Real-time data for smarter governance: As the world’s most populous country charts its course to become a global powerhouse by the time it completes 100 years of independence, it must rethink how public policy is conceived, designed, and delivered. For India’s economic growth to translate into tangible gains across all strata of society, public policymaking needs to be both inclusive and evidence-based. A critical enabler of this transformation is the availability of timely, high-quality, and granular data.
Yet, despite being the world’s largest democracy, India lacks a globally recognised public policy institution akin to the Harvard Kennedy School or the London School of Economics. Even more concerning is that many policymakers lack access to reliable, up-to-date data. This dual absence—of institutional depth and dependable data—undermines the country’s policy capacity at a time when it is needed most. Building a robust and credible data ecosystem must therefore become an urgent national priority.
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Weak data backbone limits policy ambitions
India’s economy is evolving rapidly, powered by digital infrastructure, real-time payments, and increasing formalisation. But the statistical systems that inform public policy have struggled to keep pace. Traditional sources of official data—such as large-scale surveys, administrative records, and national accounts—have long served as the backbone of policymaking. Indicators like the Consumer Price Index (CPI), Index of Industrial Production (IIP), and Gross Domestic Product (GDP) continue to inspire confidence. However, they suffer from two serious shortcomings: periodicity and granularity. Their infrequent release fails to match the velocity of a modern economy, while their aggregated nature often masks local shocks and structural imbalances.
For instance, the Periodic Labour Force Survey (PLFS), released annually, provides valuable insights into employment trends. But its utility for real-time labour market interventions is limited. In a post-pandemic economy marked by volatility and uneven recovery, policymakers need much faster and finer feedback loops.
This has brought alternative data sources into the spotlight. From satellite imagery and mobile phone usage to online booking trends and digital payments, a new universe of high-frequency data is becoming available. The ministry of statistics and programme implementation (MoSPI) is now actively exploring how to integrate these alternative sources into the official statistical framework. The goal is not to replace conventional data, but to supplement it—filling gaps with unprecedented speed, depth, and geographic detail.
A promising development is the upcoming revision of the CPI series, expected to be launched in early 2026 with a new base year of 2024. The revised series will incorporate data from online platforms for air and rail fares, subscription-based streaming services (OTT), and administrative records for fuel prices. MoSPI is in active discussions with the Indian Railway Catering and Tourism Corporation (IRCTC) and the Petroleum Planning and Analysis Cell (PPAC) to enable direct data transfers for timely integration into CPI calculations.
Similarly, satellite-based night-time luminosity data is already being used as a proxy for economic activity, especially in regions where official statistics are sparse. This can help track industrial output, road infrastructure development, and even cropping patterns. Meanwhile, granular consumption insights are emerging from mobile phone metadata and Unified Payments Interface (UPI) transactions. These real-time indicators offer policymakers a sharper view of shifting consumption patterns, regional disparities, and emerging distress.
Alternative data is promising, but not a panacea
Speaking at a recent workshop titled ‘Using Alternate Data Sources and Frontier Technologies for Policy Making’, NITI Aayog Vice-Chairman Suman Bery noted that alternative data holds high potential, especially in offering early warning signals and directional clarity in a fast-changing world. He stressed on the importance of using these technologies to support timely, targeted interventions.
However, Bery also sounded a note of caution: while innovation is vital, it must not become an all-consuming pursuit. Alternative data sources, however sophisticated, often lack the rigour, transparency, and validation mechanisms that underpin traditional statistics. For instance, prices scraped from online retail platforms may be distorted by discounts, special offers, or seasonal variations, making them poor proxies for broader inflation trends. Likewise, satellite data, while useful for trend detection, remains an indirect measure of output.
Chief Economic Adviser V Anantha Nageswaran echoed this view, advocating for the intelligent integration of new data streams into the policymaking process. Alternative data, he said, should be used to complement—not compete with—official statistics. A well-trained algorithm, he argued, is only as useful as the institutional and human capacity built around it. If misused or misinterpreted, such data could lead to flawed conclusions and policy missteps.
In parallel, MoSPI must continue refining its legacy indicators such as CPI, IIP, and GDP series. To do this effectively, it should deepen partnerships with think tanks and research institutions. A good starting point is the National Council of Applied Economic Research (NCAER), which established the National Data Innovation Centre (NDIC) in 2017. The NDIC acts as a laboratory for experimenting with new data collection methods, tools, and technologies. Collaborations between MoSPI, NCAER, and academic institutions such as the Indian Institutes of Technology (IITs) could help bridge the persistent gap between research, data generation, and policy implementation.
India needs real-time data
India can also draw lessons from countries that have pioneered data-driven governance. Singapore’s Smart Nation initiative combines sensor-based inputs, administrative records, and citizen feedback in real-time to optimise public services. Estonia’s e-governance model, anchored in secure digital identities, enables seamless data-sharing across departments while maintaining citizen privacy. These are not off-the-shelf templates, but they offer conceptual frameworks that India can adapt. What is needed is a centralised data platform that harmonises traditional and alternative sources, ensures access to verified datasets, and provides analytical tools for decision-makers across tiers of government.
Yet, as India embraces frontier technologies, it must also confront the risks they bring. Issues of data ownership, privacy, algorithmic bias, and unequal access to digital infrastructure cannot be ignored. Alternative data often originates from private platforms, raising thorny questions about consent, commercialisation, and accountability. Policymakers must put in place robust legal and ethical frameworks to regulate data collection, sharing, and usage.
Most importantly, they must invest in building institutional capacity. Data is only as good as the systems that interpret and apply it. Without trained statisticians, data scientists, and policy analysts embedded in the public sector, even the best-designed dashboards will remain ornamental. The challenge is not just technological, but also institutional and political.
The future of policymaking lies in marrying the credibility of traditional data with the agility of alternative sources. The ongoing data revolution gives India a historic opportunity to redefine how it measures, manages, and monitors its progress. But the transformation must be guided by principles of transparency, accountability, and public good. Only then can data truly empower citizens and strengthen democracy.