Socioeconomic Dashboard

Informed policymaking for Covid-19 recovery

Towards a Solution

Based on the guidelines and indicators mentioned in the Bangladesh Preparedness and Response Plan (BPRP) and the United Nations Immediate Socio-economic Response Plan (UN ISERP), this project aimed to develop an intelligence dashboard on COVID-19 impact and recovery management. The project deployed artificial intelligence and machine learning, as well as other emerging technologies and tools, in order to tailor government response to the needs of the beneficiaries and response agencies and support informed and responsible decision-making, and better management the impacts of the pandemic in Bangladesh.

The Aspire to Innovate (a2i) Programme presented the dashboard during the National Data Coordination Committee (NDCC) meeting and relevant government offices agreed on its importance. The dashboard was then presented during a meeting of the SDG Technical Working Committee, which was led by the Director General of Bangladesh Bureau of Statistics. During the meeting government stakeholders discussed the importance of such dashboard that can present the impact and guide them for better recovery from COVID-19, and the Committee approved its integration into the SDG Tracker as a new tab named “COVID-19 Recovery”.

One key lesson learned from the initiative is the effectiveness of government collaboration. Since the implementation project happened during the period of the pandemic, it was necessary to establish engagement and ownership of government policymakers from the beginning. From the developmental phase of the dashboard, the relevant government agencies were mapped and communicated to ensure the real picture of the data requirement was captured. It also helped in the generation of necessary policy insights. Otherwise, it would have been really difficult to achieve such remarkable progress during a short period of time. 

Another lesson is the use of the proxy indicator. Data-driven insight is a major component of any sort of decision-making. But sometimes, data isn’t available according to the required indicator framework. In those cases, the use of available proxy indicators can be of significant assistance in insight generation and decision process.

Another major takeaway is the understanding of the importance that non-government data has in capturing the total analytical picture for policymaking. Sometimes, administrative data availability comes under a lot of restraints. This hampers the overall data-driven decision-making and subsequent policy-making process. If non-government data such as research organizations’ data, academic data can be used in alignment with existing government data, it can play a vital role in government decision-making.