Latest news with #SaurabhGarg
Mint
24-06-2025
- Business
- Mint
NITI Aayog pushes for robust data ecosystem, cites need for reliable metrics in governance, development
New Delhi: Government think tank NITI Aayog on Tuesday proposed institutionalising data ownership, incentivising data quality, and interoperability of data across platforms as measures to improve data quality in the country in view of Indians' growing dependence on digital public infrastructure. The recommendations are part of NITI Aayog's publication India's Data Imperative: The Pivot Towards Quality. The report suggested assigning custodians at different levels, including national, state, and district, who are accountable for data health to ensure that a single entity is responsible for maintaining its integrity from end to end. Quality must also be seen as a shared responsibility across different teams, including programme heads, IT teams, and field staff, the report said. To improve data quality, the report proposes incentivising quality and not just the speed of completion of data input. 'Data quality indicators—such as error rates, completion levels, and timeliness—can be tracked and factored into programme reviews, not as punitive audits but as a reflection of delivery strength,' the report said. The report said interoperability, the ability of systems to work securely with other systems, is essential for public data to retain value across platforms, departments, and time. The report introduced two new tools: a data Quality Scorecard and a data Quality Maturity Framework. The former is to be used to turn abstract principles into trackable metrics, including accuracy, completeness, and consistency, and the Quality Maturity Framework for present self-assessment and future planning, including dimensions like data governance and ownership, standards, and metadata. NITI Aayog proposed these suggestions in response to the challenges that unreliable data pose. Budget drains from fiscal leakage and errors like duplicate or mistaken beneficiary records add an estimated 4-7% to yearly welfare expenditure. Inconsistent datasets distort evidence, causing misaligned programmes or delays in adjustments. As a consequence of unreliable data, the public loses confidence in digital governance. The report said, 'Data quality is no longer a backend concern; it is central to public trust, effective service delivery, and the success of India's own AI ecosystem.' It encouraged capacity building, leadership development, and hands-on support to maintain momentum. Saurabh Garg, secretary, ministry of statistics and program implementation, wrote in the foreword of the report that India has distinguished itself as a global leader in digital public infrastructure though UPI, Aadhaar and Ayushman Bharat, while adding that as India embarks on the next phase of digital evolution, the focus should pivot towards quality of data that powers these platforms. 'Let us champion clean, usable data as the foundation of good governance, ensuring that the dividends of our digital journey reach every citizen with precision and equity,' he said.
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Business Standard
24-06-2025
- Business
- Business Standard
Strengthen data quality to build digital trust, says NITI Aayog report
Government think tank NITI Aayog on Tuesday released a report highlighting the need to strengthen data quality frameworks across government systems, warning that poor data quality could "undermine digital governance, public trust, and service delivery". In its latest quarterly report Future Front, the think tank said, "India's digital future will be shaped not just by how many platforms we build, but by how much trust we build into them. And that begins with data that's ready to serve." Titled 'India's Data Imperative: The Pivot Towards Quality', the report examines the challenges posed by unreliable data and proposes two new tools: a Data-Quality Scorecard to evaluate and track data quality attributes, and a Data-Quality Maturity Framework for self-assessment and future planning. NITI Aayog Chief Executive Officer (CEO) BVR Subrahmanyam released the report along with Saurabh Garg, Secretary at the Ministry of Statistics and Programme Implementation (MoSPI), and Debjani Ghosh, Distinguished Fellow at the Aayog. According to the report, while India has laid strong digital foundations, the focus must now shift towards the reliability of data flowing through these platforms. 'Data quality is no longer a back-end concern; it is central to public trust, effective service delivery, and the success of India's own AI ecosystem,' it said. The report suggests that states should take the lead by institutionalising data quality cells, aligning quality metrics with service outcomes, and rewarding good practices. It also calls for sustained investments in capacity building, leadership development, and on-ground support to embed data quality as a core governance priority. (With inputs from PTI.)
Time of India
24-06-2025
- Business
- Time of India
Need for robust data quality to fortify digital governance, cultivate public trust: Niti Aayog report
Niti Aayog on Tuesday emphasised the urgent need for robust data quality to fortify digital governance , cultivate public trust , and ensure efficient service delivery. The government think-tank released the third edition of its quarterly insights series Future Front, titled 'India's Data Imperative: The Pivot Towards Quality'. The report critically examines the pervasive challenges posed by poor data quality and introduces practical, easy-to-use tools: a Data-Quality Scorecard to measure and track data quality attributes, and a Data-Quality Maturity Framework for self-assessment and roadmap development. "India's digital future will be shaped not just by how many platforms we build, but by how much trust we build into them. And that begins with data that's ready to serve," the report said. The report was released by Niti Aayog CEO B V R Subrahmanyam, Secretary of MoSPI Saurabh Garg, and Aayog's Distinguished Fellow Debjani Ghosh. Live Events It further noted that while India's digital foundation are in place, the challenge now is ensuring that what flows though them is accurate, complete, and trusted. "Data quality is no longer a back-end concern; it is central to public trust, effective service delivery, and the success of India's own AI ecosystem," it said. States can lead the way by embedding data quality cells, linking quality to service outcomes, and recognising excellence. Capacity building, leadership development, and hands-on support will be essential to sustain momentum, it added. Economic Times WhatsApp channel )
Indian Express
11-06-2025
- Business
- Indian Express
Why govts revise GDP base year and methodology, why the proposed 2026 revision matters for India's global standing
Dear Readers, In an interview to The Indian Express, Saurabh Garg, Secretary to Government of India in the Ministry of Statistics and Programme Implementation, stated that the ministry is in the process of revising the 'base year' for the calculation of Gross Domestic Product (GDP). The GDP is the central metric to assess the annual economic growth or the overall size of an economy and the so-called 'base year' refers to the year that works as a starting point for calculations. At present, the base year is 2011-12. In other words, the GDP in 2011-12 is used as a 'base' over which the GDP growth of any following year is calculated. The new base year for GDP calculations will be 2022-23 and the revised series of data will be released on February 27, 2026. Garg also confirmed that some other key macroeconomic metrics will also undergo changes in base years. The base year for Index of Industrial Production (IIP) will also be revised to 2022-23 while the base year for Consumer Price Index, which is used to assess the rate of inflation faced by consumers, will be revised to 2023-24. Is this the first time such a revision is happening? No. The revision slated for 2026 will be the eighth such. The first set of estimates of national income (GDP) for India was compiled by the 'National Income Committee', under the chairmanship of PC Mahalanobis in 1949. The first and final reports of national income by this committee were brought out in 1951 and 1954 respectively. Since then, as more and better quality data became available, the Central Statistics Office (CSO) undertook comprehensive reviews of the methodology used for calculating GDP. Apart from shifting base years of national accounts series, the CSO also tried making improvements in the compilation of national accounts series, in terms of coverage of activities, incorporation of latest datasets and latest international guidelines. The base year of national accounts have been revised on seven different occasions: From 1948-49 to 1960-61 in August 1967; From 1960-61 to 1970-71 in January 1978; From 1970-71 to 1980-81 in February 1988; From 1980-81 to 1993-94 in February 1999; From 1993-94 to 1999-2000 in January 2006; From 1999-2000 to 2004-05 in January 2010; and From 2004-05 to 2011-12 on January 30, 2015. It is important to note that revisions in base year and the broader updates in the methodology of estimating the GDP go together. The short answer is: To more accurately understand and report the state of the economy. An accurate reporting, in turn, is an essential requirement both for policymakers as well as all the other economic agents (from large business firms to budding entrepreneurs). But calculating or, more accurately, estimating the GDP of a large country such as India is not as straightforward as it may appear at first glance. The remarkable thing about GDP is that it promises to capture the vast and varied reality of an economy in just one number. Read this piece for a more detailed explainer on GDP. It can be calculated in different ways; say, either by looking at how much people spend or, alternatively, how much they earn. But if one spends some time on the definition of GDP, it will become clear that it is not easy to calculate it. On paper, GDP measures the current market value of all final goods and services produced within a country in a given period of time (say a quarter or a year). The word 'final' is crucial, but often receives very little attention. Its implication is that the GDP will only include those goods and services that are bought by the final consumers or users. For instance, a cricket bat is a final good. But, of course, it is made of many things: the rubber grip, the wood, the adhesives, the labour used to make the bat, etc. Each of these things likely went through its own production process. For instance, the rubber grip on the handle is a finished product in itself that uses other 'intermediate' and 'primary' (say rubber) products. Same holds true for the wood and how it was cut and sold and processed before it was bought by the cricket bat maker. The use of the word 'final' in the GDP definition means that only the final monetary value (in current day prices) will be used in GDP. That, in turn, means weaning away all the other prices (of intermediate and primary goods and services that went into making the bat) out of the GDP calculations. Even if all the data is available, the complexity of calculations is quite apparent. However, the fact is, all the required data isn't always available in the absolute accurate manner. Moreover, and very importantly, the economy itself undergoes fundamental change as the years roll by. India started off as a predominantly agrarian economy. That meant most of the people were involved in agriculture or related activities and most of the GDP came from those activities. With each passing decade, India's economic structure has changed. Today, most of the GDP (around 55%) comes from the so-called 'services' sector while agriculture etc. contribute less than 20%. However, the number of people involved in agriculture has not fallen in the commensurate manner. Estimating GDP from the farm and estimating from the services sector requires different data sets and different methodologies. Further, these methodologies also change with the improvements in data as well as understanding of the linkages in the economy. For instance, it is noteworthy that up until 1999, India saw the GDP series being revised once in a decade, changing the base to a year that ended with 1. This was no coincidence. The informal (or unorganised) sector playing a major role in the Indian economy and the workforce estimates for the unorganised sector were obtained from the Population Census conducted decennially in the years ending with 1. As such, it was natural to make such years the base years for each revision. However, since the 1993-94 series, the CSO started using the work force estimates from the results of Employment and Unemployment Surveys of National Sample Survey Organisation (NSSO), which are conducted once in every five years. As a result, since 1999, the base year has been changed every five years (until 2015). This practice was also in line with the recommendation of the National Statistical Commission that all economic indices should be 'rebased' at least once in every five years. Regular revisions in base years help in two broad ways. One, they capture the changes in the way India's economy functions — new industries can be included and outdated ones removed from the calculations. Two, they provide a more accurate picture of the 'real' economic growth, which is the economic growth after removing the effect of inflation. For argument's sake, an economy's GDP could double in a year in two very contrasting ways: The total output remains the same but the prices double or the prices remain the same and the 'real' output (say cars manufactured inside the country) doubles. The reality lies somewhere in the middle and revising the base year provides a more accurate understanding of how the real economy is growing. Why was the base year not changed five years after 2011-12? The fact is that the government led by Prime Minister Modi had announced in 2017 that a new GDP series will be released with 2017-18 as the new base year. The government had hoped to use the results of Consumer Expenditure Survey (CES) as well as the Periodic Labour Force Survey (PLFS was an annual survey replacing the quinquennial Employment-Unemployment Surveys), both of which were slated in 2017-18, to update the GDP data. However, both the surveys ran into trouble with the government itself raising data quality issues. The PLFS for 2017-18 had shown that the unemployment rate had risen to a 45-year high and the CES for 2017-18 showed that poverty had risen (as evidenced by a fall in spending) since 2011-12, a historic reversal of trend. Although after the election results of 2019, the government accepted PLFS findings, the CES results were never accepted. Eventually, these data gaps led to the government dropping 2017-18 as the new base year because it wasn't 'normal'. It must be noted that 2017-18 experienced the ramifications of key policy led-disruptions such as the government's decision to overnight demonetise 86% of India's currency base in November 2016 as well as the introduction of a Goods and Services Tax regime (replacing multiple indirect taxes) in July 2017. India's GDP growth rate registered a sharp deceleration starting 2017-18, falling from more than 8% in 2016-17 to less than 4% in 2019-20. Since the start of 2020, the Covid pandemic-induced disruptions have meant that neither 2020 nor the years immediately after it could be treated as 'normal' years. Why is this particular revision crucial for India's global standing? Although it is true that each revision improved the estimation of India's GDP, yet the last revision in 2015 created a lot of controversy that dented India's global standing. In particular, many experts claimed that the methodological changes incorporated in 2015 meant that India was overestimating (i.e. overstating) its GDP. These dissenting voices even included the government's own Chief Economic Advisor Arvind Subramanian, who questioned the credibility of India's GDP soon after he left office. Read this piece to understand the whole controversy better. Experts such as Prof R Nagaraj, formerly associated with the Indira Gandhi Institute of Development Research and now with IIT Bombay, have repeatedly written that the methodological changes in 2015 overstate India's GDP. In a 2021 paper published in the Economic and Political Weekly, Nagaraj found that the growth rates in the manufacturing sector are far more muted if one looks at the Annual Survey of Industries data (published by MoSPI) as against the Ministry of Corporate Affairs' MCA-21 database for the Private Corporate Sector (PCS) that is used in GDP calculations. The new base year revision and the new GDP series will be coming out after India has already missed a cycle of revisions in 2017-18, which, in turn, implies that some inaccuracies may have crept in GDP estimation. Moreover, over the past decade, thanks to the controversies surrounding the PLFS and CES data as well as long-standing gaps in poverty and inequality data, not to mention the absence of Census data, the credibility of India's macroeconomic data as well as the government's claims have been increasingly questioned. The new series will also come at a time when India will be on the verge of becoming the third-largest economy after the US and China (in nominal GDP terms). That, in turn, means global investors and analysts are likely to scrutinise the results very carefully. Accuracy of the new series will be central not just for the fortunes of billions of dollars of investor money but also for the credibility of India's data and its usefulness for domestic policymaking. Do you trust India's GDP data? If not, what can the government do to improve the credibility of its GDP data? Share your views and queries at Take care, Udit Udit Misra is Deputy Associate Editor. Follow him on Twitter @ieuditmisra ... Read More
Indian Express
10-06-2025
- Business
- Indian Express
New data sources and a fresh economic calibration
The government periodically revises the base year for key economic indicators such as the consumer price index (CPI), the index of industrial production (IIP) and gross domestic product (GDP). These revisions are meant to reflect the changing profile of consumption and production in the country and incorporate newer data sources. For instance, in 2015, the Ministry of Statistics and Programme Implementation released the new series of national accounts, revising the base year from 2004-05 to 2011-12. Also in 2015, the base year for CPI was revised to 2012 from 2010. And in May 2017, the base year for the IIP was revised from 2004-05 to 2011-12. Continuing with this practice, the next year is likely to witness the release of new data series for several indicators. In an interview to this paper, MoSPI secretary Saurabh Garg has said that the new GDP series, with 2022-23 as the base year, is scheduled to be released on February 27, 2026. The new IIP series, with 2022-23 as the likely base, is expected to be released from 2026-27 onwards, and the CPI series, with the base year of 2024, is likely to be released from the first quarter of 2026. This exercise is likely to involve the use of several new datasets. For instance, in the computation of the GDP estimates, the use of GST and UPI transaction data is being explored. Neither dataset was available the last time around. Similarly, for the new CPI series, MoSPI is exploring new data sources such as online platforms for air and rail fare and price data from e-commerce websites. For CPI, the government has now decided to draw on the latest round of the Household Consumption Expenditure Survey of 2023-24 to figure out the items and the weights. Such regular updation of economic indicators using newer sources of information not only helps to improve their accuracy but also aids policymaking. For instance, the current base year for CPI, which forms the basis of the RBI's inflation-targeting framework, is 2012. But the household consumption basket has changed dramatically over the years. For example, cereals accounted for 10.69 per cent of the consumption basket in rural areas in 2011-12. This had declined to 4.97 per cent by 2023-24. For urban areas, the comparable estimates are 6.61 per cent and 3.74 per cent. Reweighting the items of consumption based on the latest data could thus impact headline inflation and possibly have policy implications. These base year revisions are, however, not without controversy. For instance, the release of the GDP 2011-12 series was followed by questions over whether it captured the state of the economy accurately. Questions were raised over the quality of some of the data as well as the deflators used. To avoid a repeat, the government should ensure that all the data sources, along with a detailed account of the methodologies used in the process, are publicly disclosed. This could help users understand the estimation process and address concerns.
