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Using Evidence in Governance - the Need for an Enabling Ecosystem

Using Evidence in Governance - the Need for an Enabling Ecosystem

Using Evidence in Governance - the Need for an Enabling Ecosystem

27th Jul, 2022
Author Name
Nicole Almeida, Young Professional, DMEO, Soumya Kochhar, Intern, DMEO
Posted by
NITI Aayog, New Delhi, India

Over the last few years, there have been calls to make policy-making more evidence based. But what really is evidence? And how can policy-makers use it? Evidence consists of collecting information in a systematic way and using a number of approaches to answer a particular question. If one asked, what ensures the adequate use of fertilizers by farmers? There would be various ways and methods to answer this including - key informant interviews with the relevant stakeholders, case study of a particular area, an experiment where various theories are tested, etc. Here evidence is not just created and collected in one way, but a variety of approaches strengthens the analysis and conclusions drawn from the evidence. Evidence-based decision-making is grounded in such evidence rather than preconceived opinions, hinges, intuition, etc.

To enable such an environment across government, it is integral to put in place systems that generate evidence and ensure that the evidence is credible, accurate, rooted in reality, and objectively generated[1]. The users of this data – scheme and program implementers, managers, and policy makers would also need to have the capabilities or systems to structure, analyze and use this data.

Similarly, creating such systems would mean having policies to facilitate and guide data generation, sharing and use. The National Data Sharing and Accessibility Policy (NDSAP) of 2012 was published to promote evidence-based planning and enable sharing of non-sensitive government owned data with the public and other arms of the government. The Ministry of Electronics and Information Technology (MEITY) has released a draft policy titled, ‘India Data Accessibility and Use Policy’ to boost ‘government to government’ data sharing and integration of various Management Information Systems (MIS) so that datasets can be merged and analyzed.

Building such comprehensive databases is the first step in creating structures to efficiently deliver services and set up a social protection system that can withstand calamities, natural hazards and pandemics. The state of Karnataka has led the way and launched the Kutumba project which uses data from the Public Distribution System as a base and has other registries merged with it. Data is updated dynamically and is validated from other sources. The result is a dynamic comprehensive database that contains information about individuals and families, their landholdings, occupation, education level, income, etc. This beneficiary registry system also contains information regarding the benefits received by an individual or family such as housing, social security pensions, MGNREGA, COVID financial relief, etc. This information helps the government identify families that have not received benefits but are entitled to receive them. Government schemes then automatically reach those entitled to benefits through the Kutumba system[2]

Various ministries and departments in the government also have MIS and dashboards to monitor progress and collect evidence on projects and schemes. For example, in 2018, the Ministry of Women and Child Development launched the Poshan Tracker, known as ICDS-CAS (Integrated Child Development Services - Common Application Software) in its earliest avatar, which facilitates real-time monitoring and tracking of all Anganwadi Centers (AWC), Anganwadi workers (AWWs) and beneficiaries on defined indicators. The dashboard enables data collection on Integrated Child Development Services delivery and its impact on nutrition outcomes on a regular basis. Having a summary of the data in one place facilitates monitoring by all stakeholders. Such rich administrative data from ministries and departments needs to be leveraged to push India’s development and improve outcomes for the marginalized and poor. Digital India, which is a flagship program of the government, involves computerization of data such as land records, railway computerization, etc. amongst many other initiatives that form key components in the move towards evidence-based decision-making.

Institutional changes that increase the demand for data are underway. The Outcome-Output Monitoring Framework which breaks down schemes into measurable outputs and outcomes has been tabled along with the Union Budget since 2017. This framework has measurable indicators, targets and financial outlays. Such outcomes-based monitoring signifies the move from assessing progress of schemes based on financial and physical progress, to measurable and evidence-based outcomes. Monitoring performance in such a way can ensure that schemes that are non-performing be reviewed, rectified or rationalized. A demand for measurable outputs and outcomes implies a demand for systems to capture the required data. With an enabling environment and structures in place to supply and demand evidence, evidence can inform program assessment, budget development, implementation oversight, monitoring and evaluation.

To enhance the effectiveness of projects, schemes, policies and legislations, it is integral to create and collect evidence on what works and monitor and evaluate how effective it is. Efficient and cost-effective schemes that serve their purpose can be scaled up. Similarly, evaluations should inform learning, and recommendations from evaluations should be adopted to enable schemes to fulfill their objectives.

Data is always changing, improving and growing. Overtime, with new technologies, we might have multiple data points on the same subject as well as new data. While it is important to use different approaches, it is also important to understand that with new information, inferences and analysis can change. This can be of concern to the policy maker, and the public who is at the receiving end of policies. For example, in the first few months of COVID-19, the data on effectiveness of masks kept changing as more data kept coming in overtime, leading to changes in policy on wearing masks in response to the fresh evidence. Thus, another important skill for evidence-based policy making is understanding and communicating the limits and nature of the evidence and the rationale behind decisions.

Successful evidence-based policymaking requires pragmatism, will power to simplify complex evidence and the use of scientific evidence as the base of governance. Evidence-based policymaking holds a promising future but despite its appeal, it faces many institutional challenges such as difficulty in providing relevant evidence and need for more quality data and capacitation to effectively use and build evidence. However, the proliferation of agencies supporting evidence-based policymaking has fostered a results-based learning environment. It is imperative to recognize data as a public good. The more widely data is shared, greater is the likelihood of its integration into policymaking as well as effective usage of limited resources. Creating an enabling environment by leveraging technology, combining administrative datasets, building an evidence reservoir and developing capacities to use evidence can be the thrust for the government to reach the last mile and accelerate India’s development story. Many initiatives are underway in this direction.

Disclaimer: Views expressed are personal.

[1] ODI. (2005). Evidence-Based policymaking: What is it? How does it work? What relevance for developing countries?

[2] Government of Karnataka and Centre for E-Governance, 2021

Over the last few years, there have been calls to make policy-making more evidence based. But what really is evidence? And how can policy-makers use it? Evidence consists of collecting information in a systematic way and using a number of approaches to answer a particular question
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