Context

Challenges and opportunities of Data-based Governance.

Data-based Governance

  • Data is considered as the new currency currently driving governance.
  • From Hunger and other indices to the caste census, data is the centre of focus.
  • How it is coll­ected, interpreted, and developed into an index are debated and often have been controversial.
  • The pandemic management that relies heavily on data in terms of testing, vaccinating or tracking recoveries and deaths has increased this debate over data.

Gist of Economic & Political Weekly (EPW) For UPSC IAS Current Affairs Preparation

Evidence-based policy (EBP)

  • The reason for the prominence of the data-driven approaches is because of the evidence-based policy (EBP).
  • The EBP has been regarded as a rational form of governance that bases its decisions on objective data rather than external pressures.
  • According to Sutcliff and Court “the pursuit of EBP is based on the premise that policy decisions should be better informed by available evidence and should include rational analysis.”
  • EBP is said to be important for deve­loping countries as public resources are often scarce or limited.
  • It req­uires both data and the process of data collection to be scientific, rigorous and validated both in the process of coll­ection as well as analysis.

Gist of Economic & Political Weekly (EPW) For UPSC IAS Current Affairs Preparation

Historical background of the usage of EBP

  • Tracing the history of the process of data collection, it could be seen how European countries accumulated large volumes of data in the early 19th century on a range of variables that often did not lead to any meaningful analysis.
  • The analysis of Foucault’s “bio­politics” into “overt” and “subversive biopolitics” in the Canadian context where the very first census of the population took place in 1666 shows how the overt bio­political agenda i.e tax incentive for larger families in the Canadian context, did not have the intended effect but the subversive biopolitics in the form of “categorisation” of the population that took roots persists till date.
  • Analyzing the historical perspective is important as it shows how state formation has been linked to “data regi­mes, statistics and probability.”
  • Further, the entire process of data collection in the digital generation is distinct from the 19th-century processes.

Gist of Economic & Political Weekly (EPW) For UPSC IAS Current Affairs Preparation

Role of Information and communication tech­no­logies in policymaking

  • Information and communication tech­no­logies (ICTs) have had a revolutionary impact on the way data is viewed currently as it rec­onfigures relationships between states, subjects, and citizens.
  • Big data, machine learning and algorithms are the frameworks within which citizens operate, unaware of how these digital interfaces are converting them into data to be used by unknown entities.
  • It is in this context it is necessary to make the distinction bet­ween politics of data and “data politics”.
  • In the age of data politics, new players like multinational corporations that control ICTs and social media platforms are becoming more significant forces than the state.
  • This is alarming as unlike the checks and bala­nces that limit the state’s influence, these large, transnational corporations are not constrained or held accountable by any such mechanisms.

Gist of Economic & Political Weekly (EPW) For UPSC IAS Current Affairs Preparation

Data-based Governance

  • Gathering large volumes of data regarding the public by the state through census, surveys, etc, and currently via digital platforms has gained momentum in the context of EBP.
  • Aim: To assist the use of research and evidence to inform workable funding decisions.
  • Goal: To further ­invest in what works to improve outcomes for citizens based on prior evidence.
  • Data-based governance aims to create a system of reliable and validated data with associated infrastructure.
  • The governance outcomes are difficult to measure bec­ause governance outcomes are a combination of tangible outputs and intangible processes.
    • Measuring only tangible outputs without capturing the intangible processes provides ambiguous conclusions.
    • Example: in trying to evaluate women’s participation in a gram sabha, not only the number of women participants (outcomes) but also the nature of parti­cipation (process) should also be captured.

Gist of Economic & Political Weekly (EPW) For UPSC IAS Current Affairs Preparation

Challenges

  • States collect huge volumes of administrative data. But a large portion of these data are unutilised or are underutilized as these administrative data are not validated or updated.
  • The same data is collected by different agencies with different identifiers making consolidation of data difficult.
  • The admi­nistrative data is usually kept confidential and is beyond the reach of the public and researchers for scrutiny or analysis.
  • Measuring governance is a complex task. Especially the law and order aspect of governance.
    • Example:
      • Few studies use estimates of crime rates (ECR) as their indicator which looks at the total number of criminal cases reported.
      • While other studies look at the estimates of industrial disputes and strikes (EIDS) to assess worker satisfaction.
      • Similarly, another study takes into account the complaints against Police behaviour as their indicator.
    • The problem of ambiguity.
      • Example: The central government’s edu­cation survey ranks TN 4th in educational attainment, but another index shows that 27 of TN districts as being educationally backward.

Gist of Economic & Political Weekly (EPW) For UPSC IAS Current Affairs Preparation

Recommendations

  • If governance decisions are to be data-centric, there is a need to ensure a system of good, robust and reliable databases.
  • There is a need for a decentralized system of data collection process where states should build their databases from scratch.
  • States should invest in both human and technical infrastructure with quality control measures to ensure that policy decisions are based on robust and rigorous data.
  • The data-based governance req­uires validated and scientific data.
  • The policymakers should use data wisely to ensure equality and equity.

Conclusion

In the age of a data-driven world, the means of governance are being forced to become data-centric. In this situation, data-based governance or policymaking is a step in the right direction. However, the challenges associated with data-centric governance should be addressed to make it more reliable, credible, and transparent.

Similar Posts