If we don’t know what will work, then how on earth do we work out what to do? Traditional approaches to change management assume there are a set of rules which will predict what will work, and if we follow these then, surely, we will know what to do. However, these traditional approaches are woefully inadequate in the face of many of today’s challenges; challenges such as climate change, violent extremism, and the revolution that is digital technology. These are the sort of challenges that don’t stay ‘fixed’ but need constant work, the sort of challenges where the problem is difficult to define and the solution never simple and almost always unknown, the sort of challenges that need ‘adaptive’ forms of action and planning.
The idea of adaptive forms of leadership, planning and management has been around for a while. In the development sector ‘adaptive planning’ has become a common phrase, whilst the rhetoric of working in a VUCA world (volatile uncertain complex ambiguous) has been in military and corporate parlance since the 1990s. Whatever the particular phrase you use, the emphasis is similar, and that is the need to be able to adapt, to have flexible plans and flexible leaders, to recognise that events outside your organisation or programme may (will) shift and change and, however well laid your plans are, they will (probably) be disrupted. But whether you are in international development, or running a giant corporation, or sat within the British government trying to figure out what BREXIT means, there are a lot of things which make it difficult to work in an adaptive way. Whether these are demands for a long-term plan, the need to transparently show exactly what has been spent and the impact it has purchased, or the fear of a loss of shareholder confidence, we often find ourselves facing new and unpredictable challenges, whilst being asked to provide predictable, certain solutions. Understanding some of what gets in the way of ‘adaptive’ forms of planning and leadership can help us unlock how to turn the idea of adaptive into the practice of adaptive. And some of the problem is Isaac Newton’s fault.
When Newton’s apple fell, it gave us not just gravity, but a whole way of knowing the world. Newton’s laws turned the unpredictable into the predictable, by showing there is a set of observable and objective laws which link cause and consequence. Armed with this, we were able to unleash a revolution in understanding that changed the world– from steam engines to skyscrapers to jet propulsion. These changes were driven not just by Newtons’s laws, but also by the logic of cause and consequence, of inputs leading directly to outputs.
In all the excitement, Netwonian principles came to dominate not just our understanding of the physical world, but also of the metaphysical one. Gradually the principles of objective truth and observable forces, and the notion that problems which could be divided up into their constituent parts and actions which had direct consequences, were applied not just to the world of things which can be touched and measured, but also to world of the things that can’t be. It is this Newtonian approach, of seeking the fundamental rules that will make change predictable, which sits at the heart of traditional approaches to change management. It gives us our faith in the orthodoxy which has become the project plan, the logical framework, or the solution map. There is clearly nothing wrong, and a whole deal right, with a Newtonian approach. However, there are also times and contexts when it stops working, times when we need another approach.
These are times such as when we are asking “is this a good school?”, “are my children happy?”, “how do we change patient’s expectations of their doctors?”, “how do we engage our employees more?”, or “what will give investors more confidence to invest in agriculture in Africa?”. Often these can feel like intractable issues, where we have tried the ‘normal’ approaches and still things aren’t shifting in the ways we hoped (or aren’t staying ‘fixed’ when we thought we had fixed them); times when we don’t quite understand the problem and there is a lot of debate on what the solution might or could be. These are times when cause and effect are highly unclear and keep changing.
Complexity science has developed as a way of working with these sorts of issues; issues which are emergent, ill-defined and seemingly intractable, the sort of issues which don’t stay solved, but require ongoing work. With over 30 different branches, from the mathematical and the computing, to soft systems, Human Systems Dynamics, and a host of organisational development approaches– complexity science is, in itself, complex. Fundamentally, a complexity-based approach demands that we let go of the idea of change as predictable, and start working with the emergent nature of change.
But what does all this mean for those of us with practical concerns? Here are three ideas which apply to our work at Wasafiri and help us act in adaptive ways
Make a plan, so that you can change it– for most of us, our world of work asks us for plans. A good plan helps us get started, it helps us develop shared intent between different people about what we are committed to, it helps us bring together lots of different actions into combined effort, and it helps us make decisions quickly. A good plan is a means to an end. The problem with plans occurs when sticking to them becomes more important than achieving whatever change we initially set out to create. And this is often what happens. The plan has set the budget, and we must stick with the budget. The plan has set out the link between the outputs and the activities, and so we must stick to the activities. The plan took so much time and effort that we can’t face revisiting it. And so we stick with a plan that has ceased to be fit for purpose. But there is another way. Adaptive plans (sometime called strategic intent) set out how to get started and how to review how we are doing, they contain ideas for activities and outputs and the scope to test and scale. A good plan knows it will be changed, a good plan helps us expect and adapt to change, even when we have little idea of what, exactly, will change along the way. To work adaptively we need to work out when and how to review, change and recreate the plans we make.
Keep revisiting how you understand the pattern you want to change– when we are working with complex problems or opportunities, we are effectively finding ‘patterns’ which we want to either change, or embed and expand. It could be a pattern of violent extremism that emerges in a Kenyan coastal town, or a team where you want to build more trust between members, or perhaps a community where there is a growing sense of neighbours talking with one another and you wish to encourage it. Whatever the pattern, there will be different views on what generates it, and whether it is to be enhanced or disrupted. As you work with it, the pattern will change, and in ways no one has predicted. Therefore, if you are trying to work in an adaptive way it is not enough to revisit the plan– you need to keep asking “what does the pattern look like now?” or “how has the problem shifted? And what does that mean we should do next?” (which might not be what you had originally planned).
Focus on the adaptive capacity you are developing, rather than the solution you are engineering– predictable change takes us from one ‘state’ to another ‘state’, for example, I want to be 10lbs lighter, we need an A&E team who can see 20% more patients an hour, we need a distributor for our fantastic widget in Tajikistan. This sort of change is fine for predictable problems, where the desired state is clear and measurable. But, as previously discussed, there is a different sort of change – the sort where the problem doesn’t stay ‘solved’ and needs constant work. I want to maintain a lower weight, we need an A&E team who are resilient and can manage changing capacity demands, we want to develop a good market for our widget in Tajikistan. When the change you seek is less of an end state and more of a different way of being, then what really needs developing is not a single solution but ‘the adaptive capacity’ of the system you are working with to keep changing. If we take the A&E department, we could give them an extra doctor and she can see more patients, but if that is all we do then what happens when the weather turns cold and even more patients arrive? Or when the paediatric ward is full and not taking referrals and so more people turn up in A&E? Or the local GP surgery can’t recruit and so is short of appointments? Or the increase in doctors creates more demand for nurses, but there is no more money for nurses and so patients wait longer? Or… any number of other scenarios. What we need to do is not just ‘solve the problem’, but recognise that, at some point, another challenge we can’t predict will come around the corner. So, has the way we have solved the initial problem enhanced the system’s capacity to adapt in the future? Instead of just appointing another doctor, maybe we work with the medical staffing team to look at how they predict patient flows, or support better information flows between departments and primary care and hence for the local GP to run a surgery in A&E. Working adaptively means recognising that the pattern we are trying to change is a product of a set of complex interactions and it is these interactions we really need to act upon.
Breaking away from the comfort that, if only we can be as clever as Newton, then all forms of change can be predicted and controlled can be a scary thing. But how well is this approach really working for us in the face of the significant challenges we face in our own lives, organisations, and the world in which we live? Maybe the risks of sticking with what we know might just be greater than trying something new, even if we are not quite sure what will work?
The ideas in here are built on those of many clever people (including Newton) special mention goes to the Human Systems Dynamics Institute