee suggested to me, complexity theory helps us understand processes of development as continuous, emergent and full of surprises.

But aid efforts – sometimes deliberately, sometimes unintentionally, sometimes because of contractual necessity, sometimes through sheer incompetence – tend to misrepresent these evolutionary processes of change in the complex systems that are developing countries.

And so at its simplest, the lesson to draw from Ferguson’s essay is that in order to….

 

…first we have to understand better exactly how history is made.

 

(Thanks to Rick Davies for bringing the original article to my attention)

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Lessons from theatrical improvisation have clear parallels with group dynamics in other social systems, including aid agencies…

Outside of work, theatre is one of my main passions. In my tentative attempts to learn more about different aspects of stagecraft, I have stumbled across some fascinating thinking which is of real relevance for Aid on the Edge readers.
In a previous post, I touched upon jazz improvisation as an analogy for a new wave of economic thinking, and here I am interested in looking in some detail at theatrical improvisation (or improv for short, hence the Cleese-defying* title for this post) as a source of valuable insights in its own right.
One of the most interesting thinkers in this area is Michelle James, CEO of The Center for Creative Emergence,who has a theatrical background but has also run improv-based programs at major organisations like Microsoft, Kaiser Permanente and the World Bank (yes, I did a double-take at that last one too!). James is clear about the minimalist starting points of effective improv:
No structure. No outline. No character or plot development. Nothing, except for 2 locations we get from the audience at the beginning of the play. The play is then titled, “The Space Station and the Bathroom” or whatever locations we get from the audience. Two of us then run on stage and start interacting, and thus the play begins…

However, sometimes the ensuing play worked, and seemed easy. And other times, it was clunky, and seemed hard. This led James to ask some searching questions:

What creates peak level creativity in our group? What allows a complex, coherent, sense-making structure to emerge from nothing but a simple location? What is the “magic formula” that allows a fully formed, organized play – with believable characters and plot – to emerge before the audience’s (and our own) eyes? And what gets in the way? Why does it work seamlessly sometimes and not so well other times?

James’ explorations found direct correlations between the principles of improv in a performance and being able to adapt, create and perform effectively in any social system. Specifically, “the same principles that allow a performing group to improvise a 90-minute play out of nothing but a location are the same principles that allow groups, teams, and organizations to solve problems in new ways and reach peak levels of creativity and innovative thinking. The principles form the “container” that allows the group to self-organize to emerge what’s next.”

James went on to do work with the Plexus Institute (one of Aid on the Edge’s favourite think-tanks) which helped her see clearly the connection between complex adaptive systems and improvisational theatre groups:

Both are open, inclusive, non-linear, dynamic systems that use interactive agents, feedback loops and multiple variables. Both require resilience, collaboration, structure and flow, spontaneity, and engaging the unknown. Both result in a surprising emergence. In our troupe, we don’t go on stage with a pre-formed notion of our characters, plot, conflict, challenge or situation. We just let them emerge based on our interactions, actions and reactions. The “magic formula” is the adherence to the basic improv principles. When we adhere to the principles of improvisation, something emerges that is more intelligent and creative – and intelligently organized – than any one of us could have planned…

Through this work, James has managed to identify  seven basic principles of improvisation, each of which is relevant to, and challenging for, international aid agencies’ work:

1. ‘Yes and’ (not ‘no but’)… Fully accepting the reality that is being presented, and then adding a new piece of information, allows a group to be adaptive, move forward and stay generative. Each ‘actor’ interacts with what is offered and should be seen as offering a unique contribution.

Compare this with the international NGO manager who said, of a national partner organisation: ‘they have to be really special to turn to us and say, they want to do things another way’.

2. Make everyone else look good That means actors do not have to be defending or justifying themselves or their position – instead they should trust that others will do that for them and they will reciprocate. Minimising the burden of defensiveness or competition means all actors are free to create.

As highlighted in a recent piece I wrote with Michael Barnett entitled the Humanitarian’s Dilemma, we need to find ways of making aid agencies care more about each others success…

3. Be open to changed by what is said and what happens At each moment, the changing context and new information it generates is an invitation for actors to have a new reaction or experience. “Change inspires new ideas, and that naturally unfolds what’s next.”

But aid agencies, in the damning assessment by Richard Dowden, pay less attention to context than their colonial forerunners. And they are  also often described as maladaptive in the face of change, most recently by the Humanitarian Futures Programme.

4. Co-create a shared “agenda” This principle involves the recognition that even the best-laid plans are abandoned in the moment, and that it is important to serve the reality of what is right there in front of a given actor. The reality is that any agenda is being co-created in real-time.

My observation in this context is that aid agencies are all too often stymied by the need for consensus, and for delivering against pre-established goals. This radically reduces the space of possibilities, as opposed to co-creation which expands them.

5. Mistakes are invitations to change the pattern In improv, mistakes are embraced – they are the stimuli that invite actors to shift to new levels of creativity. Techniques such as ‘acknowledging any mistake’ can be transformed into surprising plot point or dialogue that never would have happened in following a conventional pattern. In improv, this creates order out of chaos. Mistakes that are acknowledged can help break existing patterns and allow new ones to emerge.

It hardly needs to be said that learning from mistakes is not an area where aid agencies excel. As the old proverb puts it: the person who fails to learn from their mistakes is condemned to repeat them.

6. Keep the energy going through uncertainty No matter what is given, or what happens, there is a fundamental need accept it and keep the energy gong. Unlike in everyday life, where people stop to analyze, criticize or negate, in improv there is a need to keep moving. A mistake happens – let it go move on. The unexpected emerges – use it to move on. Trust the process and just keep moving – after all, human systems are never static – they are alive and dynamic.

By contrast, aid works through big pendulum swings, cycling repetitively through trends, fashions and reforms in a way that is tremendously disheartening for the long-term observer. Few sectors can turn a romantic into a cynic quicker than international aid….

7. Serve the good of the whole By always carrying the question, “How can I best serve this situation?” actors will have a better sense of when to run in and when to stay back, when to take focus and when to give it, how to best support their fellow actors and how to best support the situation. By focusing away from how they will individually appear to serving the larger good there is scope for following more creative impulses and identifying new resources in unexpected places.

Again, the Humanitarian’s Dilemma piece highlights this as a vital but neglected issue on the humanitarian side of the aid sector. All too often, and often for very pragmatic reasons, individual mandates overwhelm the collective good.

The principles that allow effective improvisation seem simple and easy. However, in practice, they would appear to be almost the exactly opposite of the ways in which aid agencies navigate their strategic and tactical challenges.

James is clear about what makes improv hard, and this too is sobering stuff:

Simple: any violation of the principles. If one of us tries to orchestrate, or worse impose, our own agenda or plot on the piece. If one of us tries to be the “star” and take too much focus. If even one of us is not present to what is unfolding, moment-by-moment. If one of us worries about the plot, and starts to figure out how to “save” it. If we expect that someone should respond in a certain way. In short, anything that gets us out of the moment and what is emerging – and into our ‘controlling’ heads.

The key would seem be to find clear and convincing ways of arguing that such alternative improv-based approaches are in fact the most appropriate way of dealing with some of the longstanding problems faced in the aid sector. Take urbanisation, climate change,  institutional change, global crises… the list goes on and on. The body of knowledge is growing, as are the voices calling for radical changes in aid policy and practice. Bill Easterly’s call for scrapping Aid Planners in favour of Aid Searchers is perhaps the most high-profile and vociferous example.

Increasing numbers of aid practitioners, academics, analysts, bloggers, tweeters and external observers are now arguing that a more anticipatory, adaptive and innovative approach to development and humanitarian work is essential if aid agencies are to remain relevant in a rapidly changing world. Time will no doubt tell if they are right.

There is one parting lesson from James to bear in mind - just because you are being creative, doesn’t mean you can’t also be rigorous and tireless in your pursuit of what works and why. I find myself as inspired by her approach and the processes she has employed, as by her results and findings. Maybe that’s the secret to all successful improv.

*FOOTNOTE: John Cleese’s 3 rules – No puns, no puns and no puns.

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According to 2008 ALNAP research on organisational change in the humanitarian sector, ’all theories of organization and management are based on implicit images or metaphors that lead us to see, understand, and manage organisations in distinctive yet partial ways.’

One of the key metaphors used in that work, drawing on the groundbreaking efforts of organisational theorist Gareth Morgan, was to consider aid organisation as brains.

This idea has gathered pace in the last few decades and years. Organisational development approaches increasingly focus on the thorny issues of information, knowledge and learning. Such approaches draw - in many cases implicitly – on theories of how the brains functions.

For example, perhaps the most widespread model of organisational learning is that of ‘learning loops’, developed Chris Argyris and Donald Schön. As they put it in their classic work:

When the error detected and corrected permits the organization to carry on its present policies or achieve its presents objectives, then that error-and-correction process is single-loop learning. Single-loop learning is like a thermostat that learns when it is too hot or too cold and turns the heat on or off. The thermostat can perform this task because it can receive information (the temperature of the room) and take corrective action. Double-loop learning occurs when error is detected and corrected in ways that involve the modification of an organization’s underlying norms, policies and objectives.

So in the aid sector, single-loop learning might involve asking ‘are we delivering food aid well?’, while double-loop learning might ask ‘should we be delivering food aid at all?’

Many approaches seem to be built on some shared assumptions which draw from an underlying notion of how the brain works, including the following:

  • strong central leadership and control is necessary to direct learning efforts, akin to ‘thermostatic processes’
  • clear goals and objectives are vital provide a context and frameworks for learning
  • hierarchies are essential to allocate clear responsibilities for learning
  • getting the overall organisational structure correct is key and
  • information systems should be designed from the top down to fit with the high-level goals

While these may be sensible assumptions in some settings, it seems that the ‘learning loop’ and similar approaches draw on theories and models of the brain that are increasingly out of date. Recent advances in understanding how the brain works in practice provide contrasting perspectives for thinking about organisational learning.

First, research published this month by scientists at the University of California has identified that much of the current understanding of the brain is based on weak and outdated assumptions. As one of the researchers recently said in an interview:  “You would be amazed at how much of the current experimental neuroscience literature is dominated by ‘top-down thinking’, which goes back to the 19th Century. The approach seems to be akin to a thermostatic one, which implies power and control that is concentrated in a particular location in the brain.”

These scientists have shown that the brain is in fact a vast interconnected network much like the Internet, contradicting traditional ”top-down” views of brain structure.

If the brain has a hierarchical structure like a large company, as neurology has long held, the “to” and “from” diagram would show straight lines from independent regions up towards a central processing unit: the company’s boss. But instead, the researchers saw loops between differing regions, feeding back to and directly linking regions that were not known to communicate with one another. This is a better fit with the model of vast networks such as the internet. Such a highly interconnected structure has been hypothesised for some time, and could prove to be a powerful tool in analysing how the brain processes information. But it had not, until now, been demonstrated experimentally.”

Second, another feature of the brain that has seen speculation and hypotheses but little demonstration until relatively recently is the idea that the human brain operates “on the edge of chaos”. This is defined as a critical transition point between randomness and order (and, needless to say, this concept is a rather compelling one for Aid on the Edge :) )

This “edge of chaos” state can emerge spontaneously from the multilayered interactions between the many elements that make up a complex system. It has been identified in many different settings, including avalanches, forest fires, ecosystems, earthquakes, and heartbeat rhythms.

Recent research published by a team led by Cambridge University researchers provides new and compelling data to support this theory.

Using state-of-the-art brain imaging techniques they were able to measure changes in the synchronisation of activity between different regions of the human brain. The results suggest that the brain can spontaneously organise itself at a point on the edge of chaos between order and randomness. This point at the edge of chaos allows neurones to jump quickly between different states enabling them to alter behaviour as necessary, allowing humans to respond quickly to the environment around them. A similar idea is used in the design of fighter jets – they are designed to be aerodynamically unstable (a state of chaos) and can only be controlled with the aid of computers, though this instability means they are extremely quick to respond to commands. These results suggest that the dynamics of human brain networks – the basis for thought, emotion and action – have something in common with very different systems in nature.

What are the possible implications for organisational learning theory and practice?

For starters, a number of the assumptions about the learning organisation cited earlier which are fundamentally challenged by this new understanding of the complex functioning of the brain.

At the very least, the metaphor of the organisation as a brain needs us to shift from a model of learning based on thermostatic, centrally directed, error-detecting processes to one which considers learning as a series of networked, self-organised, spontaneous processes. This gives additional weight to the idea of ‘emergent learning’ being of critical importance  within organisations.

Rather than trying to formalise and control through information systems, the implication is that one should be trying to strengthen the social dynamics and practices that facilitate learning. While many of those working on knowledge and learning efforts in aid agencies know this to be true – and there have been some brave efforts to strengthen social learning – in practice top-down, systems-based approaches have dominated. (Some of these issues were explored in a previous post on social media, aid agencies and complexity.)

This is not to say that all top-down approaches are bad, or that all emergent processes are good. Instead, a better balance between the two is the holy grail of effective learning. In Bill Easterly lingo, becoming learning aid agencies requires both Planners and Searchers, as relevant and appropriate, and in ways demanded by circumstances and context. 

Successful learning processes always require a degree of planning, but this must be allowed to emerge and change as parts of an organisation take a lead in making their various contributions. In succesful learning processes, hierarchy and control have an emergent quality; they cannot be pre-designed and imposed.

The fundamental challenge is how to navigate the tensions and contradictions between ‘leadership + power’ and ‘adaptation + innovation’.

As Morgan puts it:

Any move away from hierarchically controlled structures toward more flexible, emergent patterns has major implications for the distribution of power and control within an organization, as the increase in autonomy granted to self-organizing units undermines the ability of those with ultimate power to keep a firm hand on day-to-day activities and developments. Moreover, the process of learning requires a degree of openness and self-criticism that is foreign to traditional modes of management. Both of these factors tend to generate resistance from the status quo. Managers are often reluctant to trust self- organizing processes among their staff and truly “let go.” Many early experiments in self-organizing work designs encountered this problem, and many still do. There is such a strong belief that order means clear structure and hierarchical control that any alternative seems to be a jump in the direction of anarchy and chaos.”

The next post on Aid on the Edge will look at ‘complex adaptive leadership’ in some more detail.

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The argument that modern organisations have to deal with complexity on a daily basis is fast becoming one of the least controversial statements any analyst, policy maker or practitioner can make. But what this actually means in practice is up for debate.

Some suggest that there is little or no rigour in statements such as ‘the world is increasingly complex’, and that beneath such arguments there is little but smoke and mirrors. See for example a recent blog which rips into the 2010 IBM CEO survey (highlighted here last month) for being based solely on perceptions rather than ‘anything real’.

Others say that we live in a qualitatively different world to previous eras, one marked by increasing interconnectedness and interdependence – economically, socially, politically, environmentally and technologically. In such an interdependent world, the argument goes, there is greater unpredictability and uncertainty. In the extreme, standard operating procedures, best practices and grand designs can be irrelevant, counterproductive or downright damaging.

Among this second group there is growing attention being paid to the the ideas of the complexity sciences,  to tap into their apparent potential to help think about an increasingly challenging world, and maybe even  better deal with its problems.

The last few weeks have seen some interesting blogs and articles that look at different crisis contexts – from global crises to humanitarian disasters and fragile states.

First, on global crises. Of special interest is the role of complexity sciences to help understand and navigate recent interwoven global crises - notably the so-called ‘Triple F’ crises of food, fuel and finance ( a previous Aid on the Edge of Chaos post highlights how Andy Haldane, a Bank of England director, used complexity science for exactly this purpose).

Lord Julian Hunt, former CEO of the UK Met Office, argues in a Reuters Blog that the rapid growth of global inter-connected problems have led to new kinds of collaborations between scientists, policymakers and the private sector. He sees “particular emphasis is being paid to global system dynamics” to inform policy making, research and practice.

Recent applications include using the ideas of complexity to understand how such crises emerge and are propagated; how individuals and organisations adapt to such crises; the resource implications of such crises; and the implications for sustainable development efforts.

Elsewhere, in an excellent post that is highly relevant to the ongoing Pakistan appeal and response, Wanderlust draws on Dave Snowden’s work on the Cynefin framework to illustrate how aid responses to humanitarian disasters are poorly matched to crises contexts:

When aid gets talked about in the public sphere, it’s generally messaged very simply in the media. Children are starving. They need food. An X-Y relationship. Ditto following an earthquake: houses are destroyed and people are in the rain: Give them tents. A Simple paradigm… When aid agencies manage their response programs, they create complicated management systems that involve careful analysis of all the factors, putting them into project documents with LogFrame Analysis that looks at cause and effect and all the possible links along the way that need to be managed. An X—Y relationship. A Complicated paradigm- certainly not Simple. However the realities of aid responses are neither Simple nor Complicated. At best, if you take a stable long-term chronic emergency like the situation in Darfur, it is fraught with feedback loops and vague inter-relations where cause and effect are highly flexible and interdependant. In Darfur there are more than two dozen armed groups operating, with their areas of control shifting on a weekly basis. When one gains strength, others weaken. They have their foundations in specific community and ethnic groups with long historical relationships. The drivers for the conflict are primarily natural resources, but there are also ethnic, political and other economic implications as well. By providing aid to one group you inadvertantly exclude or depower another, and emotions such as resentment or loyalty then shift that landscape. I could go on for pages describing the Complexity of Darfur. We can understand bits and pieces about it, and trace some of the loops and mechanisms in the systems, but we’ll probably never manage to map it in its entirety, and there will always be things outside our control – from human behaviour to the climate.

Last but not least, Foreign Policy in Focus draws on complexity principles to suggest what might really be done about Somalia, perhaps the archetypal ‘fragile state’. As is eloquently argued there:

Now that the violence of Somalia has spilled over into Uganda, western policymakers and pundits are suddenly all aflutter with the urge to ‘do something’. Exactly what that something might be is uncertain. Drone attacks, special forces, a Gaza-like blockade and even a full scale invasion have been suggested.

All of those are truly terrible ideas – and exactly the kind of legacy thinking that caused the US to hug the tar baby of IrAfPak. At best, they will generate yet another failure / quagmire, and expand the ever growing pool of pissed off people who want to car bomb Times Square. At worst, they could invite a ‘fifth column’ type of resistance on the part of the Somali diaspora and sympathizers, spreading conflict across the region and beyond. (Somewhere between 40% and 50% of ethnic Somalis live outside the country.)

Instead of pursuing the same old failed policies, the way to resolve intractable problems is to expand the ‘solution space’ – the range of available options. Solution space is determined by the perspectives – which we might also call beliefs, paradigms or ‘mental models’ – of the players involved. Because we can only act on ideas that get through our political / cultural / personal filters, the way to achieve breakthrough is to broaden our perspectives in order to see a wider range of possibilities…”

Each of these articles is challenging, thought-provoking and well worth a read. Each presents the limitations of existing approaches to analysis, policy and the subsequent actions taken by international organisations. Each attempts to present alternatives to what they view as outmoded ways of working, drawing on complexity principles.

Take Hunt’s argument that complexity science approaches can help us develop appropriate regulation of computerised financial markets. Or Wanderlust’s suggestions that a field managers’ gut instinct can prove as useful in chaotic disaster settings as a 3 week research study conducted by experts. Or the FPIF notion that imposing government structures in Somalia will be far less effective than acknowledging and working with existing governance processes, even if the government in place is disagreeable to Western sensibilities.

Perhaps the biggest challenges to the wider take-up of such complexity-inspired suggestions is that, if they stay both sensible and true to the principles of complexity, they tend not to provide recipes which can be followed. Rather, complexity theory

  • provides a set of lenses with which to look at the world,
  • helps pose questions which can help better understand the dynamics of real world systems, and
  • helps generate insights as to how these dynamics can be ‘sensed’ and ‘navigated’

Despite this, complexity sciences are all too often judged by the same set of values and mindsets inherent to existing mechanistic and top-down ways of working. All too often people seem to want to get something for nothing from the ideas of complexity – they in effect want to see complexity applied in ways that ‘tell us what to do’. For those looking to replace mechanistic recipes with complexity-inspired recipes, disappointment is inevitable.

As Cynthia Kurtz, one of the co-developers of Cynefin, recently wrote in a wonderful essay:

Emergence requires presence. It requires awareness, negotiation, the building and verification of trust, the mending of fences when they need to be mended and the removal of barriers when they obstruct. Most people do emergence well, but rarely without effort. If it is without effort, it is more likely to involve following instructions, not participating in emergence.

Perhaps this imposition of old attitudes onto new approaches is inevitable. But it is not irredeemable. As Albert Einstein has suggested: “we can’t solve problems by applying the same kind of thinking we used when we created them.”

Where to start then? However huge the political and institutional challenges may seem, there may be as many blockages and biases at the level of individual personal preferences. To close on another classic quote, this time from Tolstoy: “everyone seeks to change the world, no-one seeks to change themselves”.

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