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Indian State was set up to control, not govern. Data-driven policy-making can be antidote

The Indian State failed to evolve from the design set by the British. Today, the structure undermines its development goals—prioritising data can help.

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Currently, there is an ongoing debate on the number of deaths that the Covid pandemic caused in India, with the World Health Organization claiming it is 10 times higher than official estimates. The estimated death toll across multiple reports ranges from three to six million above the officially recorded 5,20,000+ deaths so far. The lack of data, or rather, the lack of acknowledgement of data, has wide-ranging implications for building State capacity that will promote good governance and productive growth.

The Indian State, today, still largely functions as it did under the British Raj. In an earlier article for ThePrint, we argued that the Indian State, under the colonial design, was set up to control rather than govern its citizens. Today, this structure, which failed to evolve with time, obstructs the State from providing public goods to citizens and, in turn, undermines the nation’s development goals.

This is not to say that authorities intend to be controlling, nor is this facet of the Indian State attributable to a specific government or political party. In the early 1900s, a few thousand British officials ruled over a country of 300 million people and held discretionary powers in managing the State. After Independence, the inherited administrative structure changed little. For instance, since 1947, the Indian Foreign Service has barely grown in absolute numbers. Currently, the country has a minuscule number of Foreign Service Officers — less than Sweden, which has approximately 0.007 per cent of India’s total population.

The existing system, therefore, fosters an environment that hinders large-scale changes. Moreover, the absence of quality data and knowledge of methods to analyse it yields an incomplete picture of the Indian State. This, in conjunction with the significant discretionary powers awarded to the executive and arms of the State, makes data-driven policymaking a challenging option.

Legal and political reforms to devolve powers are unlikely to occur anytime soon, but deploying data can help shape policies to be more effective and equitable while also combatting the State’s inherent controlling tendencies.


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India once prioritised data, but focus has shifted

When India achieved Independence, Prime Minister Jawaharlal Nehru stressed the importance of collecting data to ensure that policy objectives could be properly implemented. In a letter to chief ministers, he argued that the absence of effective measures to overcome poverty would be “disastrous” for the country. He asked for food provision programmes to be assessed and that CMs “take every possible step to mobilise all statistical data lying unused in village and district records and undertake special enquiries for collecting such data as may not be available.” This focus on developing India’s ‘scientific temper’ and using rationality as an intellectual basis for policy decisions enabled the proliferation of various agencies, surveys, and organisations in strengthening India’s nascent data-collection ecosystem.

Pivotal in this effort was P.C. Mahalanobis, regarded as the Father of Indian Statistics. In 1949, he was appointed as the honorary statistical adviser to the Indian Cabinet and established the Central Statistical Unit. The Central Statistical Organisation (CSO) was then formed in 1951 to coordinate the statistical activities in independent India. Simultaneously, the National Sample Survey (NSS) was established as a multi-faceted fact-finding body. In 1961, the CSO and NSS were put under the Department of Statistics and later merged with the Department of Programme Implementation in 1999 to create the Ministry of Statistics and Programme Implementation (MOSPI).

Further, the National Institute of Statistics had been globally recognised as a pioneer in survey creation and implementation by the 1950s. In parallel, the Planning Commission of India, now called NITI Aayog, enabled bureaucrats to harness statistical data to plan the economy and also share insights with state governments through frequent interactions in the National Development Council. The presence of these agencies resulted in a range of data-collection exercises, such as the decennial census, annual economic surveys, national committees to measure income levels, and more.

In recent years, this statistical heyday may be giving way to the State’s controlling tendencies, despite the volume of data continuously increasing. For instance, since the introduction of Member of Parliament Development Funds (MPLADS), nearly three-fourths of MOSPI’s budget has been allocated to the MPLADS, in contrast to approximately 10 per cent for the National Statistics Institute and NSS. It could arguably signify that MOSPI’s focus is shifting away from statistical design/modelling and implementation. For successful, accountable, and transparent governance, the Indian State needs to further leverage data collection and use.


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Policy suggestions

The way forward is not new or unknown. Multiple scholars, experts, and committees have reiterated how better data collection can help policymakers achieve their goals.

Data-driven policymaking demands robust physical infrastructure such as high-powered computers and strong internet connections, as well as human capital, including bureaucrats and other officials trained in the necessary technical skills, with frequent sessions to update themselves with the latest advancements. In almost all aspects, India falls behind in maintaining requisite standards. M.R. Sharan writes in his book Last Among Equals about the irony of local-level officials streaming videos on their phones while waiting for the internet to work in their offices. The scarcity of computers and reliable internet is a reality in many parts of the country.

However, it is not enough to have physical infrastructure and human capital; they must go hand-in-hand to translate into policy decisions. Andhra Pradesh’s data dashboards have meaningfully helped the state in reducing the impact of droughts and minimising leakages in welfare schemes.

It is also essential for state governments to give more thought to the frequency of data collection, the granularity of data, and its access. More real-time data collection can feed into quick decisions. Moreover, such data should be made publicly available for researchers, academics, and statisticians to aid the government in better understanding and reacting to ground realities.

At the same time, it is important to pay attention to data collection processes. Rukmini S. in her book Whole Numbers and Half Truths shows how the National Crime Records Bureau (NCRB) collates crime statistics using the ‘principal offence rule,’ where it only records the Indian Penal Code charge in an FIR that charges the maximum penalty. If someone were to rob a house and also murder its owner, the NCRB would only record the murder as a crime, and not the theft because of this rule. Consequently, crime statistics could be skewed because of the way that the data is collected.

It’s not just about numbers, but the considerable consequences resulting from them. Barkha Dutt in To Hell and Back shows that if a death isn’t counted as a Covid-related death, citizens are not counted as people or statistics, and families suffer the consequences emotionally and economically. For instance, the government announced schemes for children whose parent(s) succumbed to the virus, but if Covid isn’t listed on the death certificate, the child/family cannot receive the benefit.

India’s response to the pandemic has shown us that policymaking, as in many parts of the world, has been reactive rather than proactive. As India moves into a post-pandemic world, it is imperative to prioritise good quality data at national, state and local levels to encourage policymakers to not only develop nuanced and effective policies in building state capacity but to also overcome the State’s inherent tendency to centralise.

Vibhav Mariwala studied History and Anthropology at Stanford University. He tweets @VibhavMariwala. Kadambari Shah is a policy researcher. She tweets @kadambari_shah. Views are personal.

(Edited by Humra Laeeq)

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