Labor-Intensive Services: A New Way To Go

The pandemic has forced a rethink on our growth approach that brings labor-intensive services afoot to capital-intensive services and has highlighted the need for further growth in the medium-term horizons.

Simulations reveal that because of the shock and the related demand and supply-side effects, even if recovery and correction turn out to be good enough, we have fallen off from our growth trajectory and are bound to achieve targets with considerable lags at the projected growth rates.

Also, the pandemic has led to the urgency to make this growth broad-based, and employment generation at a sustained scale is one of the most effective ways to do this. Manufacturing has received ample attention from policy experts, demanding an increase in the labor intensity of manufacturing, which could rightly increase employment by our comparative advantage in terms of resource endowments.

But in the light of these manufacturing-oriented policy discussions (which is very good), we are missing the service sector, which has been the driver of growth post-1991 reforms. Almost 32% of the employment generation is being done by the service sector, which is by no means small, and it generates more than 60% of GDP. Now the time has come to make this sector broad-based and even further employment-generating in nature.

It has become a common perception to think of services as a skill-dominated sector, but it needs to be emphasized that this sector also contains a large number of unskilled labor, on which we need to focus. The more opportunities we create in this unskilled segment of labor-intensive services, the better employment we might be able to generate.


First of all, we need to have a comprehensive national policy on tourism. Tourism is one sector where a lot of labor-intensive services are consistently employed. A national policy focusing on the proper grading of these people and setting proper district authorities which keep their account will be more than beneficial in the medium term.

Example:- Lakhs of informal, untrained guides are giving their services in various places of historical importance, and if they can be properly graded, then we can effectively map out how many of them are being recruited by tourists per day, what is tourists perception of them, and how many more can be employed at similar wages.

It is quite normal if we account for a large number of guides giving incorrect information, but grading might help to map out those who need effective training alongside. Also, increased employment might make the guide sector more competitive, as currently, guides of the local area often collude to prevent entry.

Similar things need to be done with sweepers, waste handlers at historic sites, etc. This will generate employment in these labor-oriented service sectors and will lead to better profiling of these people.

Another crucial segment is daily wage service providers in urban areas like rickshaw pullers and coolies. There is a considerable mismatch between regional demand and supply for these, as a few urban centers with relatively lesser demand due to metros etc are being flooded with migrant rickshaw pullers, while newly emerging urban centers with an increased demand effectively lack them.

It is given that once assured of sustained higher wages these laborers are quite elastic in their migration attitudes, the government has a big directional role to play here. And again the first step is data on average wages per locality and the number of such service providers.

Once the supply is mapped out, check demand and then nudge migration to new places. This will not only help generate new employment but also will level out wages. The third point is that labor-intensive services are a far better way to take out the disguised unemployed from agriculture than manufacturing (due to legacy issues involved with it).

Tourism channels are not restricted to cities but go into villages, from where they pull into such services can be quickly done. Plus you don’t need much investment as well to train new guides, guards, etc. Once, for example, you give some historical site besides a village a tourist status and direct tourist channels there, the pull will take out excessive agricultural labor from agriculture and be employed there (with grading). This will also help maintain real-time data on progress. This can be tried with Sinauli remains to check how far it can go.

Labor-intensive services can also be a lure for women since they can effectively be done in less time and with a lesser burden of exploitation that prevails in factories. Services also have the proximity benefit, especially with the online model, which might attract more women. I am excited when I think of online guides being made available, which can show their touristic auspices from their home to people living across oceans!

Women already provide enormous amounts of domestic services, and the pandemic showed how the urban elites cannot live without domestic help! This domestic service sector needs a lot more work. There is a wide disparity between the number of domestic help women being employed through formal channels and informal channels.

If a simple grading mechanism, which can be easily done using AADHAAR by the government, then we can get better data on regional supplies and their average wages, and whether there is a generational movement or are the daughters continuing with the mothers’ work?

The fact that fitting into unskilled services is much easier for unskilled than to fit into manufacturing needs to be further explored and even exploited. Maybe once you get people into labor-intensive services, you can facilitate their transition to the manufacturing sector as well.

This will even facilitate the design of social security schemes, as in the Indian context, broad-based transfers are often not tabled due to shrinking fiscal space, and so we need to continue with targeting, which requires good data(not to mention implementation).

These labor-intensive service sectors can be easily mapped and targeted using technology. This will then lead to further linkages and will make growth broad-based and inclusive, with more employment generation.


Edited by Anupama Roy

Related Articles

Leave a Reply

Your email address will not be published. Required fields are marked *

Back to top button