{"id":362554,"date":"2026-05-09T21:11:47","date_gmt":"2026-05-09T15:41:47","guid":{"rendered":"https:\/\/forumias.com\/blog\/?p=362554"},"modified":"2026-05-09T21:11:47","modified_gmt":"2026-05-09T15:41:47","slug":"the-elephant-in-indias-data-room","status":"publish","type":"post","link":"https:\/\/forumias.com\/blog\/the-elephant-in-indias-data-room\/","title":{"rendered":"The elephant in India\u2019s data room"},"content":{"rendered":"

UPSC Syllabus: Gs Paper 3- <\/strong>Infrastructure And Gs Paper 2<\/strong>– Governance<\/p>\n

Introduction<\/strong><\/h2>\n

India generates massive amounts of data through Ministries, welfare schemes, and public programmes. However, much of this information remains fragmented, inconsistent, and difficult to access or integrate across departments. Parliamentary questions frequently seek basic data that should already exist in standardised public databases. The deeper problem lies in weak data standardisation and poor interoperability between government systems. Without reliable and connected databases, welfare delivery, policymaking, parliamentary accountability, and economic planning become inefficient, inaccurate, and vulnerable to leakages.<\/p>\n

Problems in India\u2019s Data Ecosystem<\/strong><\/h2>\n
    \n
  1. Fragmented data systems: <\/strong>Different Ministries and departments use separate databases and do not follow common standards for indicators, regions, or time periods. This creates confusion and weak coordination across government systems.<\/li>\n
  2. Lack of interoperability: <\/strong>Data collected for one programme often cannot be integrated smoothly with another database. Consolidating such information becomes slow, difficult, and vulnerable to errors.<\/li>\n
  3. Data abundance without usability: <\/strong>India produces more data than before, but large volumes alone do not improve governance. Poor formatting and inconsistent definitions reduce the usefulness of information.<\/li>\n
  4. Basic information not publicly accessible: <\/strong>Many parliamentary questions ask about toilets, pensions, or scheme beneficiaries. Such information should already exist in a clear, standardised, and easily accessible public database.<\/li>\n
  5. Weak standardisation practices: <\/strong>NITI Aayog observed that government departments define even basic attributes differently. The absence of shared standards weakens the overall credibility of public data systems.<\/li>\n<\/ol>\n

    Impact on Welfare Delivery and Policymaking<\/strong><\/h2>\n
      \n
    1. Duplicate beneficiaries and fiscal leakages: <\/strong>Welfare databases often contain repeated names of the same beneficiaries. According to a NITI Aayog report released in June 2025, such duplication increases spending by nearly 4%-7% annually.<\/li>\n
    2. Large savings through data clean-ups: <\/strong>Removing 17.1 million ineligible PM-KISAN (Pradhan Mantri Kisan Samman Nidhi) beneficiaries was expected to save \u20b990 billion in FY2024. Deleting 35 million bogus LPG connections could save \u20b9210 billion over two years, while eliminating 16 million fake ration cards may save nearly \u20b9100 billion annually.<\/li>\n
    3. Duplication of health data: <\/strong>Childhood tuberculosis cases are recorded separately in the Health Management Information System, disease surveillance networks, and immunisation registries. This often leads to the same patient being counted multiple times.<\/li>\n
    4. Weak evidence-based policymaking: <\/strong>Conflicting and unreliable data creates uncertainty among decision-makers. In many cases, policymakers begin relying more on anecdotal claims or political convenience instead of verified evidence.<\/li>\n
    5. Administrative burden on Parliament: <\/strong>MPs spend significant time asking for routine factual information. Better public access to standardised datasets could improve the quality of parliamentary accountability and discussions.<\/li>\n<\/ol>\n

      Economic and Global Competitiveness Concerns<\/strong><\/h2>\n
        \n
      1. Weak performance in global indices: <\/strong>In the Global Innovation Index 2024, India had missing data for two indicators and outdated information for eight indicators. Several datasets were more than a year old.<\/li>\n
      2. Poor inter-agency coordination: <\/strong>Inconsistent methodologies across departments reduce the reliability of national statistics. This weakens India\u2019s global data credibility and masks actual performance levels.<\/li>\n
      3. Economic cost of poor data governance: <\/strong>The Organisation for Economic Co-operation and Development (OECD) estimated that better public-sector data sharing could increase GDP by nearly 1.5%, which may rise to 2.5% if private-sector data is also included.<\/li>\n
      4. Loss of economic potential: <\/strong>Weak data governance affects not only policymaking but also economic efficiency. Poor coordination and unreliable information reduce the benefits that strong digital governance can deliver.<\/li>\n<\/ol>\n

        Way Forward<\/strong><\/h2>\n
          \n
        1. Strengthening the India Data Management Office (IDMO): <\/strong>Under the National Data Governance Framework Policy (NDGFP), the proposed IDMO can become the central institution for enforcing common standards, rules, and protocols across Ministries and States.<\/li>\n
        2. Giving binding authority to IDMO: <\/strong>The IDMO should have powers to audit compliance, resolve disputes, and enforce standard definitions and methodologies. Without enforcement powers, existing inefficiencies may continue.<\/li>\n
        3. Aligning with global statistical frameworks: <\/strong>India can improve consistency by adopting frameworks such as the UN\u2019s System of National Accounts. A National Statistical Standards Manual can help create uniform practices nationwide.<\/strong><\/li>\n
        4. Strengthening the national open data platform: <\/strong>The open data platform \u201cdata.gov.in\u201d should become a centralised and schema-consistent repository. Ministries should regularly upload standardised datasets to improve transparency and accessibility.<\/li>\n
        5. Improving real-time public access: <\/strong>Standardised district-level data can help parliamentarians, researchers, and policymakers access reliable information quickly. This can improve governance and reduce repetitive information requests.<\/li>\n
        6. Using accountability benchmarks: <\/strong>NITI Aayog\u2019s Data Governance Quality Index should become an annual benchmark linked with performance reviews and incentives. Competition among Ministries and States can improve data quality standards.<\/li>\n<\/ol>\n

          Conclusion<\/strong><\/h2>\n

          Data standardisation is not merely a technical issue but a basic requirement for effective governance. Fragmented and inconsistent databases weaken welfare delivery, policymaking, and economic efficiency. Strong standards, interoperable systems, and institutional accountability are necessary to make India\u2019s data reliable and future-ready. For a country aspiring to become a $5 trillion economy, future-ready governance must rest on accurate, accessible, and standardised information systems.<\/p>\n

          Question for practice:<\/strong><\/p>\n

          Discuss the major challenges in India\u2019s data governance system and suggest measures needed to improve data standardisation and interoperability.<\/p>\n

          Source<\/strong>: The Hindu<\/p>\n","protected":false},"excerpt":{"rendered":"

          UPSC Syllabus: Gs Paper 3- Infrastructure And Gs Paper 2– Governance Introduction India generates massive amounts of data through Ministries, welfare schemes, and public programmes. However, much of this information remains fragmented, inconsistent, and difficult to access or integrate across departments. Parliamentary questions frequently seek basic data that should already exist in standardised public databases.… Continue reading The elephant in India\u2019s data room<\/span><\/a><\/p>\n","protected":false},"author":10320,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"jetpack_post_was_ever_published":false,"footnotes":""},"categories":[1230],"tags":[300,212,10498],"class_list":["post-362554","post","type-post","status-publish","format-standard","hentry","category-9-pm-daily-articles","tag-governance","tag-gs-paper-2","tag-the-hindu","entry"],"jetpack_featured_media_url":"","views":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/forumias.com\/blog\/wp-json\/wp\/v2\/posts\/362554","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/forumias.com\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/forumias.com\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/forumias.com\/blog\/wp-json\/wp\/v2\/users\/10320"}],"replies":[{"embeddable":true,"href":"https:\/\/forumias.com\/blog\/wp-json\/wp\/v2\/comments?post=362554"}],"version-history":[{"count":0,"href":"https:\/\/forumias.com\/blog\/wp-json\/wp\/v2\/posts\/362554\/revisions"}],"wp:attachment":[{"href":"https:\/\/forumias.com\/blog\/wp-json\/wp\/v2\/media?parent=362554"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/forumias.com\/blog\/wp-json\/wp\/v2\/categories?post=362554"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/forumias.com\/blog\/wp-json\/wp\/v2\/tags?post=362554"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}