It is known that productivity is the key to economic prosperity. How do we raise the productivity of service workers? This is one of the biggest challenges that India faces which hasn’t yet received much attention.
Why is this important? First, low and medium-productivity service sectors (services except real estate, business and professional services) and construction account for over 70% of non-farm employment in India. This is based on productivity measured via a crude proxy in terms of real gross value added per worker. Second, there is still no proven method to raise productivity in these service sectors. Third, while India aims to expand employment in manufacturing, there is no doubt that today’s low and medium-productivity services would continue to generate most jobs going ahead.
In 2004-05, around 66% of those employed in India’s non-farm economy were working in construction, trade, transport and communication, hotels, restaurants and personal services, along with public administration and defence. By 2018-19, this proportion had increased to 72%. Employment in high-productivity services—namely business, real estate, and professional services—as a share of non-farm employment rose to 5.8% from 3.8% during the same period.
Over these 15 years, the share of low-medium productivity services in real gross value added in the non-farm economy fell by 10 percentage points to 47% and that of high-productivity services rose by 7 points to 25%. As a result, the gap between real gross value added per person between the two rose rapidly (see trend chart). In line with economic theory, the productivity of manufacturing seems to lie between high-skill and low-medium skill services, with construction the worst performer.
In 2004-05, around 66% of those employed in India’s non-farm economy were working in construction, trade, transport and communication, hotels, restaurants and personal services, along with public administration and defence. By 2018-19, this proportion had increased to 72%. Employment in high-productivity services—namely business, real estate, and professional services—as a share of non-farm employment rose to 5.8% from 3.8% during the same period.
Over these 15 years, the share of low-medium productivity services in real gross value added in the non-farm economy fell by 10 percentage points to 47% and that of high-productivity services rose by 7 points to 25%. As a result, the gap between real gross value added per person between the two rose rapidly (see trend chart). In line with economic theory, the productivity of manufacturing seems to lie between high-skill and low-medium skill services, with construction the worst performer.
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Further, there is large variation across states in the terms of value-added per worker, with Karnataka leading in terms of the highest per worker real gross value added in business, real estate and professional services on the back of the information technology sector. The other sectors in the state lag behind significantly in terms of productivity. In contrast, the gap between productivity levels is narrower in Gujarat (see bar chart).
Gulati, et al (2020) also estimate that while information and communication technology (ICT) driven industries such as business services and financial services emerged as drivers of productivity in India during the period 2008-09 to 2016-17, the trade and construction industry continued to lag (bit.ly/30ZnVZF). Such variations in productivity have implications for the distribution of income among workers and owners of capital, as well as among workers themselves. In today’s developed economies, manufacturing employment had risen during their rapid economic development to absorb excess labour from agriculture. In contrast, in several of today’s developing economies, including India, the share of manufacturing-sector jobs in the economy’s employment reached its peak well below corresponding levels for developed economies, a phenomenon economist Dani Rodrik termed “premature deindustrialization”.
India has been pushing for manufacturing expansion via its Make in India campaign, but there is little doubt that manufacturing would not be able to generate jobs at scale across India the same way it did in other Asian economies like Japan, South Korea and China, given increasingly high levels of automation. Similarly, high-skill services cannot absorb the large proportion of educated youth that remain unemployed in search of good-quality jobs.
With a change in patterns of demand towards services and the emergence of new types of services via the shared economy, there is evidence that the structure of occupations is changing and labour markets may be polarizing further. This could lead to greater inequality, which has been the case in many developed countries as well. We need to better understand gains in labour productivity across service sectors and how to make service jobs more productive, sustainable and inclusive without putting undue pressure on workers.
If a large number of young Indians are to find jobs as gig workers such as cab drivers, delivery partners, security- and personal-service workers and retail-sales executives, how do we measure their efficiency? The current matrix of going by the time taken to deliver an order, for example, is not appropriate; to overcome the negative impact of factors such as traffic conditions that are beyond a worker’s control, a worker may end up taking excessive risk in terms of vehicle speed to deliver orders on time.
Further, sectors such as manufacturing and traditional retail have restricted work hours. In the former, it leads to concentrated production efforts, while in services traditionally, customers are required to make purchases during specific time bands, which results in higher sales per hour. However, with relatively new services such as ‘any day, any time deliveries’, longer opening hours lead to dispersed consumer orders, which in turn could result in fewer hourly orders against the counter-factual situation of limited hours.
While low-productivity services will continue to employ the majority of the country’s workforce, there is no clear-cut policy path to improve the productivity of workers in these sectors. Traditionally, the scope for using technology to improve workers’ productivity was limited in these services. But in recent years, technology has helped improve productivity in service industries such as ride hailing. Could workers in other services also benefit from the use of technology, or would it lead only to bigger gains for owners of capital? Would an improvement in organizational efficiencies such as better managerial practices and soft skills help improve productivity? Would trade in services increase and offer opportunities to specialize, scale up and raise productivity? How far would quality certification help? How would an increase in real value added per person be distributed between workers and capital owners? Answers to these questions require deeper research and analysis, but would help India raise prosperity and lower inequality.
Vidya Mahambare & Sowmya Dhanaraj are, respectively, professor of economics, Great Lakes Institute of Management, Chennai and assistant professor, Madras School of Economics
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