Quality, timely data that help chart the progress or the regress of a country are critical to welfare policymaking. Over the decades, the census data had served as the pivot around which revolved planning and execution of policy interventions. The over 15-year gap between the last census and the next one — the latter has just been announced for 2026-2027 — meant that crucial policy matters were at the risk of being designed on the basis of dated data. Could this have played a role in an estimated 100 million people falling out of the welfare net of the National Food Security Act? But the mere availability of data is not enough. A recent report by the NITI Aayog has underlined the importance of ensuring data quality. The report proposed to institutionalise data ownership and assign custodians of data at different levels of governance, among other measures, to ensure that a single entity is responsible for maintaining data integrity and quality from end to end. The NITI Aayog’s concern is not without reason. Poor quality of data and errors like duplicate or mistaken beneficiary records add an estimated 4-7% to the budgeted yearly welfare expenditure. Inconsistent datasets were also found to cause misaligned programmes or delays in policymaking and implementation. The consequence of these errors on account of faulty data can be serious: public trust in efficient governance can get eroded, for instance.
Clerical errors like duplicate or erroneous data, though, are not the only challenges affecting data quality. There is concern that the efficiency of India’s once reliable statistical system has been blunted by political meddling. In 2019, a National Sample Survey that revealed a drop in real per capita monthly consumption and a spike in unemployment was suppressed by the government, which dismissed NSS data as unreliable to hide its shortcomings. Last year, the NITI Aayog itself was accused of bending the truth to come up with positive data on poverty reduction in India that did not reflect ground realities. The objectivity and the credibility of official data have thus nosedived. The NITI Aayog’s proposal to set up a custodian for data is crucial and urgent in this respect. But for this proposal to work, such a body must be immune to government influence over data collection and publication. A positive spin on public welfare is, understandably, an electoral compulsion. However, the resultant compromise in data quality has serious implications that cannot be ignored.