Copyright thehindubusinessline
Not all power is visible, and India’s most consequential growth driver rarely makes headlines. Beneath the surface of every fiscal reform, growth strategy, and social-welfare expansion lies a quietly evolving statistical architecture that converts data into actionable foresight. For a nation of 1.4 billion people, an integrated statistical data infrastructure pipeline is the foundation upon which accurate policy formulation, economic planning, and development outcomes depend. Strengthening and modernising this data-to-impact pipeline is critical for achieving the nation’s Viksit Bharat 2047 vision of a resilient, innovation-led economy. India’s statistical infrastructure combines comprehensive data collection, specialised enterprise and household surveys across ministries and data dissemination via portals, websites and apps. The Ministry of Statistics and Program Implementation acts as a frontrunner steering the enhancement of this data infrastructure. From the NSSO’s establishment in 1950 to today, statistical improvements and economic progress have moved in tandem. The ministry’s scope has broadened to conducting multiple large-scale surveys like the Periodic Labour Force Survey (PLFS), Annual Survey of Industries (ASI), and Annual Survey of Unincorporated Sector Enterprises (ASUSE), among others; and maintaining a repository of data sets. These data sets generate critical economic insights and facilitate a data-to-policy transmission mechanism for decisions with measurable impact. For instance, GDP calculations inform budget and fiscal planning, CPI variations signal monetary policy evaluation at national and State level, and Industrial Production Index trends guide sectoral interventions enabling ministries to recalibrate industrial promotion strategies. Beyond indicators, these insights catalase evidence-based policy formulation. PLFS data has enabled precision targeting of workforce development interventions, with educational attainment, vocational training and gender participation insights directly informing a more inclusive skill development programme design and vocational training resource allocation. Similarly, the NSS 67th Round’s identification of 5.75 crore small enterprises with average debt exposure of ₹17,000 provided the empirical foundation for the MUDRA scheme initiated in 2015. On similar lines, numerous policies and schemes have been devised and are refined based on data insights. Integrating new data sources To improve the data sets and deepen data availability and access, MoSPI has been committed to continuous modernisation of data collection frameworks and methodological innovations. The ministry is focusing on methodological refinement, data source diversification, and comprehensive coverage enhancement for more accurate and actionable policy insights. Recently, the ministry has showcased a proactive approach to adopting such new initiatives in its ongoing base revision exercises for key indicators like the GDP. In the new GDP series, efforts are being made to integrate new data sources — for instance, the integration of more granular data from GST filings, Public Finance Management System data, vehicle registration statistics from e-Vahan, and high-frequency transaction data from NPCI, as well as an updated methodology for informal sector estimates. Additionally, to improve timely and frequent data accessibility, the ministry is working to reduce the survey data lag. The survey-data lag has been reduced from 8-9 months to 45-90 days, IIP is released in 28 days from reference month and CPI within 12 days after the end of reference month. The Ministry will undertake new service-sector survey and has already launched a new capex survey to deepen data sets and provide previously unavailable insights. MoSPI’s data quality enhancement efforts focus on including sectoral and economic indicators and drivers along with temporal frequency. Consequentially, the upcoming iteration of PLFS will introduce district level granularity, planned to be implemented across other major surveys as well. The Ministry, recognising the need for standardised and cohesive data, released the Compendium of Datasets and Registries 2024, which consolidates information about government datasets and registries acting as a single reference point for researchers and policymakers, enhancing their ability to access and analyse data for targeted interventions. One of the most significant initiatives is the setting up of the Data Innovation Lab in the Ministry, that is working in collaboration with reputed institutes on cutting-edge AI, Machine Learning, and Big Data Analytics to modernise India’s National Statistical System. These improvements in frequency, methodology, and collection can achieve their full potential only if data is disseminated effectively to various user groups. The MoSPI delivers this through upgraded portals, e-Sankhyiki, micro data portal DataViz platforms, and the GoIStats mobile applications. India’s ongoing efforts to develop its data structure to encapsulate future oriented datapoints have evolved to include real-time data platforms aiding immediate action. Most significantly, PM Gati Shakti, multi-modal infrastructure-planning focused digital platform integrates about 1700 data layers across 57 central Ministries and Departments and 36 State/UTs and reportedly played a significant part in reducing India’s logistics costs from 13-14 per cent to 8 per cent of GDP. Multiple platforms including the Poshan Tracker, IoT-enabled train tracking, the DBT database, and the e-Shram benefits millions of Indians. However, realising their full potential requires seamless integration and coordinated analysis. Interoperability in data sets and inter-ministerial coordination enable these diverse systems to deliver the precise, actionable insights necessary for targeted development interventions. Nuanced data design Looking ahead, India’s statistical ecosystem can move towards more nuanced data design by enhancing indicator quality to facilitate in-depth analysis and capture emerging sectors that create opportunities for future-centric policy analysis. India’s measurement scope needs to expand into critical emerging sectors, including tertiary skills assessment, electric mobility, environmental sustainability metrics, and AI ecosystem indicators. Considering the advancement in digitisation, India can leverage AI as a tool for generating faster, more nuanced insights through machine learning-based models, which can enable impact assessment and anticipatory policy formulation. Along with this, advancement in cross-ministerial data integration through standardised metadata protocols and unified quality assessment systems is a non-negotiable to create seamless analytical ecosystems across government departments. A practical framework, standardised processes and capacity-building initiatives are essential requirements for developing comprehensive State-level data systems. India’s steady investment in its statistical backbone is more than a technical upgrade. It is also a quiet realignment of how the state envisions inclusive economic growth and development. By widening datasets to capture emerging industries and the vast informal economy and by harnessing emerging technologies to translate those numbers into forward looking insight, the country is shaping a governance system in which every data point carries strategic weight. As methods evolve and new sectors are brought into view, this expanding evidence base becomes not merely a tool for policy but a pillar of national development and a reminder that in the current global landscape, nations that measure best will also govern best. Garg is Secretary, Ministry of Statistics and Programme Implementation, Govt of India, and Kapoor is Honorary Chairman, Institute for Competitiveness Published on October 28, 2025
