Avoiding Data Graveyards: How can we overcome barriers to data use?

Development practitioners track mortality rates for scourges like HIV/AIDS, and malaria. But nobody tracks the mortality rate of data.

March 22, 2017

Samantha Custer, Tanya Sethi, John Custer

The data revolution has a blindspot — data graveyards. (That’s where unused data goes to die). Investors and producers of development data, including AidData, know surprisingly little about what barriers prevent decision-makers from using data and evidence in their work.

Consider this paradox: Experts estimate that we need an additional investment of $350 to $400 million per year in data and statistics capacity to monitor progress against the Sustainable Development Goals (SDGs), yet our capacity to produce data is rapidly outstripping our ability to understand who uses this data, in which contexts and why. Without addressing these questions, the data revolution will not improve people's lives.

Development practitioners track mortality rates for scourges like HIV/AIDS, and malaria. But nobody tracks the mortality rate of data. Photo by Christian Maurer/Fotolia.

Our new report, Avoiding Data Graveyards, pinpoints the barriers to data use with insights gleaned from interviews with 200 leaders in three countries. From these country deep dives, we synthesize nine broader principles for demand-driven investments in data and statistics that cut across country contexts.

As articulated in the executive summary, the report seeks to answer three questions:

  1. Who produces development data and statistics, and for whom?
  2. What are the technical and political constraints for decision-makers to use development data in their work?
  3. What can funders and producers do differently to encourage the use of data and evidence in their work?

Funded in part by the U.S. Global Development Lab, researchers at the AidData Center for Development Policy interviewed central government officials, development partner experts, and civil society leaders in Honduras, Timor-Leste and Senegal. These leaders shared how they make decisions related to development projects and described the technical and political constraints to using data in their work.

Applying a model adapted from a related World Bank study on open data and improved service delivery in the Philippines,  Avoiding Data Graveyards synthesizes these insights into three essential building blocks:

  1. Content: What makes development data fit-for-purpose?
  2. Channel: How can users easily find, access and use data?
  3. Choice: What makes the perceived benefits of using data outweigh the cost of taking action, either individually or collectively?

Uncovering the principles that drive returns on investments in data and statistics is vital, as the costs of data disuse are not trivial. Each dollar invested in the production of development data and statistics arguably diverts resources from delivering public goods and services. If policymakers and practitioners use this information to design more effective policies or find efficiency gains in project implementation, better data could pay for itself. Conversely, unused data yields a negative return on investment. In addition to the sunk cost of producing data graveyards, when leaders make decisions based upon personal discretion rather than data, they may cause more harm than good.

Ultimately, the power of data to improve development outcomes rests on its use by decision-makers, civil society groups, communities and citizens. Data-driven decisions or evidence-based policies will not be realized if investments in data and evidence do not fit real use cases or address the technical barriers and political constraints facing those who influence, allocate, or monitor development activities. Avoiding Data Graveyards provides new evidence to help overcome the data-use paradox: we need investment in more and better data to power the SDGs — but only if it doesn't end up in a data graveyard.

Read the executive summary and full report to learn more about what leaders want in their development data, and how funders and producers can avoid data graveyards. RSVP to join the discussion at our upcoming launch event on April 24, 9-11am in Washington, D.C.

Development practitioners track mortality rates for scourges like HIV/AIDS, and malaria. But nobody tracks the mortality rate of data. Photo by Christian Maurer/Fotolia.

Samantha Custer is AidData's Director of Policy Analysis.

Tanya Sethi is a Senior Research Analyst at AidData.

John Custer is AidData's Communications Manager.

The Avoiding Data Graveyards report was produced in collaboration with AidData Center for Development Policy consortium partners the College of William & MaryDevelopment Gateway, the University of Texas at Austin, and Brigham Young University.

The views expressed here are those of the authors alone, and do not necessarily reflect the views of the institutions to which the authors belong.