The abrupt closure of USAID is an extreme example of the volatile environment in which NGOs and activists work. Jonathan Roberts writes that measuring impact might help, but a total focus on evidence and measurability brings pitfalls. Doing good, for him, is both an art and a science.
Private action intended for public benefit – let’s call it “doing good” for short – has long been at the core of societies, religions and human activity. We give it names such as philanthropy, charity, voluntary action or, more recently, social entrepreneurship. And perhaps for just as long there have been debates about how to do good well. Back in the first century CE Roman philosopher Seneca had a dim view of anyone who sought to gain from an act of charity – it was “a disgraceful usury”. In Victorian London, intellectuals sparred with each other about how best (and most scientifically) to support the poor.
The arena of “doing good” is moving through a particular moment of disruption and fierce debate. Such disruption is partly due to the volatile environment in which NGOs and activists work – the abrupt termination of USAID funding in the last few weeks being an extreme example. Just as such funding disappears, it can feel as if the demands upon non-profit organisations and social enterprises are accelerating. And, as in most industries, fast-paced developments around technology and AI create ambiguity and opportunity.
But much of the disruption lies within the process of “doing good” itself. New ideologies and perspectives challenge the alleged inefficiency of traditional charity and philanthropy. There is strong emphasis on maximising the positive social impact of our altruism through techniques of scientific evaluation, probabilistic calculation and a laser-like focus on outcomes. Business and market practices are increasingly introduced to the domain of doing good – from organisational processes such as strategic planning, to commercial income streams, to complex financial arrangements such as impact investing, venture philanthropy and blended finance. Taken together, these focuses on science, measurement and market approaches represent an instrumental turn in doing good – a focus on refining the rigour and efficiency of the techniques we use in order to meet clearly defined benefits for society and the environment.
The transposition of such processes into the sphere of “doing good” is more than just the addition of a new way of working. It’s an institutional shift that disrupts existing arrangements and assumptions. A long list of oppositional archetypes or identities can be described between the new and the old ways – calculation versus empathy, efficiency versus care, competition versus collaboration, quantifiability versus intangible quality, donor versus investor. When contrasting institutional values, processes and identities crash together in this way. It’s disturbing and destabilising. But there is also rich opportunity for new combinations of innovative practice to emerge. In the middle of this turbulence are frontline practitioners – whether philanthropic funders or non-profit leaders and staff – who must navigate competing claims about techniques, methods and values.
At the heart of these debates are two simple questions around the means and ends of creating public benefit. Are these new ways of thinking and doing better means of meeting our desired ends (in other words the public benefit that we wish to attain)? And, even if they can be regarded as better means for achieving those ends, do they create any negative effects along the way that we wish to avoid? In other words, do the means get in the way of some other desired outcome?
Answer to these questions, when trying to create public benefit in complex social systems, is predictably not straightforward. Much will depend on context. Can we purposively use markets as a means to do good? Yes, it is clear that we can – but only in particular circumstances, and with particular guardrails. Is increased focus on evidence and measurement likely to help us to achieve the social impact we desire? Yes, of course.
Being more rigorous in understanding our impact, and learning therefore how we might improve our practice, is a very good thing. But we need to beware the pitfalls of a total focus on evidence and measurability. Not everything good is measurable, and not everything needs to be measured. Should social innovation be strictly evaluated? On the one hand, yes – because we want to know what works. On the other hand, no – excessive measurement and specification may constrain civil society’s “creative chaos”, a term used by political scientist Ralph Dahrendorf to describe the generation of ideas outside the realms of the market and state.
By focusing primarily on interventions that can be quantifiably measured, we risk narrowing our field of vision to fragmented projects, rather than to large-scale social change and structural transformation. The means can begin to dictate the extent of the ends that we seek.
Ultimately there are no simple answers here. Finding the best way to do good is an art and a science. It depends on the field we work in, the social or environmental problem we are fixing, and the people we are trying to help. It depends on the nature of the intervention that we are deploying. Beyond these technical considerations, it also depends on our definition of our ends – in other words, our sense of a just society. How we judge our means will depend on how we understand our ends.
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- This blog post represents the views of the author, not the position of LSE Business Review or the London School of Economics and Political Science.
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