I think Jean is great. She will be talking about her her book, “Embracing Complexity” and experiences as a manager, consultant and academic in relation to Complexity Theory and what it means for managing organisations.
This is one I don’t think you should miss.
The evening will start at 18:30 for a 19:00 start.
Meeting Title: Embracing Complexity: Adaptive management in a volatile and complex world
Presenter Names: Jean Boulton
Date: 24 April 2017
Time: 18:30 for a 19:00 start – 21:00
Venue: Atkins, 500 Park Avenue, Aztec West, Bristol, BS32 4RZ
A couple of weeks ago, we were very fortunate to have Jean Boulton come to talk to us at Systems Thinkers Anonymous. These are some rather belated reflections on what was an excellent session. It was a real thrill and a pleasure to have Jean come. A real coup. For anyone who doesn’t know who Jean is, have a look at this previous post. In person, she is as charming as she is formidably bright and enthusiastic about her subject. Happily for us, that subject is directly relevant to our work.
I’d read Jean’s book “Embracing Complexity” earlier in the year and had heard her talk at the SCiO Winter Open Meeting, so was reasonably familiar with her approach and views on how complexity theory can help us better manage our organisations. It’s a different kind of approach to the prevailing school of thought in management and for me, it feels very right.
An alternative to Reductionism and Determinism
We had about an hour and a half with Jean in total. She began by giving us a 15 minute whirlwind tour of complexity theory and the differing view it takes from linear scientific approaches, such as those influenced by Newtonian Science, before having an informal discussion. Not that Jean says there’s anything wrong with linear approaches, there’s a time and a place for everything. Holding that linear cause and effect view of all actions having equal and opposite reactions can lead us into trouble when we face complex problems in open systems though, and those are the types of problems we’re faced with in organisations everyday. In complex environments, what emerges when you take action is unpredictable and nonlinear. This is the world of Volatility, Uncertainty, Complexity and Ambiguity (VUCA). Our world.
To set the scene, I’ll recount the essential points of Complexity Theory as an alternative to the prevailing reductionist and deterministic approaches, before then giving my own reflections on what I’ve personally taken from it. Jean began by differentiating between two differing scientific viewpoints that have converged to dominate the management of our organisations, markets and societies. Those being the Newtonian, mechanical view where everything moves in a predictable, deterministic fashion, and Equilibrium Thermodynamics which see most situations as near equilibrium. This is extended to the belief that when things are close to equilibrium we can predict what will happen next as things tend to move back to equilibrium.
Jean argues that the mechanical worldview, a deterministic and reductionist one, has led to too high an importance being placed on design, control, prediction and measurement. It has come to dominate the idea of what is professional. Historically, in the West, we have been conditioned to believe that predictability and therefore control, measurement and structure are ‘scientific’ and hence professional ways of working. Management and professionalism have come to be about being “scientific”, where scientific means being singularly reductionist to the exclusion of also being systemic in enquiry.
A reductionist view believes that to solve a “big” problem we should divide it into smaller problems that can be solved. The solution to the bigger problem is therefore the sum of the solutions of the smaller problems. This is logical and seductive in its simplicity, but is actually simplistic, as it does not address the interactions between the problems. System Thinking still tends to involve dividing big problems up, but pays close attention to the relationships between the smaller components.
Reductionist and deterministic views of organisations assert that;
They behave like machines and are predictable.
The things that are important can be measured
Departments can be dealt with independently.
Change can happen top down
One method or “best practice” can work everywhere
The future is predictable and follows from the past
People behave rationally and like parts of a machine
Measurement leads to control and clarifies what to do next
Projects, functions, groups can largely be treated independently of each other (and indeed this is the best option) and can be made to follow a controllable process
This is the world of Budgets, Project Management Offices, and Strategic Visions of the future. In “machine thinking”, there is also an implicit assumption that organisations cannot learn, adapt, that nothing new can emerge and that the future is just a continuation of the present.
So what is Complexity Science?
To quote Jean:
“Complexity science is the study of the evolution of systems which are open to their environment. It explores how the reflexive interdependence of constituent elements leads to self-organisation and emergence of new characteristics in a way that is shaped by, but not determined by history.”
Jean explained to us that Complexity Science has stepped beyond Newtonian and Equilibrium Thermodynamics views of science and offers an alternative. It is grounded in Evolutionary Theory and yet emphasises that “survival of the fittest” is more like “survival of those most able to prosper in a given context”. It emphasises that what emerges is very much context/environment dependant. That which is a strength in one context, may well be a weakness in another, and the nature of contexts and environments are often beyond our control. They change in ways that are not random but not predictable either.
Complexity Theory says that the world and human systems and economies and organisations are types of ‘complex systems’, and that they behave more like living organisms than like machines. In a world that is increasingly fast-changing, things often do not go to plan, people and situations are individualistic, many things impact on each other, change can happen radically and rapidly. Thinking you can control things when you cannot can create more harm than good and lead to unintended consequences.
What does this mean for management?
Jean said that in her experience, public services are too often managed towards “economies of scale” and efficiencies are sought through hierarchical standardisation, and top down, “Command and Control”. She expressed her belief that we over measure organisations in the belief that it’s the right, professional thing to do, but the learning from these measures does not necessarily lead to better outcomes. She referred to the example of the British education system, which has been increasingly managed like a “machine”, with everything possible being measured, yet literacy and numeracy rates among British children have been decreasing and are right at the bottom of the pile compared to other developed countries. Something important is being missed.
Jean feels we need to work to understand what really matters to our customers, patients, service users, stakeholders, society, rather than simply measure what can be measured. She believes much more emphasis needs to be placed on “bottom up”, localised organisation rather than top-down machine like focus on “economies of scale” – albeit situated within clear principles and intentions, with strong review, learning and sharing processes.
So, what do I make of all this?
By and large, this all rings very true for me. I don’t think it’s a black and white case that we should forget about scientific reductionist and deterministic approaches to management and be purely systemic, as we’d end up in quite a pickle. And indeed, as Jean would point out, complexity thinking is a middle ground between thinking we can predict and control everything and thinking we know nothing. Complexity thinking is not advocating a laissez-faire approach – rather it is bringing our attention to the fact that many things are interconnected whether we like it or not – and to ignore that can bring failure.
After all, we have an enormous amount to thank scientific reductionist approaches for. I think the point though is we shouldn’t be blinded by their brilliance and in honour of their successes ignore their deficiencies and apply them inappropriately. There is a time and a place for all methods, including measurement. We just need to be careful and considered in our approach and try and ensure that the approach to measurement is fit for purpose.
As when anyone tries to argue against a status quo, in our discussion Jean took a fairly hard stance against the reductionist and deterministic approach and I know a couple of group members found this a difficult view to agree with. I think that was probably a symptom of us not having much time with Jean, as having read her book and having heard her talk more extensively, I know she values these approaches. She is after all a physicist by training. It’s just a question of finding the right balance and using the most appropriate approach for the situation and context we find ourselves in. I think it can also be quite shocking to hear someone say something negative about a “scientific” approach to management (or at least to question which ‘scientific approach suits the complex social world). I think the point though, is that there is nothing scientific about using a “scientific” approach inappropriately. And of course, complexity theory itself is a science!
Often, the things that really matter can’t be easily measured quantitatively
Something that stood out for me from Jean Boulton’s talk was that sometimes, the things that really matter just aren’t measurable. Or at least, are very difficult to define, monitor and measure. I think that’s probably the case with patient outcomes and it’s something to think about. There was a feeling among some in the group that Jean’s approach is one that dismisses measurement altogether. I’m don’t think that’s correct. I believe that for her it’s more about stepping back from measuring absolutely everything we possibly can (and then doing nothing useful with the data, apart from beating people with it) and instead really understanding what’s important and it may or may not be possible to measure that. That’s my interpretation, and also my belief. We need balanced approaches that rely as much on qualitative feedback as quantitative measurement. We need ways to spot and then monitor emerging trends and deal with multi-causal inputs and interconnected outcomes. Sounds difficult, but to me, it seems that to aim for anything less would be to let ourselves and those we serve down.
The question that “the things that really matter are not always easily measurable” is one that seems less relevant in business. That is to say, it is still true, but I wonder if it matters as much. In business, you gauge whether customer outcomes are being fulfilled by their willingness to pay you for your goods and services. It’s just so much harder in public services, where that customer supplier relationship and the direct payment for services doesn’t exist. Please don’t read that as a suggestion we privatise and introduce direct charging in healthcare services, it absolutely isn’t, it’s just a recognition of how difficult our job is in identifying and then knowing if we’re fulfilling the right outcomes for patients. Feedback may be more important than direct measurement, and the best feedback comes from open, honest and direct conversation. We need to be sure we are we having those conversations. Even then, cause and effect are often hard, if not impossible to attribute in our complex multi-causal world. Being too simplistic about what is measured and what is assumed to cause what, can not only waste money, but result in a dysfunctional “system” and unintended consequences.
We need to pay attention to context and complexity
Another point I took away from Jean’s talk was that the approach you use, hard or soft, tight or loose, reductionist or systemic depends on the stability of the environment and the degree of control you have. We need to ask ourselves where we sit on those continua. How Volatile, Uncertain, Complex and Ambiguous is our commissioning world? The approach, tools and methods we pick for doing commissioning will be influenced by the answers to those questions.
I think the answer to this will be constantly changing. I mean, even in my commissioning role and in the context of our organisations, some things are relatively clear, constant, simple and predictable, while others and most certainly not. Even then, these can quickly and easily flip and change to being more or less stable states. We need to be open to the possibility of change in our environment and honest about our ability to predict and control it.
Not only provoked, but also inspired
So taken were some of us with what Jean had to say, that we’ve been inspired to set up a small sub-group to work on a project together. We were particularly taken with the idea that “sometimes, the things that really matter can’t be measured”. This made us wonder what it means for us as commissioners and in particular, what it means for the Commissioning for Outcomes agenda.
We have resolved to write a paper titled something like, “Commissioning for Outcomes – Using systems thinking to think about how to do it.”
Ultimately, I think Systems Thinking, as a complementary approach to Complex Systems Thinking is well placed to meaningfully support commissioning for outcomes. After all, the task at hand is to design and configure a system that has the capability to deliver the defined outcomes. Initially though, we just want to think about what it means and how to do it, and good quality literature and evidence on the subject appears to be rather thin on the ground. Questions we’ll be looking at include:
What does Commissioning for Outcomes mean?
How do we go about deciding what outcomes are important?
And if they can’t be easily measured quantitatively, how do we know whether they’re being achieved?
Even if we can measure outcomes and know they’re being achieved, can we attribute that success to any particular interventions? How do we approach the difficulty of proving cause and effect in this non-linear complex world?
We plan to use the Systems Thinking tools and approaches we’ve been learning about to look at these questions. Thank you to Jean, and watch this space!