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The Ministry of Statistics and Programme Implementation (MoSPI) recently published a revised draft of its National Policy on Official Statistics (NPOS), which intends to offer a comprehensive and cohesive framework for the production and dissemination of official statistics in India.
The proposed policy emphasizes the need of using big data analytics, artificial intelligence (AI), and machine learning (ML) to improve the quality, timeliness, and relevance of government statistics.
It also emphasizes the importance of collaboration and coordination among many stakeholders in India’s official statistical system, such as central and state governments, research institutes, the commercial sector, civil society, and international organizations.
The draft policy is an update to the previous draft, which was presented in 2018, and is based on suggestions from the National Statistical Commission (NSC) and the United Nations Fundamental Principles of Official Statistics (UNFPOS).
The UNFPOS, which India adopted in 2016, establishes rules for maintaining professional independence, impartiality, accountability, and transparency in official statistics.
The draft policy aims to put these ideas into practice in the Indian context and to link them with developing data demands and difficulties.
The draft policy recognizes the potential of big data sources, such as administrative records, satellite imagery, social media, mobile phone data, internet transactions, and so on, to complement and supplement traditional sources of official statistics, such as censuses, surveys, and registers.
According to the draft strategy, the Indian official statistical system must realign its policies to collect, assemble, process, store, integrate, analyze, and disseminate data using emerging technologies such as AI/ML.
It also recognizes the importance of addressing concerns such as data quality, privacy, security, ethics, and governance when using big data for official statistics.
Another critical part of the draft strategy is the creation of an integrated data system (IDS), which will allow data to be shared and linked across different domains and levels of government.
The IDS will aid in the production of core statistics, which are defined as a set of essential indicators reflecting key aspects of national life such as national income, production, services, budgetary transactions, money and banking, capital market, external sector, demography, social and environmental sectors.
All levels of government will be required to gather and disseminate key statistics, which will be issued on a regular basis.
The draft policy also calls for innovation in survey design and technique in order to lessen the burden on respondents and increase response rates.
To reduce survey costs and improve survey quality, it proposes using mixed-mode data collection methods such as web-based surveys, computer-assisted personal interviews (CAPI), computer-assisted telephone interviews (CATI), and so on.
It also advises adopting adaptive sampling strategies to increase survey efficiency and accuracy, such as responsive design and adaptive cluster sampling.
The new strategy also aspires to improve the quality of official statistics by implementing international best practices and standards. It suggests creating a quality assurance framework (QAF) for official statistics that specifies the quality dimensions, criteria, and indicators for measuring and improving the quality of statistical products and processes.
It also intends to set up a quality audit mechanism (QAM) for official statistics, which will perform independent audits and evaluations of statistical activities and outputs.
In addition, the proposed policy emphasizes the timely transmission of official data in order to meet the information needs of various consumers. It recommends the use of an advance release calendar (ARC) for official statistics, which specifies the dates and frequency with which statistical reports and publications are released.
It also suggests employing other modes and platforms for communicating government statistics, such as web portals, mobile applications, dashboards, infographics, and so on, to improve accessibility and usability.
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