Last week I had the honour of being involved in a set of meetings in Beijing, which represented the inaugural meeting of the Hanwang Forum, of which I am a member.  There are many very supportive things I would say about this Forum but in this article I would like to focus on how this Forum came to be, which was due to the leadership of a Taoist master.  I want to relay my experiences here because we Westerners have a lot to learn from the Chinese philosophy of Taoism, which curiously has a great deal of overlap with Complexity theory.

I must emphasise up front that I am referring to a Taoist style of leadership, not Chinese.  For most of the past 60 years, China has been influenced by a centrally-controlled way of thinking, which is very much the antithesis of Taoist leadership.

Over-generalising slightly, the Western attitude to leadership is about the leader deciding and articulating the destination of a group, and developing a strategy for reaching that destination.  They articulate both the ends and the means, which are carried out by those being led.  Ideally, also, the leader declares the principles and values upon which the whole movement is based, which the followers are required to adhere to.  In my experience this tends to be followed by a lot of mutterings about the lack of leadership skills of the shepherd by the sheep.

The famous Yin and Yang of Taoism

The Hanwang Forum came about through the leadership of a Taoist master who in effect did exactly the opposite of this Western leadership model.  In a nutshell, what he did was to engage in dialogue with various people around the world, which led to the practical emergence of the Forum.  This Forum enables a group of people to co-construct the meaning of what looks more like a movement than a forum; to co-construct the values and principles upon which the movement is and will be based; and to co-construct the nature of the problems we face and to imagine solutions together.  The meetings I joined in Beijing were mostly about problems and solutions but it was clear to me that meaning, values and principles were discussed implicitly.  So the nature of the leadership was to create an enabling platform and, rather than articulate end-points, principles and values, the Taoist master had developed a Forum in which this was being done by its members.

Clearly, such an approach requires trust in the people involved because they are being empowered as well as enabled.  The over-generalised Western approach described above is a very low-trust approach and it is one in which trust and power is conferred only on the leader.

I should also mention that for the whole of the two days of meetings, the Taoist master stood in the background.  There was a two-minute slot when he had to take the microphone but, ironically, this was in service to a sub-group presenting its conclusions to the whole group.  I took that opportunity to mention to a number of people that he was the Taoist master largely responsible for the Forum.  Most of them had heard of him but weren’t aware of who he was.

Over the past 18 months in preparing for this inaugural meeting, I have witnessed other instructive parts of his leadership that I wish I could mention here in detail.  I should not say too much because to be effective some of it probably requires people to be unaware of what is being done (or not) and why.  But I will say that on two occasions I noted this Taoist master not do something.  On one of these occasions I was made aware that the non-action was a deliberate choice that had a specific reason.  I was told about this quiet decision not to do something on this occasion for a good reason, and it made me ponder how many other non-actions I hadn’t observed.  Importantly, the intent was not to be manipulative, it was a part of the whole enabling process.  Another very clever thing he did was to choose a Western counterpart who, frankly, has similar (humble) leadership skills and who has helped to cultivate the forum from the Western end.  He is a good enough friend of mine that I know he would be uncomfortable with me mentioning him by name.

As the world has become more complex, and as this complexity intensifies further (which is probably likely), we need more of this Taoist style of leadership.  The Western approach is really only useful in non-changing and relatively simple environments, which are now less prevalent.  If an environment were simple enough for one person to fully grasp, and that same person could choose an appropriate destination and route, then a Western leadership style might not be unreasonable.  But, as is now cliché to say, the world is now more interconnected and complex than ever, which renders the Western approach increasingly obsolete (aside: it now feels cliché to say it’s a cliché).

The Taoist leadership approach is conducive to crowd-sourcing analysis of some problem-space and the legitimate co-construction of meaning, values, etc., within a group of people.  This style is much more suited to the world in which we now live.  By contrast, the Western approach will be relatively uninformed because it does not seek the views of all stakeholders; and it would be illegitimate because the so-called strategy (and values) do not emerge from these same stakeholders.

I wish I could say, with hand on heart, that Complexity theory leads us to a view of leadership that is identical to what I saw before and during the meetings in Beijing.  I cannot.  It does get us miles away from the traditional (and over-generalised, I know) model of Western leadership described above to something much more like what I witnessed.  But the key difference is that Complexity theory would, in my interpretation, give us impersonal recommendations about servant / host / enabling leadership.  What I saw before and in Beijing was a whole personality manifesting itself in many ways, including in the form of leadership, and communicating on multiple levels, including personal and intellectual.  It was very natural, very humble, and born of a very deep and mature philosophy from which we have a lot to learn.

Over the past few years, the spillover of complexity theory from the natural into the social realms has intensified, instigating a whole range of new theories and insights about the manner in which complex human systems emerge, behave, and transform.  But, with a few honourable exceptions, complexity theory has struggled to make the leap from the academic community into the real world.  Could policy makers use ideas emanating from complexity theories, to design and implement better policies? Or, to paraphrase Eric Beinhocker, could complexity evolve from a Sunday afternoon thought into a Monday morning action?

The Origin of Wealth by Eric Beinhocker

Complexity experts have produced a growing array of books and articles presenting the added value of analysing social environments as complex systems, be it new understandings into the behaviour of markets; the manner in which tastes and preferences are shaped through network effects; the indirect impacts of infrastructure development; or the optimisation of knowledge retrieval. However, as might be expected from any emerging field, much of this new knowledge is still structured from an R&D perspective rather than an end-user’s point of view, thereby potentially slowing down adoption, integration, and learning. Put another way, the complexity community looks rather supply-side heavy and demand-side light.

Curiously, the problem of bridging the theory-policy gap is much more acute with complexity theory than other approaches because complexity puts a great deal of emphasis on uniqueness, both in time and space.  Idiosyncrasies matter, which means that some policy adopted in one area might not be appropriate elsewhere; and a policy implemented now might not work in the future (in the same area) because complex human systems are constantly evolving (unpredictably).  However, far from saying policy is pointless, it means that policy analysis has to be differently focused and any outcomes better tailored to a dynamic environment.

Helping to create the bridge from the theoretical to the practical will entail an end-user’s exploration into complexity, i.e. the people making decisions, designing action plans and leading implementation. Given the impressive strides already made in the field, this short article aims to answer the following: given a policy maker’s perspective, what could complexity ever do for us?

Policy-making: between design and outcome

Reforming the NHS? Developing new growth strategies? Fighting human trafficking? Or contemplating military intervention? It would be hard to find policy makers who wouldn’t describe their challenges as complex, comprising of seemingly endless interrelated elements, actors and uncertainties. At the same time, the mere acknowledgment of life as complex is rather futile. The real question is whether complexity theory can provide decision-makers with an actual toolbox for better dealing with their challenges. We suggest that complexity based methodologies can contribute to policy makers on three main fronts – redefining end goals; providing new knowledge bases for both background research and implementation; and supplying new tools for policy design.

1. Redefining the aims of policy: traditionally, we tend to think of policy in terms of problem solving. Any social or economic challenge is viewed as part of a complicated machine that can be improved through careful calibration. At the same time, complexity science depicts our social system not as a complicated machine but as a complex ecology. Ecologies cannot be calibrated, designed or controlled as there will always be too many dynamic elements, uncertain relations and consequences involved. They can however be transformed. Hence, from a complexity perspective, the aim of policy is to transform a social or economic challenge rather than “solve” it. While this might seem abstract or merely semantic, it holds huge practical ramifications. When planning a solution to a problem, the planner must be able to present an end-state as well as the backward-engineering steps for achieving it. Alternatively, if the aim of a policy is to continually disrupt forces and trends making up a given problem through iterative interventions, it no longer requires a clearly defined end-state and a “proven” path of cause-effect relations. What it does necessitate is a systemic direction. Such a shift from problem solving to transformation opens up a whole new realm of policy options, some of which might have made much sense to policy makers in the past, but were deemed “un-proven” or merely intuitive. A complexity approach can provide new tools for supporting such ideas through new sources of knowledge and implementation tools.
2. New knowledge bases: perhaps the most advanced area so far, complexity based research provides new means for collating and making sense of social information. Advances made in network research and ‘big data’ have set the ground for the development of new indicators and real time data mining. For example, assessing indirect policy impacts in urban development projects, simulating alternative growth trajectories, and following the dispersion of various health concerns. Moreover, together with smarter and more dynamic organisational structures, such new knowledge bases also provide policy makers with new tools for implementation. These include the ability to run multiple pilots and experimentations, create new platforms for outreach and participation, and assess real time feedback. In fact, without such tools the strategic goal of transformation cannot be operationalised. Used effectively, the new knowledge bases will allow policy makers the actual resources needed to persistently adapt their moves so as to continuously maximize impacts and minimize negative effects.
3. New methodologies for policy design: if policy objectives are to be seen as transforming or disrupting existing challenges then the manner in which they are designed will need to incorporate new rationales and modes of operation. To date, while complexity insights have been incorporated into a wide range of social challenges, coherent methodological frameworks for strategising have been developed mostly within the military. For example, Operational Design has emerged out of the integration between complexity principles and architectural theories on structures and space, providing militaries with new practical tools for operating within current conflict environments. It includes a structured process for policy development, starting with information gathering, systems framing, detecting rationales for action and organising the forces’ operations. Unless equivalent, practical methodologies are developed for policy makers in the civilian realms, complexity will not enter the day-to-day workings of governments.

Overall, while we would like to think of policy-making as a rational problem-solving exercise, in which problems are analysed, solutions based on reliable evidence gathering are modeled, authorised and translated into effective end-results, we also know that real life policy-making is a messy and fuzzy process involving only partial knowledge, political bargaining, egos, pre-conceived positions, chance events and unintended consequences. To a large extent, policy makers seem to have inevitably accepted this chasm between rational modeling on the one hand and messy decision-making and implementation on the other – i.e. the inevitable friction between theory and practice. We believe complexity theory provides a foundation upon which this chasm can be bridged, providing policy makers with more genuine and dynamic means for successfully creating the social impacts they seek. Building on this foundation will now require the joint efforts of complexity experts and policy practitioners i.e. to bring the supply-side and the demand-side much closer together.

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I was recently given two papers to read on the nature of “Multiple Exclusion Homelessness”, which is about people with multiple care needs e.g. housing, drug addiction, unemployment, etc.  The papers covered (i) Tackling homelessness and exclusion: Understanding complex lives i.e. need and (ii) Implications for Workforce Development and Interprofessional Practice i.e. the attempted satisfaction of need.  In this article I’d like to consider this subject from a “complexity perspective”.

The reports painted a picture I had feared was probably true, given the tension between (i) how we run our government services in a silo-based way; and (ii) the idiosyncratic nature of human nature.  In summary, the first paper noted how those with multiple and acute needs (e.g. a combination of drug addiction, homelessness and mental health) are “complex cases” involving inter-dependence of need; and the second paper noted that by and large the delivery of care is silo-based.  The papers did highlight some rays of hope, including interdisciplinary co-ordination but I was left with the impression these were rare.  As should be obvious, a silo-based system is most likely to fail those with the most complex of complex of care needs, which can only be described as tragic. I am not blaming care workers here: this is a problem of organisation and the management of resources, and the location of authority and responsibility.

An enormous amount of work has been done in this area by people who are much more familiar with the problems than I.  But here I would like to offer a “complexity perspective” on these most complex of care cases.  I think this perspective could add a lot of value.  The challenge is best represented by quoting one of the case studies in the first report cited above:

“Sharon was 34 and living in shared accommodation with support when interviewed.  She was kicked out when she was 12 after the man her mother had married sexually and physically abused her.  She stayed with a street sex worker for a while, before being taken in to local authority care.  By the time she was 14, Sharon was a sex worker herself and on drugs, moving between squats, punters’ flats and rough sleeping, with brief periods in hostels.  She started sniffing gas and glue, but she was groomed by a pimp who got her on to crack cocaine.  Other drugs quickly followed.

Sharon had four children by various men, all of them taken into care and three now adopted.  Relationships were brief affairs, normally ending in her being subject to violence and needing to leave for her own safety.  There might then be a period in accommodation before she was drawn back into her street lifestyle of drink and drugs, maintained by sex work.  There were periods of imprisonment when, for instance, she was violent to a social worker trying to take her children into care.  It was the prospect of getting custody of her fourth child that eventually led Sharon to seek help to stabilise her life and get a place in supported accommodation.”

There are two principles I would like to emphasise in this blog post.  The first is that human psychology is relatively “plastic”, which is to say that our own values and actions in part shape the values and actions of others; and vice versa – we are shaped by the values and actions of others.  The principle that bears on this in complex systems is co-evolution: in effect, we evolve together, simultaneously.  This principle highlights another important point, that a person’s character is path-dependent i.e. it will reflect the combination of their life experiences, including (and most importantly) their interaction with other people.

The second principle is that every person is unique when viewed close enough.  Idiosyncrasies tend to be emphasised in complex systems more than in other approaches.

We can contrast these two principles with how public policy has typically been delivered in the UK and many other countries.  Silo-based systems are the organisational manifestation of reductionist thinking.  In simple terms, what I mean is that with a reductionist mindset, people are viewed as the sum of their parts and this is also true of care requirements.  If someone has a drug problem, is homeless and has a mental health problem, then they will need to access specialists in these separate fields.  That’s true –but there is an additional point that reductionist approaches miss: the interdependence of need means the provision of care needs to be cohesive and appropriate (i.e. tailored) to each unique individual.

As noted in both papers, quoting a housing support worker:

“everyone has got snippets of the individual but no one is collating it.”

I will emphasise this again because it is so important: it is those most in need of cohesive, tailored care that will suffer from support services supplied by silo-based departments.

So what are the policy implications?  It is tempting to suggest that in light of the care needs of ultimately unique individuals, everything should be devolved to the individual level.  However that would be to under-emphasise the importance of patterns in complex social systems.  There are clearly a lot of people with very specific care needs e.g. a mentally healthy person without a drug problem who just needs housing.  The needs of such people can be satisfied by a system that provides “buckets” of focused care (although this is not to argue for the highly centralised system we now have at the moment – I am merely arguing that specialisms can align with specific patterns of need).

The studies behind the two summary papers mentioned at the beginning included a pattern recognition exercise to identify “typical” Multiple Exclusion (ME) needs.  These patterns (highlighted more in the first paper referenced above) illustrated the high “complexity”, or interconnectedness, of ME but with noticeable “paths” that many people follow.  The policy conclusion I would draw is that those with ME needs require a single representative to appreciate the “whole need” of specific individuals, who could draw on the plethora of statutory resources available as befits an individual.  The metaphor is that of a GP being the gatekeeper of the general public’s access to health care services: those with ME needs require tailored support.  I should emphasise that the two papers referred to an increase in emphasis on bottom-up approaches, noting the idea of personalisation, which seems to be the same as what I am talking about here.  A complexity perspective supports such an approach to ME cases, in my opinion.

When it comes to policy recommendations, it is important not to offer unfunded advice i.e. that which simply says “the government should spend more”.  Here my policy conclusion is purely organisational – under a care budget of given size, a part of it should be allocated to a cadre of people who in effect specialise in being care generalists.  This fits nicely in to the Big Society agenda because it is about devolving power.

Judging by the two papers cited in the first paragraph, a change in primary legislation would probably not be required because the 1990 NHS and Community Care Act appears sufficiently flexible; and the Department of Health has sufficient discretion over interpretation via its guidance notes.

As might be obvious to many readers, a key area I have not touched on in this blog is “causation”.  I have taken for granted some ME need but, as with any problem, ex ante prevention is better than ex post fixing it after the fact.  That’s an entirely different kettle of fish.

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What does accountability look like in a world that is uncertain and in which innovation is not only prevalent but also essential?  In this blog I would like to argue that how we currently “do” accountability stifles innovation.  This is an important issue given how rapidly the world is now changing with the on-going diffusion of information and communications technology.  I conclude by calling for a serious re-think about what accountability looks like in organisational life, notably for those organisations operating in highly dynamic environments.

The genesis of this blog came while reading an excellent draft paper written by NESTA and MindLab, which looked at “Decision making in complexity and uncertainty”.  The draft was provocative and focused on resilience through innovation in public policy.  However, much of the content was about human decision-making processes in general, so it was relevant in all areas of our lives, including in the private sector.

I should emphasise up front (an obvious point) that accountability and innovation are both valuable.  If, for instance, someone in the public sector were being paid a wage by the taxpayer to do some job, it is important they are held accountable for what they do.  I doubt many would disagree.  In addition, it is eminently sensible that we, as a species, innovate.  We have been doing this for a very, very long time and it would not be unreasonable to say that innovation is substantially responsible for the standards of living we enjoy in the West today.  But have we organised our governance and management systems such that there is a conflict between accountability and innovation, both of which we value?  More specifically, does our current approach to accountability stifle innovation?  I suspect this is generally the case, both in the public and private sector.  Let me articulate what I mean.

In a nutshell, I believe that how we currently practice accountability in organisations is based on linear thinking in which the future is treated as predictable; but in reality the world is constantly evolving in unpredictable ways i.e. it is inherently uncertain.  These two points together are, I believe, the source of tension between accountability and innovation.

I should emphasise, however, that this tension should be viewed as a sub-set of a broader tension between two different “teleological” frameworks, or “mental models”, of how we understand and frame human systems.  For example, do we think of organisations as machines, as organisms, or something else?  In the language of Ralph Stacey, we need to make a distinction between formative teleology and transformative teleology.  Formative teleology is where human systems are framed as if they were like predictable machines in which people are automatons, and where the future unfolds in a predictable way.  Transformative teleology is the recognition that human systems are changing continuously: organisations are in a constant state of flux because of the adaptive nature of human beings.  (For those more technically minded, there is an equivalent debate concerning the difference between ergodic and non-ergodic systems.)  Stacey has emphasised that orthodox management science is orientated around prediction and control (within a formative teleological framework) whereas reality is transformative.  Our methods for holding people to account are based on the formative teleology i.e. it is designed as if the future were controllable and predictable and as if human behaviour and relationships were constant over time.

Our conventional approach to accountability typically requires the setting of targets to achieve some aim or set of aims.  When set, these targets will be indicative of success in achieving the aim(s): they form a benchmark for performance evaluation.  Ideally the targets will be quantified so that success is measured objectively.  The distinction between aims and targets is important because if the environment in which the person being held to account changes, the original targets may be decoupled from the original aims i.e. they become inappropriate.  In addition, an environmental context may change so much that even the original aims might to be called in to question.  But in orthodox management science, the inherent changing nature of the world tends not to be recognised.  Or, at the very least, it is under-emphasised, which means the re-consideration of targets may not be institutionalised in organisational practices.

In a world that is in a constant (and unpredictable) state of flux, there is a fundamental problem with this approach to accountability.  The crux of the problem is this: targets set up front can only ever be about “knowns” and “unknown knowns”.  It is impossible to set targets about “unknown unknowns”.  That would require us to anticipate the inherently unpredictable, which is a paradox.  Moreover, if the environment in which someone is working changes, such that the original targets become inappropriate, time might be spent pursuing those targets regardless, leaving less time for any innovation that might be required to adapt to the new environment.  What this tends to mean is that the prescriptive approach to accountability described above will leave too little time and attention for innovation.

As an aside, it is worth highlighting here the nature of co-evolution in innovation, which is to say that one person’s innovation is another person’s environmental change.  So, for example, when an employee of a company notices that the “environmental context” in which they are working has changed, they might need to innovate to adapt as best they can (such as a small change in their working practices or a change in a supply chain).  Their innovation will change the environmental context of the people with whom they are interacting, who in turn may have to adapt, and so on.  This process of continuous of iterative, mutual adaptation is called co-evolution in Complexity theory.  Of course, innovation is not only triggered by a need to adapt.  It can happen spontaneously simply by someone reflecting on some problem, or simply by two people interacting.

Now, back to accountability.  I have over-generalised in my comments above about accountability and innovation in at least two ways, to help emphasise my point.  First, in practice people can and do recognise that the world evolves and they will probably allow time for innovation and for targets to change too.  Often people will do this through basic common sense.  But it will be against the framing of what Stacey calls the “dominant discourse” in management science.  In that framing, any change ought to have been anticipated ahead of time, and built in to the articulation of aims and targets.

Second, the rate and nature of change will vary between different organisations and industries, and the value of the approach to accountability described above will be contingent on this point.  Compare for example a mature market such as milk production and the hi-tech industry of Silicon Valley.  Rapid-change environments can make the type of accountability described above both tricky and even harmful if it leads to the pursuit of inappropriate targets.  Such environments require near-continuous innovative thinking, and this can render future target setting rather pointless.  But in mature industries, where production, distribution, and consumption patterns are expected to be stable, the type of accountability measures described above might be reasonable at both the organisation and employee level (though I am not saying these industries would never need to innovate).  The point I am making here is that most organisations operate somewhere between these two extremes; and the more dynamic the environment, the more the traditional approach to accountability will stifle innovation.

There was a very good example of some of the points raised in this blog outlined in the NESTA and MindLab draft paper regarding the experience with “Public-Private Initiative” (PPI) in Denmark.  After some difficulties with PPI, there was an understandable demand by the public for accountability measures to be taken, including “authoritative guidelines” and “a blueprint for guiding practice” for PPI.  This can be interpreted as a desire by the general public for those involved with PPI to nail down certainty about the challenges faced.  The problem with this is that PPI was (i) operating in multiple, idiosyncratic domains; (ii) it involved the interaction of the public and private sector (which is likely to be a source of creativity itself); and (iii) it is a relatively new initiative (relative to mature industries that is).  All of these points mean that guidelines and accountability measures would be difficult to draw up because the environment is one of change, idiosyncrasies, innovation, and uncertainty.

Curiously, this subject relates to something that Stuart Kauffman, one of the leading figures in Complexity theory, has emphasised: the need to reduce our emphasis on quantification and the equivalent need to raise our emphasis on the quantitative aspects of life.

To conclude, innovation is necessary in dynamic environments but accountability is important too.  So what should accountability look like in environments in which innovation is essential?  For what it’s worth, I think there are at least two important and complementary ways of starting to address this question.  One would be to look at the most successful innovative and creative organisations to see how they do it, to see if we can learn any general principles.  Most (if not all) successful organisations operating in highly dynamic environments will probably have scrapped the approach to accountability described above long ago (else they wouldn’t be successful).  Second, these empirical experiences should be complemented with a conceptual approach that encompasses transformative teleology and the inherent nature and importance of innovation in social systems.

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Recently I have spent a lot of time thinking about the relationship between human values and economics & finance.  Specifically, this has been in two related areas: the types of corporate legal forms that exist (see Paul’s blog on this); and the “Social Investment market”.  In this blog I would like to begin to flesh out a way of thinking about these issues: at the core is an emphasis on human values in an economic and financial system that has a number of collective action challenges.  In particular, I believe that most people in the UK value living in a healthy society and they also value a “sense of community” but our economic system currently does an imperfect job of mirroring these values, and this needs to change.

This blog is timely: today marked the launch of Big Society Capital, which will have an important role in ways that I think are essential to a healthy society, and which I discuss in this blog.

In terms of corporate forms, I think a key challenge is to allow the creation of legal vehicles that enable (and remove the restrictions on) those people who want to pursue pro-social (and possibly less profitable) activities.  An excellent example of what I mean here is the “Community Interest Company” (CIC), which was a legal vehicle made possible through legislation changes in 2005.  In a nutshell, these organisations are social enterprises whose aims are pro-community.  CICs are constrained in particular ways e.g. there is an “asset lock”, which prevents them being sold to and absorbed by private corporations; and they are regulated by the CIC Regulator, which is the gatekeeper to the CIC label.  An important implication of these constraints is that other people (including potential customers and investors) can identify these organisations as being social enterprises: the “CIC” label can be viewed as an expression of the values and aims of those running the organisation.  It is a ready-made brand that has particular meaning.

There is a question here about whether different organisational legal forms are necessary.  I shall leave this to a future blog but in short, yes I think they are because they confer meaning and aims to stakeholders (actual and potential) in a credible way.  Consider this question: why don’t charities just set up as private companies and simply tell the word that they’re in fact doing charitable work?

Another fundamental question is whether we have the legislative environment that enables new legal forms of organisation, like the CIC, to emerge; and for legal forms that might be damaging to society in some way, to die.  I’m not sure we do.  Having spoken to one of the two originators of the CIC idea, he said a great deal of luck was involved in allowing the idea to manifest itself in to legislation.  We need a better legislative environment to enable such new organisational forms to emerge, which allow people to express their values in what they do.  Paul Ormerod and I are currently contemplating this in conjunction with Civitas.  For those familiar with Hayek, I am talking about what (I think) he meant by the emergence of institutions within the economy.

The second area I have been concerned with recently is the Social Investment market.  We can think of this market as supplying capital to those organisations pursuing dual bottom line activities.

For those unfamiliar with “social investments”, you can think of the return on such investments as having two components, or bottom lines.  One is the conventional financial bottom line and the other is the additional impact of the investment on society.  For example, suppose someone were to invest £1,000 in a social enterprise that delivered care services to the elderly in their area.  They might receive a lower return than on a single bottom line investment but if they valued care for elderly people, they would also receive a heart-warming feeling that would constitute a second bottom line (I will skip over the question of the measurability of social return – including whether it is necessary – in this blog).  Hence these investments are often referred to as dual bottom line.

Now, conventional economics would indicate that a free market system should lead to investments that mimic people’s preferences, so if people valued pro-social things, that’s what they’d get.  I’m very sympathetic to this although I prefer to frame the issue through the notion of values and not preferences because I feel the latter term is loaded with a number of inaccurate abstractions.  Human values are related to preferences but they are a better description of reality, in my opinion, and this term helps us to bridge the relevant literature in the field of psychology, and economics.

However – and this is a substantive point – conventional free market economics does not recognise collective action problems, and if we frame the problem in a conventional way, it will prevent the development of a market in the first place.  Related to this, there is now a deep literature on institutions in economics (e.g. New Institutional Economics), which means that many in the economics profession understand this point (but it is less understood by free market ideologues).  What I mean is that collective action is often required to agree a number of details concerning the architecture of a market before it can flourish.  For example, how do we measure social return?  What should the accounting standards for such things look like?  Do we need to agree new types of instruments or institutions?  How should this market be regulated?  Are there any legal barriers to this market?  These are institutional requirements that cannot be met by individuals acting in isolation and at the margin (which describes the world of conventional free market economics).

There are other, subtler forms of collective action required if the Social Investment market is to mature from its current nascent state.  For example, a report written last year by ClearlySo for the City of London Corporation, noted that one of the things discouraging institutional investors from being involved in this market is the lack of liquidity (i.e. market depth).  Of course, this is a Catch 22 problem (a lack of participation discouraging participation) that is not really about institutions.  So there are institutional and non-institutional collective action challenges.  If the market were to be catalysed by the likes of the City of London Corporation and Big Society Capital, these two could facilitate both the institutional framework and also things like benchmark securities, which would help to encourage liquidity.

"Build it and they will come" from the film "A Field of Dreams"

Once these forms of collective action are enabled and executed, the market should then look after itself and we would expect market forces to work, albeit within the context of a designed institutional framework (institutions should always remain under review of course).  Without these institutional changes, traditional (single bottom line) finance will be locked-in and the financial sector will perpetuate the problem I outlined at the beginning of this blog: our economic system will continue to do an imperfect job of mirroring our values.  Build it and they will come.

The good news is that both the City of London Corporation and Big Society capital are putting resources behind the type of collective action I mentioned above (I have enjoyed discussing it with people from both organisations).  They should both be applauded for this and, having only recently embarked on a journey, their challenge now is to frame a broad and cohesive vision of the destination, and a route to get there.  This would require going beyond conventional free market economics, and enabling the right sort of collective action to ensure the market achieves its full potential of better mirroring our values.  Another way of putting this is that the financial intermediation process would be “democratised”.

To conclude, one of my ambitions in Synthesis is to encourage the economy to better reflect society’s values.  One part of this is about developing a legislative system that enables new legal entities to emerge, which better reflect our values.  Another part is to encourage the development of a Social Investment market within the existing financial system.  I should emphasise very clearly that this is not inconsistent with a broadly economic liberal approach.  In fact, it is better to think of my framework as Hayekian (albeit informed by the new science of complex systems) because it includes a mixture of both requisite institutional formation and individuals responding to incentives.

The corporate world exhibits a wide variety of structures.  Co-operatives and partnerships have been around for a long time and have some well known examples.  The Co-op, for example, was founded in Rochdale as long ago as 1844 and now is represented worldwide.  Goldman Sachs was a partnership for most of its existence.  There are more exotic forms of the corporate beast, such as companies limited by guarantee, industrial and provident societies, friendly societies and, recently made possible by legislation in the UK, community interest companies.

But by far the dominant form of corporate organisation is that of the joint stock company with limited liability.  In other words, companies ultimately controlled by shareholders.  These can range from one person bands to the world’s largest firms such as Google.

Although the concept had been around for a long time, the shareholder company came into dominance in the corporate world in the late 19^th century.  It remains by far the single most important form of corporate structure, even if we count the frequencies of the various structures on a simple head count rather than by value or turnover.

Companies run by managers on behalf of shareholders are coming in for increasing criticism.  In the financial crisis, the value of the equity of many banks collapsed and shareholders were sometimes left with nothing at all.  But in the process, the managers had enriched themselves.  The issue of the pay of senior executives in such companies remains a very live and sensitive political issue.

Is it time to call a day on this form of organisation, and if so how is it to be done?

A lot depends on why we think this particular structure came to exercise such dominance in what we might think of as the ecology of corporate organisation.  Many different forms of organisation compete to be adopted by entrepreneurs setting up in business.  But it is the shareholder company which is by far the most frequent choice.

If we do a simple plot of the relative frequencies with which the different types of structure are observed – even on a simple head count – we observe a highly skewed outcome.  Huge numbers of shareholder based companies, a lot of partnerships, but far fewer than the number of the ‘market leader’, some co-ops, then fewer and fewer until we get down to recent innovations such as the community interest company, with very few examples.

Charles Darwin

Pure Darwinism would lead us to believe that the shareholder company is dominant because it is better suited to the environment, to the ecology of corporate structure.  It is somehow fitter than its rivals.  Selection by fitness, however, does not by itself account for the relative frequencies with which we observe the different corporate forms.

A quite different theory also comes from biology, to account for the frequencies with which different species are observed in any given ecology.  Stephen Hubbell, based at the University of California at Los Angeles, came up with the so-called ‘neutral’ theory, which generates results which conform to the outcome which we observe empirically in ecological systems.  A few species have lots of members, most species have very few.  Exactly what we see with corporate forms.

A plausible hypothesis is that, in any given system, rare species are rare because, for whatever reason, they have not adapted well to their environment.  Similarly, abundant species must have particular attributes which enable them to flourish.  But the word ‘neutral’ in this context means that no species has any special qualities or characteristics which make it more or less suitable to operate in its given environment.  Their relative success or failure is ‘neutral’ to their attributes.  In other words, how a species behaves, what it can and cannot do, is irrelevant to whether or not at any point in time its numbers are small or large.  The outcomes which we observe are the result of purely random processes.

It is a disturbing theory, which appears to defy common sense.  But common sense tells us that it is the Sun which goes round the Earth and not vice versa.  We see the Sun move, but we seem to stay still.  It has the great strength that it fits the facts.  Yes, evolution takes place, but the eventual outcome and the eventual ‘winner’ are determined much more at random than by inherent fitness.

The policy implications of this are important.  If we think the neutral theory applies in any serious way to corporate structures, the way to remove the dominance of the shareholder company is to allow more innovation, to allow different forms to come forward, one of which will eventually replace the dominant species.

Ann is currently Head of Policy at Ealing Council, where she leads on strategic partnerships and multi-agency efficiency projects, corporate policy, and innovation. She is writing in a personal capacity.

During questions at the 21^st Century Policy Development event hosted by Synthesis and the RSA, an observer noted that what I had to talk about probably wasn’t really complexity. In its scientific sense, I’m inclined to agree – but for the purposes of making an impact on public policy, I’m not sure it matters.

I’m interested in the practical application of complexity thinking and approaches to real world problems, particularly those faced in large, challenging programmes of continuous work, like public service redesign.

While systems-thinking has been on the agenda for a while in public services, moving beyond this into systems-doing often remains a challenge. Complexity perspectives have the potential to offer us a nuanced and flexible approach to solving problems by understanding and working with whole systems and networks – but if complexity theory seeks to be mainstreamed within public policy, its tangible, practical applications need to be demonstrated in ways that move beyond the academic and into narratives and demonstrations that people can relate to.

Anyone who has worked on the ‘Troubled Families’ programme or similar, and attempted to get to an understanding of how service for families operate, even at a local level, will appreciate how complex even a single area of public policy and practice can be.

Mapping multiple funding flows in, out, through and between organisations, which fund a vast system of processes and services across dozens of organisations, transferring huge quantities of data, and resulting in continuous interactions between thousands of individuals, reveals complexity at every level.

The whole system can be nearly impossible to map, yet we know that changes to one element of the system impact on others in diverse and sometimes unpredictable ways – whether a change to human components (responsibilities, personnel, requirements), a diversion of funding flow, a change to a process or a changed use of information – and in doing so often have a profound impact on people’s lives.

We’d do well then, to better understand these systems. In an ideal world, we’d be able to make decisions on changes to a service, funding or to processes based on a well-evidenced understanding of the wider impact that might have, given our knowledge of the system that the decision was taken in. Imagine for example, a model that showed reliably what was likely to happen across a range of acute services in an area when investment was made in x early intervention services.

Eric Pickles, Secretary of State for Communities and Local Government

Unfortunately, being able to do this scientifically requires an understanding of how the parts of the system fit together and interact, which most of us simply don’t have at the moment. Complexity theory also teaches us the ideal of total control and prediction is impossible because we cannot predict the effect of changes on such a complex system. However, we can do better than the silo-based approach we currently operate, in which decisions are made on the basis of evidence from separate parts of the system, which is then mixed with experience, expertise and knowledge from years of working within the system. This can be effective but the ability to provide robust, systems-based evidence could add a new perspective to this mix to help effective decision-making further.

On a really basic level, most of us don’t have access to anything like the kind of tech that could help out in comprehending and modelling complex systems, and as long as complexity remains the reserve of those with high-powered technology, its appeal and application will remain out of the reach of most.

Even if we did have the tech, we might not have the right data to put into it. Knowing what’s happening, where and when, and the impact it is having, is vital, and probably the key element in being able to accurately consider how we could do things better in the future; yet it’s too rarely done well. A shift to measuring outcomes indicators (rather than just throughput and output) is occurring, but to apply complexity approaches properly in public services we need to be smarter at collecting and analysing data from key points in our systems, and using the increasing ability of technology to capture and understand system flows in real time. The more this can be developed and supported the more likely we are to be able to make complex systems come to life in public policy. To repeat, Complexity theory tells us we can never achieve a perfectly controllable and predictable system but it ought to help us make sense of, and make decisions within, such a complex terrain.

The systems we operate in often aren’t very neat; they’re the legacy of many years of changing strategy and policy and resulting layered approaches. As long as the funding flows and policy steers that shape service and process design decisions remain unpredictable and disparate, understanding and designing greater coherence in our systems is likely to be limited.

By their nature, public policy and practice systems are also so human-focussed that a large proportion of activity and outcomes are behavioural, and difficult to predict. But while we can’t necessarily model individuals, if we collect enough information about impacts, outcomes and behaviours of people in general in our systems, we might be able to get a clearer view of overall likely impacts and outcomes of changes through a process of pattern recognition.

And it is this very centrality of human behaviour in public service redesign that may offer a complexity approach unique opportunities. The variety of skills, enthusiasm and expertise within public services, and a growing appetite for innovation in a time of unprecedented change, growing demand and shrinking resources, offers an open door to new ways of thinking about efficiency and systems that can be proven to have a positive impact on people’s ability to deliver better services with fewer resources.

Complexity approaches may offer a way to help articulate the issues and opportunities within the systems people operate in, and provide tools to conceptualise and model these vast, complex systems, supporting informed redesign decisions.

In order to really make an impact on the ground, however, they need to be brought into and applied by those with a real, first-hand experience of the reality of what happens on the ground, with sincere respect for those for whom complexity in its most practical sense, is all too familiar a reality in the jobs that they do every day.

If achieved, complexity approaches could help create new understanding and better-informed decision-making, facilitating a practical, positive impact on the way that people receive services.

I spoke last week at a fascinating day on how policy development needs to be rethought, organised by Synthesis of which I am an Associate.  The day made clear that both the techniques now available to us (computer modelling, simulation techniques) and our understanding of the elements of our problems (dynamics, feedbacks, behaviours, networks) suggest that we are making as big a policy shift as when big government first became fashionable in the twentieth century.

Then people believed, from the Webbs to Gordon Brown, that government could solve all our problems and make us be happy.  Now we are more sceptical of these claims, even though we are starting to measure happiness, and of our government’s ability to devise and execute appropriate policies.  Hats off to Matt Hancock and Jesse Norman, MPs who supported last week’s conference and opened and closed it with their own perspectives.

My own contribution to the debate was from my engagement over the couple of decades with infrastructure projects.  I found it hard to stop grinning when the Chancellor, in his Autumn Statement, stated that infrastructure supports economic growth, since this is a case I have been making for more than a little while.  However, the analytical underpinnings of this argument and how it relates to both the financing and the funding of projects is still not well articulated or understood and I talked about some of these issues in relation to investments that I have been involved in, such as Crossrail, High Speed rail, Thames Gateway Bridge (and more).

Successful policy development requires several different perspectives and this was illustrated in the context of security policy as well as infrastructure.  Generating the right analysis is one essential element, but asking the right question is an important starting point, and getting support across the spectrum for a new approach is also key.  The right analysis has to address the right question.  ‘Is this railway worth paying for?’ is a good question and leads to asking who will pay for it and why.  Is it passengers?  Or property developers?  Or does the taxpayer have to cough up for something unspecified, such as a welfare benefit?

Clear questions also require clearly articulated answers and the challenge to analysts and modellers is to provide models that policy makers can understand and challenge.  Models cannot capture everything – by definition they are simplifications.  Are the simplifications the right ones?  Outcomes are inherently uncertain.  Can the model show the likely range of outcomes with any degree of robustness?  Our policy makers need to ask these questions of analysts rather than rely on a black box and their academics and civil servants.

There is a risk that one set of black boxes will be replaced by another set – cleverer ones no doubt.  I hope not.  I myself try to present arguments that have a common sense element but can be backed up by data and models.  I need policy makers and politicians to challenge me and everyone else to make sure I succeed in creating these so that we can have a healthy policy debate rather than a technocratic one.

On Thursday we co-hosted an event with the RSA called “21^st Century Policy Development” (21CPD).  This blog is a sort of follow-up to that event, arising out of a number of the questions asked during Q&A.

What I want to do is to illustrate quite how intractable social systems and the biosphere (and in fact the whole universe) are; and to contextualise what value I believe networks and complex systems add to our understanding (and, by implication, our ability to make good decisions).  There were some questions at 21CPD which hinted that perhaps complexity scientists were seeking to achieve some nirvana of understanding with the right model and right data.  Ironically, the same approach tells us such perfection is impossible – the world is inherently intractable, uncertain, and it is constantly evolving; and human cognition is limited.  My point here is that an approach based on complex systems and networks is a firm step in the right direction if our aim is to improve our understanding of reality.

So how intractable are things around us?

Let’s start off with the agent in our social systems, the human being.  Traditional approaches to social sciences would typically reduce people to over-simplified algorithms of behaviour.  In fact, as we know, in reality people are a messy mix of emotions and reasoning, conscious and sub-conscious processes.  And we know that people are made up of multiple organs, including the brain, that interact with each other – so people can be viewed as complex systems themselves.  Moreover, if we drill further “down”, we can see that people are made up of complex sub-systems, and we can see that the smallest stuff has self-organised in to atoms, chemicals, cells, organs, etc.  We get to the point where we realise that we are merely time-consistent patterns of energy and matter.  This is quite mind-boggling.

Stuart Kauffman, Author of "Re-Inventing the Sacred"

Traditional approaches to social science have tended to over-simplify this complexity through reductionism.  What this means is that people have specialised in particular aspects of human nature (psychology, neuroscience, the blood stream, etc).  As Stuart Kauffman wrote in Re-Inventing the Sacred, a lot of stunning discoveries have come out of this silo-based scientific system, orientated around the idea that you can break something like a person in to constituent parts and then add it together to understand the whole.  But if a human being is a complex system of interacting complex sub-systems, this silo-based approach can only take us so far.  Biologically, everything relates to everything else.

Of course, for those familiar with the weird and wonderful world of quantum theory, the mind boggles at an accelerating rate once we delve into the sub-atomic level.  The notion of subject-object duality is brought in to sharp focus by quantum theorists who have shown that outcomes in their experiments depend on whether the experiment is being observed or not.  And quantum uncertain is one of a number of apparent sources of inherent uncertainty in our universe.  I’ll note two others below.

So much for drilling down in to the human being.  It leads to us to an intractable mess that makes me want to run away screaming.

Now let’s go “upwards” from the human being.  If a person is a complex system, then we can also think of society as a complex system of interacting complex systems.  *sigh*, as my cousin sometimes messages me.  Moreover, it is important not to draw “discrete” boundaries around interacting complex systems – we are not finite, given “things”.  Rather, we are open systems that are constantly being influenced by other open systems.  We don’t just evolve, we co-evolve.

One of the implications of this is that the economy cannot be detached from the rest of the biosphere and treated as if it were a discrete object of analysis.  For example, I have argued elsewhere that we cannot understand the macroeconomy properly without understanding how narratives emerge among groups of people.  This means that the complex nature of human psychology affects the allocation of resources (behavioural economics has not got us there yet).  And to truly understand psychology we have to understand neurology, including how different parts of the brain (including the reptilian, mammalian and neo-cortex layers) mix in a conscious and sub-conscious maze, as well as cognition, and all of the facets of being human.  More generally, the biosphere and the economy are intimately linked such that we cannot hope to understand the economy in isolation.

But, not only are “we” not discrete units, we are also in a constant state of flux.  A number of people in the complexity community prefer to emphasise verbs more than nouns because of this e.g. referring to the process of “patterning” rather than “patterns” to emphasise that patterns exist but they are constantly emerging and changing.  Related to this, in his talk on Thursday, Jamie MacIntosh referred to leadership as a social process, distinguishing it from “leaders”.

So we humans are open systems that are constantly changing (and, together, these should lead us to question what “we” actually mean by “we”).  Indeed, there is also the curious problem of reflexivity, which we have to contend with in our daily lives.  I described reflexivity in a blog entitled Reflexivity and Narratives.  One way of looking at this concept in human systems is that when we interact, I am trying to anticipate you anticipating me anticipating you anticipating me, etc.  It’s an important concept and a second source of inherent uncertainty in human systems.  And, by nature, it is not solvable, it is simply something we have to live with.

We can also see a third inherent source of complexity in the form of emergence, which is also prevalent in human systems.  Emergence is probably the most important concept from complex systems and which, to paraphrase Stuart Kauffman again, breaks the whole idea of the deterministic, clockwork universe.  One important example of emergence in human systems is the evolution and perpetuation of human values.  To understand this, it is important to appreciate that humans are neurologically plastic i.e. our neurology (and cognition with it) can evolve through time.  In fact, when it comes to human values we can see that we influence others’ values and they influence ours – both at the same time.  As some people have put it, we simultaneously create and are created by the rest of society.  Human values emerge and evolve within human systems.

Further-furthermore, we have to contend with the “problem” of subjectivity.  I’d prefer not to delve too far in to philosophy here but it is unfortunately true that there is no objective reality.  Sorry.  Everything is filtered through our own subjective, cognitive lens and we cannot get away from that.  This relates to a point Richard Bronk made on Thursday when he pushed against the idea of data as if it were some objective artefact.  Our models of reality can influence what data we collect and how we then make sense of that data.  So, we have to deal with this pesky lack of (ultimate) objectivity in the worlds we create for ourselves.

We can keep going further “up” from social systems and the biosphere.  For instance, the biosphere itself is not a closed, discrete system.  It is also open, not only to the sun but also to radiation left over from the Big Bang and pesky little asteroids that hit us every now and again.  And, to return to quantum theory, assuming I remember this correctly (my apologies to physicists if I don’t) it turns out that every sub-atomic particle in the universe is related to all the others; and they can (metaphorically) “communicate” at faster than the speed of light (cf the Aspect experiment).

And, finally, it is perhaps worth bringing the agent and the whole system together to contrast the limitations of human cognition against the complexity of the universe in which we are living.  When I think about this I feel like a microbe sat on a flee, which is in turn on a mouse scurrying around a field on this little planet.

To conclude, let me re-iterate why I have mentioned all of this.  I wanted to note many of the legitimate explicit or implicit critiques aired last Thursday and to emphasise that I agreed with their thrust.  Complexity theorists should not sell complexity theory and networks as a toolbox that will move us to a heavenly world of understanding.  These are better tools, they are not perfect.

From my own (subjective) point of view, a complexity perspective helps me in two ways.  One, it teaches me humility because I note all of the above, especially the inherent sources of uncertainty, and it causes me to pause, and to be acutely conscious of how much I don’t know.  This is an irony Steve Broome, Director of Research at the RSA, noted in his presentation on Thursday – the more he became familiar with complexity and network approaches, the more he realised how little he knew.  Second, despite this, I am as confident as I can be that such a complexity perspective is an improvement in how we understand ourselves, our own societies, and the universe more widely.  I am confident because older, reductionist approaches (like orthodox economics) can be reached by constraining a complex system.  This tells me we are not only going through a change in our understanding but we are also experiencing a “meta-revolution” because our older approaches are a sub-set of the new.  At 21CPD, Jeff Johnson emphasised that we are going through a scientific revolution that spans both the natural and social sciences.  The network and complexity approaches emphasised at that event are, I believe, a step in the right direction.

A fundamental feature of 21^st century society is the way in which networks shape and determine outcomes.  This implies a radical shift in the conduct of public policy.  It does not mean ‘no government’.  But it means ‘smart government’.

But the complex systems community needs to recognise what a huge change is required to make that possible.

Governments have certain advantages not available to the other actors in society. They have a monopoly of the use of legal force. They can within certain limits set the rules by which everyone else has to abide. But against these advantages they are subjected to limitations imposed by a variety of forces.

For example, they are largely prevented from retrospective legislation. The tax collection system sets down rules and then allows private sector players to find ways round them. Financial regulation is much the same. Contract negotiations are governed by rules to ensure fairness. And so on. There is something to be said for these restraints and they are deeply embedded.

Add to these questions of propriety the desire for private business to have what it calls ” a stable environment” by which it means laws that it knows in advance and government action based on clear rules. I have never been a fan of this as a principle, because if you can’t handle change and uncertainty I think you shouldn’t be in business. For example, it’s absurd that government is not allowed to take an opportunistic view on the nature and timing of the way it sells debt. IBM sells lots of debt when the market will bear it and very little debt when it won’t. It gives no forewarning of its plans. Government on the other hand volunteers lots of information.

Gordon Brown bought into this idea of transparency and passivity very strongly. The civil service is imbued with it and contains few people capable of doing anything different.

Consider how the restrictions on government limit it from doing things which it would otherwise do. An aircraft manufacturer planning a new model will look around for a launch customer., They seek a big airline which can place a substantial order and which is well respected in the industry. If Singapore airlines chooses Airbus with a Rolls-Royce engine this will influence other less well-respected airlines. It thus makes sense to offer Singapore special discounts.

Tesco opens shops where it thinks it will do well. It then charges what it can get away with in that shop. Most people are shocked when they find out that prices vary between different branches of Tesco, but they then have the choice of accepting it or going elsewhere. Government does not have the option of saying you can use another government.

Whatever, more flexible government and smarter government is more discretionary government.

This is an exceptionally interesting idea it’s going to be hard work getting it done. But here the concept of the Overton window I think is relevant. At any given moment, the “window” includes a range of policies considered to be politically acceptable in the current climate of public opinion, which a politician can recommend without being considered too “extreme” or outside the mainstream to gain or keep public office.

Although network based policy and smart government are well outside the range of current discourse, having outliers who propose things which are too far outside mainstream to be considered for implementation can actually shift the window.