Data Collection: from Burden to Benefit

Devex recently reported on the early progress of a three-year project to increase enrollment and improve learning outcomes for girls in Rajasthan, India. The project is among the first to be funded through a “development impact bond,” or DIB. A DIB is similar to a social impact bond, in which a funder – typically a government agency – agrees to pay the cost of a social program if certain outcomes are met. In the case of the girls’ education DIB in India, a Swiss foundation paid the upfront costs, a local NGO was the implementer, and a UK-based foundation agreed to repay the bond (depending on performance).

Initial results are positive, but the novelty of the funding arrangement created some challenges. Measurement and evaluation of outcomes is standard for most development projects, but tying the results to repayment is a different matter. Crafting the agreement required intense negotiation of how to measure things that, under the best circumstances, are difficult to quantify. At one point, for example, it became clear that students were falling short of their English learning goals, which were part of the repayment conditions. The implementers asked a third party to survey instructors, revealing a lack of confidence in their own English abilities, and reluctance to follow pre-designed lesson plans. The director of the implementing organization noted: “This was the first time that we were using data not just to aggregate at each level, but actually sharing all data….The DIB actually forces us to really codify everything much stronger and easier for field staff.”

The Educate Girls DIB demonstrates a fundamental principle of building a data culture:  Incentives for collecting and using data must align with the project’s goals. When data flow upward for the sole benefit of funders or government bosses, data collection can be seen as a burden or a distraction. In the case of Educate Girls, a randomized control trial satisfied funders that their investment is having an impact, but a simple teachers’ survey may have been a more effective driver of the essential goal, which was to help girls learn. When all stakeholders – funders, implementers, partners, and beneficiaries – understand the importance of collecting and using information to get better results, the first tough roots of a data culture are established.

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