We are all concerned about the resilience of communities facing disruptive change. But how resilient are the organizations serving vulnerable communities?
Development agencies are often the front-line responders for economic, health, climate and conflict-related shocks. They are expected to act fast during emergencies. And at the same time, they are expected to invest in long-term recovery and growth.
These are complex challenges. Are development agencies up to the task? Are they investing enough in their own resilience?
A resilient organization can sense changes in its network of clients and suppliers, and it can modify operations in near real time. It can perform in diverse contexts or markets, and it invests in a range of coping strategies — from redundancy and decentralization, to rapid learning and adaptation.
The private sector has poured significant resources into building these capacities. Key strategies include maintaining diversified supply chains and consumer segments, purchasing sophisticated insurance instruments, and pursuing risk-adjusted investment strategies. The sector has also adopted information systems and data analytics that help identify risks, monitor threats and automate response.
In comparison, the public and social sectors have been slow to adopt new tools and practices.
There are some outliers. BRAC, the world’s largest development NGO, has developed a series of innovative software and SMS-based solutions for environmental monitoring, client communications and electronic payments. They have also launched a Social Innovation Lab to continue building capacity for change.
Similarly, the World Bank has led in the adoption of new technologies for Monitoring and Evaluation — including the use of call detail records for transportation planning or high frequency satellite data to monitor agricultural productivity.
The satellite project is sponsored by the Center for Effective Global Action, an academic network focused on data analytics for development. There is a long history of collaboration between CEGA and the World Bank. Economists in these two institutions were early pioneers in the movement toward randomized evaluation of development programs. Now, we are working together to advance the analytics agenda.
Predictive analytics requires access to high frequency, high-quality data streams for key outcomes of interest. Of course, private companies have readily quantifiable outcomes — something that the public and nonprofit sectors struggle with.
Regardless, data analytics — namely, the use of large, often heterogeneous data to monitor trends and make decisions — have already transformed the effectiveness of public health departments and relief organizations.
For example after the 2010 Haiti earthquake, researchers at Stanford, Tufts, Carnegie Mellon and other universities collaborated with tech companies to develop robust emergency communications, enabling rescuers to save lives and reunite families. Similarly, the InSTEDD program was launched, in part, in response to the 2005 avian influenza pandemic, with early support from Google. The devastating Nepal earthquake on April 25 has also showcased how real-time crisis mapping can target relief efforts to reduce loss and suffering.
One concern is that these programs are typically led by academics and technology companies — and they’re often developed only in the midst of a disaster. This isn’t sustainable. Public service agencies need to maintain an ongoing capacity to create, use and institutionalize data analytics for decision-making. Without this capacity, vulnerable communities will suffer.
A perfect example is the collective failure to harness mobile data for epidemiological tracking and response during the Ebola crisis in West Africa. As a development community, we need to experiment with new technologies as part of the design and evaluation of routine programs — not just during emergencies.
What if we were to mainstream real-time data analytics within development agencies? This would make social programs more adaptive and responsive to community needs. It would build the resilience of the communities served by NGOs and government.
It might also facilitate rigorous evaluation during disaster response, enabling us to learn as we go. Traditionally, it has been difficult to conduct evaluations during emergencies, as highlighted in an article not so long ago on evaluation in conflict settings. Can we change this?
With support from the Global Resilience Partnership, BRAC and CEGA are investigating activities that build more resilient development agencies. Our approach is to solve a series of failures in the market for analytics solutions, on both the demand and supply sides. And we are driving toward three key objectives.
“Tech for dev” is a noisy space: There are lots of pilot projects, and few solutions that actually reach scale. So development agencies must learn to identify the most effective, scalable technologies. They need access to vendors that can deliver long-term support, and they need to invest in interoperable tools that facilitate cross-agency cooperation. In-house, small-scale data management solutions can be cheaper in the short run, but they can impose costs on the broader community.
Building capacity includes forging market linkages (and reducing search costs) between tech companies and development practitioners — two communities that have not traditionally worked together. This could result in the co-creation of analytics solutions that can be scaled over time. Co-creation could have real benefits for the tech sector, because development agencies bring important expertise in areas like gender analysis and social norms.
To reduce the risks of adopting a new technology, we must benchmark new analytic solutions against the industry “gold standard.” In development, many decisions are made on the basis of focus groups, polls, pen-and-paper surveys and qualitative assessments. CEGA has begun running a series of experiments that compare satellite, sensor and mobile data with more traditional tools for M&E. This will help us understand the reliability of new classes of data — and how these data should be priced.
But we also need to think about incentives for the tech sector to develop new use cases for economic development. Startup companies face serious opportunity costs in pursuing public sector products, which can be less profitable in the short-term. How can we overcome this challenge? Innovative financing mechanisms may be needed to transform mobile, satellite and sensor data into tools for development decision-making.
To sustain technology adoption and institutionalize data-driven decision-making, organizations must invest in incentives for their staff and partners. The World Bank has been successful in incentivizing its managers to rigorously evaluate its development programs. Part of this effort came from within the bank, but outside actors like Center for Global Development also played a role, especially in mobilizing commitments and resources for impact evaluation. Incentives, if institutionalized, can promote sustained adoption. Otherwise, we’ll end up with more one-off pilot projects that never achieve scale.
In the coming years, the Global Resilience Partnership will harness new kinds of data to build the resilience of organizations like BRAC and the World Bank. It will also foster new kinds of partnerships, including with Silicon Valley tech companies like Premise Data, Planet Labs and Skybox.
Long term, we hope it will institutionalize the use of real-time analytics within key development agencies — not just for coordination of disaster response, but to optimize ongoing programs and services. This strategy could improve the resilience of social organizations, as well as the communities that they serve.
This blog post is part of a series highlighting the innovative projects supported by the Global Resilience Partnership, an initiative by The Rockefeller Foundation, U.S. Agency for International Development and Swedish International Development Cooperation Agency designed to help millions in Africa and Asia build more resilient futures.
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