Work from Home in the time of COVID-19

The outbreak of the novel coronavirus (COVID-19) and the subsequent work-from-home imperatives and lockdowns have led to significant economic disruptions around the world.   | Photo Credit: Getty Images

The outbreak of the novel coronavirus (COVID-19) and the subsequent work-from-home imperatives and lockdowns have led to significant economic disruptions around the world. As several millions of workers across diverse sectors are asked to self-quarantine, an understanding of the impact of this shift and mitigation strategies becomes critical. The insights from prior studies on the impact of work from home arrangements do not extend to the current context since these arrangements were mostly limited to a select group of workers and/or organizations and were often self-selected.

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To better understand the implications of the current imperative to work from home, including readiness of different sectors, cities, and occupations, we measured suitability of diverse occupations to work from home in India. We use a survey of over 3000 workers done in 2019 over 100 occupations listed in the 2004 National Classification of Occupations to assess the susceptibility of the occupations to automation. We use the survey questions to generate an index of suitability of the occupation to remote work or work from home (WFH) and the need for human proximity (HP). We then used the survey questions to create scores for WFH and HP for each occupation. The questions are designed such that a “1” (Strongly Disagree) corresponds to low WFH and HP and a “5” (Strongly Agree) corresponds to high WFH and HP for the occupation. The values for each occupation-level score are then averaged to obtain occupation-weighted industry and district scores for WFH and HP.

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Figure I below presents the distribution of occupations along the two dimensions. The figure highlights the negative association between the two dimensions — the greater the need for human proximity, the lower is the suitability of the occupation to work from home. For example, occupations with highest suitability to work from home include occupations such as directors, computing professionals, and general managers, who also require minimal human proximity in executing their jobs. In contrast, the occupations with least suitability to work from home include professions like drivers, shop sales professionals, and domestic help that are also characterized by high human proximity.


However, what is interesting is that certain occupations, although characterized by high human proximity and low suitability to work from home, may well be amenable to this shift through technological innovation and technology-enabled business models. For example, teaching associate professionals is an occupation with low suitability to work from home. However, in the past few days, we have witnessed several ed-tech companies like Byjus and Coursera offer their content for free to students. This can likely lead to changes in consumer behavior and render learning and teaching more suitable to work from home than in the past. Similar innovations are coming to light in other areas such as telemedicine as well.

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We further use the occupation-level scores on WFH and HP to construct a district-wise measure to understand the geographical impact of lockdown across India. We measure it by dividing our HP index by the WFH index. Disruption will be higher if jobs require more human proximity and at the same time, there is less potential for WFH. The distribution of this disruption across districts is shown in Figure II below. In this figure, the darker the color, the higher the economic disruption.