Forging Common Ground – Series of Oxford Student Insights to the Skoll World Forum 2017.
MBA Candidate 2016-17, Davidson Edwards, at the Saïd Business School gives his perspective on the Skoll World Forum session “Data-Driven Models for Change”.
As I pushed open the doors of the well-lit lecture theatre and entered into the business school corridor, my mind ran busily over the last session’s insights. I’d just listened to a panel comprised of Jessi Baker, Ania Calderon, Sarah Jakiel, Oren Yakobovich and Ma Jan; moderated by Jake Porway. Each panelist was a change-maker and innovator, leading an organisation that leverages data-driven models to tackle pressing social problems. Their selected mission ranged from combatting modern-day slavery, as with Polaris, to validating the ethics of supply chains, as with Provenance, to exposing producers’ non-compliance with environmental standards, as with IPE (Institute of Public & Environmental Affairs).
The thesis behind their session was simple: without the necessary data, we cannot even begin to address these massive problems. This fact is well evidenced by Polaris, whose analysis of 33,000 cases of human trafficking in the United States has revealed 25 predominant types, each with their own business model and network of stakeholders. Furthermore, with these insights, partnering law enforcement and non-governmental organisations are now able to execute targeted interventions and more effectively save lives.
As I sat in the lecture hall, I was both excited to hear of the progress and troubled by an unsettling question: “have we only started doing this recently?” You see, an estimated “21 million people worldwide are victims of forced labour” (Unseen, 2017), so given that cluster analysis was discovered in the 1930’s (Driver & Kroeber, 1932), I’d assumed it had long been thrown at the issue. But after listening to Ania talk about Open Data Charter’s challenges getting governments and organisations to share data, or even agree on standards, I began to empathise with the systemic nature of the problem. As emphasised in Atul Gawande’s moving opening plenary speech, the problem was not discovery, but delivery.
To lend jargon from Saïd Business School’s Strategy and Innovation courses, the ‘nascent space’ that is data-driven social impact, has yet to agree on a dominant model. We have yet to figure out how to incentivise governments to share their data with organisations, or what standards social impact organisations should adhere to, or how to provide the mass of human capital necessary to make data-driven impact commonplace. But the power of viewing the problem through this lens is that we already know how to deal with nascent spaces. We prioritize collaboration over competition and share lessons learnt, we set universal standards to allow efficient transactions, we consider the landscape as a network of actors with individual motivations, and we work to build up complementary resources.
Thankfully, the panelist session highlighted efforts in this direction, Open Data Charter has gotten over 70 governments to agree on standards for publishing data (Open Data Charter, 2017), Polaris is partnering with Mexican organisations to curtail sex trafficking across the border, Videre Est Credere sources data from various actors with various motivations and factors this into its data checking process. And efforts such as Skoll’s organisation of this panel, serve to move data-driven models away from the early adopters to the mass of social impact leaders taking on today’s pressing problems. There is much left to do but these valiant efforts show significant promise.
If our ‘impact motive’ can mirror the ‘profit motive’ in capitalist markets, then our collaborative efforts should make well-thought-out, tech-enabled approached to solving social problems the norm, in coming years. I’m eager to see the development of this space and play my part.