CHARTS ON WHICH SCHOOLS FEED THE MOST TO TOP IB/MC POSITIONS 2017
Here are charts I created when deciding which schools I should apply to as an undergrad. As a transfer student with internships in the media industry, and seeking to switch careers into either consulting or IB, this chart came in handy in racking and stacking the schools.
Obviously HYPC + NYU are top feeders, but I wanted to see the numbers compared to other schools. This chart was made in June 2017, and as a prospective transfer student, Princeton had yet to allow transfers (I think they will allow them next year) so I left it out. Plus it's obvious that had it been on the chart it would have placed top 5.
I left out schools in the midwest such as UChicago, UMich, UTA, Northwestern because I couldn't imagine myself living in those parts--it's either East of West coast (literary on the coast) for me.
I hope this chart can be helpful to a degree, although its not the precise representation of alumni of these schools in either GS or McKinsey, but, it should give one an idea of where these two companies recruit the most.
One interesting nugget is that Goldman Sachs hires more from certain schools compared to McKinsey and vice versa. For example McKinsey will higher more people from Stanford while GS would hire far few from the same school.
I used LinkedIn search to get the info, and its important to note that the numbers from LinkedIn shows people who are both actively working for either of these companies or previously did and have left.
One surprise for me was to see that Rutgers placed a huge amount (please discuss), top 10--more than Duke and UVA did. Not a surprise however was that public universities had a very low representation, which I hope will start a discussion as to why. Is there a stigma against public schools that's unacknowledged? I also threw in a state school bc I'm from San Diego, and wanted to see how SDSU did.
Please comment, critique, support, question, yell--let your thoughts out and hope for a lively discussion!
Hi Varkem, whoops, looks like nobody chimed in here.... maybe one of these discussions below is relevant:
If we're lucky, the following pros may have something to say: giudici ctrouba13 PrivateMarketplace
Fingers crossed that one of those helps you.
It's spelled Middlebury not Middleburry just FYI
Out of curiosity, how did you even come up with this list? Wondering because working at Goldman doesn't necessarily mean you work in IB.
LinkedIn
OP - three thoughts:
The more relative data points would be hires as a % of the student body, to control for which schools are simply larger.
If you're going to release something like this, you shouldn't exclude a few top programs just because you're not interested. It's an invitation to get flamed and doesn't provide an accurate picture for your target audience. Though it's good you mentioned that you intentionally excluded them.
This list is really incomplete with just two firms. If you really want to give a picture as to what schools are top feeders for top MC/IB firms, you should include at least their equivalent competitors (i.e. Bain/BCG for McKinsey). Top programs have some biases that are more a function of partner preferences/office size per location than anything else and that should smooth that out.
Agree and thanks for your points. I think there's an inherent narcissism that fueled an interest only in those two firms (best of the best). And I also think it's quite obvious which schools produce more students and thus in turn, have a higher numbers compared to smaller sized schools that produce fewer students but send a higher percentage compared to other larger schools. This chart was simply for inference. I'm confident that if it was polished further with more data points I think the schools would more or less have the same or near outcome as found here with an acceptable degree of variance.
As PWM said, this should be in % not gross number.
Second, you also left out Cornell.
Cornell is on the list. I also know people from Cornell who don't have much praise for their school compared to others.
Are these numbers strictly FO roles? (Ex: This is just Goldman IBD or is this across all job functions?)
Rutgers placement isn't too surprising for me. I went there and there's a strong placement for BO and MO across Wall Street.
When it comes to FO (IBD and S&T) the school does place some students, primarily out of the business and engineering schools. And in recent years FO recruiting has gotten stronger. From what I've seen, more banks are conducting Front Office OCR at Rutgers.
Rutgers is the closest major state / Power 5 university to NYC. It's going to have a presence on the Street the fact it's only 35 miles away. (re: mentioning Power 5 there's a bias to sports on Wall Street - even given our recent performance in revenue sports)
I'd love to know the specific search parameters you did on LinkedIn so we can better understand these numbers.
Ok since I was curious on the parameters you searched (mentioned in my original post). I did a LinkedIn search for "Schools = Rutgers", "Current Company = Goldman Sachs" and got 319 results which seems pretty aligned to the search you did in June and received 307.
Based off that this search doesn't paint an accurate picture described in your title as mentioned by others in this thread.
So basically...these charts don't really mean anything.
Yep...
how can a chart mean nothing? it's very difficult to look at these numbers and not make at least one accurate inference, like harvard beats everyone, and that rutgers has surprisingly high numbers, or that mckinsey is more selective
rrttg
It's not a helpful list if the numbers are inaccurate. You're trying to find placement numbers for a specific role (ex: IBD) but including results that include other roles.
Then what's the point of trying to rank which schools place the highest number of students when you won't even follow your own methodology? That statement completely contradicts the entire exercise you did. (though I do agree Georgetown > RU, Amherst > SDSU for MC/IBD)
You have multiple people here say why this list is flawed and how it can be improved yet get defensive and refuse to accept some feedback.
yes, no discrimination between fo, mo, bo--or ug, grad.
the numbers did provide some value, a rough estimate if you will of where people attended schools and their level of attractiveness to these firms
It doesn't. Without knowing the roles, this is pretty worthless. The other thing you would need to adjust for is to only capture roles immediately after graduation. If for example, someone went to Rutgers and then did an MBA at HBS, their job at Mckinsey is obviously not the result of going to Rutgers.
that was harvard college...not HBS which are separate on linkedin
that was harvard college...not HBS which are separate on linkedin. i should have been clear, there is* discrimination btwn ug and grad
that was harvard college...not HBS which are separate on linkedin
Interesting. Wonder how's the EU/UKs situation
Interesting idea in thought. but there are so many flaws in this methodology that you'd be hard pressed even to use this as a data point in college selection.
You cannot distinguish between roles, as many others have pointed out. If you're making a list of Goldman and McKinsey folks, you're capturing office assistants, BOs, etc. which is going to result in a strong bias for New York/"in the neighborhood" schools like Rutgers -- which is a short train ride from NYC
It does not prove helpful in evaluating trends. For example, I know that some schools have been crushing recruiting lately and others have been stagnating. This does not seem to distinguish how many are being sent every year. Tracking amount of analysts being sent now is the more important statistic in which school you ought to pick.
Even with this methodology, some schools that should be on the list are missing. There are some great schools excluded -- where are the schools like Vanderbilt/Notre Dame or the business-feeders like IU Kelley/BYU? Even with your methodology, it seems like you've literally forgotten to include them on the list. Any of those schools, but especially Vandy in consulting or BYU in IB should definitely be on that list. Looks like on LinkedIn, BYU has 346 at Goldman Sachs -- this would put them in the top 3! Hope you're ready to convert.
As many others have pointed out, doing it as a % of the student body would have been an easy calculation and could have contributed significantly to the analysis
As many others have pointed out, GS/McK is going to skew the data set. If you look at the IB data set from WSO even you'll see that some schools have very strong relationships with particular BB firms or MBB firms.
I really hope this data set did not substantially influence how you ended up selecting where you would go to school, as you mentioned in the original post. If you were making a choice between Amherst, Pomona, or Williams and instead decided to go to Villanova or Rutgers (barring location, scholarships, or any other sort of factor) that would be pretty poor judgement.
first, those schools were left out as stated because they were not quite near either coasts (what the fuck is in Tennessee, or Utah? like really? fly over country?--fuck that) It has to be the coasts!!--I've been to those middle states and couldn't stand their ambiance from people to general idea of being there Even at UChicago) . And yes, this did influence my decision--I've applied to all these schools besides SDSU and Pepperdine. Will end up prioritizing small LAC's and heavy hitters in NY, Boston, DC, SF and Philly. Thanks for the input on the shitty analysis tho.
Bro, you're a kid, so I think we're going easy on you. You put out a chart with all caps letters claiming "CHARTS ON WHICH SCHOOLS FEED THE MOST TO TOP IB/MC POSITIONS 2017". Nothing about that tagline is relevant to your chart - you're missing a ton of top programs simply because you're not applying there, the data is skewed towards two firms and ignoring their comparable peers, doesn't count quality of the roles, it's not 2017 data, etc, etc, etc. You seriously don't see why you're getting such a strong reaction?
Learn how to take feedback rather than getting all pissy every time someone gives you constructive criticism. I applaud your attempt at quantifying your decision and sharing your results, but the methodology and output are both heavily flawed.
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