Empowering Action: Lessons from India’s Data Capacity Accelerator for Climate and Health

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Empowering Purpose-driven Data Talent

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Background

The journey of the India Data Capacity Accelerator (IDCA) began in 2022 with a scoping exercise with the help of GDi Partners to understand the landscape of data talent for social impact in India. This exercise was pivotal in shaping IDCA’s design, ensuring it addressed both the challenges and opportunities in developing a robust pipeline of data professionals equipped to tackle interdisciplinary problems in climate change and health. By examining the supply and demand dynamics of data talent, this scoping exercise provided critical insights to design a programme that bridges gaps and catalyses the ecosystem for data for social impact (DSI). The scoping exercise helped uncover:

  • pathways for creating a pipeline of data talent (supply side).
  • avenues where data talent could be absorbed and effectively leveraged in the social impact sector (demand side).
  • systemic barriers and opportunities for stakeholders to intervene and foster an inclusive and thriving DSI ecosystem.

Process Undertaken

To map the current landscape, GDi Partners supported data.org to conduct extensive primary and secondary research, focusing on higher education institutions (HEIs), online learning platforms, social impact organisations (SIOs), and the larger ecosystem. The exercise involved analysis of academic pathways for data science, examination of associated job market dynamics, study of online learning platforms, and research for contextualising findings within broader national and global trends. More than 70 data-focused academic courses were reviewed during the exercise along with interviews with 80+ students and industry experts, analysis of 60+ data science job descriptions by SIOs and government entities, and 80+ reports and articles. Findings through this process were further validated through stakeholder consultations to ensure resonance with on-the-ground realities.

Key Findings

Supply-Side Insights

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  • Limited Accessibility to Data / AI Education: Access to data-focused courses is skewed by gender, caste, location, and income. Students from marginalised groups, including women, those from rural or tier-3 cities, and low-income families are underrepresented in data education pathways.
  • High Cost of Education: Over 90% of data-focused courses in India in 2022 were offered by private HEIs, often with high costs, making them unaffordable for many.
  • Disconnect Between Academia and Industry: Only 35% of graduates in data-focused disciplines are employable in technical or data-related roles due to a lack of experiential learning and alignment with market demands. Additionally, more than 75% of courses lack interdisciplinary focus, leaving students unprepared for social sector applications.
  • Online Learning Platforms: While accessible, online platforms primarily cater to corporate needs and lack tailored content for social impact disciplines.

Demand-Side Insights

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  • Varied Data Proficiency Needs in SIOs:
    • Organisations working in research and advocacy require advanced skills such as statistical programming and data storytelling using tools like Python, R, and AWS.
    • Smaller NGOs focus on basic data skills, relying on tools like Excel and Canva.
  • Limited Recruitment from SIOs: The absence of SIOs from campus placements and talent recruitment events, especially for data roles, leads to a lack of awareness and opportunities for students to explore social sector careers in data and AI.
  • Capability Gaps in SIOs: Challenges in recruiting data professionals, promoting their work, upskilling staff, and acquiring digital infrastructure hinder the effective integration of data practices.

IDCA Design

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The scoping exercise emphasised the importance of:

  • Embedding experiential and interdisciplinary approaches into curricula.
  • Building pathways for underrepresented groups to access and succeed in data-focused programmes.
  • Enhancing SIOs’ capacity to recruit, retain, and upskill data professionals.

The IDCA Fellowship model is uniquely designed to drive real-world impact by combining rigorous training with practical, hands-on experience. Fellows engage in collaborative projects with leading host institutions, benefiting from mentorship by industry and academic experts. They are equipped with the skills to effectively communicate their findings to governments, civil society organisations, and other stakeholders.

This holistic approach ensures that fellows develop actionable, data-driven solutions to pressing challenges in climate and health, aligning with J-PAL’s mission to tackle some of the world’s most critical problems through the power of science and data, and data.org’s mission of creating a data talent pipeline for the future.

The vision, model, and approach of the India Data Capacity Accelerator was built on the foundation of this study and is elaborated in the following sections.

Intersection with Climate and Health

Data can play a pivotal role in addressing complex social challenges, enabling evidence-based solutions that drive impact. One such complex area lies at the intersection of climate change and public health, which underscores the urgency of leveraging data for informed action. According to the World Health Organization (WHO, 2023), climate change is expected to cause approximately 250,000 additional deaths annually between 2030 and 2050. Global initiatives such as the National Institutes of Health’s Climate Change and Health Initiative (NIH CCHI) and the Climate and Health Outcomes Research Data Systems (CHORDS) are already leveraging climate and health data to enhance diagnosis, streamline routine planning, and monitor the hazardous impacts of climate change on public health.

In India, the impacts of climate change can be observed at an unprecedented pace, with intensified heat waves, extreme precipitation events, and a rising burden of climate-sensitive diseases. Ranked as the seventh-most vulnerable country to climate extremes (Germanwatch, 2021), India faces an urgent need to solve problems at the intersection of climate and health. Despite the availability of vast amounts of datasets today, there is a dearth of comprehensive platforms that can streamline data collection and analysis to fully understand these effects. By leveraging data to mitigate impacts of climate change on public health, the IDCA aims to contribute towards bridging this gap that can yield far-reaching benefits for human development, including resource efficiency, economic security, sustainability of ecosystems, and increased economic dynamism (UNECE, 2016).

Addressing Priorities in the Climate-Health Nexus through Curated Use Cases

In India, social impact organisations are playing a vital role in augmenting efforts of governments and policymakers towards climate change effects. IDCA fellows work with social impact organisations on data projects that encompass critical stages of the data lifecycle. These projects align with one or more of the following stages: data collection, ingestion, storage, transformation and modeling, analytics, prediction, and monitoring. The following are some upcoming use cases at the intersection of data science, climate, and health:

  • Improving air quality by reducing emissions from transportation and industrial activities, and by promoting cleaner energy sources such as renewable energy and energy-efficient buildings.
  • Strengthening public health surveillance systems (early warning systems) for urban and rural areas to better track and respond to climate-related health risks, such as injuries, infections, epidemics, malnutrition, stroke etc caused by heatwaves, landslides, floods, and droughts.
  • Strengthening hospital preparedness for climate-related health risks such as epidemics, pandemics, antimicrobial resistance, trauma care and resource allocation.
  • Improving food security by promoting sustainable agriculture practices, supporting small-scale farmers, and developing drought-resistant crops.
  • Reducing the mental health impacts caused by extreme weather events through improved psychological health surveillance after the event.
  • Developing and implementing community-based adaptation strategies, including community-based planning and decision-making processes, which empower local communities to take action on climate change.
  • Deploying energy-efficient cooling infrastructure and increased access to drinking water, along with accessible and affordable healthcare facilities, to reduce the heat effects of climate change.

Building an Inclusive, Diverse, and Quality Data Workforce

In order to harness the underutilised potential of data for social impact (DSI), a significant investment needs to be made in developing quality talent for the near future. In recent years, data professionals are emerging from diverse backgrounds such as engineering, public policy, healthcare, and management consulting to engage in opportunities rooted in interdisciplinary problem solving. data.org’s Workforce Wanted report in 2022 highlighted an opportunity to create 3.5 million data for social impact jobs in low-and middle-income contexts (LMICs) by 2032 if the labour market were sufficiently incentivised.

As highlighted in the scoping exercise by GDi Partners, diversity and inclusion should be more thoughtfully integrated into the programmes building the field of data for social impact. It is important to identify and consider the barriers to education and training in data for disadvantaged populations in terms of gender, socioeconomic class, caste, etc. Despite a significant growth in the number of data programmes offered today, the majority of them are not centred on inclusion, diversity, equity, and accessibility (IDEA) in the DSI field.

Moreover, the quality of talent in the field is affected by unique dynamics of the social sector itself. Wage differentiation, variable data maturity of organisations, limited access to data and datasets, low levels of data usability, and lack of tech capacity to build and grow the ecosystem are all contributing factors. Additionally, traditional STEM programmes in India lack social impact orientation and are insufficient in terms of both the number of institutions and volume of qualified data professionals. Thus, stronger linkages between training programmes and employing social impact organisations are important to coordinate complementary efforts to advance data-driven strategies. 

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