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action or later. Please see Debugging in WordPress for more information. (This message was added in version 6.7.0.) in /var/www/html/wp-includes/functions.php on line 6114COVID-19 has seen governments across the globe walk a tightrope as they scramble to contain the spread of the disease while keeping the economy stable. In this unprecedented situation, ground-level data for evidence-based decision-making assumes critical significance. This blog looks at five key lessons from MSC’s research on COVID-19.
As of 2ndJune, 2020 10:06 am CEST, the COVID-19 pandemic reached 216 countries across the globe, infected 6,140,934people, and claimed 373,548 lives. Despite the unprecedented global effort, the now infamous curve of COVID-19 shows no sign of “flattening”. Governments across the globe continue to struggle as they impose containment measures to reduce the spread, keep the health infrastructure up and running, and manage the fragile economy. In this unprecedented situation, donor agencies and research agencies across the globe are doing their bit by trying to equip policymakers with ground-level data for evidence-based decision-making.
In the past three or four months, we have seen the publication of multiple research reports. These research exercises focused on different aspects of the crisis, namely health behavior, food availability and consumer behavior, economic impact and finances, and government responses, among others. At MSC, we have a deep understanding of the poor, their household-decision making and gender dynamics, and the relationship of these factors with governments, regulators, and private sector players. The pandemic made it imperative for us to spearhead efforts to support policymakers with evidence and generate recommendations for decision-making through a series of synergistic research studies.
Five key lessons
One common challenge in all these studies was our inability to conduct face-to-face interviews to gather evidence. The uncertainty around how long the crisis will continue and how long we would have to wait to return to normal life made the process of planning the research difficult. Our solution was the tried-and-tested telephonic or online surveys. In this blog, we explain five key lessons from the research conducted by MSC in the past two months.
We have also used implementation staff, such as MFI managers and loan officers, as data collectors to utilize the existing rapport that they have with respondents. We have seen the rising use of mobile phone data to track population movement and location data to identify communities at risk. Another interesting trend is the increased use of high-frequency data collection methods like financial diaries.
Thus, agile monitoring and feedback loops are essential, as are the channels to provide insights to key decision-makers. This also highlights the need for country-level research systems that can respond to this type of emergency by providing high-frequency monitoring data to policymakers. For years, MSC has been providing rapid feedback to the Government of India to identify successes and failures in policies and to do course correction as needed.
The successful implementation of DBT in Fertilizer in India is one such example where we provided rapid and iterative feedback to the government for it to modify parts of the program as it was scaled up across the country. Similarly, MSC created an index to rank states to provide rapid feedback on COVID-19 to the Indian government based on the states’ initiatives.
The report structure is prepared ahead of the data collection commences and analysis syntaxes are readied before the data starts coming in, based on the data structure decided in the beginning. This is setting a new benchmark for the industry, and even in the post-COVID scenario, we can expect results within a similarly rapid turnaround time.
Several words of caution
Research agencies are competing with each other to reveal results before anyone else. In the process, they sometimes miss important nuances. We are seeing many “percentage values” that are offset with inadequate discussions of the story and the drivers behind them. A meaningful research story often depends on the collection of qualitative data, which is much harder to do effectively over the phone and requires skilled moderators. Recitation of data, without answering the “why?”, “where?” and “so what?” questions that flow from it, short-changes policymakers.
We have also seen that where pre-enrolled panels of respondents are used, these have often answered too many quantitative and qualitative questions already and suffer response fatigue—an upshot of the plethora of research underway.
Another challenge is the fact that sometimes these insights come at the price of compromising statistical robustness—a challenge that the reports themselves do not acknowledge adequately.
Moreover, there is a high chance of making technology-driven data collection the “new normal” in the post-pandemic scenario. Yet that will widen the already existing exclusion of peoples’ voices from the ground, as we depend evermore on survey agencies that offer access to pre-enrolled panels of respondents, which are typically designed to provide rapid feedback to FMCG companies. Hence, these panels are therefore typically drawn from the affluent and middle classes rather than the poor and vulnerable communities that have been hit the hardest by the pandemic.
Moreover, the entire population, which largely lacks access to the phone or internet, is by definition completely excluded from these insights. These very people are most vulnerable to the pandemic. It is therefore essential to be selective in choosing panels and to force these research companies to focus on gathering voices from the poorer and marginalized corners of society.
Just as we have changed the way we conduct our lives in a fundamentally different way after COVID-19, research protocols, too, are likely to undergo a seismic shift as the world looks toward the long path of recovery.
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