Should You Trust the LinkedIn MBA Rankings?

LinkedIn came out with the 2025 version of its global “Best MBA Programs for Career Growth” ranking in September. With its huge user base providing extensive data to work with, LinkedIn seems uniquely well placed to construct this kind of ranking.

Yet the results are nothing if not controversial. Unusually high rankings for the Indian School of Business (ISB) and Oxford Saïd, and spots outside the top 25 for such mainstays as Michigan Ross and UCLA Anderson, have been particular points of contention.

This ranking and others are of course constructed precisely to stir up drama, getting readers’ attention with unlikely claims and artificially shuffling schools up and down the ranking from year to year. Let’s look at how LinkedIn’s ranking was constructed.

How LinkedIn Creates Its MBA Rankings

LinkedIn’s MBA ranking, while it attempts to measure some of the same factors as other rankings, is unique in attempting to do so using only the site’s own user data. No surveys or external stats went into the ranking—only existing LinkedIn data.

The methodology of the LinkedIn ranking is based on five “pillars,” each made up of one to three metrics:

• Hiring and demand
  • Job placement rates, based on hiring data
  • Labor market demand, based on recruiter InMail outreach data
• Ability to advance
  • Promotions among recent cohorts
  • How quickly past alumni have achieved director/VP leadership positions
• Network strength
  • Network depth (how connected alumni are to each other)
  • Network quality (average connections recent cohorts have with those in director-level positions and above)
  • Network growth rate of recent cohorts
• Leadership potential
  • Percentage of alumni with post-MBA entrepreneurship experience
  • Percentage of alumni with post-MBA C-suite experience
• Gender diversity
  • Gender parity in recent cohorts

The first four pillars are all weighted equally, while gender diversity is given half the weight of the others. This means that each pillar counts for two-ninths of the total ranking, except gender diversity, which is one-ninth.

A “where they stand out” feature in some of the schools’ rankings highlights if that school was in the top 5 for a particular pillar, but does not give its exact ranking for that pillar. If a school wasn’t in the top 5, the ranking gives no information at all about how it did for that pillar, making the strengths and weaknesses of most schools unclear.

“Recent cohorts” are defined as those graduating from 2019 to 2024. The methodology doesn’t specify whether all metrics are equally weighted within each pillar, nor how exactly each metric is calculated. It’s therefore difficult to assess the reliability of the analysis.

The scope of the ranking is ostensibly global, but it excludes mainland China, because LinkedIn no longer operates there. Therefore, no Chinese B-schools appear in the list. The list also only considers full-time MBA programs; executive and part-time MBAs are not included.

Issues with LinkedIn’s Methodology

There are a few major flaws in the methodology of the LinkedIn ranking that make its results unreliable.

Network Strength

First, the “network strength” pillar, focused on the size and “quality” of alumni’s LinkedIn networks, is highly gameable and virtually meaningless. Many people accept LinkedIn connections indiscriminately even if they don’t know the person inviting them and have no intention of speaking to them—let alone meaningfully advancing their career.

Fundamentally, no one would seriously argue that the person with the highest number of LinkedIn connections is the most successful. It would be just as reasonable to interpret the number as an indication that they’ve spent a lot of time on the site, looking for work.

Speculatively, this could even bias the results toward schools in countries where the work culture places a strong emphasis on this kind of scattershot networking—and, of course, those where LinkedIn is particularly ubiquitous.

Hiring Data

A similar issue arises with the “hiring and demand” pillar: The complete reliance on LinkedIn hiring and messaging data means that the ranking completely ignores all hiring that didn’t take place through LinkedIn. Given the importance of on-campus recruiting for desirable post-MBA industries like consulting and finance, this is a major blind spot.

A secondary issue with this pillar is that no attempt is made to distinguish between different types of companies or even different industries.

One could imagine a LinkedIn ranking that looked at how successfully different programs placed candidates into MBB consulting firms or PE megafunds; this ranking instead looks at whether graduates were able to get … a job.

Exclusive Reliance on LinkedIn Data

The unreliability of LinkedIn data is also a concern. For example, it’s not uncommon for students of one program who did a study-abroad semester at another school to list both schools on their profiles.

We have no indication of how the ranking team would deal with such ambiguity, but it’s hard to imagine they’d have the capacity to check each individual really got their degree at the school they list.

It’s also a simple fact that not everyone keeps their LinkedIn profile up to date with every detail of their education and professional activities. A user who didn’t list their MBA program on their profile would necessarily be left out of this analysis; one who listed their job title inaccurately, or didn’t list it at all, would skew the results in a different way.

There’s also the fact that LinkedIn does not have data about its users’ salaries—a crucial data point in most other MBA rankings. In this case, the data is not unreliable but simply missing, meaning that the ranking fails to capture what is arguably the single most important factor for most MBA applicants.

Unclear Methodology

Finally, as mentioned above, an overarching issue is that the way LinkedIn describes its methodology is vague and incomplete. Without more specificity, one could imagine a variety of plausible ways to calculate such metrics as “labor market demand” or “how connected alumni of the same program are to each other”—but we don’t know which ones the LinkedIn team chose.

Nor do we have any indication of the specific scores each school received on each pillar; or the relative importance of the different measures within each pillar; or how ambiguous job titles or alma maters were disambiguated.

A lack of clarity on such important details raises questions about how much care went into the ranking process itself.

LinkedIn vs. Financial Times

To get some perspective on the LinkedIn rankings, it’s useful to compare them to another prominent global MBA ranking, that of the Financial Times.

The following table compares the two rankings at a glance:

Program	Country	LinkedIn	Financial Times
Stanford GSB	US	1st	—*
Harvard	US	2nd	13th
INSEAD	France	3rd	4th
UPenn Wharton	US	4th	1st
ISB	India	5th	27th
Northwestern Kellogg	US	6th	10th
MIT Sloan	US	7th	6th
Dartmouth Tuck	US	8th	20th
Columbia	US	9th	2nd
LBS	UK	10th	7th
Chicago Booth	US	11th	17th
Oxford Saïd	UK	12th	26th
Duke Fuqua	US	13th	11th
Yale SOM	US	14th	24th
Berkeley Haas	US	15th	15th
IIM Calcutta	India	16th	61st
IIM Ahmedabad	India	17th	31st
UVA Darden	US	18th	20th
Cornell Johnson	US	19th	13th
IIM Bangalore	India	20th	57th
NYU Stern	US	21st	31st
IESE	Spain	22nd	3rd
IMD	Switzerland	23rd	22nd
HEC Paris	France	24th	9th
Emory Goizueta	US	25th	45th
UCLA Anderson	US	27th	19th
IE	Spain	35th	18th
ESADE	Spain	46th	8th
SDA Bocconi	Italy	47th	4th
CEIBS	China	—**	12th
SUFE College of Business	China	—**	15th
Nanyang	Singapore	—	22nd
Peking Guanghua	China	—**	25th

Now, the FT ranking has its own quirks; we’re not trying to set it up as a perfect list to contrast with LinkedIn’s kooky one. But the big differences are revealing of potential biases in LinkedIn’s methodology:

• There are four Indian schools—ISB at 5th, and three IIM locations further down—in LinkedIn’s top 25. None of them made the FT’s top 25; IIM Calcutta is 45 places lower on the FT list.
• Several well-regarded European MBA programs—IESE, ESADE, SDA Bocconi, and HEC Paris—make the top 10 in the FT list but fall dramatically lower (a 43-place difference for Bocconi) on the LinkedIn list.
• As discussed above, Chinese schools are excluded entirely from LinkedIn’s list, while several appear in FT’s top 25.

Apart from the last point, any explanations of these differences are necessarily speculative—especially given the previously mentioned ambiguity surrounding LinkedIn’s methodology.

But we do see that most of the Indian schools included are described as “top 5 for networking.” In fact, every school in the list that has this designation is an Indian school. In other words, the shoddy networking metrics in the methodology seem to have created a bias toward these schools that boosted their rankings significantly.

In any case, this and other disparities are striking enough that they should give you pause and make you take both rankings with a grain of salt.

So How Can You Find the Best MBA Program (Without Rankings)?

Once you determine roughly which schools you are qualified to attend—and MBA program rankings can be useful tools for building this initial list—we encourage you to leave the rankings behind and instead focus on the questions that will help you figure out which MBA program will provide value to your career. These are simple, practical questions:

• Does the school have relationships with your target employers?
• Is the alumni network interesting for your post-MBA career field and location?
• Is the curriculum, both inside and outside the classroom, going to fill the gaps in your skills and experiences?
• Are the faculty and research centers relevant to your interests?
• Will you fit in culturally at the school?

Answering these questions will help you find the right MBA program to enhance your career.

Navigate through the intricacies of MBA rankings with our expert MBA consultants and gain clarity on your journey toward your dream school.