High quality development data is a must for development impact
We know that high quality development data is the foundation for meaningful policy-making, efficient resource allocation, and effective public service delivery. Unfortunately, even as new technology makes more data and wider uses of data possible, there are still many blank spaces on the global data map. A paper by my colleague Umar Serajuddin et al. (2015) describes this phenomenon as “data deprivation”, finding that as of just a few years ago, 77 countries still lacked the data needed to adequately measure poverty. What’s worse, data is often most scarce in the areas where it is most desperately needed. For one, the scarcity of individual-level data on issues like assets and consumption severely curtails our ability to make decisions to reduce gender disparities. Similarly, despite the urgency of the need to manage climate risk, significant voids remain with regards to climate data, such as impacts on freshwater resources. Education, health, food security, and infrastructure are just a few of the many other areas where more and better data is needed to deliver progress.
So what’s to be done? Looking forward, I propose three data priorities, which we are working to put into practice.
We need to focus on both the fundamentals and the frontier
While I share the data world’s excitement about the latest shiny (or Shiny!) object, I’m convinced that the fundamental building blocks of development data – civil registration and vital statistics, other administrative data, household surveys – will always be a critical component of how we work to improve the lives of people around the world. That said, there’s also a huge amount of potential offered by new technologies and new sources of data that didn’t exist before: they can help us save time, increase accuracy, enhance precision, and understand and manage our world in new ways.
That’s why, for me, the real excitement is about integrating traditional sources of data like household surveys with new and innovative sources of data such as geospatial data, satellite imagery, mobile device data, and data from social media. This requires us to push the frontier by increasing our own expertise in new types of data, skilling up in data analytics like machine learning, and leveraging collaboration with the private sector, while also maintaining our focus on capacity building in client countries to promote high quality public-sector data.
We need to balance data profusion with data protection
A lot has changed in the data world since the World Bank threw open the doors to its data almost a decade ago. Since the launch of our Open Data Initiative in 2010, we have seen huge increases in both the number of indicators we make available as well as the global consumption of our data. We haven’t been content to rest on our open data laurels either – we’re opening up our analytics by sharing our code and algorithms to reach our ultimate goal of open knowledge for development impact.
But I believe in a world where the profusion of data goes hand in hand with effective data governance, including the proper protection of personal data. Data privacy is on everyone’s mind these days, and for good reason. It’s critical for us to curb the dark side of data misuse and ensure that data serve a higher social purpose. At this juncture, what the world needs urgently is global data governance based on a set of universally recognized values, which will require a political process to bring private companies and the tech sector together with legal experts and the public sector. That’s why I welcome the announcement of Japanese Prime Minister Shinzo Abe to include global data governance as a key priority at the upcoming G20 discussions this year. For my part, I’m working to promote effective data governance at the Bank in my capacity as co-chair of the Development Data Council (DDC) along with my Poverty Global Practice counterpart Carolina Sanchez. Through the DDC, we work with senior leadership and technical teams across the Bank to coordinate our collective vision, priorities and activities related to data.
We need to do data from farm to table
In our work, we like to say that we do data from farm to table. On the farm side, there’s the recently announced Data to End Hunger 50x2030 Initiative, where my colleagues will find themselves in farms across 50 low and middle-income countries, supporting national statistical offices and ministries to collect better agricultural data towards ending hunger worldwide by 2030. On the table side, our data scientists, statisticians and economists make data accessible and actionable by transforming it into attractive tables and visualizations, as seen in the fully reproducible 2018 Atlas of Sustainable Development Goals.
In other words, we work with data along all aspects of the development data value chain, from collection, to management, to curation, to analysis, to use. And when it comes to data use, let’s not stop at statistical tables – let’s make sure that data improves people’s lives at their dinner tables. To get there, we need to support data literacy and invest in people’s capacity around the world to transform data into policy outcomes that really affect people’s lives in the ways that matter most.
Putting our priorities into practice: investing in data, people and ideas
To put these priorities into practice, we must commit to comprehensive data financing. We need to invest in countries in every step of the way, from improving their methods, to collecting better data, anonymizing and curating the information, and increasing their capacity to use and analyze data to bring about real development impact. We must stand ready to work with the UN and other donors to accelerate data progress by complementing country investment with sustainable financing through increased International Development Association (IDA) investment and new trust fund facilities.
We also need to make sure that our statisticians and data scientists have the support to move the institution toward the data frontiers of the future, and encourage teams to integrate new and creative uses for data into our operational work. I want our data scientists to become the connectors between data technology and meaningful applications for development impact.
Finally, we must invest in innovative ideas to better support countries and create global public goods, by pioneering new applications of data technologies to help us monitor and achieve the Sustainable Development Goals. For example, the recently launched Global Nightlights platform allows us to identify electricity access down to the settlement level in 30 countries, while our Development Data Hub is the World Bank’s first-ever one-stop shop to discover, manage, and use data for development impact.
Are you a part of the data revolution? How are you using the power of data for development impact? Leave your comments here, so we can continue the conversation.
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