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Archive for the ‘Institutions’ Category

Why Managers Haven’t Embraced Complexity

Posted in Economics, Facilitation, Innovation, Institutions, Knowledge and learning, Leadership, Research, Strategy, Technology on May 10, 2013 | 3 Comments »

This is a cross-post from the HBR written by Richard Straub, and is one of a series of perspectives that will be published leading up to the fifth annual Global Drucker Forum in November 2013 on the theme of Managing Complexity.

Nobody would deny that the world has become more complex during the past decades. With digitization, the interconnectivity between people and things has jumped by leaps and bounds. Dense networks now define the technical, social, and economic landscape.

I remember well when the idea of applying complexity science to management was first being eagerly discussed in the 1990s. By then, for example, scholars at the University of St. Gallen had developed a management model based on systems thinking. Popular literature propagated the ideas of complexity theory — in particular, the notion of the “butterfly effect” by which a small event in a remote part of the world (like the flap of a butterfly’s wings) could trigger a chain of events that would add up to a disruptive change in the larger system (such as a hurricane). Managers’ eyes were opened to the reality that organizations are not just complicated but complex.

Why did this interest and work in complexity not lead to major changes in management practices? There are, I think, a few major reasons that it didn’t — and that also suggest that the overdue change might now finally take place.

Complexity wasn’t a convenient reality given managers’ desire for control.
The promise of applying complexity science to business has undoubtedly been held up by managers’ reluctance to see the world as it is. Where complexity exists, managers have always created models and mechanisms that wish it away. It is much easier to make decisions with fewer variables and a straightforward understanding of cause-and-effect. Here, the shareholder value philosophy, which determines so much of how our corporations operate these days, is the perfect example. Placing a rigid priority on maximizing shareholder returns makes things clear for decision-makers and relieves them of considering difficult tradeoffs. Of course we know that constantly dialing down expenses and investments to boost short-term margins inevitably damages the long-term health of the company. It takes a complexity approach to keep competing values and priorities and the effects of decisions on all of them in view — and not just for management, but equally for investors, analysts, and regulators.

Technology was not yet powerful enough to capture much complexity.
When systems thinkers and theorists turned their attention to economies and organizations in the 1980s and 90s, the tools simply did not exist to model their workings at a level that would yield practical insight. Now, the exponential increase in computing power and the progress in mathematics and statistics have propelled us into a new era. With the ability to draw on data bases and map networks at scales that were unthinkable before, we can hope to understand communication flows through large organizations, and the impact of disturbances and managerial interventions on these flows.

The prospect of non-human decision-making is unnerving.
More recently, with the surge of computer processing power, another nagging concern has formed in some people’s minds. Does the fact that massive computing power is required for systems-level comprehension mean that the interpretation of information, sense-making, and learning will become “extra-human” activities? Will the computer take over the role of the knowledge worker? Will we soon reach a tipping point when human brainpower is obsolete? Some technophiles (many of them inspired by Ray Kurzweil’s ideas) respond to questions like this with a resounding yes. Yet for most of us it is a disturbing thought, because we have seen so many of the models designed to predict the future state of complex systems (from economies to climates) fall short of accuracy, to say the least.

The eager futurists talking about machines taking over evaluation of situations and decision-making have set back their own cause, as others see them ignoring an essential fact: sense-making is always informed by values. The idea that we might look for value judgments from algorithms is just badly flawed. But fortunately, the recognition is growing that, while computers can provide us with enormous extensions of our storage and processing capacity, they must and will remain only inputs to human brains, where the ultimate evaluation and deliberation must continue to take place. Think of the brain as our own “complexity processor” and itself our most complex organ: It helps us to address complex issues and yet come up with seemingly simple solutions. Those are made possible when we unconsciously see through the myriad of information elements that are stored in our brain as raw material to build meaningful patterns, or the famous “big picture” that humans can develop best.

The recognition of complexity is at its core a view of the world that that makes us more humble and more open. It is the awareness that too often our interventions will not achieve what we wanted and we will be shocked by unintended consequences. (The fact that, following the creation of the Cap-and-Trade Carbon Emission Scheme as a clever new artificial market, more coal is being burned in Europe than before is a mind-boggling example.) At the same time, it is the acknowledgement that simplistic “can do” thinking and linear approaches in organizations and markets, which are by definition complex, won’t be sufficient. And it is the prod to us to better understand why.

There has been no watershed event to make it true that managers will apply complexity science to their work today, whereas they could not, or would not, yesterday. Rather, there has been a gradual change in mindset, pushed along by the increasingly evident damage of narrow, simplistic thinking. The toolkit that allows us to understand the dynamics of large systems has continued to evolve. And the reassuring truth has been reasserted that, on top of the logic of algorithms, human values and judgment are essential.

Managers, I think, should now get ready to face the full complexity of their organizations and economic environments and, if not control them, learn how to intervene with deliberate, positive effect. Embracing complexity will not make their jobs easier, but it is a recognition of reality, and an idea whose time has come.

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The Aid Explorer: Mapping the Hyperspace of International Aid

Posted in Accountability, Evaluation, Facilitation, Innovation, Institutions, Knowledge and learning, Leadership, Networks, Organisations, Public Policy, Reports and Studies, Research, Self organisation on May 2, 2013 | 1 Comment »

The team behind the Atlas of Economic Complexity (see my post on this here) have come up with a fascinating network-based approach for analysing the global aid system.

As they put it:

International development is a complex global goal that faces massive coordination barriers. The difference in income between rich and poor has expanded over the years from a four to one factor to a hundred to one. Where there once were only a handful of development agencies, thousands have now emerged. The system that connects donor agencies, recipient countries and development challenges is extremely complex and should not be managed with a top-down approach… The Aid Explorer was developed as a tool to facilitate better aid coordination. The Aid Explorer enables users to understand what issues face which countries and which aid organizations are aligned to address these issues.

Some specific pointers:

  • The Aid Explorer’s Profile pages enables us to see which issues face which countries and which organisations are best aligned to address them
  • The Network maps can be used to explore how issues, countries, and organizations relate to each other
  • The Rankings presents the findings and the best alignments of countries, issues and organizations

The process of developing the dataset, and how to use it, is described in more detail in the accompanying paper “The Structure and Dynamics of International Development Assistance“, published earlier this year in the Journal of Globalization and Development.

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Is this the ‘Next Big One’?

Posted in Agriculture, Biology, Communications, Evolution, Healthcare, Innovation, Institutions, Knowledge and learning, Leadership, Networks, Organisations, Public Policy, Research, Resilience, Strategy, Technology on April 23, 2013 | Leave a Comment »

As concern grows about H7N9 in China, this post explores the importance of managing such pandemic risks through collaboration, innovation and systemic thinking

In the month of World Health Day (April 8th), the latest outbreak of bird flu in Asia provided a sobering sense of the challenges the international community still faces. To date, H7N9 has killed 21 people, infected 104, shut down poultry markets across Asia, and has led to Chinese shares tumbling.

The WHO originally announced that the likelihood of this latest pathogen is transmittable between people is low, and that the world should not ‘get into a flap’ – as one observer memorably put it. The potential of bird flu to be the source of the “Next Big One” means however that we cannot be complacent. In terms of global catastrophic risks, it is hard to think of one more serious than the 1918 avian influenza epidemic which killed 50-100 million people worldwide – 3-5% of the global population. This was so devastating in part because the virus had acquired mutations that allowed it to cross from birds to humans, and then to ‘go pandemic’. Based on analysis of the mutations in H7N9, scientists fear that this latest variant may have the same potential.

But there is still a lot we don’t know about H7N9. Where has it come from, why, and how? What is its relationship to earlier variants? How might it mutate? What impact might it have in the future? What does it mean for our ongoing, historically loaded, battle with avian flu?

To answer such questions, we need to draw on a variety of disciplines: epidemiology, molecular biology, virology, all of which fit nicely with the current models of public health. The problem is that many of these models set us, humans, apart from nature. Diseases, the standard narrative goes, encroach on our territory and we need to fend them off. The reality is in fact the exact opposite.

It is now widely acknowledged that many – the majority, in fact – diseases are born in the intersection between society, environment and economy. More than 2/3 of all human infectious diseases are zoonotic in origin, meaning that they somehow crossed species boundaries. The terminology likely to be adopted in future Hollywood blockbusters on the topic is simple but evocative: ‘spillover’. Primates, birds, bats, pigs, rats, mice, dogs, insects – any creature we co-exist with can act as sources or carriers of pathogenic lifeforms.

Spillover is driven by a pattern of activity which is becoming all too familiar. Deforestation: 4% increase can lead to 50% increase in malaria rates. Hunting has led to HIV-AIDS, Ebola, all crossing the species boundary. And, to bring it back to bird flu, livestock. Around 70% of the rural poor and 10% of the urban poor are dependent on livestock. Livestock conditions are increasingly creating tremendous opportunities for pathogens to cross from wild birds to caged birds, and onto humans. And the demand for animal-based protein is expected to grow 50% by 2020, much of it in the developing world. This problem is not going to go away any time soon.

Leapfrogging on the success of the human race, trade and transport linkages provide a morbid global transmission network. The rate at which new diseases are emerging and spreading is nothing short of shocking.  Zoonotic diseases have increased in the past 40 years, with at least 43 identified outbreaks since 2004. ILRI estimates that 1.7 million people die each year thanks to spillover diseases. By way of comparison, the highly respected CRED crunch on disaster epidemiology found that the 2001-2010 average annual deaths from natural disasters was 107k  per year.

Ecological and evolutionary principles are vital in understanding these complex system effects on a more solid scientific basis. Experts at the University of Florida made the point in pithy fashion a couple of weeks ago, “If we don’t understand the reservoir and the ecology of the virus, it’s hard to design interventions to protect humans.” But such understanding is – with a few exceptions – still under-utilised in public health.

Of course, every disease is different, every context is unique. But the process by which spillover happens is similar. We can point to ecologies under stress. Life forms under duress. As an excellent briefing by colleagues in the Consortium on Disease Dynamics (CDD) puts it, “The health of people and animals are… interconnected and inextricably linked to the environments both inhabit. Given the complex pathways that lead to spillovers, it is important that prevention and control measures are undertaken with a strategic approach and an understanding of the many interdependencies.”

What does this challenge add up to for the global risk management community? The work by the CDD gives some very useful pointers.

First, multi-disciplinary approaches are vital. The WEF Global Risks report has for some years now been calling for better disciplinary collaboration in order to think about emerging risks. With avian influenza there is a clear need for better collaboration between public health specialists, disease ecologists and evolutionary biologists. Some important work is already happening, under the auspices of entities such as the global One Health initiative, organisations like the EcoHealth Alliance, and initiatives like the USAID-funded Predict, and this work needs to move firmly to the centre of the debate.

Second, anticipation and warning systems – new investments in surveillance are urgently needed to establish and maintain necessary systems at multiple levels – community, national, regional and global. We need multi-stakeholder information platforms, bringing together government, civil society and the private sector in new kinds of networks, in order to establish ‘systemic  surveillance approaches’. This needs to move beyond a focus on specific disease to looking at the whole system, looking at the intersection between disease drivers, disease incidence, and socio-economic factors.

Third, new approaches – especially in the realm of complex adaptive systems – have a lot of relevance for how we think about such outbreaks in the future. Methods such as systems thinking, network analysis, agent-based simulations, and dynamical systems theories can help develop a more precise and accurate understanding of the complex dynamics of disease. Together with the rise in ‘big data’ approaches, there is scope to develop new models and theories of how pandemics unfold which are more appropriate to our ‘hyperconnected world’. We need to be careful however to ground this science in local, community understanding – to support affected communities to become the frontline of defence: adaptive managers of emerging risks.

Fourth, we need changed funding models – funding prevention, not just response, and linking pandemic risks to high-risk development activities, and ensuring that we don’t forget history too quickly. There needs to be attention even when the threats may not be imminent. The private sector, with interests in business continuity, can be key actors here. Done right, such investments can engender what might be seen as positive spillovers. As the CDD work suggests, investments in prevention of avian influenza can provide the basis for such work on other potential pandemics.

In closing, if we want to take a wide-angle lens on the problem of disease outbreaks like HN79, to understand why these diseases are occurring at an increasing rate, we could do worse than taking a lead from Nathan Wolfe. A globally renowned virologist, a couple of weeks ago Wolfe wrote a tub-thumping piece on the WEF blog about the continued risks of unregulated hunting, especially bushmeat, which gave birth to human immunodeficiency virus (HIV). His basic argument was by ignoring the implications of our food production systems, we are running an unacceptably high risk of terrifying global scourges in the future.

Clearly, we all need to start pay much more attention to the intersection of economy, society and the environment if we are serious about proofing ourselves against the Next Big One.

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Conversations on Complexity: A Tribute to Elinor Ostrom

Posted in Biology, Evolution, Influence, Institutions, Knowledge and learning, Leadership, Organisations, Public Policy, Resilience, Strategy on August 16, 2012 | 12 Comments »

Many people around the world were deeply saddened to hear of the death of Elinor Ostrom in June this year. By way of a tribute, this extended piece brings together some of her ideas on the implications of complexity science for development aid. It draws on material from a series of interviews I conducted with Professor Ostrom between 2009-2012 for use in my forthcoming book, and has been approved for publication by her colleagues at The Workshop, Indiana University.     

When Elinor Ostrom won the Nobel Prize in 2009, the Swedish Royal Academy of Sciences made the following statement:

[she] has challenged the conventional wisdom that common property is poorly managed and should be either regulated by central authorities or privatized. Based on numerous studies of user-managed fish stocks, pastures, woods, lakes, and groundwater basins, Ostrom concluded that the outcomes are, more often than not, better than predicted by standard theories.”

Challenging standard theories was a running theme Professor Ostrom’s work. Ideas of the commons and how they really worked were central to this, as was the analysis of institutions and the sustainability of social-ecological systems. Complexity was a particular interest: ideas of systems, self-organisation, the evolution of rules, institutions as emergent phenomena and resilience are all repeated motifs in her papers, books and speeches. Indeed, her 2009 Nobel Prize Lecture – she was the first and, to date, only woman to win the Economics Prize – builds on the distinction between simple and complex human systems, and closes with the following words:

We should continue to use simple models where they capture enough of the core underlying structure and incentives that they usefully predict outcomes. When the world we are trying to explain and improve, however, is not well described by a simple model, we must continue to improve our frameworks and theories so as to be able to understand complexity and not simply reject it.

She was on the Santa Fe Institute (SFI) Science Board for five years. Corresponding in 2011 while I was visiting the Institute, she wrote to tell me that it was one of her favourite places in the world. It is easy to imagine how the SFI approach naturally appealed to someone who had spent her life’s work breaking down disciplinary boundaries.

My small-scale engagement with Professor Ostrom started in 2009 following the publication of a report on complexity science and aid I led on while at ODI. She used it as reading material for her students in Autumn 2010 and kindly wrote back to tell me how useful she had found it. We subsequently had telephone and face-to-face interviews on the topic of complex systems, development and aid. These discussions, and of course her rich body of work,  helped to shape the ideas in my forthcoming book, which she warmly encouraged from the outset. I have used material from these interviews to write this post.

*

What is your view on complexity and the complexity sciences? What is the value of this approach?

I get so upset when people use complexity as a reason not to do things – complexity and context are essential for operating in many different situations. In order to make sure decisions are relevant, we have to understand the context of decisions, and the complexity of the situation. My take on complexity is that it is a key set of concepts which are essential for understanding how the world works. There are many situations where simple models don’t work – when there are 10, 15, 20 variables. For example, think about situations where problems are nested within each other or situations where there are many actors capable of actions, conflicting information about transmissions and payoffs and diverse outcomes. Here, the ideas of complexity can lend a hand by providing a means of analysis and understanding the reality of these action situations.

How would you apply these ideas to international aid agencies?

The last thing aid agencies want to do is analyse things as a complex system! (laughs) But how do you unpack systems without such analyses? In biology and ecology, there is a necessity of using complexity science and related ideas as a model – although it is not always acknowledged, they do have to use it. For example, in a situation with 10, 15, 20 species, how do you understand the potential impact of the elimination of one species, when one unit being eradicated would cause disaster rather than simply being important. We can’t address these questions without drawing on complexity theory in some way.

The lack of long timeframes and a lack of supporting cultures means that aid agencies don’t help people learn how to think about and change the structure of the situations they are facing. In many situations, this is because of colonial roots of aid, which did not respect local institutions – they didn’t understand them so they were treated as non-existent.

The difference between this approach and that of Darwin is stark – the care and diligence that was given to studying animal species in the 19th century is so evident, and it from this that we have evolutionary theory. But these countries also had people, but there was no attempt to understand their knowledge systems, the rules they had developed to manage various kinds of socio-ecological systems… Colonial powers assumed we have the answers, and destroyed social capital. Aid agencies, unfortunately, do much the same thing.

What are the biases of development aid that you see inhibiting the take-up of a more complex, realistic way of doing things?

Development aid asks the question: where can we pour money in to make the most difference in the most visible way (laughs). This is not especially amenable to complex ways of understanding the world. Most projects are 2-3 years, some are 7, but these are big engineering projects, and then they disappear.

‘Fitting’ is all important in this context. Many agencies today have blue prints for situation A, but they are so ingrained they can’t deal with B, C, D and E. Some employ very inspiring young people, but they are not keen to stay long in their organisation – 4-6 years max, they tend not to be sanguine about the future. This is understandable, but it also goes against what we know about bringing about social change.

Take the Sida work. We said, we want to understand the role you play in sustainable development – tell us what your best projects are. And we found that their best projects were relative failures because of exactly these issues.

The most fundamental change is to change the social science curriculum to change the way that development is taught. We need to get away from treating governance as top-down. The presumption of almost all work is that a hierarchy will work effectively, gather information from variety of sources and develop tactics of behaviour. In complex systems, there are many different areas, all moving in different directions and at different speeds, doing localised things which are relevant. The idea that a central processing unit that can gather up all of this information and make decisions about the whole system… the theories fall down.

I developed a framework to understand complex social-ecological systems, which builds on my work on governing the commons. This sets out the key design principles for complex systems which sit on the interface of society and ecology: watersheds, fisheries, increasingly the whole planet. Some of the reaction has been very enthusiastic – some people, the biologists, the ecologists, the complexity scientists, love it. Others hate it, they say it’s not science, it’s too complex.

What examples do you see of good development practice, which do take account of complexity?

I was at a conference recently in the north of Sweden, for the Childbirth Foundation, 1000 young people from 100 countries. They were trying to answer the question – how do you change the way the world works to develop more opportunities in developing countries. There were lots of ideas, using the market, ideas like cooking stoves and many others, all aimed at the broader goal of dealing with climate change, bringing about development. Some of these ideas have already been applied; some are still being tried out. But the key is that they are doing development in a way that has a chance of working.

And there were no international development agencies present. They should have been there, just to see what was being discussed. The key difference was that while international development agency way of thinking has seen a lot of failure, they haven’t picked up yet on the answer, which is that we must have multiple approaches, small and experimental and larger and more concrete. But apparently the taxpayer doesn’t like to see experimentation with their money!

Aid agencies tend to not involve staff in anything other than a project, and sometimes only for part of a project. And when the project ends, they leave. Mr Shivakumar, a colleague who worked on the Samaritan’s Dilemma, has done work with Action Aid in their Ethiopia programme. They will go to a site where they are trying to help farmers build up their capacity, say for public services. They are there for some time, but they try to do something 5 years before they are going to leave. They will call a meeting and say ‘we will fund 1 year for 100%, after that, we will drop to 80%, and you need to support 20%, then down to 60%, and so on… If we are doing something good, then you should want to carry it on. If not, that’s fine, the project closes. That is an example of an aid  philosophy that takes account of complexity.

Look at Grameen Bank, that started off slowly, and if it was cut down after 2 years it would never have turned into the institution it is today. But it worked because it was a system within a system within a system. It didn’t have public official waiting for a report on a Friday afternoon before they could go home. It had lots of people in localised situations who presented and developed rules for how things would work, providing some basic structure for example, you have to meet every week, we have to put money on the table, we have to be forgiving at times… These small-scale units proved to be very innovative and creative. Small-scale units can be very adaptive in changing – look at family units when a child arrives, or a job changes. They can deal with the complex, but they are guided by a different philosophy to development agencies. They don’t have to come up with winning solutions, they can learn from their own successes and diversity of other approaches, they can change things if they are not working.

There is a growing interest in resilience in development circles. Do you see this a promising line of enquiry?

Resilience and sustainability are very similar – these systems have similar properties. It is another attempt to get this kind of thinking into institutions, and just the latest one. The work of the Stockholm Resilience Centre is very important here, and they have been successful in influencing a number of research agendas. But I think a lot of the time policy people are just using the language without knowing what they are talking about (waves hand in mock exasperation). When I did my work on social-ecological systems I was very careful to build on the work of ecologists and social scientists, so it was a truly integrated framework. The trouble with much of the development policy work around resilience I see is that so much of it doesn’t really try to engage with the science of resilience, but instead uses as a catch-all to further particular institutional interests. We need some real serious thinking on this issue if it is going to make a meaningful contribution.

What do you think are the implications of the science of complexity for big conferences like Planet Under Pressure and Rio+20?

We are lucky that there is growing interest in this area, from academics and researchers across the world. The work you have been leading on your book – I think this is work of immense value and importance for the development sector. The crucial question is whether international agencies are ready to hear the message and willing to act on the lessons. I know there are others leading similar work in other closely related sectors like environmental sustainability, community development and social entrepreneurship – about the complexity inherent in different resource systems and under different rules.

We need a broader approach to these systems. What we are lacking at the moment is a shared framework. Without this, how are we to ensure our knowledge accumulates? A shared framework of complex systems can help us ensure knowledge in these different fields is not isolated. There are more people working on this, and they are working together more, but not enough is being done yet.

What do you see as the key to the success of Rio+20?

There needs to be more connection around this challenge through a shared lens of complex social-ecological systems, and these large-scale events provide an opportunity to do this. The key principle informing all of this has to be taking a more evolutionary, polycentric approach to policy making.

This is the key challenge we face, and it is only going to grow with time. I am hopeful though. If there is one thing I think I have learned it is that just because we have a certain emphasis in our institutions today, it doesn’t mean we are stuck with it forever.

 What three things would you change among aid agencies to get them to take more account of complex realities?

The number one thing is the ‘spend it or lose it’ mentality – it is common to most bureaucracies, but getting it changes is essential if aid is going to be tailored to the complex realities of development. This institutional change will allow many others to come about, and so it is a very important one.

Number two is getting aid agencies to be more of a learning enterprise and less of a doing enterprise. This means feedback, training, reflection. This means not assuming we have the answer. We need to create an environment where discussion and debate are openly welcomed, and where redundancy is not always seen as bad, just excessive redundancy.

Third, we need to reward people for developing imaginative ideas that draw on the complexity of the real world, that leave people in developing countries more autonomous, less dependent, and more capable of crafting their own future.

*

There are of course many tributes to Professor Ostrom, by people far more qualified than me to write them. For my own small part, I feel grateful to simply to have known her: for her time and support; for how generous she was with the benefits of her towering intellect; and for her gentle, playful sense of humour. The fact that someone of her stature could take the time and care to engage with and mentor me and so many others like me around the world speaks volumes about the extraordinary person she was.

She will be deeply missed – as the Indiana University president said in his statement, we have “lost an irreplaceable and magnificent treasure”.

“We have to think through how to choose a meaningful life
where we’re helping one another in ways that really help the Earth.”

Elinor Ostrom, 1933-2012

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JP Morgan and the Price of Complexity

Posted in Accountability, Biology, Chaos, Economics, Evolution, Financial crisis, Innovation, Institutions, Knowledge and learning, Leadership, Networks, Organisations, Self organisation, Strategy, Technology, Trade on May 15, 2012 | 1 Comment »

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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Taming fragility?

Posted in Strategy, Knowledge and learning, Networks, Leadership, Institutions, Conflict and peace building, Innovation, Evolution, Influence on March 12, 2012 | 6 Comments »

This is a guest post by Frauke de Weijer (pictured), policy and fragile states specialist at the excellent ECDPM think tank. 

In a previous post on this blog, Ben explored the potential of complex systems research for thinking about statebuilding and fragility.

In this guest post, I would like to take this discussion one step further by asking what the specific implications are for development policy and practice if we start treating fragility as a wicked problem.

Since I came across the term ‘wicked problems’ a few years ago, I have been convinced that state fragility can indeed be described as a wicked problem. The trick with wicked problems is that they are actually a set of problems (or messes, as Russell Ackoff would describe them), some of which are more technical (or tame) in nature and others are wicked again.

Our tendency, in the development world, is to treat them all as technical; i.e. as problems to which the solutions are already known and simply need to be applied. This is what contributes to the consistent failure in addressing state fragility.

This is not to say that applying a different approach, i.e. a ‘complexity theory approach’, will fix the problem. Wicked problems are not particularly ‘fixable’, which is exactly why they are wicked in the first place! What it means is that we have to start from the premise that we do not know the solutions and that we have to discover those solutions as we go along. This is also what Ben speaks about when he says to ‘avoid silver bullet strategies and attempt multiple parallel experiments’.

How to apply these ideas in practice? Fragile states should not be seen as playing grounds for experimentation, especially not for the international community. Yet, in many instances it is possible to test out different ideas; create the conditions for different endogenous solutions to come about; to allow for learning to flow and for strategies to be continuously adapted to the emerging insights of what it would take for a complex social system to change. The key lies in creating feedback loops and learning systems, something the international development community is notoriously bad at.

In a separate article on ECDPM’s Talking Points blog, I have made a further attempt to translate some of the principles stemming from complexity theory into actual practice in fragile states. In my mind, a number of starting points can be described:

1) We have to start from the premise that we do not understand the complexity and interconnectedness within a social system and that we do not know what the solutions are.

2) New ways forward need to be found through ‘wrestling the problems to the ground’; i.e. by enabling local actors to identify potential solutions, test these, and learn from these.

3) Societal change is painful, takes time, is unpredictable and does not follow well-established paths. For external actors engaging in such settings, conflict-sensitivity is key, but the principle of doing no harm is naïve. It is a matter of mitigating these risks to the best of our ability.

4) In rare cases does the national development strategy reflect a genuine consensus of the people, and ownership is often limited to a small group. This raises questions on whether the principle of alignment with national government strategies can be maintained as a self-evident choice.

5) Long-term engagement and having an over-the-horizon strategic vision is essential in fragile states. However, as long as international development continues to work on the basis of current management models, its impact on fragile states will remain limited.

6) For a new approach to fragility to emerge, the policy making and operational systems in use in development cooperation need to undergo fundamental change. It means going beyond a mentality in which experts know the solutions, and putting ‘learning systems’ at the center of development policy.

I elaborate on these principles in a new article on ECDPM’s Talking Points blog website. Do take a look and share any thoughts there.

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South Africa’s democracy: Complexity theory in action

Posted in Accountability, Economics, Evolution, Innovation, Institutions, Leadership, Public Policy, Resilience, Strategy on December 16, 2011 | 4 Comments »

Dr Brian Levy is a Public Sector Governance Advisor at the World Bank, andused to head up the unit responsible implementing the Bank’s governance and anti-corruption strategy.

In this guest post, cross-posted from here, he explores the relevance of complexity theory insights for South Africa. A fascinating read.

The edge of chaos is the balance point where the components of a system never quite lock into place, and yet never quite dissolve into turbulence, either…The edge of chaos is the constantly shifting battle zone between stagnation and anarchy, the one place where a complex system can be spontaneous, adaptive and alive…”
M. Mitchell Waldrop, Complexity.

We human beings do not like uncertainty. We seek to understand what events portend, taking comfort in coming up with an answer. So whenever something new in South Africa makes headlines – and that’s been happening quite often recently, the news not always happy – people ask me, “What do you think? Is the political settlement falling apart?”. And always, the expectation is for a definitive answer, one way or the other.

Yet sometimes there is more wisdom, and more comfort to be taken, in acknowledging a more humbling truth – that which of many alternative futures (including ones we cannot imagine) will come to pass is unknowable, is a product of decisions and actions that have not yet been made. This understanding of change as something ‘emergent’, evolving, which can unfold in far-reaching yet ex ante unpredictable directions, is the key insight of ‘complexity theory’ – an insight which can offer a useful dose of humility to governance prognosticators.

In a previous post, I described South Africa’s abiding tension between democracy and inequality. As that post suggested, one of the results of that tension could be a rise of patronage, personalized decision-making as to how to share the ‘spoils’ of power. Indeed, the strains on the country’s constitutional democracy are visible in the drumbeat of daily headlines, as I found when I recently spent some time in the country. Consider the following:

  • Over the past year, the country’s estimable Public Protector, Thuli Madonsela, investigated and made public compelling evidence of corruption on the part of two sitting cabinet ministers, and the chief of police. For many months, President Zuma did nothing – until October 24th  2011, when he unexpectedly fired the cabinet ministers, suspended the police chief, and announced the appointment of a judicial commission to re-investigate long festering allegations of corruption (including against himself) in a weapons procurement deal.
  • Then there’s the populist demagoguery of the leader of the ruling African National Congress’s Youth League, Julius Malema, whose political star, and polarizing influence on South Africa’s political discourse, seemed to be rising – until a disciplinary committee of the ANC announced on November 10th, 2011 that it had found Malema guilty of bringing the ANC into disrepute, and suspended him from the party for five years.
  • There’s the China connection. Across Africa, a context is raging between China and Africa’s erstwhile Western colonial (and post-colonial) hegemonies – for hearts, minds, natural resources, and business more generally. With its sophisticated institutions, and proud transition to constitutional democracy, it might be thought that South Africa would be unambiguously in the Western camp. So against that backdrop, the failure to grant the global human rights icon, the Dalai Lama, a visa in time to attend the October 2011 80th birthday celebration of his friend, Archbishop Desmond Tutu, is startling – and can best be explained by a desire to curry favor with the Chinese.
  • Finally, there’s the on-again, off-again – but then on again – Protection of Information Bill which (after numerous delays, and promises of consultation before finalization) was rushed through South Africa’s parliament on 22nd November 2011. Passage of the bill was seen as a catastrophe by many in South Africa’s civil rights community. Indeed, it signals a startling turn away from a post-apartheid commitment to openness. But no less an observer than The Economist, noting that the bill had been ‘vastly improved’ over earlier versions, suggested that some of the doomsday criticism ‘may be over the top’. And, in light of the ANC’s hitherto ironclad hold on the loyalties of its core constituencies, it is surely no small matter that the Congress of South African Trade Unions (a stalwart part of the ANC alliance) has threatened to take the bill to the Constitutional Court if it is not amended to incorporate a ‘public interest’ exception for whistleblowers.

In the face of all of these cross-currents, any claims of certainty as to where this interplay of forces will lead is surely illusory. Each of them could turn out to be a salutary example of checks and balances in action – of how democratic institutions can keep a country on track, even in the face of pressures to the contrary. But they could also be portents of a future that will become increasingly challenging for the country’s constitutional order.

But in South Africa’s case, and surely elsewhere, too.   perhaps the lack of certainty is a source of comfort. Knowing that the future is not preordained can free us from endless preoccupation with what is inherently unknowable, enabling us instead to direct energy towards action, in service of a hopeful future that we can, perhaps, yet help to create.

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New Scientist Briefing: Can ecosystems show how to fix the euro?

Posted in Public Policy, Knowledge and learning, Trade, Networks, Technology, Financial crisis, Institutions, Innovation, Economics, Biology on November 10, 2011 | 6 Comments »

The eurozone, like the rest of the world economy, is a complex networked system. That gives it properties economists rarely consider but which could help us understand the current crisis. This New Scientist ‘Science in Society’ Briefing examines the issues.

What is a complex network?

Complex networks have many interconnected components which influence each other’s behaviour. These changes then feed back on each other. A famous example is the numbers of predators and prey in a given environment, which vary in a complex interdependent way. The eurozone – the 17 countries that share a common currency, the euro – is similarly interdependent, with similar feedback mechanisms.

All complex networks are governed by a balance between negative feedback, such as interest rates, which is stabilising, and positive feedback, such as the self-reinforcing erosion of trust in markets, which is destabilising, says physicist Len Fisher at the University of Bristol, author of Crashes, Crises and Calamities: How we can use science to read the early-warning signs.

How does that help us understand economic crises?

In certain circumstances, one type of feedback can end up dominating the system, causing it to change so dramatically that it flips to another state. Examples include the way animal populations can suddenly collapse or the way economies can slip into recession.

These tipping points tend to be highly unpredictable. Even so, Fisher says computer models of the system can still show how the system can change. Yet leading economics journals, he says, do not accept computer-modelling studies. “Mainstream economists have not considered these non-linear effects,” agrees Oonsie Biggs of Stockholm University’s Stockholm Resilience Center in Sweden.

Can we understand complex systems well enough to control them?

Maybe. The diversity of a network’s components and the density and strength of its connections – called its connectivity – affect the system’s resilience, or resistance to change. More connections make a system more resilient: if one component fails others can fill in. But only up to a point. Go past a certain threshold and more connectivity makes the system less resilient because a single failure can cascade to every other component.

The trick is to get the balance right. “Cascades of failure may be controlled by changing the nature and strength of the links between various parts of the networks,” says Fisher. Much current research in complex systems focuses on assessing connectivity correctly to enable that. Other work aims to detect behaviour that indicates an imminent collapse.

So turning 17 separate currencies into one eurozone was a cascading failure waiting to happen?

Yes. That is why Greek debt is a crisis, even though Greece accounts for only 2.5 per cent of the eurozone’s GDP. News of its debts caused the trust that markets placed in Greek government bonds to plummet. Its creditors are mainly in the eurozone, so a Greek default is causing markets to lose confidence in other members, such as Italy – which is too big to bail out.

Could the crisis have been avoided?

Complexity theory shows what went wrong. Yaneer Bar Yam of the New England Complex Systems Institute in Cambridge, Massachusetts, says his still-unpublished studies show that investors profited by driving down the value of Greek government bonds, triggering the crisis. If instead of national bonds issued by sometimes weak economies, the eurozone had one common bond backed by powerhouses such as Germany, such an attack could not have happened.

Germany rejects eurobonds. But, says Bar Yam, complex systems such as multicellular organisms show that “if you are going to accept common risk, you have to invest in defences that extend to the weakest member”. Either that or make sure an attack on a weak member cannot spread, a technique that ant colonies have perfected: the death of a single ant has little effect on the colony as a whole. “Biology has solved this problem several ways,” says Bar Yam.

If connectivity is a risk, why create the euro?

Connectivity is also profitable as it makes economic production much more efficient. And it can adapt to problems: connectivity allows other eurozone countries to help Greece, and to build better common defences.

Trade-offs between efficiency and resilience may mean we need to develop ways to make systems more stable, such as pruning connectivity or paying for defence measures. “We now have the quantitative, analytical tools to do that,” says Bar Yam. Such models may also show when short-term costs that reduce a system’s efficiency may be warranted because of the long-term benefits of increased system resilience.

Some connectivity problems could be hard to prune, though. Biggs says close coupling between major global hubs, such as the eurozone and the US, is a big source of instability that which may threaten strong contributors in future, like France and Germany.

Why don’t economists know this?

They are starting to. Some economic theorists have drawn parallels between financial networks where bank failures are prevented, and forests where small fires are always put out. Such forests accumulate deadwood fuel and lose patchiness, increasing connectivity. When a fire eventually breaks out, it becomes huge. That’s why forest managers now encourage regular, small burns. Similarly, banking networks may need low-level failures to prune connectivity and risk.

Systems-based thinking has even reached the Bank for International Settlements in Basel, Switzerland, which sets global rules for the capital a bank must hold to back loans. It announced this month that the risks posed by banks depend on their “size, interconnectedness, complexity and global scope”. So from 2016, “global systemically important banks” – initially 29 of them – will be required to keep more capital on hand per dollar loaned than less vital banks. This is partly to “discourage banks from becoming even more systemically important” – in other worlds, too big to fail.

This recognition of the importance of complexity has been largely confined to banking, however. The eurozone is a network of governments. It is not clear how eagerly they will adopt a way of thinking that truly puts collective interests first.

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Results 2.0: Towards a portfolio-based approach

Posted in Accountability, Evaluation, Healthcare, Innovation, Institutions, Knowledge and learning, Leadership, Malaria, Meetings, Organisations, Public Policy, Strategy on June 30, 2011 | 9 Comments »

The international development sector has been in a tug of war around the ‘results agenda’ for the past few months. This post explores the tensions and suggests a way to bring the sides together by focusing on the relevance and appropriateness of different approaches.*

I: The Results Tug of War

Development results is one of many areas where discussion and debate seem increasingly polarised. On one side of the results tug of war are those calling for more and better results, more rigour in analysis and more discipline in reporting. The failure of development, they argue, is basically about the failure to focus on results. ‘Modern management techniques’, especially those that are embodied by ‘results-based management’ are seen as the answer.

On the other side are those who argue for a ‘push back’ against this approach. Such reductionist approaches are seen as only suitable for certain kinds of development interventions, and that at their worst, these approaches inhibit the creativity and innovation needed to achieve results in the first place. The danger here is that we throw out the results baby with the reductionist bathwater (see here for a previous Aid on the Edge post on this).

What is increasingly evident is that, in the diverse and dynamic aid landscape we face today, all agencies attempting to genuinely strengthen accountability and learning face a number of common challenges. This is a preliminary list, I am sure readers will be able to think of more.

  • Data availability, coverage and quality are perennial problems
  • Participation and ownership - as Robert Chambers might ask: ’whose results count?’
  • Incentives and disincentives to use information and results, especially when they run counter to individual and institutional interests
  • Bureaucratic inertia: all too often results-related work is placed on top of and increases the already considerable bureaucratic and administrative burden on aid agencies, rather than simplifying and reducing it
  • Risks and fear of failure: How can we manage and be transparent about the different kinds of risk failures inherent to development projects & programmes?
  • Many conflicting imperatives: learning vs accountability, policy vs operations, domestic vs international

The key point is that these apply equally to both sides of the results tug of war. As a result, a lot of effort is being wasted, with problems being dealt with in entrenched intellectual silos rather than in a collective manner.

So what to do to move beyond the ‘tug of war’? I would argue that a first step would to think about how to bring the different results approaches together to establish a more constructive dialogue. What is needed is a more flexible and differentiated approach to results, one which takes account of the diversity of the development and humanitarian portfolio.

II: A Draft ‘Portfolio of Results’ Framework

What might such a portfolio-based approach look like? There are a number of useful approaches from academia, civil society and business strategy that can help here. These include Brenda Zimmerman’s simple-complicated-complex distinction, the Cynefin framework of Cognitive Edge, work done by Alnoor Ebrahim at Harvard University, work done by Eliot Stern on relevance of different approaches to impact assessment and finally a recent model put forward by Patrick Moriarty of IRC.

All of these suggest in their different ways that appropriate strategic approaches (and by extension, results approaches) need to be based on:

(a) the nature of the intervention we are looking at, and

(b) the context in which it is being delivered.

Reading across these approaches we can suggest a preliminary framework which may prove useful in bringing together different results approaches in a productive and mutually beneficial way.

First, imagine an agencies projects and programmes being distributed across a spectrum of the ‘nature of interventions’, placing relatively simple interventions on one end, and more complex issues, at the other.

Then let’s add in a vertical axes on context. Again, think of a spectrum, this time from stable / identical to dynamic / diverse.

This gives us a 2 by 2 framework for analysing and mapping different development interventions - in effect, this is a draft ‘portfolio of results’ framework. Where an intervention is positioned on this framework has implications for the kinds of results orientation we can take, as shown below.

In the top left corner of simple interventions in identical stable settings, is the Plan and Control zone – here ‘traditional’ results-based management approach, conventional value for money analyses and randomised control trials work well.

The bottom right corner of complex interventions in diverse, dynamic settings is what I have termed Managing Turbulence – here the philosophy is less ‘Ready, Aim, Fire’ (as in the Plan and Contol zone) and more ‘Fire, Ready, Aim’. Here we need to learn from the work of professional crisis managers, the military and others working in dynamic and fluid contexts.

In between is what I have called Adaptive Management, where either because of the nature of the intervention or the nature of the context, multiple parallel experiments need to be undertaken, with real-time learning to check their relative effectiveness, scaling up those that work and scaling down those that don’t.

III: Applying a Portfolio of Results Approach: A health-focused illustration

By way of illustration, let’s look at three health interventions – vaccines, HIV-AIDs, and rebuilding national health systems. I would argue that they could be distributed on the matrix something like this.

So if we are looking at simple interventions in a stable / identical environment, or what might be called the plan and control domain, randomised control trials, traditional cost-based ’value for money and results-based management approaches work great. Vaccines are perhaps the best example here. And as the ongoing MSF campaign on reforming GAVI suggests, a focus numbers and bean-counting can be of vital importance to ensuring effectiveness.

But we may find ourselves managing interventions that are more complex, in stable contexts. We can also think about situations where the intervention is simple but the context is dynamic. In both of these instances we may need to move away from blueprints towards a more adaptive management approach, trying out multiple parallel experiments and monitoring progress and rates of success and adapting to context. In HIV-AIDS responses, the optimal mix of responses is key and almost always locally determined (see previous Aid on the Edge post here). Also increasingly relevant are global malaria responses which need to adapt to the changing patterns of incidence and the evolution of resistance (ditto here).

Finally, in environments where our interventions are complex and the context is dynamic and diverse, we have to take a leaf out of the book of those who work in high risk environments – professional crisis managers, military and so on. Programmes to rebuild health systems, especially in fragile states, are a good example here. Here we need to be doing action research, real-time assessments and learning by doing.

This is not a rigid framework and there is overlap between the different areas. But different approaches to results can be shown to be more or less effective in different domains. In general terms, you can do a detailed RCT in the bottom right quadrant, but it may be a thankless task and not the best use of resources. You can do an RCT in the top right quadrant, but it could well prove to be a necessary but not sufficient condition for success. And so on.

(This also helps think about the concerns of one side of the tug of war – that there is a pressure to push development to the top left domain, and a widespread misapplication of the top-left tools for the other domains.)

Obviously this is a preliminary framework based on reflection and discussion, and is open to critique and debate. The key principle is that a more nuanced approach to results will have to be based on a systematic assessment of, at a minimum, our interventions and the context we are working within.

IV: Taking the Results 2.0 agenda forward

This kind of framework can also be used to think strategically about our overall portfolio of projects and programmes. How is our overall spend allocated between these ‘domains’? What are the implications for risk? I think there is a useful analogy with investment portfolio managers are used to diversifying their portfolios in order to reduce their exposure (see diagram below).

We urgently need to develop new ways of analysing the different elements of our portfolio. Through this we can start to unpack and understand the diversity of our efforts, and ensure we don’t take a ‘one-size-fits-all’ approach to results and all that entails.

There are a number of follow-on issues about how we might take this area of work forward.

  • We will need to refine or adjust the draft ‘portfolio of results’ framework, based on more in-depth analysis, discussion and debate. Of course, we may need something completely different to what is proposed here (all feedback, however critical is warmly welcomed!), but the key is that we need something to bring diverse constituencies and approaches together.
  • We need to think about which sectors are amenable to a portfolio type  approach to results, where we can pilot a ‘Results 2.0 process’ and we need to think about what new kinds of tools and methods might be required. I think health would be a great sector to start on.
  • Different kinds of interventions will need different kinds of information, which will call for different tools for managing this information. New kinds of tools and techniques will be necessary. Importantly, these should help to consolidate and simplify, rather than just increase, the reporting and administrative burden on the sector.
  • We urgently need to think about how this affects development communications, and how we can start to develop more sophisticated framing and messaging of positive and negative results, based on the different elements of our portfolio. This will be perhaps the hardest part of this new results agenda, as it means that we will have to tell our key stakeholders things like ‘we don’t know’, or even worse, ‘we failed’. This may mean riding with punches in the short-term. But this will also mean we will need to think hard about what different stakeholders expectations are, and how they can be best met. The overall legitimacy and sustainability of such efforts demands greater involvement of national governments, civil society and poor communities.

I want to close with this thought from a cross-country study of results-based  management looking at Western countries – that results are not an end in themselves, but are a means by which to establish trust in the system. I would add: and within the system.

Because we do so many different things in development, we have to do different things to earn trust of our diverse constituencies. (We may also have to accept that in some quarters, trust will never be established, but that is another story.) What we cannot do is move forward without finding ways of trusting each other, whatever our methodological or conceptual background and prejudices.

Bringing our diverse opinions and ideas together to test their relevance and appropriateness seems like an essential first step.

* This is the summary of a talk I gave at the June 2011 IDS-ODI roundtable on results with the UK Secretary of State Andrew Mitchell, revised following useful comments from participants. Special thanks go to Robert Chambers and Simon Maxwell for thoughtful and constructive feedback.

Fellow participants have also blogged on the meeting:

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Success, failure and what lies between

Posted in Accountability, Economics, Evolution, Innovation, Institutions, Knowledge and learning, Leadership, Meetings, Public Policy, Strategy on June 17, 2011 | 1 Comment »

Earlier this week Tim Harford, also known as the Undercover Economist, gave a fantastic talk at ODI on the topic of ‘Development as Trial and Error’. Drawing on his latest book, Adapt: Why Success Always Starts with Failure, Tim provided the audience with a compelling account of the need for a different way of thinking about and navigating complex problems. (click here and scroll down for videos of the talk and
subsequent discussion)

One of his starting points was to highlight the considerable complexity of the economy, drawing on the work of Eric Beinhocker. This compared the ‘product space’ in different societies – the number of distinct products that are on offer. In hunter gatherer societies, it amounts to some 300 products. In the average Wal-Mart, it is 100,000. In a city like New York or London, it is 10 billion. (you can see Eric’s explanation of this in his presentation at a UKCDS workshop in May)

Tim used this concept, and a story about an unusual project to build a toaster from scratch, to argue that this kind of complexity can most effectively be navigated through evolutionary principles of ‘variation, selection and amplification’ that enable lots of small ‘trial and error’ experiments to be aggregated as effectively as possible.

The market was given as one example of such an aggregator, but there are obvious shortcomings. It has worked for some kinds of problems – Western affluence, most notably. But there are other problems where the market has failed, or where its influence has been far from desirable. Other examples include the scientific enterprise, consisting of diverse means of submitting and peer review of new ideas and experiments. But of course the scientific establishment is also prone to conservatism and inhibiting innovation.

So what can we say about situations where the market is not working or cannot work, where peer review mechanisms are not in place, and where tolerance of failure is impossibly high? The public sector was the example that everyone kept coming back to. How do you get the process of trial and error working in such settings? There are numerous ways Tim touched upon, including innovation prizes, creating artificial marketplaces, finding ways of supporting entrepreneurs, and so on. This is a great article he wrote for Slate, drawing from the book, on exactly this topic. As he puts it there:

Here’s the thing about failure in innovation: It’s a price worth paying. We don’t expect every lottery ticket to pay a prize, but if we want any chance of winning that prize, then we buy a ticket. In the statistical jargon, the pattern of innovative returns is heavily skewed to the upside; that means a lot of small failures and a few gigantic successes.

The paradox at the heart of the need to be more systematic (i.e. controlled,
managerial) about innovation (i.e. disruptive, entrepreneurial) is one that is
not easily overcome. Tim’s remarkable achievement in Adapt is in his clear and
eloquent articulation of this challenge, along some excellent accounts of how it
has been addressed. Let’s hope we in development and humanitarian aid are able to take his ideas and lessons on board.

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