Indian states, with their diverse and intensive interactions with citizens and businesses, are responsible for 60% of public expenditure. State governments in India together spend more than the Union government on subjects ranging from medical insurance and social protection for unorganized workers to solar panel subsidies and MSME incentives. The frequency of announcements of new subsidies and overhauling existing welfare schemes has seen an uptick, and states are acting to maximize use of collected data for better service delivery and policymaking.
Since 2010, Right To Public Services legislation has been enacted by 22 states and Union territories (UTs), primarily increasing responsiveness of the large range of citizen- and business-facing functions that need to be accomplished in a timely manner. This foundational framework that made public service delivery by states visible and accountable needs a 21st-century upgrade.
Recent state-level initiatives such as Kutumba in Karnataka and Parivar Pehchan in Haryana hope to create family and beneficiary-oriented systems for one-stop platforms for public service delivery and disbursement of entitlements. These are complex endeavors, requiring linking and sharing data across different schemes and departments, creating registries to better identify and serve potential beneficiaries, and continued vigilance on how the systems interact with each other. It makes significant demands on state capacity, and with the digital data protection regime now active in India, states need to articulate their data governance strategy through comprehensive data policies for responsible use of data that not only maximize use but also strengthen protections for citizen data.
Many states have policies that provide guidelines on open data or incentivize data center infrastructure and crowded-in IT/ITeS investment. However, the lack of policy guidance to state-level machinery on stewarding and responsibly sharing citizen data is affecting service delivery. In the past five years, Tamil Nadu, Punjab, and Assam have notified holistic data policies (and Odisha has one in the draft stage) for the use of data towards improved service delivery and efficiency gains.
Three key motivations and associated actions for states to improve data governance follow.
First, the need to have inter-operability across departments and schemes makes it necessary for states to adhere to open standards, formats and software in their data systems. Connecting decades-old legacy systems with more recent ones for data to be shared and used meaningfully is a challenge being tackled throughout the country. This also has lessons for how these systems are designed and procured going forward. Current efforts focus on within-state sharing, but inter-state cooperation and data sharing will become a priority as service delivery becomes responsive to migration, with beneficiary families split across different states. Further, to effectively include vulnerable groups, these digital systems should be designed to minimize denial of service and structural exclusion. States can learn from each other’s experiences of operationalising various data exchange mechanisms in the past. Internalising the ‘build once, use many times’ philosophy requires the adoption of modular, API-based approaches, and use of open protocols and standards, with recent notable efforts including Maharashtra’s MahaVISTAAR initiative and Telangana’s Agricultural Data Exchange (ADeX).
Second, the data stored in these systems suffers from quality issues, which impacts its usefulness. Credible data about beneficiaries, such as their eligibility and past interactions with the State, can reduce the need to repeatedly request citizens to re-apply for services delivered by different schemes/departments, which involves processes that are manual and effort-intensive. When data is shared and re-used across schemes and departments, it makes cross-team and department collaboration the norm, and positively impacts the data culture — the way data is collected, stored and managed by frontline staff. While advanced analytics as a capability is ubiquitous in government data systems, making data AI-ready hinges on data quality. A recent NITI Aayog report on the subject emphasizes that the move from “scale to precision” is not just an aspiration; it is a national imperative. Catalogs/inventories of States’ data systems covering their capabilities, contents and the utility of existing data is a first step toward improving data quality. States should create inventories of data they collect, examine how it can be used and improved, and develop the necessary competencies, with tools like NITI’s Data Quality Scorecard and Maturity Framework for public institutions available to guide them.
Third, the vision for a Digital India is not limited to the state alone, but envisages a major role for partnerships with civil society and the private sector. Previous attempts have shown limitations in the states’ abilities to plan, design, and maintain these systems by themselves. These challenges can be overcome if, building on the learnings from major road infrastructure PPP projects and the journey of creating the IIITs, states adopt the DPI approach. As seen in Agristack, GSTN, and UPI, Samaaj and Bazaar can be active ecosystem participants and unlock new markets and opportunities. Nuanced policy interventions such as regulatory sandbox for businesses to test new products and services, and purpose limitations and transparency in data sharing to ensure citizen data and rights are safeguarded, can set these partnerships up for success.
An approach that governs public data responsibly while delivering value for citizens and businesses is long overdue at the state level, and we should build on the momentum and urgency provided by the Digital Data Protection Act and frontrunner states.
Sridhar Ganapathy is principal (technology and innovation), Artha Global. The views expressed are personal
