The Capacity Accelerator Network (CAN) is building a workforce of purpose-driven data and AI practitioners to unlock the power of data for social impact. Nikhila Vijay is a research manager in the energy, environment, and climate change space at Abdul Latif Jameel Poverty Action Lab (J-PAL) South Asia. Nikhila was one of the first India Data Capacity Fellows at J-PAL, working with the host organization, Janaagraha, a nonprofit transforming the quality of life in India’s cities and towns.
Tell us about your work with the Capacity Accelerator Network. What impact or outcome are you most excited or encouraged by? How do you measure your success?
I worked with the Research and Insights team at an organization called Janaagraha, a well-known foundation in India that works with governments and citizens to improve the delivery of infrastructure and services in urban areas.
The project I worked on focused on identifying pathways for cleaner energy transitions in household fuel usage among the urban poor in the state of Odisha. My primary responsibility was analyzing a survey dataset of over 5,000 respondents, which provided insights into household fuel usage and behaviour in low-income settlements. The goal was to identify potential cleaner energy sources, with a specific focus on cooking fuels.
Additionally, I worked on developing tools to:
- Link cooking fuel usage to health outcomes, one of the key evaluation criteria for cleaner fuels.
- Understand the costs associated with transitioning to cleaner fuels.
Given the substantial body of research linking adverse health outcomes to indoor air pollution caused by traditional cooking fuels, I was particularly excited about quantifying the costs of transitioning to cleaner cooking fuels. I was also excited to work with spatial data, and provide a visual map of fuel usage across Odisha.
For me, success meant two things: first, completing the project deliverables to meet my team’s expectations and achieving the outcomes I had envisioned at the outset. Second, and more challenging in the short term, was creating outputs that could be used by relevant stakeholders to inform their decision-making processes.
It is essential to take time to understand specific objectives and activities of the government and other implementation or policy partners, and try to engage with them at each stage of the project.
Nikhila Vijay Research Manager The Abdul Latif Jameel Poverty Action Lab (J-PAL)
How has your approach and work evolved based on what you have learned and observed from your colleagues across the CAN network?
As the point person for data analysis on this project, I relied on the CAN network to identify spatial datasets at the district and sub-district levels and to navigate reliable publicly available health datasets. It pushed me to seek help – reaching out to colleagues from other projects, clearly explaining the outputs I wanted to achieve, and leveraging their expertise and contacts to support my work.
From my colleagues at Janaagraha, I learned how to meaningfully integrate different research methods and analyses with inputs from stakeholders across community, government, and industry, creating a cohesive and comprehensive framework for the study. Specifically, I gained valuable experience in co-creating energy pathways with inputs from local community members, and in designing a representative sampling approach in the absence of administrative data.
There can be a disconnect between academia or government institutions and social impact organizations doing the work on the ground. How do you build trust and increase adoption?
From my experience, the following approaches have proven effective:
- Involving relevant stakeholders in the design process. It is essential to take time to understand specific objectives and activities of the government and other implementation or policy partners, and try to engage with them at each stage of the project. This could be done by providing regular status updates, incorporating stakeholder feedback, and having a primary point of contact, among others. It is not possible to achieve this for every project, though, as it really depends on the scope of work and nature of your partnerships.
- Recognizing that communication and advocacy are integral to the research process. In many cases, research efforts end with the publication of a paper or presentation. However, building trust and fostering adoption requires actively promoting your research and tailoring communication to meet the needs of each stakeholder. This process demands significant time, resources, and persistent effort but is crucial to ensuring that your work is meaningfully utilized.
It is important to note that despite identifying the best approaches to minimize disconnect, you can still be constrained by the initial theory of change design, funding, organizational capacity, and your own connections with the government and other stakeholders. Transparency about those kinds of limitations can help maintain trust and confidence.
My advice to data practitioners is that there is a trade off to working in the social impact sector, and to not be discouraged by the bureaucracy and limited resource capacity that is more common in this space.
Nikhila Vijay Research Manager The Abdul Latif Jameel Poverty Action Lab (J-PAL)
How is your data-driven work driving impact at the intersection of climate and health? What is the importance of an interdisciplinary approach to data training?
Using the National Family and Health Survey, I explored correlations between household cooking fuel choice and related health impacts, such as heart disease and respiratory issues on adult women, caused by indoor air pollution. I also spatially mapped this data at the sub-district and cluster level in Odisha to identify areas where this correlation was strong.
In the case of my project, it became clear that we needed more robust data to measure these linkages, and that the sample size at smaller geographic units was not representative enough to draw localized insights.
An interdisciplinary approach to data training is very important as it helps you ask the right questions you want from your data. If you are a generalist in the data space, you are usually connected with domain experts to advise you. In the absence of such experts, it is essential to have training in reading policy reports and research papers to help you understand a particular sector or linkages between two or more sectors. For example, such an approach can enrich your insights by contextualizing your analyses based on various demographic cuts, such as geography, caste, gender etc., that you may apply having had such training.
What advice do you have for data practitioners as they begin purpose-driven careers? Why should they apply their skills in the social impact sector?
Having worked previously in the corporate sector, I think there is a difference in rigor applied to designing and achieving goals using data between the private and public sector. While results and impact-driven work is normalized in the private sector, it is often less mature in the government and social impact sector. This is why we need skilled data personnel in the social impact sector who can improve service delivery through monitoring and reporting, and who can help develop quantifiable goals and measure the impact of programs so that funds are channeled to the most effective and efficient policies.
My advice to data practitioners is that there is a trade off to working in the social impact sector, and to not be discouraged by the bureaucracy and limited resource capacity that is more common in this space. It is important to remember that you are working towards social and economic good in a sector that is meaningful to you, and that your skills are helping to improve livelihoods and address these structural challenges.
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