THE/WSJ analysis of business schools: methodology

December 6, 2018

The rankings adopt a balanced scorecard approach, with 20 individual performance indicators combining to create an overall score that reflects the strength of each programme and school. The indicators are drawn either from institutional data or from a survey of business school alumni. In most cases, the data are normalised so that the values assigned in each metric can be compared sensibly with those in other metrics. These scores are then aggregated into four key areas, which we call pillars. The methodology is common to all four of the rankings, with the exception of the salary metric, with differences detailed below.

Resources

Faculty per student 11%
Teaching qualifications 6%
Career support staff per student 4%
Career support effectiveness 4%

This pillar reflects the human and instructional resources made available by the school to their students. Faculty per student gives a sense of whether the school has enough teachers to ensure students are fully supported. Teaching qualifications measures the proportion of teaching staff with a doctorate. Given the strong focus of business schools on career improvement, we also look at career support facilities, taking in both the number of career support staff per student and the effectiveness of the career support, according to the alumni surveyed.

The first three metrics are at the school level, and the last one is at the programme level.

Engagement

Learning engagement 5%
Interaction with teachers and
students 5%
Student recommendation 5%
Real-world relevance 5%
Research in teaching 5%

This pillar is built entirely from data collected in our alumni survey, which elicited almost 23,000 responses from students from three different cohorts: those who finished their studies in 2012 (y−5), 2013 (y−4) and 2015 (y−2). Responses to 10 questions are compiled into five metrics.

To assess learning engagement, we look at the answers to four questions:

To what extent did the respondent’s school support critical thinking? For example, developing new concepts or evaluating different points of view;

To what extent did the teaching support reflection on, or making connections among, the things that the student has learned? For example, combining ideas from different lessons to complete a task;

To what extent did the teaching support the application of the students’ learning to the real world? For example, taking study excursions to see concepts in action;

To what extent did the classes challenge the respondent? For example, presenting new ways of thinking to challenge assumptions or values.

To capture a student’s opportunity to interact with others to support learning, we use the responses to two questions:

To what extent does the student have the opportunity to interact with faculty and teachers? For example, talking about personal progress in feedback sessions;

To what extent does the college provide opportunities for collaborative learning? For example, group assignments.

In view of the practical nature of business degrees and to assess the level of relevance to the real world, we asked alumni the degree to which real-world cases were used in teaching, and whether they had the opportunity to meet or work with professionals with current real-world knowledge (outside the teaching itself). To account for the use of research in teaching, we asked about the extent to which current research was used and discussed during class.

Finally, we asked alumni about the likelihood of their recommending the school to a friend or family member. All those metrics are at the programme level.

Outcomes

Salary difference 12% (MBA: difference after/before. MIM, MIF: after)
Network 6%
Social good 5%
Entrepreneurship 5%
Opportunities 5%
Worth 5%

This pillar looks at various measures of outcomes, using alumni data from our survey.

The salary metric looks at the reported salaries of alumni: in the case of the MBA ranking, we look at the difference between current and pre-MBA salary; in the case of the MIM and MIF rankings, we look at the current salary only.

All salaries are adjusted for location, sector and gender; we also account for the employment status of the respondents (self-employed or salaried) and their work frequency (part-time or full-time). This allows us to draw meaningful comparisons between both the various respondents and respondents’ “before” and “after” salaries (such as in cases where alumni moved from one sector to another, or changed country or work frequency).

The other metrics in the outcomes pillar are derived from scores given on several questions in the alumni survey.

For the opportunities metric, we asked alumni how useful their degree was in helping them find opportunities in their chosen professional field.

For the entrepreneurship metric, we asked about how useful the knowledge acquired during their degree was (or would be) in helping them set up their own business.

For the worth metric, we asked alumni to rate the extent to which their degree was worth the amount paid for it.

For the social good metric, we asked alumni whether they had volunteered during the last year.

For the network metric, we combined responses to four questions asking alumni to rate both how much they had used and contributed to the alumni network for both professional and non-professional interactions.

All those metrics are at the programme level.

Environment

International students 3%
Female students 3%
International staff 2%
Female staff 2%
Economic diversity 2%

This pillar looks at the make-up of the student and staff body at each school, helping students to determine whether they will find themselves in a diverse, supportive and inclusive university environment.

We examine the schools’ proportion of international students and international staff, which are key indicators of whether they are able to attract talent from across the world. It also demonstrates which institutions have cultivated a multicultural campus where students from different backgrounds have the opportunity to learn from one another.

We examine gender diversity, by measuring the percentage of female students and percentage of female staff.

Finally, in order to address the contribution of the business school to social mobility, we measure its proportion of first-generation students

The first four metrics are at the school level, and the last one is at the programme level.

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