Methodology

The Bloomberg Businessweek Best B-Schools ranking starts from the basic premise that the best judges of MBA programs are graduating students, recent alumni, and companies that recruit MBAs. We ask those stakeholders questions about everything from jobs to salaries, classroom learning to alumni networks. Their answers form the heart of this ranking. Because these stakeholders can have differing and overlapping needs and interests, we rank schools based on five indexes that capture fundamental elements of business school education: Compensation, Learning, Networking, Entrepreneurship, and Diversity (for US schools only).

Our methodology consists of two steps.

Step 1: Generating weightings for each index.

Rather than define the relative weighting of the indexes ourselves, as most rankings do, we let the stakeholders define them. Surveys for all three stakeholder groups begin by asking respondents to rank the five most important factors when considering business school (or in the case of employers, the most important qualities when hiring business school graduates).

We provide a dozen options, such as “increase my earnings potential,” “build my professional network,” and “learn how to start or develop a business.” We also offer diversity options such as “learn in a diverse, equitable, and inclusive B-school environment” and “learn how to work successfully in an increasingly diverse workforce.” Each factor is tied to one of the five indexes. Stakeholders’ answers determine the weightings of each of our indexes. Five points are awarded for each top-ranked factor, four points for the second-ranked answer, and so on. Totals are adjusted in two stages:

  1. We adjust point totals according to which stakeholder group they belong to:
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  1. We adjust point totals to account for the fact that not all indexes are equally represented in the factor choices.

This year’s surveys resulted in the following index weightings:

US Schools
Compensation Index 37.4%
Learning Index 25.5%
Networking Index 17.4%
Entrepreneurship Index 11.6%
Diversity Index 8.0%
(Figures do not sum to 100% due to rounding.)
Schools in Europe, Asia, and Canada
Compensation Index 36.9%
Learning Index 25.2%
Networking Index 24.1%
Entrepreneurship Index 13.8%

Step 2: Determining school scores for each index.

Survey takers first answer how well their schools delivered on the five factors chosen in the previous section based on a seven-point scale (“completely agree” receiving seven points and “completely disagree” receiving one point). Next, they are asked to agree or disagree with statements regarding their business school experience that appear for all respondents, regardless of which factors they chose initially. These universal statements are also tied to one of the five indexes and are scored on the same seven-point scale. Statements tied to each index touch on the following themes:

Learning: For the schools’ core mission, we explore the quality, depth, and range of instruction, focusing on the curriculum relative to real-world business situations; emphasis on innovation, problem-solving, and strategic thinking; mentoring and support from instructors; class size; and collaboration.

Networking: This index gauges the quality of networks cultivated by classmates; students’ interactions with alumni; effectiveness of the career services office; quality and breadth of alumni-to-alumni interactions; and the school’s brand power, according to recruiters.

Entrepreneurship: Students and alumni tell us whether their school took entrepreneurship as seriously as other career paths and rate the quality of training they received to start a small business or startup. Recruiters rate schools according to whether graduates show exceptional entrepreneurial skills and drive.

As the table below shows, these survey questions account for the entirety of each school’s raw score on the Learning, Networking, and Entrepreneurship Indexes. Point totals are adjusted according to the first table above. The Compensation Index has additional components, and the Diversity Index score is based on demographics of the first-year class:

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Compensation Index

In addition to survey questions regarding compensation, we also collect MBA Career Services & Employer Alliance (MBA CSEA) employment and compensation data from schools. These figures, outlined in the table above, collectively account for 75% of a school’s Compensation Index score.

For each of these variables, the school with the minimum figure among all schools was given one point while the school with the maximum figure was given seven points. All other schools were scored proportionally between these two extremes. The following diagram illustrates an example for assigning scores to the “salary after graduation” component:

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For non-US schools, salaries submitted in local currencies are converted to US dollars, using the average exchange rate for the year ended June 30, 2022. Salaries are not adjusted for parity in purchasing power.

The 1-7 raw scores from the survey questions and the compensation data are then weighted 25% and 75%, respectively, for a final raw score for the Compensation Index.

Diversity Index

From US schools, we also collect data on the race, ethnicity, and gender of their class members. The Diversity Index rewards schools for recruiting both minority students and women, with additional weight given to underrepresented minorities. It is calculated as follows:

Race and Ethnicity (50%)

Total minority population

Schools provide us with percentages of the first-year class of American students for the following groups: White, Black, Asian, American Indian, Hawaiian/Pacific Islander, Multiracial, and Hispanic. These groups are categorized as such by institutes of education when submitting data to the federal government.

Before summing up the minority percentages, we adjust each group’s figure according to the “GMAT pipeline.” A multiplier is used to adjust a school’s minority group population based on that group’s presence in the GMAT test-taking population relative to the US population. By comparing the GMAT makeup and the US population makeup, we are able to identify overrepresented minority groups such as Asian American students (GMAT % greater than US %) and such underrepresented minority groups as Black and Hispanic students (GMAT % less than US %). We then give schools more credit for the underrepresented minority students they recruit.

That multiplier is then applied to each group’s true percentage. For example, a school with 20% Black students would have an “adjusted Black share” of (20*1.72) = 34.4%. Below are the multipliers.

Race/Ethnicity US population percentage (Q) GMAT population percentage (P) Multiplier (Q/P)
Black 14.23 8.29 1.72
American Indian and Alaska Native 1.73 0.96 1.80
Asian American 6.82 16.08 0.42
Native Hawaiian and Other Pacific Islander 0.44 0.58 0.76
Multiracial 3.45 2.97 1.16
Hispanic or Latino (of any race) 18.43 9.18 2.01

Students can identify as more than one race and/or ethnicity. Because of this, when including White students, the total summed population of all racial/ethnic groups can exceed 100%. Similarly, if the identities of some students are unknown, the summed total can be less than 100%. To treat schools equally, a normalizing factor is introduced to assume all schools’ totals equate to 100%. For example, if a school’s summed total of all groups equals 115%, while another’s equals 90%, the former’s figures will each be adjusted down by a factor of (100/115 = 0.87), while the latter’s figures will be adjusted upward by (100/90 = 1.11).

We then sum up all adjusted racial/ethnic shares of all minority groups for each school and multiply it by that school’s normalizing factor to obtain a total adjusted percentage of minority students.

To reduce the impact of outliers, we next take the logarithm of each total percentage score. The transformed scores are normalized onto a 1-100 scale. Schools that do not provide race and ethnicity data receive a zero.

Gender (50%)

Total women + nonbinary population

We calculate the total percentages of women and nonbinary students for each school.

We then take the logarithm of each total percentage score to reduce the impact of outliers. The transformed scores are then normalized onto a 1-100 scale. Schools that do not provide gender data receive a zero.

Final Scoring

For the final diversity score, log-adjusted scores for race/ethnicity and gender are averaged, then rescaled from 1-7 for a final number (7 would be awarded to a theoretical school with the maximum minority and women/nonbinary populations of all schools in the ranking; 1 represents a school with the lowest percentages of both minority and women/nonbinary enrollment). This figure is used when applying the Diversity Index’s weighting to a school’s overall score for the entire ranking. Schools with fewer than 10 US students are excluded from the Diversity Index.

Final Overall Score

Following the above calculations schools have raw scores between 1 and 7 for each index. These index scores are then rescaled from 0 to 100. A raw score of 7 equates to 100, while a raw score of 1 is represented by 0. A school’s raw score for each index is calculated proportionally between these two extremes.

These 0-100 scores are then weighted according to the index weights outlined in Step 1 for a final overall score and ranking.

A note on scoring:

This year’s final scores look different compared with those in prior editions of Bloomberg Businessweek’s Best B-Schools ranking. However, the numbers are simply scaled differently and have no effect on the underlying measurement of schools’ performance relative to one another or their ultimate ranks.

Previously, schools’ raw scores of 1-7 for each index were weighted according to the stakeholder-determined weights for a final overall score of 1-7. This final overall score was then normalized onto a 0-100 scale. The school with the highest 1-7 raw score received a 100, while the school with the lowest received a 0. All other schools were scored proportionally in between. Under this system, this year’s scores would look like this, with each bar representing a school. The black bar represents a single school and its score in each index:

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To better highlight the competitiveness between schools within and across each index, we’ve adjusted the scale. Schools’ raw scores of 1-7 for each index are first transformed into a 0-100 score, where 100 represents the theoretical maximum of 7, and 0 represents a 1. Then these 0-100 scores are weighted according to the stakeholder-determined weights for a final overall score of 0-100.

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The approach means a final score of 100 represents a theoretical “perfect” school that scores a 7 on every index’s raw score, whereas last year a 100 was awarded to the school with the highest overall raw score. A 0 is now reserved for a theoretical school that scores a 1 for every index, as opposed to the school that has the lowest overall raw score. This scoring method does not change the overall ranking or the relative distance in scoring between schools.

Regional Results

We display regional pages for Europe, Asia, and Canada in addition to one for the US. We scored schools in two separate groups, US and non-US, on a 0-100 scale.

Other Features

Ranking Personalization

To help readers customize their use of the tool and explore the schools more broadly, we created filtering tools enabling readers to sort schools by a range of salaries, geographic preferences, and industry choices.

Campus Atmosphere

We asked broad questions to describe what campus life is like for female, LGBTQ, and minority students, such as whether “women are given equal opportunity to participate in class discussions and on teams” and whether “minorities are well represented among the faculty and administration.” We also focused on questions about the B-school curriculum, such as whether “minority protagonists are well represented in case studies.”

Quotes Highlighting What’s Best About a School

“What is the best thing about your MBA program?” Six thousand nine hundred twenty nine students and alumni answered. We used natural language-processing to identify representative comments from each school based on their common themes and keywords. After eliminating duplicates, we present these comments on each school’s page.

Key Numbers

The Universe

Bloomberg ranked 117 business schools around the world. Programs can be based in any country, but MBA classes must be taught primarily in English.

All schools were required to submit employment data for the Class of 2021, following standards set by MBA CSEA, a trade group founded in 1994 to establish and collect consistent, comparable, peer-reviewed data.

Schools were then given surveys to distribute to three stakeholder groups:

  • Students who graduated from Oct. 1, 2021, through Sept. 30, 2022
  • Alumni who graduated from Oct. 1, 2013, through Sept. 30, 2016
  • Employers that recruited MBA graduates for full-time positions in 2020 and 2021

With the help of the business schools, we surveyed 6,422 students, 11,304 alumni, and 778 employers. Schools must abide by Bloomberg’s strict code of ethics, which is meant to ensure that all survey respondents voluntarily take part in our surveys with no bias or pressure from school officials or their peers.

Minimum thresholds for survey response rates are based on the size of a school’s graduating and alumni classes. Schools that did not meet survey thresholds were eliminated. We qualified one school that met participation requirements for two of the three stakeholders, but was one response shy of the stated threshold for the third group of surveys.

All ranked schools confirmed the accuracy of the data they had submitted to Bloomberg in August and September.