Ian Burbidge

In my previous article I shared some of the assumptions embedded in our legacy approaches to creating social change, grounded as they are in increasingly outdated ideals of delivery, scale, solutionism and paternalism. In many respects this is why change is so hard: it’s not enough to have a critique of the failings of the current approaches, it’s necessary to test out new approaches. But we are having to do this while working within a failing paradigm, and so we come up against a system that will fight to preserve its known and comfortable approaches to change. This isn’t to deter us from testing new ways of working, though, but it is to recognise the challenges we face in generating evidence to show that not only are old ways ineffective, but also that new ones can be better for those we are seeking to serve. 

Our design-led innovation programming is intended to generate this evidence in the Humanitarian sector. More than word-bingo, it is an approach to programming based on a ‘test-learn-adapt’ approach that works with – and is led by – local communities. In other words, we don’t define up front the clear outcomes that the funding – and therefore also our programmes – will deliver. This is because in a complex environment or context such certainty is simply not possible. To promise otherwise is to pray to false gods. 

We’ve seen that traditional linear, outcome-led programming lets us down: if we start with a promise to deliver an intended outcome we are doomed from the start and anything that follows will be sub-optimal. When we are incentivised to deliver the outcome we are blinded to any other possibility – or necessity – which might arise as we engage with the challenge and learn more about it. Any evidence to the contrary is ignored as it don’t support the successful delivery of the outcome, even if now it’s clear the pre-defined outcome isn’t the right one: we have money to spend and donors to appease in doing so. As a result, we are likely to make the situation much worse. 

The lack of logical, linear steps through which to implement the plan are a casualty of this innovation-led approach. Instead of linear programming we do what human beings have always done when they have sought to understand and make progress in uncertainty: take a step forwards, see what’s different, see what’s being learned, and use that new intelligence to inform the next step. We start from the possibilities we can see in the present. 

Another casualty of linear programming when we adopt a more innovative-led approach is the traditional notion of scale, because it’s predicated on their being a single, best solution for a given problem, which can then be ‘lifted and shifted’ to other places with the same problem. Design once, implement multiple times, and with each additional deployment the cost of developing the solution reduces. Yet given that we are not able to define and deliver a clear outcome due to the complexity of the situation, and because this complexity is context-dependent, what works in one community or setting will, in all probability, be completely unsuited to another. What we can scale instead is great questions, and we can spread our current best answers to those questions, not in terms of ‘what works’ as an outcome but rather more in terms of what works in terms of process. It’s the process – the approach – that is scaleable because it can be adapted to different contexts. 

Our programming, therefore, is more likely to be effective when it is inquiry-led and focused on intent: the situation / problems that we want to address. In the case of the innovation programming in South Sudan and Guatemala it is about empowering communities to respond to their own needs, develop their own approaches to resilience and be as prepared as possible for the inevitable crises that will emerge. To design and deliver a programme like this would be to impose our western-thinking and ideas – neatly captured in outcomes – on local communities. Another form of colonialism, at its worst, rendering populations dependent on our funding and expertise and not liberating their talents in pursuance of locally-defined objectives that are in turn a response to community needs. Needs which no one else can truly understand because we are not of that context. I’ll explore what this looks like in practice in my next article.