CONTACT US

084594-00000

About Us  :  Online Enquiry

Download

Data Governance Quality Index

Data Governance Quality Index

Introduction

  • Data Governance Quality Index Report, a Survey conducted by Development Monitoring and Evaluation Office (DMEO), NITI Aayog to assess different Ministries /Departments’ performance on the implementation of Central Sector Schemes (CS) and Centrally Sponsored Schemes (CSS).

About Data Governance Quality Index

  • It is a survey conducted by Development Monitoring and Evaluation Office (DMEO), NITI Aayog.
  • The objective of the survey is to assess different Ministries /Departments’ performance on the implementation of Central Sector Schemes (CS) and Centrally Sponsored Schemes (CSS).
  • The DMEO, Niti Aayog has undertaken DGQI exercise for the following purpose:
  • Self-assessment based review of data preparedness levels across Ministries / Departments to produce a DGQI score card;
  • Assessing data preparedness of Ministries / Departments on a standardized framework to drive healthy competition among them; and
  • Promote cooperative peer learning from best practices.

Central Schemes

  • The central schemes are divided into Central Sector Schemes and Centrally Sponsored Schemes (CSS). rd nd 1/3
  • Central sector schemes:
    • These schemes are 100% funded by the Central government.
    • Implemented by the Central Government machinery.
    • Formulated on subjects mainly from the Union List.
    • g.: Bharatnet, Namami Gange-National Ganga Plan, etc.
  • Centrally Sponsored Schemes are the schemes by the centre where there is financial participation by both the centre and states.
  • Centrally Sponsored Schemes (CSS) are again divided into Core of the Core Schemes, Core Schemes and Optional schemes.
  • Currently, there are 6 core of the core schemes while 22 core schemes.
  • Most of these schemes prescribe specific financial participation by states. For example, in the case of MGNREGA, state governments have to incur 25% material expenditure.
  • The 6 core of the core CSSare:
    • Umbrella Programme for Development of Other Vulnerable Groups
    • National Social Assistance Programme
    • Umbrella Programme for Development of Minorities
    • Mahatma Gandhi National Rural Employment Guarantee Program
    • Umbrella Programme for Development of Scheduled Tribes
    • Umbrella Scheme for Development of Scheduled Castes

What is the role of data in governance?

  • For digital economy growth: Affordable access to the internet and an encouraging regulatory system has made India the country with the second-largest internet users in the world and has powered its digital economy.
  • Better decision making: The rapid technological advances have led to large volumes of data being generated by various activities, thus, increasing the dependence of business on data-decision making.
  • Political accountability: Open government data can create political accountability, generate economic value, and improve the quality of federal initiatives. The possible benefits of Big Data analytics in government could range from transforming government programmes and empowering citizens to improving transparency and enabling the participation of all stakeholders.
  • Citizen empowerment: Since the launch of the Digital India Program, the country has witnessed tremendous growth in digital infrastructure and initiatives in innovating e-governance policies that can lead to digital empowerment of citizens.
  • Prevents leakage: Real time monitoring of Direct Benefit Transfer could reduce any potential leakage. It would also lead to need based improvisation in the governance without any lag.
  • Efficient administration: Actively engaging policy makers and researchers with the processed data is crucial for making targeted and tailored programmes could improve the efficiency of programmes.

Development Monitoring and Evaluation Office

  • Constituted in September 2015 by merging the erstwhile Program Evaluation Office (PEO) and the Independent Evaluation Office (IEO).
  • Attached office under NITI Aayog, aimed at fulfilling the organization’s monitoring and evaluation (M&E) mandate and building the M&E ecosystem in India.
  • DMEO’s vision is to improve sustainable outcomes and impacts of the government.
  • It aims to enable high-quality monitoring and evaluation of government programs to improve effectiveness, efficiency, equity and sustainability of service delivery, outcomes and impacts.

Challenges

  • Collection of data:
    • Collection of data is a paramount task for government as data is received from multiple online and offline channels.
    • Sharing data between departments and across ministries is a challenge, given the jurisdictional boundaries that exist.
    • Moreover, there has been a lack of consistent dialogue and coordination between key stakeholders.
  • Political will for utilizing data in governance:
    • Data driven policies would be more realist and may target long term benefits. This may go against popular will. Hence, strong political will is required to implement such policies.
  • Privacy concerns:
    • While privacy of data is important for businesses and government, public trust in government is particularly important. Hence, any breach of confidentiality regarding data that is collected and processed by the government could have serious ramifications.
    • According to The Internet Crime Report for 2019, India stands third in the world among top 20 countries that are victims of internet crimes.
  • Funding & Innovations:
    • While access to personal data has skyrocketed, funding targeted towards cross disciplinary research on data governance has remained limited. This has led to a dearth of original research that policymakers can draw upon when trying to make sound policy decisions on data governance in India

Way ahead

  • Capacity building: Technological companies and start-ups, which can offer solutions in data analytics by managing massive, complex data, need to be encouraged.
  • Open Data Policy: Holistic decisions could be made if various government organizations share the pieces of data in their possession. Sharing and monitoring the collected data can help to make a democratic and cost effective governance process
  • Legislative reforms: Data collected by various entities is processed and disseminated in various forms. During this process, it should be ensured that the information is not distorted; not disclosed; not appropriated; not stolen; and not intruded upon within specified rules and guidelines.
  • The proposed “Data Protection bill” and the report by Kris Gopalakrishnan committee may prove a milestone in this direction.
  • Also, data protection and privacy regulations and guidelines, as exemplified by the EU’s General Data Protection Regulation, is prerequisite.
  • Funding the innovations and research: A structured mechanism should be established for financial contribution of industries in the research field. Also government should put funding of research in priority list.

Conclusion

  • Quality data, if analysed at the right time, can be critical for programmatic decision-making, efficient delivery of schemes, and proactive policy revision. Big Data can have a big impact only if used on a massive scale (with safeguards) by governments for the delivery of public goods and services.

ALSO READ: https://www.brainyias.com/iasbuzz/centrally-sponsored-schemes-css/

Mussoorie Times

close-link

Send this to a friend