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Business Masters Tops Methodology
Learn more about the methodology behind the

QS Business Masters Tops 2019

.

Data was collected in early 2018, using three surveys; the , the and a survey completed by the business schools themselves. For the purpose of these rankings QS did not ask schools to survey their alumni.

Data received was based on 2017 graduating class (for career/employment statistics) and 2017 starting class for information on class makeup. For employment information we requested that the data is relevant to six months after graduation. When this data was not available we used the most recent available data provided by the schools.

To be included in the Masters in Finance Tops 2019, Masters in Management Tops 2019, Masters in Marketing Tops 2019 or Masters in Business Analytics Tops 2019 programs had to:

  • Be taught mainly on-campus (i.e. not distance learning)
  • Have had at least one graduated class
  • A class size of at least 10 students to qualify

The methodology is adapted to accept both full and part-time programs as well as pre and post-experience programs.

QS Masters in Management Tops 2019 Breakdown

  • Employability – 35%
  • Alumni Outcomes – 15%
  • Value for Money – 20%
  • Thought Leadership – 20%
  • Class & Faculty Diversity – 10%
Indicator

Source

Weight

Employer Reputation (Employability)

QS Employer Survey 2013-2018

30.0%

Employment Rate (Employability)

Reported by Business School, Validated by QSIU

5.0%

Alumni Outcomes Index (Alumni Outcomes)

Various Lists of Successful and Diverse Companies

15.0%

10Y ROI (Value for Money)

Reported by Business School, Validated by QSIU

15.0%

Payback Month (Value for Money)

Reported by Business School, Validated by QSIU

5.0%

Academic Reputation (Thought Leadership)

QS Academic Survey 2013-2017

15.0%

Research Impact (Thought Leadership)

Scopus - 2012-2017 Period

2.5%

PhD Faculty (Thought Leadership)

Reported by Business School, Validated by QSIU

2.5%

Gender Balance – Students (Class & Faculty Diversity)

Reported by Business School, Validated by QSIU

2.5%

Gender Balance – Faculty (Class & Faculty Diversity)

Reported by Business School, Validated by QSIU

2.5%

International Mix – Students (Class & Faculty Diversity)

Reported by Business School, Validated by QSIU

2.5%

International Mix – Faculty (Class & Faculty Diversity)

Reported by Business School, Validated by QSIU

2.5%

To be included in the Masters in Management Tops 2019 the program has to be taught by the business faculty and mostly related to business management. Where doubts arose we consulted with the schools regarding the curriculum.

QS Masters in Finance Tops 2019 Breakdown

  • Employability – 30%
  • Alumni Outcomes – 20%
  • Value for Money – 20%
  • Thought Leadership – 20%
  • Class & Faculty Diversity – 10%
Indicator

Source

Weight

Employer Reputation (Employability)

QS Employer Survey 2013-2018

30.0%

Alumni Outcomes Index (Alumni Outcomes)

Various Lists of Successful and Diverse Companies

20.0%

10Y ROI (Value for Money)

Reported by Business School, Validated by QSIU

15.0%

Payback Month (Value for Money)

Reported by Business School, Validated by QSIU

5.0%

Academic Reputation (Thought Leadership)

QS Academic Survey 2013-2017

15.0%

Research Impact (Thought Leadership)

Scopus - 2012-2017 Period

2.5%

PhD Faculty (Thought Leadership)

Reported by Business School, Validated by QSIU

2.5%

Gender Balance – Students (Class & Faculty Diversity)

Reported by Business School, Validated by QSIU

2.5%

Gender Balance – Faculty (Class & Faculty Diversity)

Reported by Business School, Validated by QSIU

2.5%

International Mix – Students (Class & Faculty Diversity)

Reported by Business School, Validated by QSIU

2.5%

International Mix – Faculty (Class & Faculty Diversity)

Reported by Business School, Validated by QSIU

2.5%

 To be included in the Masters in Finance Tops 2019 the program has to be taught in business faculty and related to finance. We also included Masters in Financial Engineering (MSFE) programs when looking at masters in finance. While it has been argued MSFE programs place too much of an emphasis on quantitative skills, we find that this is not always the case and as such, they are comparable.

QS Masters in Business Analytics Tops 2019 Breakdown

  • Employability – 30%
  • Alumni Outcomes – 20%
  • Value for Money – 20%
  • Thought Leadership – 20%
  • Class & Faculty Diversity – 10%
Indicator

Source

Weight

Employer Reputation (Employability)

QS Employer Survey 2013-2018

30.0%

Alumni Outcomes Index (Alumni Outcomes)

Various Lists of Successful and Diverse Companies

20.0%

10Y ROI (Value for Money)

Reported by Business School, Validated by QSIU

15.0%

Payback Month (Value for Money)

Reported by Business School, Validated by QSIU

5.0%

Academic Reputation (Thought Leadership)

QS Academic Survey 2013-2017

15.0%

Research Impact (Thought Leadership)

Scopus - 2012-2017 Period

2.5%

PhD Faculty (Thought Leadership)

Reported by Business School, Validated by QSIU

2.5%

Gender Balance – Students (Class & Faculty Diversity)

Reported by Business School, Validated by QSIU

2.5%

Gender Balance – Faculty (Class & Faculty Diversity)

Reported by Business School, Validated by QSIU

2.5%

International Mix – Students (Class & Faculty Diversity)

Reported by Business School, Validated by QSIU

2.5%

International Mix – Faculty (Class & Faculty Diversity)

Reported by Business School, Validated by QSIU

2.5%

The Indicators:

Employability

Between 2012-2018, we gathered over 218,821 responses to the QS Global Employer Survey, regarding which schools employers prefer to hire from. This large pool of information, gained from companies across all sectors and industries, has allowed us to put a significant weighting on employability in these rankings. Recent employers to take part in the survey include McKinsey & Company, Bank of America, Uber, Facebook, Google etc.  

Alumni Outcomes

We looked at over 150 regional and global lists such as the FT Global 500, the Forbes 2000 etc., to form the basis of our Alumni Outcomes Index. This is used to track over 49,000 executives, board members and CEOs of the largest companies in the world, and the business school programs with which they are associated. Companies include JPMorgan Chase &Co., Wells Fargo, Apple, Microsoft and AXA Group.

Value for Money

We used a number of data points to determine return on investment, which can often be one of the hardest metrics to accurately predict, with many permutations and possibilities. We looked at a 10-year return on investment, mapping average post-masters salaries against average regional salaries for non-masters graduates, taking into account forgone salary as well as tuition and cost of living (using Mercer statistics). Salary increases are factored into both non-masters and masters salary, with the latter increasing at a higher rate, as you would expect. We also take into account payback period and the percentage of graduates accepting employment within three months of finishing their studies.

We feel 10 years gives a more representative and meaningful return on investment compared with some rankings that use a five-year approach. No loans or scholarships were included in this methodology. We recognize no ROI calculation is perfect but believe we have come up with the best approximate value for money calculation with the data available.

Thought Leadership

We take a number of things into consideration when determining thought leadership. First, we look at 260,920 responses from academics from 60 countries across the globe. The percentage of faculty with a doctoral degree is also taken into account, as is research impact. As per the QS World University Tops by Subject methodology we measure citations per paper, rather than citations per faculty member.

Class & Faculty Diversity

To give a reflection of diversity within a program we look at a combination of both female students and faculty within a program (schools with an equal split receiving the highest possible score). In addition we also take into account the percentage of international students on the program and international faculty at the business school as a whole.

QS Masters in Marketing Tops 2019 Breakdown

  • Employability – 35%
  • Alumni Outcomes – 15%
  • Value for Money – 20%
  • Thought Leadership – 20%
  • Class & Faculty Diversity – 10%
Indicator

Source

Weight

Employer Reputation (Employability)

QS Employer Survey 2013-2018

30.0%

Employment Rate (Employability)

Reported by Business School, Validated by QSIU

5.0%

Alumni Outcomes Index (Alumni Outcomes)

Various Lists of Successful and Diverse Companies

15.0%

10Y ROI (Value for Money)

Reported by Business School, Validated by QSIU

15.0%

Payback Month (Value for Money)

Reported by Business School, Validated by QSIU

5.0%

Academic Reputation (Thought Leadership)

QS Academic Survey 2013-2017

15.0%

Research Impact (Thought Leadership)

Scopus - 2012-2017 Period

2.5%

PhD Faculty (Thought Leadership)

Reported by Business School, Validated by QSIU

2.5%

Gender Balance – Students (Class & Faculty Diversity)

Reported by Business School, Validated by QSIU

2.5%

Gender Balance – Faculty (Class & Faculty Diversity)

Reported by Business School, Validated by QSIU

2.5%

International Mix – Students (Class & Faculty Diversity)

Reported by Business School, Validated by QSIU

2.5%

International Mix – Faculty (Class & Faculty Diversity)

Reported by Business School, Validated by QSIU

2.5%

FAQs

Why are the indicator weightings different for Masters in Management/Marketing Tops 2019 compared to Masters in Finance Tops 2019 and Masters in Business Analytics Tops 2019?

The only difference in method pertains to the inclusion of employment rate in the Management/Marketing Tops 2019. We would like to have included that for Masters in Finance and Masters in Business Analytics Tops, and in the future hope to be able to, but were unable to gather enough data this year.

What if more than one program per ranking was submitted by the business school?

Only the top-ranked program is included. That is not to say subsequent programs would not rank highly. They are not ranked for the sake of clarity. As one of our main indicators includes diversity, including or combining multiple programs from different locations could lead to inaccurate data.

 How are currency rates calculated?

Currency rates are accurate as of 1/1/2018, while salaries reported in reputational surveys were converted using an average of the years in question. Conversion rates do fluctuate and we take this into account in our calculations.

How is the data validated?

All data received from schools was subject to verification checks, including, where possible, comparison with historical data, peer schools and other published sources. QS reserves the right to alter information if a more accurate source was found. Employer/academic questionnaires were also audited for multiple or false entries.

What if a school didn’t provide all the data required?

When data was not supplied (by a minority of schools), QS surveys such as the , the were used in conjunction with QS research into public to make an accurate estimate. Examples of sources include schools’ employment reports and class profiles.

If a school didn’t provide data how can you be sure the information used was accurate?

Information used in these cases was compared with a number of sources and verified as best as possible to produce the most accurate figure.

How are weightings fairly applied to get an overall score?

We use z-scores to ensure the data is reliably combined to produce an accurate and fair overall ranking. You can .

Why are there schools missing who you might expect to be present?

Schools are excluded if they did not fit the criteria necessary to be present in the ranking, if the program was too new, not enough data was provided etc.

We’re a business school and want to be involved in the next rankings. What do we need to do?

Contact to find out and for any other questions you might have regarding the rankings.

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Written by QS Staff Writer

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2 Comments

This is not a great methodology. These metrics say almost nothing about the quality of business analytics programs.

1. Your academic and employer reputation survey responses are associated with the reputation of the University and not with the analytics program. You additionally chose to aggregate responses from the past 5 years. when most of these programs didn’t exist 5 years ago.

2. Your alumni outcomes are based on business school programs when not all of these Analytics programs are even associated with their institution’s business school.

3.Your “Value for Money” calculation uses a 10-year return on investment. As I already stated, the vast majority of these programs didn’t exist 10 years ago. For example your top program - MIT’s Masters in Business Analytics was founded in 2017.

How about rank for Master of Commerce Business Analityc UNSW?

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