Q) The ongoing pandemic has shown that the lack of accurate and workable data can have disastrous consequences. What are the challenges that India faces in the adoption of data-based policymaking? Suggest measures to address these challenges. (250 Words)
Source: https://www.thehindu.com/opinion/lead/under-reporting-does-hurt-the-covid-fight/article34474676.ece
GS 2: Governance, Government Policy
Approach Answer:
Introduction: Based on ICMR's third Sero-survey, it is estimated that only 6% of all COVID cases were detected till January 2021. This meant that the authorities were prepared for the lesser number of patients based on the faulty data from the first wave of corona virus, when the 2nd wave hit. This has shown the importance of accurate data in the governance and planning of a country.
- Importance of Data-based policy making:
- Marginal benefit: For every cost of expenditure done on analysis, greater benefit is achieved in terms of policy outcome. For example - price discovery mechanism under e-NAM benefits millions of farmers.
- Responsive policy: Such a policy have an opportunity to change with the changing data.
- Resource allocation efficient: Resources are deployed where they are needed.
- Citizen-centric Governance: Government can plan targeted policies on health and education.
- Curbing Leakage: Such as in taxation, subsidies etc.
The data based policy making is thus like 'crossing the river by feeling the stones'. Without it, policy is blind.
- Challenges in Adoption of data based Policy making:
- Silos of Data: There is a lack of unified data. For example around 53% of public data lies under the corporate sector in India.
- Privacy Problem: There is a fiduciary responsibility of the data collector. Greater the data collected, greater is the risk of breach of privacy.
- Poor data analytics: The Government has huge amounts of data with tax departments, banks, hospitals etc. However, it lacks the ability to analyse it adding more to the risks than advantage.
- Integration challenge: The COVID-19 has shown that there is no mechanism of data verification or its integration between different levels of government. The Data from Municipalities of number of COVID dead bodies cremated and those which are declared dead do not match.
- Technology deficit: Many government departments are not connected with the centralized system, making data collection a challenge.
- Difficult to work on: Much of data is not in easily searchable format, which makes data analysis even more difficult.
- Measures to address these challenges:
- Data Gathering: Digitalization of all existing paper-based data, which is also mandated by Section 4 of RTI act. Further the digitalized collection of data at source.
- Storage: Initiating real time storage, by reducing lag between data collection and its entry. This can be made easier once each government office is connected with BHARATNET.
- Data Processing: Building capacities in government offices, for analysis and generation of insight. For this private sector must be involved.
- Data dissemination: Non-sensitive government data must be open for all for third party studies. This would allow universities in India to come up with better research regarding development and planning.
- Enhanced Integration: Integration between government departments. PRAGATI portal is one of finest example regarding this.
- Investment: in big data analytics, connecting all government offices with a centralized network like NIC or SWAN, installing computer systems in all Panchayats and government offices requires huge investments.
- Training: Further, after creating all the infrastructure, human resources must be trained too.
- Addressing privacy: The recommendations of BN Srikrishna committee and the Data protection bill are great steps in this regard.
Conclusion: The Economic Survey of 2018-19 proposes that the data collected by the government must be treated as a public good. Since it is data by the people, of the people; everything must be done to use it for the people. In this age of fourth Industrial revolution, data based policy making becomes the way forward.
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