Giving Compass' Take:

• The Rockefeller Foundation co-hosted Innovative Frontiers of Development, where they gathered insight on how to achieve systems change through data-driven practices. 

• How are you approaching systems change in your philanthropy? Is data driving your decision-making? 

• Read more about the roots of philanthropic systems change. 

Earlier this month, my colleague Matthew Bishop and I co-hosted a wonderful group of thinkers and doers at The Rockefeller Foundation’s Bellagio Center in Italy. We explored the Innovative Frontiers of Development with a focus on achieving 21st Century Systems change. The ideas flowed through plenary sessions debating our biggest political challenges and in smaller breakout groups shaping specific 30-day deliverables and projects.

This year I’ve been quite focused on the application of data science to realize the Foundation’s vision. With that lens, I heard notes throughout our Bellagio discussions relating to data. They helped me see how data can help overcome many challenges in systems change work. In particular, I saw the importance of data-driven approaches to increasing clarity, adaptation, and innovation in systems change efforts.

Clarity by seeking measurable goals

Those advocating data-driven approaches for systems change often chant “if you can’t measure it, you can’t improve it” only to be rejoined by those dismissive of such approaches with “what matters can’t always be measured”. What really matters in systems change efforts is that people mobilize to common goals, or at least they understand each other’s goals.

Adaptation through monitoring and learning 

No one fully understands a system or can predict how it will change. We are all crossing the river one stone at a time. Having a data-driven strategy allows you to be specific in what you’re trying to achieve. You can then more frequently and precisely test and improve your approach. You can take more risk with your strategy because you have broken your plans into more manageable and measurable steps, allowing for course corrections before it’s too late.

Innovation from outside our current frame

The traditional approach to big scale change efforts is to create a logic model based on a few hypotheses. We then invest in data gathering and monitoring based on those hypotheses.

Read the full article about driving systems change with data by Zia Khan at The Rockefeller Foundation.