I’ve come up with a set of rules that describe our reactions to technologies:
1. Anything that is in the world when you’re born is normal and ordinary and is just a natural part of the way the world works.
2. Anything that’s invented between when you’re fifteen and thirty-five is new and exciting and revolutionary and you can probably get a career in it.
3. Anything invented after you’re thirty-five is against the natural order of things.”
Douglas Adams, 2002
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
Bias is an inescapable element of research, especially in fields… that strive to isolate cause–effect relations in complex systems in which relevant variables and phenomena can never be fully identified or characterized…”
The field Sarewitz is writing here about is biomedicine, but he could easily be describing development or humanitarian work. The fundamental problem, as he sees it, is that biases are not random but systemic: “if biases were random, then multiple studies ought to converge on truth [but] evidence is mounting that biases are not random.”
This claim is not new, of course. As the piece argues, systematic positive bias was identfied in clinical trials funded by the pharmaceutical industry back in the mid-1990s. More recently, reviews of so-called ‘landmark’ studies in fields such as cancer research has shown that positive results could only be replicated in a minority of cases.
However, these previous assessments tended to assume that the problem was not with science per se, but rather with those forces that sought to co-op it: industry, government, special interests, and so on. Reduce the influence of these interests, the argument went, and you would eradicate such biases.
But it is now emerging that there are some serious underlying problems within science itself. The cases are wide-ranging across biomedicine: “evidence of systematic positive bias [is] turning up in research ranging from basic to clinical, and on subjects ranging from genetic disease markers to testing of traditional Chinese medical practices.”
The two major faultlines, according to Sarewitz, are the methodological narrowness of the approaches employed to generate evidence, and the culture and incentives of scientists and science funders.
The first one is pertinent for readers of this blog. Researchers seek to reduce bias “through tightly controlled experimental investigations. In doing so, however, they are also moving farther away from the real-world complexity in which scientific results must be applied to solve problems.” Ironically, “the canonical tenets of ‘scientific excellence’” are threatening to undermine the whole enterprise. One rather shocking (for me, at least) example relates to the latest developments in research on mice, where a lot of resources and funds have been poured into the cloning of genetically identical animals, in order to enable fully controlled, replicable experiments and rigorous hypothesis-testing. Any sense of moral repugnance aside, perhaps the worst thing about this endeavour is that the findings of the research subsequently undertaken have turned out to be useless when applied in the real world.
Sarewitz also writes about the lack of incentives to ‘report negative results, replicate experiments or recognize inconsistencies, ambiguities and uncertainties’. There are also challenges around the various cultural and attitudinal positions taken toward science among funders, scientists, the media and the public at large. Sound familiar?
It should – such issues are not a problem for biomedicine alone:
[they are] likely to be prevalent in any field that seeks to predict the behaviour of complex systems — economics, ecology, environmental science, epidemiology and so on. The cracks will be there, they are just harder to spot because it is harder to test research results through direct technological applications… and straightforward indicators of desired outcomes…
Sarewitz closes with one potential solution, which may also be of relevance for work in development and humanitarian fields:
Scientists rightly extol the capacity of research to self-correct. But the lesson coming from biomedicine is that this self-correction depends… on the close ties between science and its application that allow society to push back against biased and useless results.
So what can we in the aid sector do about such bias, if indeed it is present in our work?
The first idea is the one that Sarewitz suggests: “societal push back”. Sadly, despite the rhetoric and growing practice of participation, the scope for Southern stakeholders – especially aid recipients – to ‘push back’ against useless results in development and humanitarian research is still severely limited. This doesn’t mean we should stop the effort, however, and perhaps new technologies and feedback processes can help us here.
The second strategy might be to address issues of the incentives and cultures which perpetuate such biases. But we seem to be far too concerned with developing country actor incentives and motivations to look at those in our own organisations. As one participant at a recent ODI event put it: “why do we always say that developing country leaders have mixed motives at best whereas the motives of donors [and other aid actors] are always considered impeccable?” We should find a way to ensure that these aid “physicians” first heal themselves.
The final course of action is to try to expand and adapt the concepts and models used in our work. This effort (of which this blog is one small part) is still very much a work-in-progress, but the growing interest among researchers and practitioners should give us some small cause for hope. After all, the key to paradigm shifts in science – and in other fields – is not just logical argument and experimental proof. In the words of Thomas Kuhn:
as in political revolutions, so in paradigm choice—there is no standard higher than the assent of the relevant community.”
Innovation is getting a lot of attention at the moment in development and humanitarian work. Many, including myself, see this as long overdue. But, according to an article in this weeks Economist, this attention may be misplaced. The piece makes a strong argument for the importance of imitation in business, and its advantages over innovation. In this post I want to take a look at these arguments for imitation. I also want to see what complex systems research tells us about the limits and possibilities of such an approach.
I: The Virtues of Copying?
Innovation is essential. Countless speeches, articles and books attest to its central importance – in economic growth, business success, and organisational effectiveness. As a result, imitation is a “heretical idea”. But the uncomfortable truth, according to the piece in this weeks Economist at any rate, is that in the real world, firms that copy others are more successful.
- The iPod, the iPhone and the iPad were not the first of their kind: “Apple imitated others’ products but made them far more appealing.”
- Pharmaceutical firms can be divided into inventors and imitators, and some inventors have joined the copycats, selling generic drugs
- Supermarket own-label products copy well-known brands, making for a multi-billion dollar product category
- High street fashion firms consistently copy innovations from the catwalk.
Such imitators often proved to be the winners in business:
copying is not only far commoner than innovation in business… but a surer route to growth and profits…. studies show that imitators do at least as well and often better from any new product than innovators do. Followers have lower research-and-development costs, and less risk of failure because the product has already been market-tested…”
So why isn’t imitation lauded? The key issue is that the incentives for copying are weak – whether legal, individual, organisational or cultural. Set aside the obvious issue around patents, and we learn that “praise and promotion do not go to employees who borrow from other firms.” A study of how new product development firms go about their work found that none had a formal or informal policy for responding to other firms’ innovations, making them slow to learn from others successes. And there may well be cultural factors at play here, although the piece made what for me was a rather lazy and out-dated comparison: US firms tend to be obsessed with innovation, whereas Asian firms are far better at legal imitation.
II: Imitation or Exploring Adjacent Possibilities?
I finished the piece feeling that there was more to this issue than the author acknowledged. At best, the analysis was incomplete, at worst, very simplistic.
First, many of the successful “copying” efforts highlighted in the article highlights were far from easy or straightforward. The process of imitation involves numerous adaptations and innovations – some of them significant and certainly not cheap.
Take the iPhone, which is held up as a kind of archetype of copying. Clearly it wasn’t the first smartphone, but compare it to what was around at the time and it is clear that Apple weren’t simply copying and pasting ideas. The idea that Apple somehow saved on the R&D costs of the iPhone because of the advances made in prior products seems risible.
To borrow an idea from evolutionary biology, I would argue that the key to the most of the successful imitations that the article presents is really that many of the so-called copycat firms explored the “adjacent possibilities” – the diverse and emergent possibilities that spring up around a new idea, product or process.
Stuart Kauffman uses this concept to explain how such powerful biological innovations as sight and flight came into being. More recently, Steven Johnson showed that it’s also applicable to science, culture, and technology.
The core of the idea is that people arrive at the best new ideas when they combine prior, adjacent, ideas in new ways. Most combinations fail; a few succeed spectacularly. So, copying might succeed – but there are all kinds of examples where it doesn’t.
III: Innovation in the App Ecosystem
Second, and perhaps even more importantly – you need innovators to copy from in the first place. No innovators means nothing to copy which means nothing to sell. To really get to grips with the ‘imitation vs innovation’ debate, the Economist piece needed to pay more attention to the overall system of firms, consumers and products – and the dynamics and interactions in that system. Fortunately, recent and excellent work by two researchers at University College London addresses exactly this issue in the context of mobile applications, and presents some very pertinent conclusions.
The “app economy” of producers and users that has sprung up around the applications that run on mobile phones and devices is nothing short of startling. It has been referred to by industry experts as “one of the biggest economic and technological phenomena today”.
Lim and Bentley – one is a prize-winning software engineer, the other a successful “app entrepreneur” – started with the insight that will be familiar to Aid on the Edge readers: that the app economy was best seen as a “co-evolving system of apps, developers, and users [who] form complex relationships, filling niches, competing and cooperating, similar to species in a biological ecosystem.”
Apple releases very little data on its stores and so the researchers decided that the best way to get around this would be to build an ecosystem model to simulate the dynamics they observed. They programmed agents in their model – appropriately named AppEco – to mimic the behaviour of developers and consumers.
Developers build and upload apps to the app store; while consumers browse the store and download the apps. They also programmed apps – passive artefacts in the ecosystem which are the key means by which the agents interact.
They then programmed their developers with different characteristics. They identified five broad types of developers in the real app economy, and built these characteristics into their model agents. They are innovators, optimisers, milkers and copycats, and flexibles. Although specific to the app economy, there are clear parallels in most other sectors and contexts.
- Innovators are those developers who come up with groundbreaking apps – like AroundMe or TuneIn Radio. In te model, innovators were developers who produced different apps in a variety of categories – including social networking, business, utilities, and productivity.
- Optimisers take a hit formula, such as the Angry Birds franchise, and try to adapt and continually improve it. In the model, these developers were the learners – they took their own best app and made variations on it.
- Milkers have one specific idea and use it repeatedly. They might, for example, create apps for each of hundreds of town maps, rather than building one app that can call up many maps. In the model, they used their most recent idea and varied it repeatedly.
- Copycats build knock-offs of top-selling apps – see Angry Chickens or Angry Dogs – and work by appealing to or confusing users who end up buying the facsimiles.
- Flexibles begin with one of the strategies above, but change their strategy based on the strategy of the top developers.
Lim and Bentley then calibrated the model to match the behaviour of a real app store, in this case, the Apple iOS App Store, which is the oldest and best established store. They used three years worth of publicly available data from the store and primed the model until it closely resembled the behaviour of the real store.
The next stage was to run some “what if” experiments. The specific questions that inspired these experiments have direct relevance to the Economist piece. For example, with so many developers trying out different strategies to increase their downloads, Lim and Bentley wanted to know if an innovative developer would receive more downloads compared to a copycat developer.
At the start of each simulation of the App economy, all five categories of developers contributed an equal number of apps, but different constraints were placed on the system. A whole range of different scenarios then evolved, including the following:
- If the proportion of apps from each group was kept constant, copycats made the most money initially.
- Over time, however, the overall ecosystem suffered from a lack of novel products. Dissatisfied users moved onto better platforms
- Copycats rely on good apps created by other strategies; it is extremely difficult for an ecosystem to support a large proportion of copycats. (This result mirrors the app stores in the real world – copycat developers regularly appear and take advantage of the success of others, but nevertheless their strategy remains in the minority.)
- When consumer choices dictated which apps were successful, it was the optimisers who sold the most apps, followed by innovators, milkers and finally the copycats.
The general conclusions in the authors’ summary paper seem clear:
In a complex ecosystem no strategy can be a guaranteed winner, but our results indicate that some strategies should be chosen more frequently than others. Innovators produce diverse apps, but they are hit or miss – some apps will be popular, some will not. Milkers may dwell on average or bad apps as they churn out new variations of the same idea. Optimisers produce diverse apps and tailor their development towards users’ needs. Finally, Copycats may seem like the best strategy to guarantee downloads in an app ecosystem, but the strategy can only work when there are enough other strategies to copy from. In addition, this strategy can only exist in a minority, otherwise app diversity will decrease (many duplicated apps result in a scarcity of some features desired by users) and the fitness of the ecosystem will suffer.” (emphasis added)
IV: Conclusions: Mix it Up
Both of these ideas – “adjacent possibilities” and the ecosystem model – suggest that the Economist article downplayed the difficulties and limitations of imitation. While it briefly acknowledges Schumpeter’s concerns about imitation dominating industry, the overall tone is bullish, suggesting that: “copying is here to stay; businesses may as well get good at it.”
The reality, however, is that copying is seldom a straightforward matter, and can take as much creativity and resources as innovation.
And there should be serious concerns about the overall health of a ‘ecosystem’ dominated by copycats. Copying is a strategy that can only work for a minority of players, and then only for limited periods.
Any lessons here for the aid system, I wonder?
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.
Posted in Accountability, Biology, Chaos, Economics, Evolution, Financial crisis, Innovation, Institutions, Knowledge and learning, Leadership, Networks, Organisations, Self organisation, Strategy, Technology, Trade | 1 Comment »
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.
There’s been a lot of interest in the imminent vacancy of World Bank President, with numerous suggestions of qualified individuals who should be on the list. This post looks at one particular aspect of the role which seems to be missing from most of this debate, and which should be high on the list of criteria for a successful future leader of the Bank.
I: The Official Views of ‘Development Churches’
David Ellerman, currently a visiting scholar at the University of California in Riverside, and World Bank Staffer for over a decade (where his roles including being senior advisor to the Chief Economist Joseph Stiglitz), is one of the most original and innovative thinkers in development. In 2000 he published a paper entitled ‘Must the World Bank have Official Views?’ in which he argued that the Bank spent a lot of time and effort determining its Official Views on particular development issues, and that this practice undermined in efforts in a number of ways.
- it impedes the open contesting of adverse opinions that is so crucial to the advancement of knowledge
- it impedes the Bank as a learning organization since the overturning of an older view is all the more difficult if it has been branded and enshrined as an Official View
- it impedes client countries being intellectually in the driver’s seat as they will inevitably be encouraged in a multitude of ways to accept an opinion because it is an Official View
(The fact that Ellerman wrote and published this while still at the Bank gives some indication of his intellectual courage – I don’t know the backstory so cannot say what impact this had on him personally or professionally.)
Ellerman expanded on this in a subsequent paper for Development in Practice Journal. Through its focus on Official Views, the World Bank and other aid agencies become, in effect, ‘Development Churches’:
“…giving definitive ex cathedra ‘official views’ on the substantive and controversial questions of development. As with the dogmas of a Church, the brand name of the organisation is invested with its views….”
Ellerman argues that in the face of these Official Views, adverse opinions and critical reasoning tend to give way to authority, rules and bureaucratic reasoning shaped by the hierarchies within the organisation. Moreover, these Official Views “short-circuit” and bypass the active learning capability of national and local actors, and substitute the authority of external agencies in its place.
…Once an ‘Official View’ has been adopted, then to question it is to attack the agency itself and the value of its franchise. As a result, new learning at the expense of established Official Views is not encouraged…”
II: Moving Away From Doing the Wrong Thing Righter
The conclusions of a recent, still draft study on the World Bank’s efforts in participatory development indicates that the issues Ellerman highlighted are still an issue within the agency:
Project structures need to change to allow for flexible, long-term engagement. Projects need to be informed more seriously by carefully done political and social analyses, in addition to the usual economic analysis, so that both project design and expected outcomes can be adapted to deal with the specific challenges posed by country or regional context… Most importantly, there needs to be a tolerance for honest feedback to facilitate learning, instead of a tendency to rush to judgment coupled with a pervasive fear of failure. The complexity of development requires, if anything, a higher tolerance for failure. This requires a change in the mindset of management and clear incentives for project team leaders to investigate what does and does not work in their projects and to report on it (emphasis added)
This general phenomena is not unique to aid agencies, of course. The late great Russell Ackoff, a systems thinking pioneer, used to argue that almost every problem confronting our society is a result of the fact that our public policy makers are doing the wrong things and are trying to do them ‘righter’.
The righter we do the wrong thing, the wronger we become. When we make a mistake doing the wrong thing and correct it, we become wronger. When we make a mistake doing the right thing and correct it, we become righter. Therefore, it is better to do the right thing wrong than the wrong thing right.
Back in 2000, David Ellerman suggested a way of overcoming the addiction to Official Views, which involves presenting the following message to client countries, and then acting upon it:
“…To the best of our accumulated experience (which we deem to call “knowledge”), here is what works best in countries like yours. Why don’t you study these principles together with their corroboration to date, take a look at these case studies, contact these people who designed those reforms, set up horizontal learning programs with those best practice cases, and try some experiments to see what
works in your own country? After carrying out this learning process on your own, you might call us back if you feel we could help…”
III: Implications for World Bank Presidency Candidates: A Simple Questionnaire
Building on all of this, we might view the current candidates for the World Bank Presidency in a different, and hopefully useful, light. We need someone who can take Ellerman’s message and Ackoff’s philosophy make them part and parcel of the way the organisation works.
To test candidates suitability in this regard, we might sensibly ask them, and those who know of them, the following yes / no questions (which should take no more than fifteen minutes of their time).
- Does the candidates track record indicate they have the ability to be a leader who facilitates as well as one who directs?
- Is the candidate able to let go of the notion of selling to, or controlling, others using a set of predefined strategies and results? (Can they effectively manage the uncertainty and ambiguity that ensues?)
- Does the candidate instinctively seek out challenges to their institution’s ideas and policies, and see their leadership role as catalysing ‘mutual learning’? (Does the candidate routinely present their viewpoints as ‘permanently provisional’ and ‘up for debate’?)
- Can they respectfully but purposefully elicit the insights, creativity, and wisdom from others? (Can they do this even when others disagree with them?)
- Can they encourage multi-stakeholder dialogue and debate as a route to experimentation and innovation?
- Are they courageous enough to say ‘I was wrong’, and enable their learning process to be public, to allow others in their organisation and more widely to follow suit? (Are they willing to hear about, and learn from, failure, even in high-profile programmes?)
- Can their leadership help diverse groups and constituencies accomplish the results that they want? (Are they willing to share the credit for successes with others?)
I would tentatively suggest that if we have ‘yes’ responses against most of these questions for a given candidate, we could be looking at a genuinely interesting appointment.
If we have mostly ‘no’s, then we should all get ready for another term or two of Official Views, and all that goes with them.