NITI Aayog pushes for robust data ecosystem, cites need for reliable metrics in governance, development

New Delhi: Government think tank NITI Aayog on Tuesday proposed institutionalising data ownership, incentivising data quality, and interoperability of data across platforms as measures to improve data quality in the country in view of Indians' growing dependence on digital public infrastructure. 

The recommendations are part of NITI Aayog's publication India’s Data Imperative: The Pivot Towards Quality.

The report suggested assigning custodians at different levels, including national, state, and district, who are accountable for data health to ensure that a single entity is responsible for maintaining its integrity from end to end. 

Read more: India’s informal sector isn’t off the map: It’s being tracked better than ever

Quality must also be seen as a shared responsibility across different teams, including programme heads, IT teams, and field staff, the report said.

To improve data quality, the report proposes incentivising quality and not just the speed of completion of data input. “Data quality indicators—such as error rates, completion levels, and timeliness—can be tracked and factored into programme reviews, not as punitive audits but as a reflection of delivery strength,” the report said.

The report said interoperability, the ability of systems to work securely with other systems, is essential for public data to retain value across platforms, departments, and time.

New tools for assessment

The report introduced two new tools: a data Quality Scorecard and a data Quality Maturity Framework. The former is to be used to turn abstract principles into trackable metrics, including accuracy, completeness, and consistency, and the Quality Maturity Framework for present self-assessment and future planning, including dimensions like data governance and ownership, standards, and metadata.

NITI Aayog proposed these suggestions in response to the challenges that unreliable data pose. Budget drains from fiscal leakage and errors like duplicate or mistaken beneficiary records add an estimated 4-7% to yearly welfare expenditure. Inconsistent datasets distort evidence, causing misaligned programmes or delays in adjustments. As a consequence of unreliable data, the public loses confidence in digital governance.

The report said, “Data quality is no longer a backend concern; it is central to public trust, effective service delivery, and the success of India’s own AI ecosystem.” It encouraged capacity building, leadership development, and hands-on support to maintain momentum.

Read more: Viksit aim: India’s progress will depend on Centre-state relations

Saurabh Garg, secretary, ministry of statistics and program implementation, wrote in the foreword of the report that India has distinguished itself as a global leader in digital public infrastructure though UPI, Aadhaar and Ayushman Bharat, while adding that as India embarks on the next phase of digital evolution, the focus should pivot towards quality of data that powers these platforms.

“Let us champion clean, usable data as the foundation of good governance, ensuring that the dividends of our digital journey reach every citizen with precision and equity,” he said.