Are Southern States better equipped to absorb the impact of the lockdown? A study by Hyderabad-based Indian School of Business (ISB) says so.
The work disruption due to the lockdown, to check the spread of coronavirus, has been the least in South India when compared with the rest of the country, the study has revealed, stating the reason of Southern States have a high work-from-home potential.
The ISB study was based on a survey of 3,000 workers to measure the impact of the lockdown on over 100 occupations as defined in the National Classification of Occupations (NCO) of the Ministry of Labour and Employment.
The objective of the study was to find out how the lockdown has impacted occupations and industries across several districts of India.
The researchers gave each occupation a: 1) “work from home” (WFH) index to denote an employee’s likelihood of working remotely and 2) “human proximity” index (PI) to denote an employee’s need to physically work with other people.
For instance, a computer programmer’s job would have high WFH potential and agricultural labour would be at the lower end.
When researchers mapped the two indices based on location, they found that cities had a higher potential for work from home. Likewise, urban districts were found to be more amenable to the WFH factor.
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Overall, the companies located in the southern states are found to be better equipped to deal with the prevailing conditions because of a higher flexibility to adopt work-from-home practices or automate work.
“Not just the urban centres such as Hyderabad, Chennai or Bangalore but the entire peninsular south India scored high on WFH home index,” said Shekar Tomar of the ISB faculty of economics and public policy who was involved in the study.
“We have used these two indices to create a third measure– Disruption Index (DI)–to assess the impact of lockdown on a given profession. The results have indicated that south India, which is high on WFH potential and low on human proximity, would face moderate disruption compared to higher disruption across north India,” said Deepa Mani, the executive director of a research centre at ISB.
Even within urban areas, there were variations. In Delhi, for instance, the north-eastern part of the national capital was found to be facing higher disruption compared to the southern part. This could be explained as Northeast Delhi had more labour-intensive manufacturing units.
The researchers felt disruption index data would help policymakers determine the extent of fiscal support needed by different sectors.
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With the two indices — WFH and PI — lined-up perpendicular to each other, the occupations were classified into four quadrants — low work from home and high human proximity, low work from home and low human proximity, high work from home and high human proximity and high work from home and low human proximity.
A set of six questions was developed by the researchers to assess if physical proximity, on-site presence or working with teams were vital to do the job. The study found that the two indices had a significant negative correlation with each other.
The results were reasonably intuitive, like in the cases of drivers, housemaids, and nurses who displayed low work from home potential.
The sectors like computer programming have high work from home potential. In contrast, those like agriculture, wholesale or retail trade and collaborative manufacturing had a lower potential for work from home. A few sectors, like textiles and occupations like restaurant services, were found to have little human proximity and low potential for work from home.
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Some occupations, like middle school teaching associates, which have a high work from home potential and high human proximity, were found to be highly susceptible to automation. This is because of their high work from home potential.
“Though we see very few occupations in this quadrant, this might well be the time when a lot of occupations move to this quadrant of high work from home potential and high human proximity,” said Deepa Mani who heads the Srini Raju Centre for IT and the Networked Economy (SRITNE).
The two indices (WFI and PI) were mapped, district-wise and industry-wise, to determine the impact of the current lockdown.
In this district-level measure, researchers find that cities had a higher potential for work from home, with many services based from here. Also, some urban districts were found more amenable to work from home.