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This week sees what promises to be a fascinating event bringing together practitioners and scientists to reflect on issues of complex adaptive systems and rural development, organised by World Vision Canada in Arusha.
The three day conference has a special focus on the lessons from an innovative programme to enhance aid agency staff and community leaders capabilities to “deal with the changing and complex nature of poverty and development”.
Governance, Ecosystems, Livelihoods (GEL) is a three-year program funded by Canadian International Development Agency, World Vision Canada and the Manitoba Council of International Cooperation (MCIC) and is aimed at improving community resilience in four African countries.
What makes GEL stand out, to my mind, is the explicit attempt to bring complexity thinking into aid policy and practice, and at the largest international NGO, no less.
The GEL program proposes the use of complex adaptive systems (CAS) approach as an effective and sustainable framework for World Vision Canada and its partners to promote good governance, advance environmental sustainability and create a better environment for economic development.
As the GEL programme information suggests:
The need for this program emerged from a growing awareness that, despite the best of efforts, many poverty and health indicators in sub Saharan Africa are actually getting worse. Traditional sector based approaches were not fully addressing the complex underlying causes of poverty. Development assumptions have been made and strategies developed, on the fact that the needs of people were based on a homogeneous and essentially static knowledge of communities and environments. The situation of individuals within communities varies temporally, spatially and socially at a variety of scales. Attempts to “sector” peoples lives have often ignored important external problems, influences and feedback loops that affect poverty. The current challenge is the need to develop tools and frameworks to deal with this complexity. New strategies for transformational development are needed.
The speakers at the event include David Waltner-Toews, Chris Burman and Harry Jones (who worked with me on the ODI working paper on Exploring the Science of Complexity). I managed to speak to David and Chris before the event, and they both had some fascinating insights to share which will resonate with regular Aid on the Edge readers. Here are a couple of their insights, rapidly transcribed – I hope I have done them justice!
David:
…complexity enables us to simultaneously address technical, ethical and political issues – it allows you to do so, in fact, done right it even forces you to do so. There is a strong tendency in large development bureaucracies to separate out these things – so for example, there may be a new strategy which says, we are doing agricultural development, and therefore we want to increase productivity and value for money. But if you ask, what are the implications for equity, community, gender, taking into account that women tend to do better in the informal economy and men in the formal economy, the standard response is, that’s not our department, go to health, or the place where that is dealt with… Give me a legitimate theoretical basis for saying ‘this is just agriculture, this is just health, this is just environment’. We need to bring together disciplinary perspectives on the same complex reality because ultimately the world we live in is all of these things…
Chris:
…complexity enables us to begin to get people to think about the world in different ways – which means they have an expansive learning field as opposed to a rigid learning field… much aid learning is very limited and it has almost no space for creativity – it is learning as a bureaucratic tick-box. Complexity approaches open up new potentials and horizons within which learning can take place, and if we can play around with new ways of situating learning in the context of peoples lives, we can find ways of moving beyond the linear and predictable. The key is to use complexity to reframe the context for learning…”
Compelling stuff. I will be blogging more about the event in the next week, hopefully with some of the presentation files and real-time updates from the participants, and will also be writing about the some of the lessons emerging from the GEL programme in the coming weeks. Watch this space!
Posted in Agriculture, Facilitation, Innovation, Institutions, Knowledge and learning, Organisations, Resilience, Strategy | 1 Comment »
“In these troubled, uncertain times, we don’t need more command and control; we need better means to engage everyone’s intelligence in solving challenges and crises as they arise.”
Traditional perspectives on leadership are based on a view of organisations as mechanical systems. Organisations are made up of prescriptive rules, formalised control mechanisms and hierarchical authority structures – all adding up to clearly defined responses to a changing but knowable world.
This machine model of organisations is prevalent among international agencies, as ALNAP research identified in 2008, and carries with it some clear assumptions about what effective leadership means in the aid sector.
The aim of the machine organisation is to achieve routines, equilibrium, stability and order, and leaders are expected to contribute to this stabilisation through directive actions, based on planning for the future and controlling organisational responses.
However, in complex systems, as regular readers of this blog will be well aware, the future cannot be perfectly predicted and change cannot be precisely directed. Russ Marion and Mary Uhl-Bien have undertaken over 10 years of research which suggests that in complex systems there is a need for distinctive leadership qualities.
Empirical research in many different organisations – they range from church-based community organisations to Al Qaeda – has highlighted a number of vital ‘complex adaptive leadership’ qualities. Some of these findings resonate with Marshall Ganz’s analysis of the 2008 Obama Presidential Campaign, examined in a previous Aid on the Edge post.
Specifically, ‘complex adaptive leaders’ are characterised by their ability to 1) disrupt existing patterns; 2) encourage novelty; and 3) use ‘sensemaking’.
- Leaders disrupt existing patterns in organisational behaviour by creating and highlighting conflicts, rather than stabilising the organisation. For example, in the organisations under study, successful leaders made several radical and controversial changes, internally and externally, and used communications to bring attention to these changes as a way of highlighting the importance of the ongoing change. This contrasts with the traditional leadership approach of creating predictable behaviours by minimising conflict and eliminating uncertainty. Another way for leaders to disrupt existing patterns is by acknowledging and embracing uncertainty, refusing to back away from uncomfortable truths, talking openly about the most serious issues, and challenging institutional ‘taboos’. This can encourage more open thinking about these issues, and provide legitimate ground for new ideas and patterns to emerge. Again, the traditional leadership approach was to shy away from difficult conversations and focus on hoped-for certainties.
- Leaders encourage novelty by actively looking and promoting innovation rather than standard operating procedures. They do this by generating and reinforcing simple rules which could allow innovation to emerge at local levels. Such “distributed leadership” is based on ‘tenacious rigidity about principles and complete flexibility in how to go about carrying out the principle’. Facilitating interactions was also key, enabling staff to start interacting with each other in new and different ways. Instead of creating a single ‘assembly point’, successful leaders kickstarted many small group interactions, increasing connections between people and creating a richer and more unpredictable dialogue within the organisations in question. This contrasts with the traditional model of a leader as using command and control approaches, and maintaining strict hierarchies of reporting relationships.
- Finally, leaders act as ‘sensemakers’, helping to interpret rather than ‘forge’ or ‘drive’ change. Leaders so this by giving meaning to what is happening, acting as ‘tags’ (Holland, 1995). Tags enable specific behaviours by directing attention to what is important and what things mean. Leaders become tags when others recognise that they symbolise deeper messages of change. Leaders also make sense of emergent and unanticipated events through reframing, either in the principles of the organisation, or in the context of the hoped-for changes and how important they are. And leaders label behaviours in ways that provide coherence and shared understanding. Using language carefully, leaders are able to articulate meanings, lend weight to collective action, and clarify the hoped-for image of the organisation.
The overall conclusion of this research was that the leaders of successful organisations did play a key role in radical transformations of those organisations, but not by specifying it or directing it but by creating the conditions which allowed for the emergence of such change.
The contrasts between traditional and complex adaptive leadership are shown below, drawing on research from the University of Minnesota.
| Conventional View of Leadership | Complex Adaptive Leadership | |
| Leadership is… | a position or role of authority | an activity or behavior that can arise anywhere in a human system |
| Leadership flows… | in one direction: from the top-down | in all directions |
| Leadership is exercised… | by individuals with special leadership traits | collectively by groups and/or by individuals informed by the collective |
| Effective leadership comes from… | accurately anticipating a predictable path to a predetermined outcome | recognizing and influencing patterns that are present in human systems at all levels |
| Leadership requires… | certainty, clear vision, and the power of persuasion and control | willingness to embrace uncertainty, listen to all voices and take adaptive action, often in collaboration with others |
| Leadership creates… | harmony and stability | conditions that are conducive to groups moving forward — which sometimes means disrupting the habitual patterns of engagement so that groups, communities, or organizations can set the conditions for a preferred future |
| The purpose of leadership is to… | fix problems and leverage opportunities to achieve goals | enable adaptability, learning, and innovation so that groups make progress on the issues they care about –even in unpredictable and changing conditions |
| Leadership can make a difference through… | one large strategic intervention designed to fix a problem or achieve a goal | recognizing emerging patterns in human systems and making meaning out of many small changes |
This is challenging, not least because it subverts the sources of power traditionally relied upon by leaders for their authority. This is especially the case in the aid sector, which relies on a degree of certainty for its very existence (“give us more aid so the flood victims suffering will be eased”, “give us money so we can make poverty history”, etc etc etc).
Instead of a culture of compliance, so predominant among aid agencies, leaders need to foster a culture of curiosity. This leads to a paradox of leadership in complex settings such as those faced by aid agencies: leaders need to undercut their sources of power, while simultaneously retaining people’s confidence and trust. They need to outline the uncertainties they face while simultaneously eliciting trust of key stakeholders (for more on trust, see the previous Aid on the Edge post). This may ultimately mean that aid agencies need to go for smaller, more humble, more realistic, but ultimately more effective approaches.
This is the aid leadership paradox – if anyone wants to truly lead an aid organisation in complex settings, they need to give up on conventional ideas of being a leader of an organisation.
This calls for being less worried about growth, and more focused on relevance; less about branding and profile, and more about partners and relationships; less concerned with ’being the first and the best’, and more obsessed with the collective, longer-term effectiveness of aid efforts.
A good guiding principle might be the old Teddy Roosevelt quote: “There is no limit to what a person can achieve if they don’t mind who gets the credit”.
Posted in Facilitation, Innovation, Institutions, Knowledge and learning, Leadership, Networks, Organisations, Resilience, Self organisation, Strategy | 2 Comments »
For one reason or another, I have been thinking about trust this week. Trust is regularly cited as a critical factor in effective aid organisations, is seen as the essential for partnerships, and creating it is seen as a primary task for aid leadership.
But all too often trust is mentioned as if it can simply be designed, imposed and managed. As a concept, trust is both over-used and poorly understood.
From the viewpoint of aid organisations as complex social processes, and drawing on Chris Rogers’ Informal Coalitions approach, trust has three specific features which are overlooked or ignored.
First, trust is a property of relations and interactions. Second, trust is multidimensional. Third, trust is emergent. It’s worth looking at each of these in turn.
1. Trust as a property of relations and interactions
…people’s sense of trust is embodied – or not – in the unscripted detail of each and every interaction that they have with one another. It is personally and socially constructed – both consciously and subconsciously – in these moments that people come together. As such, it reflects participants’ past history of interactions, their future hopes and expectations about this and/or other important relationships, and the current immediacy of the exchange. At the same time, the emerging outcomes of this ongoing process shift the ways in which ‘the past’ is recalled, ‘the future’ is constructed and the present is lived – all in the here and now.”
2. Trust is multidimensional:
…we might believe that someone is being genuine and truthful when they say that they intend to do something, and yet still not trust them to do it because we don’t think that they have the necessary competence.
The dimensions include:
- character (perceived integrity and trustworthiness)…
- community (whether the person is recognized as being ‘one of us’, with shared perspectives, common interests and sense of identity)
- communication (perceived openness, honesty and straightforwardness);
- confidentiality (sense that it is ‘safe’ to share confidences) – “I believe that I can be open with you, without fear of you taking advantage of me or breaching that confidence.”
- credibility (whether or not the ‘story’ makes sense and is believable in it’s own right) – “I believe that your ‘story’ (proposition, strategy, system etc) is credible and makes sense in its own right.”
- capability (perceived knowledge, skills and abilities in relevant areas) –“I believe that you have the necessary capacity and competence to do what is needed in this situation.”
- commitments (dependability in keeping agreements and promises) – “I believe that I can depend on you to do what you say you will do.”
- context (whether the patterns of taken-for-granted cultural assumptions are tending to channel behaviour in ways that enhance or undermine trust) – “I believe that the organizational culture and climate fosters an environment of trust.”
3. Trust is Emergent
Complexity science has long been used to understand issues of trust and cooperation. In his now-classic work, noted complexity thinker Robert Axelrod showed how trust can emerge even in situations where there are self-interested actors with no central authority. More generally,
People derive their sense of trust from the detail of the actions, interactions and transactions that comprise everyday life in the organization. The sense they make of their world, including the feeling of trust (or mistrust) that this evokes, emerges from this ongoing interactional process. Also, the more that a particular ‘sense’ of trust is ‘taken up’ by others, through the diverse interplay of conversations across an organization (or fragments of it), the more generalized it becomes. It is then more likely to be taken up in similar ways by those same people in future – and, potentially, by others with whom they interact… It is the self-organizing process of ‘shared’ meaning-making, through which patterns of assumptions emerge and become taken-for-granted over time. These patterns create expectancy and tend to channel ongoing sensemaking, imperceptibly, down familiar ‘pathways’. Since this patterning process is self-organizing, it means that trust cannot be ‘designed and built’ by managers, as part of a structured ‘culture change programme’. However, a major influence on this ongoing sensemaking and action-taking is people’s observation of the behaviours of those in formal leadership positions – throughout the organization.”
These different properties of trust may be essential to understand if we are serious about furthering aid efforts. For example, in aid reform processes, trust is repeatedly highlighted as one of the enduring challenges facing progress. On the development side, the Paris Declaration advocates for harmonisation between donors and mutual accountability with national governments; on the humanitarian side, the Cluster approach seeks to coordinate international relief efforts by bring the NGOs together in UN-led, sector-specific networks. Both approaches have been stymied by, among other things, a lack of trust between diverse actors.
The central take-away from the above should be that trust is not some box to be ticked in order to achieve aid success. Trust takes time, effort, presence, engagement, commitment and humility. Trust means putting a human face on overtly technical endeavours. Trust means starting something without necessarily knowing how it is going to end. Creating the space for trust in aid may mean re-casting aid as being primarily about relationships, as Ros Eyben and others have argued, and seeing what might emerge as a result.
Scary, eh?
FOOTNOTE: All of this makes the recent revelation in the Economist all the more intriguing. New research seems to indicate that just having a dog around can boost human cooperation levels—potentially altering well known game theory results.
….The researchers explored how the presence of an animal altered players’ behaviour in a game known as the prisoner’s dilemma…Having a dog around made volunteers 30% less likely to snitch than those who played without one.”
So, should the next Paris Declaration meeting have canine observers??
Posted in Conflict and peace building, Facilitation, Institutions, Knowledge and learning, Leadership, Organisations, Public Policy, Strategy | 7 Comments »
Complexity refers to the condition of the universe which is integrated and yet too rich and varied for us to understand in simple common mechanistic or linear ways.
We can understand many parts of the universe in these ways but the larger and more intricately related phenomena can only be understood by principles and patterns – not in detail.
Complexity deals with the nature of emergence, innovation, learning and adaptation
Santa Fe Group 1996
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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.
Posted in Chaos, Innovation, Institutions, Knowledge and learning, Leadership, Networks, Organisations, Self organisation, Strategy | 3 Comments »
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”.
Posted in Chaos, Conflict and peace building, Financial crisis, Innovation, Institutions, Leadership, Natural disasters, Networks, Organisations, Public Policy, Self organisation | 3 Comments »
Over on Rethinking Development Economics, a recent post highlights a provocative speech by Dr DeLisle Worrell, Governor of the Central Bank of Barbados. Worrell focused on the problems with economics today, with much of his talk given over to ‘complexity economics‘.
To quote directly from Worrell:
Delisle Worrell
Our theories can’t deal with reality, so we ignore the real world and spend our time “testing” our theories. If economics is to have any advice to offer which is useful for the management of real economies, we must speak to the reality in all its rich complexity, using all the data we have, all the methodologies we can devise, and all the sources of insight we can borrow. We must dig as deeply as we can, and become sleuths in pursuit of deeper understanding of our economies, even if our search leads us into paths that are dark and uncertain.
Economyths
Elsewhere, the new book by David Orrell, Economyths, also focuses on why standard economic theory has little to do with reality. The wonderful phrase ‘Neoclassical Logic Piano‘ is Orrell’s label for the outmoded economic paradigm – a cluster of conventions including efficient market hypothesis, equilibrium theory, rational expectations which he happily debunks. Orrell recommends an interdisciplinary approach to a “new economics”, again drawing on complexity theory.
Both of these accounts owe something to the 2006 publication The Origin of Wealth by Eric Beinhocker, which explores complexity economics and related issues to great effect, and which was covered at length last year by Duncan Green on the From Poverty to Power blog.
But what might the ‘dark and uncertain’ alternatives to the Neoclassical Logic Piano look like in practice? And what might be the relevance for development economists – a group which, one suspects, may be even more wedded to the assumptions of the Neoclassical Logic Piano than is the norm for the profession as a whole? In a recent article in the Economist, there was a glimpse of one possible answer.
The article gives a succinct explanation for the growing interest in rethinking conventional economic principles: “Mainstream economics has always had its dissidents. But the discipline’s failure to predict the financial crisis has made the ground especially fertile for a rethink…. [experts have] attacked many of the assumptions, including efficient financial markets and rational expectations, on which these models are predicated. These assumptions were clearly too simplistic. But there is less agreement on what should replace the old ways.“
The article goes on to focus on what is seen as ‘one of the most promising options’ – agent-based modeling (ABM). As Joshua Epstein discusses in the clip below, ABM is a key tool of the complexity scientist and has many diverse applications, including the smallpox example he mentions.
The implications of ABM for economic analysis are set out as follows:
Agent-based modelling (ABM) does not assume that the economy can achieve a settled equilibrium. No order or design is imposed on the economy from the top down. Unlike many models, ABMs are not populated with “representative agents”: identical traders, firms or households whose individual behaviour mirrors the economy as a whole. Rather, an ABM uses a bottom-up approach which assigns particular behavioural rules to each agent. For example, some may believe that prices reflect fundamentals whereas others may rely on empirical observations of past price trends.
Crucially, agents’ behaviour may be determined (and altered) by direct interactions between them, whereas in conventional models interaction happens only indirectly through pricing. This feature of ABMs enables, for example, the copycat behaviour that leads to “herding” among investors. The agents may learn from experience or switch their strategies according to majority opinion. They can aggregate into institutional structures such as banks and firms. These things are very hard, sometimes impossible, to build into conventional models. But in an agent-based model you simply run a computer simulation to see what emerges, free from any top-down assumptions…
ABMs… make no assumptions about the existence of efficient markets or general equilibrium. The markets that they generate are more like a turbulent river or the weather system, subject to constant storms and seizures of all sizes. Big fluctuations and even crashes are an inherent feature. That is because ABMs contain feedback mechanisms that can amplify small effects, such as the herding and panic that generate bubbles and crashes. In mathematical terms the models are “non-linear”, meaning that effects need not be proportional to their causes. These non-linearities were clearly on show in the credit crunch.
The article goes on to list the kinds of things ABMs are good at capturing, from ‘the web of interdependencies created by the use of complex derivatives’ and ‘network-based vulnerabilities’ to the ‘the role of interactions between different sectors of the economy’.
More generally, as an article published by the US National Academy of Sciences in 2002 suggests, there are 4 areas where ABM can be of use:
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Flows: evacuation, traffic, and customer flow management.
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Markets: stock market, shopbots and software agents, and strategic simulation.
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Organisations: operational risk and organisational design.
- Diffusion: diffusion of innovation and adoption dynamics.
(…as an interesting aside, these four areas of flows, markets, organisations and diffusion would seem to form a pretty good framework for understanding the aid system…)
To extend Orrell’s metaphor, the ABM approach seems to take the rule-based neo-classical logic piano and replace it with something more akin to improvisational jazz. In fact, researchers at Cornell have made exactly this link – suggesting that while traditional models have tried to understand social life as a structured system of institutions and norms that shape individual behavior from the top down, agent-based models assume that much of social life emerges from the bottom up, more like improvisational jazz than a symphony.
The clip below in which Mulgrew Millar likens jazz improvisation to language acquisition is a revealing one, especially as ABM has been used extensively in linguistics.
Of course, there are many dangers associated with treating any new approach as a silver bullet for the failings of the old, and ABM is no exception. Patrick Beautement, a good friend of Aid on the Edge of Chaos, and Director of Abaci Partners, has thought long and hard about the ‘real-world relevance’ of agent-based models, and argues that there are some outstanding questions to be addressed.
In particular, it is important to be clear about assumptions, limitations and constraints of ABM (just as with any models), and to use such models as the basis for dialogue and discussion rather than as prediction engines.
The Economist article highlights a suggestion which came from, among others, researchers at the Santa Fe Institute, the leading complexity sciences think-tank, to construct an agent-based model of the global economy, to permit real-time simulation and analysis - “in the manner of global climate simulations, which project various possible futures”.
One would imagine that – just as with climate simulations – such models would be subject to rigorous and extensive scrutiny / debate. One would also hope that the debate would be rather less politicised and dysfunctional than those surrounding climate change, but that’s a different story…
The article closes by drawing a strong link between economic analysis and seismology – (for more on comparisons between earthquakes and economic crises, see a 2009 Aid on the Edge of Chaos post):
Seismologists may not be able to forecast earthquakes precisely but it would be deplorable if they were to resign themselves to modelling just the regular, gradual movements of tectonic plates. Instead they have developed ways of mapping the evolution of stress patterns, identifying areas at risk and refining heuristics for hazard assessment. Why not do the same for the economy?”
Why not indeed? And while we are at it, why not do the same in development economics?
Posted in Financial crisis, Innovation, Public Policy, Resilience | Tagged Agent-Based Modelling, Earthquakes | 2 Comments »
…while Ben is on paternity leave. Normal service to resume at the end of July…
Posted in Uncategorized | Leave a Comment »
Over the past two years in ALNAP, we have been leading work on humanitarian innovations which resulted in a major study, an international conference and a significant investment in innovation processes by a major donor.
It is clear to us that the term innovation is being used more and more across the aid sector, whether by senior leaders like Rajiv Shah at USAID or John Holmes of UNOCHA, operational agencies working on the ground like Oxfam and the American Red Cross, or research institutes like IDS and the Humanitarian Futures Programme.
In a recent interview with Karin Wall of Innovation Management magazine, Dr. Curt Lindberg of the Plexus Institute, provided a detailed explanation of the relationship between innovation management and complexity science.
The interview transcript is below, and contains much of relevance to international aid agencies and those seeking to improve their performance.
Q: Could you define complexity science for our readers?
A: Complexity science is the most current attempt by scholars to understand how change and stability occur in systems of all kinds and the underlying dynamics that produce these patterns. The scientific community has identified a number of core principles of complex systems. Two of the most prominent are self-organization and emergence. These principles suggest that no individual agent in a system is able to control the behavior or outcomes in a system as they are a consequence of interactions within the system and with other systems. Complex systems thus by nature are unpredictable and generate surprises, which for those interested in innovation is promising news.
Q: Why would you, as a manager working with innovation, be concerned with complexity science?
A: If you more fully understand the dynamics associated with change and innovation, you can make better choices on how to foster change and innovation. You can also make better choices about who should be involved both within and outside the organization and what you can do to foster creative relationships and conversations. And you can make sure that there are diverse voices and experiences involved in your innovation processes because diversity is one of the driving forces in change and novelty in complex systems.
This young science also helps managers temper their expectations about control. Because complex systems, like organizations and groups, are self-organizing and unpredictable, no one no matter how powerful can control them. Managers with awareness of complex systems drop the burden and unrealistic expectation of control and focus on small actions they can take to influence patterns of interaction.
Q: Many people say that smaller companies are better at innovation because they are more flexible. And that bigger organizations are slower and resistant to change and that this is the reason why they are less innovative. Maybe the whole innovation game has more to do with complexity rather than size?
A: I think it might have something to do with the quality and the nature of interactions. Sometimes in smaller organizations there are more opportunities for the development of healthy, creative relationships among people.
I know there are some larger companies that try to structure themselves in ‘smaller’ ways to help ensure there are ample opportunities for people to interact.
Some larger organizations may become more rigid and rule-bound because many leaders and staff feel the need for more consistency and coherence across the firm. They fail to realize that adaptive, resilient systems are characterized by the paradoxical coexistence of order and disorder or stability and variability. People tend to divide into two camps on this spectrum. Some think that routines, predictability and order are required in organizations. Others think that experimentation, freedom and the pursuit of new ideas are what are required. They are both right.
Q: How would you approach innovation from a complexity perspective?
A: I would come at it with several questions in mind. One would be what kind of opportunities can I, as a manager, provide for a diverse group of people to interact in creative ways? What kind of processes might we employ to increase the likelihood of creative, generative interactions? In Plexus we have come to call these processes Liberating Structures. You may have heard of some of them – appreciative inquiry, positive deviance, open space, conversation café.
Next I would suggest that instead of trying to develop a grand plan or long term blue print for becoming more innovative managers should adopt a shorter-term perspective that focuses on the creation of “good enough” plans and stimulation of multiple small experiments, combined with a sense making orientation. What emerged from our plans, our actions? What did we learn? What seemed to be underneath the outcomes that were generated? What do the resulting insights suggest about the next series of steps and actions.
Q: You mean like a learning cycle?
Yes, rapid learning cycles, because if you go into a planning cycle with a very long term detailed “blueprint” orientation you are assuming it is possible to make long term projections about your organization and the economy and base detailed plans on these forecasts. Complexity suggests that, like the weather, it´s very difficult to always be right about your organizational forecasts. You may have heard the old adage, “If you want to make God laugh, tell him your plans.”
There is an ongoing discussion if innovation should be managed centrally in MNCs. What is your idea about this from an organizational perspective?
I think I would return to paradox and ask leaders to explore how innovations can be pursued from decentralized and centralized perspectives. For example, how can you build an organization-wide network to generate and spread innovations, a “centralized” undertaking, while simultaneously encouraging lots of experimentation at the local level, a “decentralized” undertaking.
Such a strategy, a broad network and abundant experimentation, builds on the observation that in complex systems large scale change comes from small changes. The scientific term for this in nonlinearity.
Q: What can you do then to make sure that you don´t miss those small actions or ideas that might result in something bigger and more important?
A: You can never be sure that you don´t miss anything, but you can have your antennae “on alert” and rely on a diverse network to listen for promising developments. Others may notice something you do not. You can provide opportunities for people to connect across the organization. The resulting conversations may uncover patterns, new innovations that were not previously apparent.
Q: Could you mention the three most important skills for leadership in making innovation happening?
A: First I would observe that leaders cannot make innovation happen. What they can do is lead and interact with colleagues in a manner that fosters innovation. How others respond and what they do will determine whether a culture of innovation is created.
Leaders can certainly provide time, space and skills to enable employees to participate and interact in creative ways around issues of importance. Too often we act like there are more important things to do than converse and make sense.
Leaders can also work on their personal skills – learning to be truly present and listen, to notice what new is emerging in conversation and how people are interacting, and to let go of the notion that as a leaders we know best.
The third skill would be the development of the ability to encourage employees to experiment, take risks and to learn from them. Accompanying such encouragement must be the genuine signal that if things do not turn out as expected “that’s OK, what can we learn”. Innovation is by definition out of the ordinary. This raises anxiety. Will it work, what will people think of me, would the leader have done it this way? Trusting that the leader will understand these feelings and stands ready to provide support and opportunities for learning may help employees to work with the anxiety associated with change and innovation.
Posted in Innovation, Knowledge and learning, Leadership, Networks, Organisations, Strategy | 1 Comment »
