Complexity in Reality

by Ann Griffiths

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.

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.