Consulting Work Characteristics: Differences Between US & India Case Work

by Jaineel Aga

This chapter is a free excerpt from The Best Book on Getting Consulting Jobs In India.

Data Abundance Versus Data Scarcity

International students choosing between consulting work in the U.S. and consulting practices in countries like India should think about the type of case work they want to get involved in.

In countries with mature economies, like the U.S., the data infrastructure is much better in terms of market data and company research, which is not the case in countries like India and China.

Typically, a lot of the consulting work in countries like India is very difficult, especially when working in sectors whose statistics are not closely tracked. For this kind of work, data gathering itself becomes one of the most challenging aspects of consulting work, unlike in the U.S., where most economic and demographic data is consistently well tracked and analyzed because its industries have been mature for a very long time.

When there’s a lack of data availability, the type of income or market forecasting that needs to be done relies on much more solid research. The assumptions you make as a consultant need to be vetted out by talking with industry experts and economists.

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Data Abundance Versus Data Scarcity

International students choosing between consulting work in the U.S. and consulting practices in countries like India should think about the type of case work they want to get involved in.

In countries with mature economies, like the U.S., the data infrastructure is much better in terms of market data and company research, which is not the case in countries like India and China.

Typically, a lot of the consulting work in countries like India is very difficult, especially when working in sectors whose statistics are not closely tracked. For this kind of work, data gathering itself becomes one of the most challenging aspects of consulting work, unlike in the U.S., where most economic and demographic data is consistently well tracked and analyzed because its industries have been mature for a very long time.

When there’s a lack of data availability, the type of income or market forecasting that needs to be done relies on much more solid research. The assumptions you make as a consultant need to be vetted out by talking with industry experts and economists.

Compare this work style to countries like the U.S., where most of the income data that you get comes from the government’s own statistics. Some of the best statistical information I’ve seen in my career has come from Australia, where they track the minutest things and have a very user friendly way of extracting that information, either in Excel or Access.

Managing Growth Versus Efficiency & Streamlining

In spite of the difficulties in terms of data gathering, working in consulting firms in developing countries can be very exciting because you get more exposure to growth stories. If you’re interested in understanding how companies are grow or scale up, I think India is definitely the place to be. Every private equity deal that I’ve seen over the last couple of years has been at companies that have grown at a fantastic rate,  something unimaginable for most companies in developed industries in developed nations.

If ambiguity, complexity, and a lack of data don't bother you, and you're happy being involved in high growth case work, testing out the feasibility of new concepts, then definitely look for work in high growth regions like India, China, or Singapore.

If you are more comfortable with having a reliable supply of data and would like to be involved in the efficiency and optimization processes, then you would probably like to work in a country like the US, where companies typically look to consultants to streamline their businesses and improve their margins. In general, the consulting industry is much more mature in the US, and a lot of the fancy analysis work, like conjoint analysis and S-curves, or complex regressions, are possible only when there is solid historical data available. When you’re working in India, this kind of data is often unavailable to you.

Just to give you an example of working with a scarcity of data, I once worked on a project in an area that didn’t even have an income survey. We had to build an economical model. Just coming up with basic assumptions required a lot of collective effort, and even then we had to make models and projections based on whatever information we had. Sometimes, when you are working in a developing region, it might be impossible to get even the most basic and fundamental information, information that would be a given in a country like the US.
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