Welcome to GMAT Club’s first ever Full Time MBA Rankings!
October 5, 2020Why MBA Rankings?Over the last few decades, ranking MBA programs (and other graduate and undergraduate schools) have become more and more prevalent. Some publications have become so desperate to have a ranking, they have merely averaged other rankings so they might have something to publish!
Common complaints include observations that rankings often offer results that are either non-conclusive (such as many programs are tied) or so unexpected and deviate so far from general perception so as to render them unhelpful (at best) and misleading (at worst). GMATClub exists to provide helpful information, and for too long, the vast majority of rankings provide insufficient help to the typical MBA applicant in making a monumental decision.
Over the years, many GMAT Club members have expressed their frustration with the status-quo rankings and have expressed a need to have something more logical and transparent. And, in this a year of craziness and mayhem brought on by COVID-19, since most of the major rankings taking a hiatus of at least one year, we decided that now, more than ever, prospective MBA applicants all over the world would benefit from a fresh perspective.
The market has spoken and we have been listening.
(NOTE: The size of the space between the tiers is proportionate to the actual gap in the aggregate score between the bottom of one tier and the top of the next – AND – for the purposes of this analysis, each time the score drops by 3.0 or more between schools, we established a new tier):
Why Are Only the US Schools Ranked? One of the great goals we had for this project (and still have) was to combine US and International rankings into a single table where one could look up how Tuck stacks up against LBS (for example). That goal is still very much alive but for the sake of time (and sanity) we have decided to, for now, focus just on the top US Schools.
Why Did These Specific Schools Get Selected for Being Ranked?We sought to use a consensus list of the 30-50 top schools. Our list was built after considering those schools positively ranked by other ranking systems, seeking commonality across multiple methodologies. We eliminated outliers (i.e., schools that appeared only once or twice, but weren’t consistently ranked well across multiple platforms) in pursuit of consistency; the end result just so happened to be exactly 40 schools. While we believe these forty schools represent the top forty programs in the USA, we understand that others may disagree. Future years may see the list of schools get longer or shorter, and there may be some turnover from year to year.
How Did We Rank B-Schools? Our approach is exclusively based on years of talking to prospective MBA applicants and current MBA students about their priorities in a program and their hopes for their careers after graduation, and being frustrated about the shortcomings of popular MBA ranking methodologies. Most aspiring MBA students state their primary purpose for getting an MBA is to super-charge their career, and they pick their school trying to assess which one is most likely to do that, with the highest probability of success at the lowest possible risk.
Over the last several months, hundreds of data points were analyzed for potential inclusion in our proprietary models. After much thought and consideration, we limited the parameters to only those factors we believe are most intimately related to comparing why a student might prefer one school over another. In the final analysis, even though several schools might fulfill most (or even all) of each MBA students' needs and desires and no matter how many great schools are out there, each person can still only pick one.
As a result, our models did not dedicate any attention to things such as quality of the school building, location of the school, average temperature in February, how many professors have published papers, etc. Those factors may be important to some but we believe they do not ultimately matter to the typical MBA student while they are pursuing (and being pursued by) prospective employers.
We zeroed in four core areas for this ranking (Brand, ROI, Cohort Strength, Diversity), and have built proprietary models assessing the strength of each of the forty schools in our analysis in each of these four key areas. The strength of each school was assessed in each of the four key areas, and then these sub-scores were weighted to derive an overall score for each school. The composite scores in each area and the final scores range from 0.0 to 100.0.
This is the heart of the rankings; please see more detailed description of each of the four core areas below:
30% Brand
(i.e., the relative and absolute difficulty to gain admission to any specific program, relative and absolute tendency of applicants to prefer any specific program, and the correlation between the strengths of a program and the preferred areas of study expressed by the typical MBA student)- 20% Composite score is an algorithm based on three key pieces of raw data, and derivatives and combinations of the same: (i) total number of applicants, (ii) total number of admitted students and (iii) total number of matriculating students. Our goal was to try to answer the question: “If a student got into each school they applied to, which one would they be most likely to pick.” We believe our models measure market demand factors and perception factors among other aspiring MBA students. The stronger the market demand for a school, the higher the score.
- 5% Composite score measuring whether or not McKinsey, Bain and/or Boston Consulting Group have determined students admitted to a school are suitable for pre-MBA internship opportunities at their firm; the more companies have approved a program, the higher it’s score; this measures prestige among prospective employers.
- 5% Composite score measuring the perception of a programs’ strengths by the administration at other schools as compared to the stated desires of MBA students at all programs measured; the more tightly a schools reputation across its’ departments correlates with the desires of the typical MBA student’s academic interests, the higher the schools’ score. By way of providing an example, most MBA students want to improve their abilities in marketing – so, if a school has a highly regarded marketing department they will score higher than a school with a highly regarded real estate department (since only a small number of MBA students are seeking this specific expertise).
Brand Rankings
30% ROI
(1st Year Post-MBA compensation and total program cost (tuition, room, board, books, fees, etc.))- 20% Composite score measuring the published average first year total compensation (signing bonus, salary, other guaranteed bonuses), adjusted downward based on the percentage of the graduating class who does not report their employment details back to the school. Our model is predicated on the belief that graduates who do not report in are either unemployed (but looking for work), unemployed (and no longer looking for work), under-employed (and embarrassed by it), starting their own business (at low initial compensation), are working at an unknown start-up (and are potentially embarrassed by the lack of prestige and/or a compensation package they know is lower than others in their cohort). In each instance, these non-reporting students are almost assuredly making less than their peers who did report. Since social norms common among MBA students include a bias against self-reporting below-average information, graduates with low-paying jobs and/or at employers they deem unremarkable are less likely to be reflected in the compensation statistics published by the schools. As a result, in this model, a school reporting higher compensation levels from a higher percentage of their graduating class will score more highly than a school with either lower compensation or a lower percentage of graduates reporting (or both).
- 5% Composite score which rewards schools who have graduates who (i) have accepted a job prior to graduation, (ii) have accepted a job prior to 90 days after graduation and (iii) have achieved a high level of compensation in the process. The idea is that graduates would prefer to get a great job that pays well as soon as possible, and the longer they have to wait to achieve this goal, the higher the risk they may not actually achieve it – and since achieving a great, high-paying job after graduation is the primary goal of most MBA students, not achieving the primary goal represents a material aspect of whether or not a school is desirable (when compared to others).
- 5% Composite score reflecting the financial costs to attend a school; tuition, books, room, board, fees, etc. Note that this does not include the opportunity cost of attending other schools, pursuing other degrees, forgoing compensation being earned prior to attending school, etc. A lower cost result in higher score; lower costs reduce the risks a student faces of not achieving a great job prior to (or upon) graduation.
ROI Rankings
30% Peers
(Cohort intellect and experience)- 15% Composite score reflecting a schools’ average GMAT score (adjusted based on the percentage of the cohort who has reported their GMAT) and a schools’ average GRE-V and GRE-Q scores (adjusted based on the percentage of the cohort reporting their GRE). In our model, the average GRE scores for all schools reporting their GRE scores were converted to a GMAT equivalent using a widely known and publicly available formula.
NOTE: Six schools did not provide GRE scores (Booth, Columbia, Goizueta, Kellogg, Marriott and Tuck). To incorporate these six schools into this metric, the lowest GMAT:GRE ratio for all other schools in the tier above, the same tier and the tier below each of these six schools was used to fill in the blank. As a result, we understand that it is possible these six schools may be slightly disadvantaged as a result of their own choice to not publish their GRE scores. - 15% Composite score reflecting a schools’ average GMAT / GRE score (as discussed above), average GPA, average pre-matriculation work experience, and the relative amount of emphasis a school places on any of those three factors (vs. taking a balanced approach to all three); generally, a school that is consistently above average in each of these three metrics, not favoring one attribute above the others, will score most highly.
Peers Rankings
10% Diversity
(the percentage of the program comprised of women, international students and traditionally under-represented US minorities)- 5% Composite score measuring traditional aspects of demographic diversity – the percentage of women, the percentage of international students and the percentage of historically under-represented US minorities. There are three things to note: (i) schools under-indexing in the percentage of women were given extra negative marks in proportion to the amount they under-indexed; (ii) since this is a ranking of US schools, schools who materially over-indexed or under-indexed on the percentage of international students as compared to the mean of all of the Top 40 programs considered here scored lower than those closer to the mean, and (iii) the greater the percentage of historically under-represented US minorities, the higher the score.
- 5% Composite score measuring the relative reliance on international applicants for strengths in the quantitative measures published by a school; since this is a ranking of US programs (not global or international programs), if a school relies more heavily than their peers on the strength of the international applicant pool, that schools’ score in this measurement would be lower than it otherwise would be.
Diversity Rankings
Where is the Data From?The rankings are based on publicly available data such as school websites, class profiles, employment reports, employer sites, and other public data sources. The rankings currently are based on the class of 2021 information. We anticipate updating the results once the class of 2022 data is released by all of the schools (a handful of programs have released their latest class profile but we have to wait until all programs release the data so we have an equitable comparison).
Who Built These Rankings?In the early 1990s,
Regenerate was considering attending a full-time MBA program. Due to life’s circumstances, he elected to remain in full-time employment, pursuing other avenues for professional development. In the midst of the chaos of the past few months, he began considering going for either an Executive MBA or Online MBA in advance of the second half of his career. After having spent the bulk of the past 25 years in quantitative endeavors, and periodically following the ever-changing ranking systems used by others, he developed strong opinions about shortcomings in the commonly-used rankings. In conjunction with his research into various MBA programs earlier this year, he approached
bb about the subject of rankings, sharing his quarter-century of disappointment in the MBA ranking industry.
As discussed at the outset, BB had been considering a rankings project for many years, and after considering Regenerate’s ideas and perspectives, BB decided to ask him to lead the charge for GMATClub’s inaugural MBA rankings.
The data compilation, analytical models and methodology were built by Regenerate, however, several others (led by BB) provided critical feedback and perspective, ensuring the entire project would fulfill the overarching goal – to help to the GMATClub’s community members make one of the most momentous decisions they’ll ever make!
Regenerate and BB wish to extend specific a very “Thank You” to
texas101,
souvik101990 and @workout for the time and insights shared over the last several weeks.
Are These Rankings Perfect? Good question. First of all, we are not ranking all 2,000 MBA programs. In this first version we are only focusing on Top 40 MBA Programs. Additionally, while a school might offer several different avenues to achieving the MBA degree, we are only considering a schools’ full-time MBA program (which is typically awarded after 20-22 months of study, broken up only by a summer break between years).
Second, we know the inaugural GMATClub rankings are not perfect and we did not try to make them perfect. We did, however, try to overcome shortcomings we perceive in other ranking methodologies. The approach we’ve taken would fall under the analytical umbrella of “we’d rather be generally right than precisely wrong.” We did not curve fit the data; we did not begin with a target slotting for any school; we did not get cute with weightings of sub-scores; we simply tried to take the data that was relevant, available and complete, consider the questions the majority of MBA applicants ask themselves (and others) when deciding where to apply and attend, and apply a fresh set of eyes and some new ideas towards analyzing the inputs. We understand (and embrace) the notion that the best school for you might be different than the best school for someone else; we understand (and embrace) the notion you may place more importance on being close to home or moving to a different country or perhaps seeking a comfortable 70 degrees in February. While important to some, this ranking does not consider any of those factors (or whether or not the university’s football program is competitive).
Third, because of the first two items mentioned above, there was a great number of potential avenues to make the rankings below far more robust – however – we simply didn’t have full data sets for some of the analytical models that had been built and considered. For example, we wished to consider the issue of whether or not a school had more “regional” or “national” influence, but we were unable to consider the question fully as several schools did not report regional career placement statistics and others did not report the relative compensation packages for domestic vs. international students, and a host of other potentially relevant statistics. In future releases, we hope to roll-out additional analytical tools derived from better / additional data, any of which might impact the relative ranking of schools at that time. At this time,
if all of the necessary data could be located and verified, it is anticipated the most important of these additional models would entail an expansion of the ROI calculation to consider the average debt of students at graduation and the percentage of students carrying debt at graduation.
So, this bit of prose lays out a bit of the background as to “why” and a bit of the “how” … we hope you enjoy these rankings and find them helpful. We welcome your feedback for future iterations!
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05 Oct 2020, 19:04
