Arjun Kumar, Anshula Mehta, Mahima Kapoor, Swati Solanki
Data is a word that has taken center stage in most mainstream discussions in recent times. The World Bank’s World Development report is based on the common theme “Data for better lives” showing the level of importance of data in current times. The topic of data has been troubling many with regards to it being used to violate an individual’s privacy or using it for commercial purposes by third parties. The evolution of data has reached a peak where interpreting it is relatively easier, granting more access to the common public.
As part of the understanding, the role of data in development, Generation Alpha Data Center (GenAlphaDC) at IMPRI Impact and Policy Research Institute, New Delhi hosted #WebPolicyTalk as part of The State of Statistics – #DataDiscources-Practitioner Reflections on the Data & Evidence Ecosystem on 22nd July 2021, with Abhirup Bhunia as the guest speaker for the event.
The chair of the session by P C Mohanan, Former Acting Chairperson, National Statistical Commission (NSC), Government of India initiated the discussion by establishing the importance of data and the evolving discourse around its usage.
With this, he welcomed Abhirup Bhunia to talk about his experience being an independent development practitioner. His presentation was titled, “Reflections on evidence-based policy – Views from development practice”. He gave a detailed description of the issue his talk would cover and how it is related to the general theme of the talk.
What is Evidence?
Mr. Bhunia firstly explained the basic understanding of “evidence” in the public policy sphere and his interaction with qualitative data. Qualitative data plays a key role in influencing decisions rather than having a broad statement that includes figures to intend at trends. The latest World Development Report by the World Bank has highlighted the use of administrative data. Therefore Mr. Bhunia wanted to elaborate on the benefit of using Qualitative and administrative data that would aid the evidence generation process.
In the beginning, Mr. Bhunia distinguishes between private and public indent data comparing the quantitative and qualitative spheres that exist in these spaces. He further defined administrative data and how they are made available.
The Role of administrative data
The administrative data used must provide insights for making efficient decisions for policymaking. Mr. Bhunia breaks down different aspects of assessing administrative data such as passive, accessibility, representativeness, discoverability, and quality. To explain the benefit of having reliable administrative data he uses the example of Self-Help Groups which operates at a micro level which can provide data about the people involved in the SHG and on possible financial indicators that can be seen in the daily operations of the SHG. His point was to prove how administrative data complements the evidence ecosystem. The lack of confidence in the reliability of administrative data leads to the use of primary collection or surveys.
Generating Best evidence through Qualitative aspects
Mr. Bhunia emphasized the need for having more qualitative nuances in the process of evidence generation. There is often a misunderstood understanding that evidence generation takes place in a bubble. However, this is not the reality. Evidence generation operates in a particular political economy. The fundamental explanation for evidence lies in qualitative aspects, this is a convention being highly accepted by the stakeholders. Mr. Bhunia created a hypothetical example of data collected through a process, highly quantitative. He explains the qualitative nuances that one must explore before creating conclusions. Looking at quantitative data can only provide indicative trends and not firm conclusions.
Real word Complexities
He further commented that there exist real-world complexities in the pathways to change with information overload. He talked about the black box of process. Also, the multiplicity of stakeholders is important and needs to be understood. There exist various interests and incentives that operate within a given time and hence evidence that is generated does not operate in a bubble. Further there exist many unknowns to add up to real-world complexities.
Takeaways
In conclusion, Mr. Bhunia listed the takeaways from his talk and summarized his points on how to use data, both qualitative and quantitative in a manner that would complement each other and provide meaningful conclusions for evidence-based policy design.
He emphasized more tapping into administrative data and capacity building to have quality admin data in place. Also, Evidence needs to be situated within a complex real-world policy-making context.
The primary surveys which are being done should give consideration to the length of the questionnaire, available data points, and variables used while analyzing and generating evidence.
Reflections and Concluding remarks
Dr. Mohanan added to the discussion on the use of administrative data and described the issues presented by official and government platforms that produce this data are often in the form of metadata. The lack of detailed elaboration on the methodology used is the reason why administrative data has not found its popular use. He also supported the point on creating better platforms to get administrative data which would put less burden on the use of surveys and primary collection of data. There is also the issue of the high level of volatility in definitions and methodology set by administrations which reduces the level of confidence in administrative data.
Abhirup stated that there is a need for technological investment for having high-quality reliable data at a massive scale. He further commented that though theories inhibit a lot of potential the use cases need to be more varied to make a dent.
We should be looking at Rationalising data collection.
Acknowledgment: Arjun Sujit Varma is a Research Intern at IMPRI
Youtube Video : Practitioner Reflections on the Data & Evidence Ecosystem
Picture Courtesy: analyticsindiamag.com
