How Many IIM, FMS, XLRI Grads Work With FAANG?

This report has been split into two clusters based on the years in which the top b-schools considered for this report were established. The rationale behind such as a selection criterion is to ensure that the alumni base is strong and comparable for the b-schools under comparison. For a more detailed explanation, please refer to the section titled 'Methodology' in this report.

The report has been further split into two sub-clusters for each of the two primary clusters. These two sub-clusters are:

1. Company-wise Slicing, i.e., the percentage of alumni of all b-schools at a particular company (view row-wise).
2. B-School wise Slicing, i.e., the percentage of alumni of a particular b-school at all companies (view column-wise).

The table above contains the raw data for Indian b-schools established before 1966. Please note the following:

1. Relevant filters have been applied in the research process. However, the existence of anomalies is also quite possible. So, there can be a positive or negative variance from the actual figures.
2. All possible businesses of the companies have been considered.
3. In this report, a higher number does not equal more influence on alumni of specific business schools. The seniority of alumni, quality and diversity of roles play a bigger part. Unfortunately, this cannot be captured with exact accuracy given the subjectivity involved.

The table above comprises the raw data for Indian business schools established post-1966. Please note the following:

1. Relevant filters have been applied in the research process. However, the existence of anomalies is also quite possible. So, there can be a positive or negative variance from the actual figures.
2. All possible businesses of the companies have been considered.
3. In this report, a higher number does not equal more influence on alumni of specific business schools. The seniority of alumni, quality and diversity of roles play a bigger part. Unfortunately, this cannot be captured with exact accuracy given the paucity of time and subjectivity involved.
4. The figures at NMIMS Mumbai may be heavily influenced by the alumni of NMIMS who may have pursued a non-MBA undergraduate degree from NMIMS, though the filters applied during the research will minimise such anomalies.
5. The data for IIM Kozhikode are to be treated with caution, given previous technical glitches resulting in incorrect mapping IIM K alumni on LinkedIn.

Limitations Of The Report

As mentioned at the beginning, certain limitations of the research process prevent us from arriving at conclusions with pinpoint accuracy. Some of the major limitations are:

• Not everyone is on LinkedIn B-school alumni may not necessarily have registered on LinkedIn, therefore not giving a comprehensive overview of the actual figures of alumni concentration at India's most desirable technology and ecommerce companies. It is also possible that those on LinkedIn may not necessarily update their profiles, thereby giving erroneous or incomplete employment data.
• Not everyone is a B-school student: Unfortunately, LinkedIn does not allow one to filter out MBA graduates from the crowd, and therefore, it is difficult to distinguish between MBA alumni and those who have pursued a certificate course, those who have pursued a short-term duration program, or summer interns at the companies mentioned in this report. Additionally, for institutes such as NMIMS Mumbai that offer multiple courses, there are chances of errors in attempting to distinguish between NMIMS alumni who have pursued undergraduate programs, and those who have pursued a PGDM program.

How can we improve this report? Please let us know in the comments below. We look forward to your valuable feedback.