For the last two years we’ve been experimenting with a variety of methods and approaches to development that were, up until recently, entirely new to us – from gamification to open policymaking, from behavioural science to user-driven innovation, from design thinking to micronarratives and real time monitoring.
In total, we ran around 60 interventions following a portfolio approach, the assumption being that some high risk interventions would fail while others might lead us in unexpected directions.
We are about to embark on an independent evaluation to see whether our initial hypotheses were correct.
While we cannot claim that our early work was totally exempt from pilotitis, we like to think that we set the basis for taking our innovation early work to the next stage – and the organizational learning that goes with it.
And this is where we are encountering an interesting challenge. If we follow the common innovation parlance, it is time for us to focus on “scaling up” (or “scaling out”) – with an implicit (and sometimes explicit) expectation that this means going bigger – investing more money, replicating one success to more countries and cities.
We found this type of linear, manufacturing-style approach of running-one-good-project-and-then-exporting-it-to-someplace-else not in line with some of our own experience in applying complexity science in projects:
- Micronarratives in Georgia: How to collect feedback from citizen experts
- Storytelling gets it due: Micro narratives provide an in-depth look at society
- Real time feedback loops in action!
As Anna Davies at the Young Foundation put it:
“… the concept of scaling has strong connotations of standardization. It has its origins in manufacturing, where the aim is to achieve economies of scale, by spreading fixed costs across more units of output. But in the messy social field, the potential for standardization is more limited. Here, concepts of reinvention and adaptation will be at least as important, if not more so, than standardization. Social outcomes are not products that can be easily made to formula and packaged. This is especially clear in the context of innovation in public services.”
To make an analogy, Galapagos finches didn’t get a memo one day instructing them to come up (or scale up) to 17 different beaks that will allow for a more efficient food gathering, but the different beaks in 17 different types of finches evolved through time and depending on where different finches lived and what type of food they eat.
In our practice, we are increasingly learning that to be effective, we need to spend far more time ‘listening’ and sensing where the system is and where it is moving to (some would call it monitoring), with constant probing (or prototyping) as a way to understand the issue better and inform our next move.
Our experience seems to chime in with others’. Paina and Papers put it in their analysis of scaling up efforts in the health sector, we need to shift “from the current models around scaling up .. which revolve around linear, predictable processes, to models that embrace uncertainty, non-linear processes, the uniqueness of local context and emergent characteristics.”
Similar considerations emerge, to a name a few from Lant Pritchett’s work on systems thinking and education and institutions and isomorphic mimicry, Owen Barder’s lecture on applying complexity theory to international development and Duncan Green’s reflections on redefining project design.
Where to start if we want to develop something akin to evolutionary principles to re-frame the approach to growing successful interventions?
Our plan is to bring together players from cognitive and complexity science, biology, design and development practitioners to compare notes on how they look at “scale”, but also, importantly to answer some very practical questions, such as:
- How to set up a project management system for development projects that mirrors evolutionary principles of variation, selection and adaptation?
- If we were to design a “scaling up” fund for development, what criteria would we use to stay away from the “replicating best practice” curse and adopt evolutionary approaches?
- How can we design an intervention that helps us move from rhetoric to action on feedback loops?
If you are interested in joining the journey, please get in touch.