Was Shakespeare naïve in thinking that the name of a person is not a true indication of his net present value (in true B-school jargon)? Given a certain set of starting similarities- here, the environment of a B-school, statistics, flawed or otherwise, clearly indicate that there is some correlation between the name a person possesses and the type of career path he/she is looking at.
This innocuous yet insightful observation is going to revolutionize the naming industry for ever and throw all the nosey pundits out of jobs and last but not the least, parents are going to thank me for years to come. In retrospect what I am going to propose is not for the faint hearted and has to be absorbed slowly in the quintessential “zor ka jhatka dheere se” style.
If we have a look at the summer placements that happened in 2006 at IIM B we find that a stupendous 110 people got foreign offers of a motley group of 250 odd people. We surely broke some records here. There was a sense of euphoria among the batch and err…..pardon me for the digression but those were good old times. Well coming back, we find an interesting correlation between names and location of placement. Strangely all the Rohits of the world got foreign locations so did all the Shrutis of the world. The table below would give you some sense of what I am talking about here.
The propensity to attain nirvana during summer internships be measured by the fx (Ma, I am going phoren) factor. This can be calculated by a simple equation:
fx(Name)= N(Number of foreign internships, Name)/N(Name)
For the purposes of this study, a sample of 253 students were chosen. They then underwent 5 days of chaos to emerge as nothing but nameless (not really) statistics for this paper.
The fx factor of the batch is found out to be 0.44. This implies that this threshold value must be crossed in order for the name to have any value in the marriage market.
A second test was also run on common surnames in order to provide the best name that you can ever choose for a new-born baby. As you can see, unlike most papers, this one might actually prove useful later in life.
The findings for the first name test are summarized (not really) below. Some clarifications are appended as footnotes as applicable.
| Name | fx= Frequency of phoren internships | Total number of occurrences | Locations |
| Abhay | 1 | 2 | London, Germany |
| Abhishek | 0.5 | 6 | Hong Kong |
| Akash | 0 | 2 | India |
| Amit* | 0.60 | 5 | New York |
| Ashwin** | 0.67 | 3 | New York |
| Ankit | 1 | 3 | Hong Kong, London |
| Ayush* | 1 | 2 | Hong Kong, London |
| Deepak | 1 | 2 | London, Hong Kong |
| Gaurav | 1 | 2 | London, Germany |
| Gautam* | 0.67 | 3 | London, New York |
| Karthik* | 0.5 | 4 | Singapore, Hong Kong |
| Kiran# | 0.5 | 2 | Hong Kong |
| Manoj | 0 | 2 | 100% fill rate- ICICI Bank |
| Mohit | 0.33 | 3 | Texas |
| Neha | 0.5 | 2 | Singapore |
| Prasanna** | 0 | 2 | India |
| Praveen | 0.5 | 2 | Hong Kong |
| Prasun | 0.5 | 2 | London |
| Rahul | 0.33 | 3 | New York |
| Rohit | 1 | 3 | Hong Kong, Tokyo, London |
| Rajesh | 0 | 3 | India |
| Sandeep | 0 | 4 | India |
| Saurabh | 0.5 | 2 | Czech Republic |
| Soumya** | 0.33 | 3 | Germany |
| Shruti | 1 | 3 | New York, Benelux |
| Sumit | 0.75 | 2 | New York, India/Hong Kong |
| Uday* | 0.33 | 3 | London/New York |
| Varun | 1 | 2 | Singapore, Hong Kong |
| Vineet | 0.5 | 2 | London/New York |
| Vivek | 0.5 | 2 | London |
| Yashaswi# | 0.5 | 2 | New York |
*Includes derivatives of the name with alternate spellings and different endings
**Includes the name as a prefix or suffix only in the first name. Both male and female specimens included
#One specimen left out/added due to ‘used name’ convention
This test was also run on some common last names. The summarization of THESE results are given below:
| Last Name | fx= Frequency of phoren internships | Total number of occurrences | Locations |
| Agarwal* | 0.67 | 6 | Hong Kong, Germany |
| Arya | 0.50 | 2 | New York |
| Bansal | 0.50 | 2 | London |
| Behera | 0.50 | 2 | Germany |
| Chowdhuri* | 1 | 2 | Hong Kong |
| Daga | 0.5 | 2 | London |
| Goyal* | 0.33 | 3 | Singapore |
| Gupta | 0.88 | 9 | London, New York, Hong Kong, Singapore |
| Hari## | 1 | 2 | Singapore, London |
| Jain | 1 | 3 | London, New York |
| Krishna## | 0.30 | 9 | Singapore, Hong Kong, London |
| Kumar## | 0.43 | 14 | Germany, New York, Singapore, Texas |
| Mohan## | 0.67 | 3 | Singapore, Germany |
| Prakash | 0.67 | 3 | New York, London |
| Rao | 0 | 2 | India |
| Sharma | 0.66 | 3 | London, New York |
| Singh## | 0.66 | 3 | Singapore |
| Sinha | 0.67 | 3 | Hong Kong, London |
Table 2: Summary of Last Name Conventions
Purists might say that the sample set is too small. To this contention, the author would like to point out that even if the statistics mean nothing… like most statistics are, these numbers are at least interesting!
Further analysis shows that if you are Gaurav Jain or Amit Gupta, you have a high probability of ending up in London or New York (though this is a rather circular argument). Similarly, women, if you want your child to achieve good things in life, like being among the top b-schools in the country but also chalking out an interesting “phoren location” based career, marry a Gupta. Evidently, they do quite well for themselves.
Alternatively, you can just name your child Kenny Hsieh and teach him Chinese. Whichever works for you.
Going one step further though the sample set involved in the above survey who might blame their parents for the lack of imagination they should rather thank their parents.
So next time there is a naming ceremony happening anywhere you know what names to suggest and with the statistics and “data” to back you up you will surely make the right choice.
P.S. Sorry for putting this a little late but a certain B-(stung at the wrong place) aka shrutz aka co-author has been instrumental in collecting invaluable data for this research and also making amends to this article thus making it a masterpiece :) :: from co-author phirahuadimag