Accelerator Labs: the challenge of engaging the mothership

Chris Barbalis on Unsplash

First move: of antibodies and centrifugal forces

To oversimplify, then, our current pivot can be described as the transition from a largely centrifugal to a centripetal trajectory. It is a trajectory similar to the one described in a magisterial post by Dan Hill when he talks about moving from user centered design to strategic design:

“In Argentina recently, a digital government-led service design approach envisioned, designed and delivered digital driving licenses in 65 days, from scratch. This is extraordinary compared to the comparatively geological pace typically witnessed in policymaking and delivery. But could such processes radically reduce the number of people driving in the first place?” Dan Hill

For us, going “centripetal” means asking more fundamental questions of the “should we be driving in the first place?” type (without, of course, neglecting the importance of doing that got the innovation agenda running in the first place).

Second move (inwards) — focusing on the core

The new phase of our innovation journey has brought a new frame to it — namely, relevance. What we realised is that for many of our country or regional offices, it is still quite difficult to answer two fundamental questions:

  1. Why do we have this particular set of projects at this point in time?
  2. Are our solutions relevant and coherent with the complex problems faced by the country in which we operate? (This is not too far away from a government having to make sense of its current set of policies, say, on climate or future of work as they are dispersed across different ministries and often focused on “quick fixes” rather than systemic solutions).

Second move (upwards): abstraction and creating new meaning

“This is often what we mean by creativity: seeing in new ways, spotting patterns, and generating frames. ” Geoff Mulgan

Our attention was drawn to a particular approach to sensemaking, developed by Axilo. We are now working with them to adapt the protocol to a development context, embed it in our accelerator labs, and, eventually, offer it to our government counterparts. In practice, this would mean that the first step in our engagement process with UNDP programs and partners will be to offer the capability of looking at an existing set of projects and activities, separate the noise from relevant patterns and signals, create new frames and extrapolate actionable intelligence from them. Note that in this process the word “innovation” is hardly ever mentioned — yet another notable difference from our engagement model in the past.

Early draft architecture of UNDP sensemaking protocol
  • Many of the foresight or system mapping exercises we have been involved with in the past often fall short of practical insights into what to do next, once the complexity and interrelated nature of the challenges we have to face has been recognised. The emphasis on sensemaking, as an eminently social and iterative process, partially compensates for these shortcomings. This is not about a consultant or a small group of experts producing an analysis of the current portfolio and then presenting recommendation for action, but, in our case, a whole office (and external partners) having a shared, recurrent experience of reflection and extraction of meaning from a current set of activities by focusing on patterns. If the process is managed successfully, a group can move from “first loop learning” (learning from within an existing paradigm) to creating new categories and models to think with (“second loop learning”, as per Geoff Mulgan’s definition)
Loops of intelligent learning (Source: Geoff Mulgan)
  • The clear distinction between sensemaking as a process and actionable intelligence as an outcome. The latter zeroes in on those decision patterns that we are interested in shifting. If sensemaking allows options and possibilities for renewal to emerge, someone, somewhere, at any level within the organisation has to take a decision to accept, reject or reframe those options. An argument for change has been made, based on learnings from experience. Someone has to respond to that argument. The decision is under the spotlight. This is where learning effects can be accelerated: no more pilots, but genuine experiments, in a portfolio logic. This is also where we can build capacity and organisational muscle to produce compelling arguments for change.
  • The relentless focus on the “why” (“can we get less people to drive?”) rather than the “what”, or “how” of existing projects (“can we make it easier for people to get a driving licences) — and how this relates to the stated intent of the organisation. Being able to reflect on the difference (if any) between original intent and how this was translated into projects on the ground is ultimately a mindset shift
  • The networking effect generated as collective reflection “connects the dots” across organisational silos, allowing for stronger coherence to emerge. For instance, in one of the first field sense-making experiences we discovered that operation of e-commerce centers in rural Bangladesh has not only led to more dynamic economic life there (an anticipated 1st round effect), but also through women empowerment as they have started e-shopping (unanticipated 2nd round effect). This opens the way for a more systemic and concerted programming but also help teams rethink their portfolio from systems’ change perspective.
  • The shift from portfolio as a management/accountability tool to a learning tool. Ever since Panthea Lee’s seminal post on “downstream vs upstream” data, we’ve been keen to distinguish reporting from learning. With sensemaking we are de facto prototyping a system focused on accelerating learning (whilst most of our current systems are geared towards reporting, for obvious, and important, reasons).
Sensemaking session in action in Bangladesh: identifying patterns to create new frames

Third move: building portfolios of learning options

“The important thing for government is not to do things which individuals are doing already and to do them a little bit better or a little bit worse, but to do those things which at present are not done at all” R. M. Keynes

Of course, sensemaking and intelligence are not an end in themselves. And there’s only that much acceleration impact that can be derived by layering and aggregating what is already there. If we want to live true to our promise of being the fastest learning network on development challenges, we will need to develop the capability of building portfolios of learning options around topics that are new both to us and the governments we are working with. Take for example a question like the future of work. Analysis and predictions from experts and consultancies in this area are endless, and endlessly diverging. Governments are sold a variety of quick fixes: from teaching everyone to code to blockchain for traceability. The paradox of the obsession with single point solutions is that rather than providing more options in face of complexity, they reduce them.



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UNDP Accelerator Labs

UNDP Accelerator Labs

Building the world’s largest learning network around development challenges. 91 Labs in 115 countries.