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Despite India’s robust digital infrastructure and statistical legacy, policymaking often remains divorced from credible, transparent data. How has politicisation, data opacity, and top-down governance continued to undermine the promise of evidence-based policy?
Peter Drucker once said, “What gets measured, gets managed”, emphasising on the role of quantifiable data for policy targeting but what he overlooks is the role of quality and accuracy of this data. Where once the biggest challenge was statistical sampling, today, the crisis lies deeper in the politicisation and lack of transparency in policy-making. In 2019, the government withheld the release of a nationwide consumption expenditure survey for the first time in decades citing reasons of data quality. However, the data merely showed trends of decline in household consumption, especially in rural areas, that could negatively affect political performance indicators. Are our current policies still based on assumptions and not realities? Is there any scope for evidence-based policies in the future?
With a rich statistical legacy built on the contributions of P C Mahalanobis and institutions such as the Indian Statistical Institute (ISI) and National Sample Survey (NSS), the statistical machinery in India is undeniably massive and well-equipped. Despite this robust system, the data quality, frequency, and independence have shown worrying decline. Former chief economic adviser Arvind Subramanian has stated that India’s GDP numbers between 2011-12 and 2016-17 were overestimated by about 2.5 percentage points annually and called for a revamp of the country’s statistical system. This captures rightly his concerns that such data distortions aren’t just technical or calculation issues but play an important role in reshaping public perception, policy design, and investor confidence.
India’s data paradox has become more relevant than ever now, due to multiple CAG reports on the overreporting of data and incomplete record-keeping relating to multiple flagship schemes (the CAG found over 42 lakh ineligible farmers receiving payments under PM-KISAN, pointing to a troubling disconnect between digital reach and on-ground verification), questionable GDP rebasing, and disparity in unemployment numbers. While it is absolutely clear that evidence-based policies are the way ahead, they have been failing over a decade due to the lack of bureaucratic data literacy, the absence of an outcome-based evaluation of policies, and missing feedback loops. Even though such issues sound trivial, they are a clear representation of India’s top-down governance that we aim to change through federal structures.
Revamping processes
However, one would be on the wrong to assume data deficiency as a problem in achieving this. India has created an impressive architecture of digital platforms through Aadhaar (identity), DigiLocker (document storage), and the JAM Trinity (Jan Dhan, Aadhaar, Mobile). However, collection and storage of large data does not necessarily translate to decisions informed by that data, describing India’s digital governance as data-rich, insight-poor. The myth of digital governance as a substitute to evidence-based policy often results in techno-managerial solutions imposed without context where systems end up collecting performance data but not the impact data. India has built a digital infrastructure fit for the 21st century, but it still governs with the instincts of the 20th century – centralised, opaque, and resistant to feedback. Until digital data is used to question policy, not just decorate it, the promise of evidence-based governance will remain a myth.
It is important to recognise that building a culture of evidence-based policy is not only about numbers, but also about process. Data systems need to be complemented by greater coordination between ministries, wider consultation with independent experts, and mechanisms for continuous feedback from both states and citizens. Without these, even high-quality data risks being underutilised. The challenge, therefore, is less about the absence of data and more about ensuring that it is meaningfully utilised in everyday governance.
The situation is not entirely bleak. India’s digital governance infrastructure has laid a strong foundation for data-driven policymaking. However, what is missing is the political and institutional will to use it transparently and accountably. Globally, countries that have adopted independent statistical commissions and autonomous evaluation units have seen better public trust in numbers and course correction in policies. Mandatory impact assessments for major schemes and laws inspired by the best practices in developed economies, open access to all micro-level data, and institutionalising the feedback loops though formal independent policy evaluation cells in concerned ministries will go a long way in bringing evidence-based policies to reality. Ultimately, for a democracy that prides itself on accountability, evidence cannot remain optional.
(The writer has worked in parliamentary offices, think tanks, and development organisations on issues of trade policy,
environmental economics, gender, and governance)