UCLA Anderson Post MBA Job Placement and Salary

by Matthew Kuo on May 11, 2013

in MBA

To learn more about Excel, go to the organized listing of all my Excel tutorial posts or review the
 

UCLA Anderson Post MBA Job Placement1

The following aggregated salary data has been pulled for UCLA Anderson’s Class of 2012 from REIS, or the Recruiting and Employment Insights System.  REIS is basically a “salary transparency” service created by an Anderson alumni to empower MBA students during the offer negotiations process.  You can’t look up any one person’s individual salary, but you can look at consolidated views for your own school by industry, function, and company.  REIS used to be called SalaryView, and I assume they had to change the name for legal reasons (because the name REIS is much worse).

UCLA Anderson Post MBA Job Placement2

Looking at the data, you can see that there does appear to be some correlation between the amount of salary offered and how many students end up working for a particular specialization.  This would imply that students in our MBA program are generally recruiting for higher paying jobs.  Real Estate and Public Sector jobs are predictably at the bottom of the scale while Consulting and Technology positions offer the highest base salary.  One interesting data point is Entertainment & Media, which shows a relatively high base salary for given the stories about how difficult it is to recruit for this industry, but many different types of positions can be grouped in this category.

However, there are a number of issues with the data to consider before making any conclusions:

  • No Mandatory Reporting – It’s still a bit odd to me, but Anderson doesn’t really have a mandatory salary reporting rule, even though this metric plays a significant role in our overall rankings.  Therefore, some students haven’t reported their job placement and are therefore not present in this data set.  People with lower salaries tend to be less likely to report their job placement.
  • Recruiting Office Adjustments – Some of this data gets adjusted before it goes to the ranking publications to fix errors and probably fill in some of the aforementioned unreported data points.  I obviously don’t get any feedback on that process until I see it in the rankings.
  • Industry versus Functional Grouping – The grouping I’ve listed is titled “specialization” because it includes both industries and functions.  There’s no real consistent methodology on whether a job is grouped within its industry or its function; at the end of the day, it’s the student who decides how to categorize it.  Therefore, there can be some discrepancies within the group totals.
  • Other Grouping – The original data also included a group called “other” which I’ve excluded because the data was so varied.  This included people who started their own companies, receiving no salary, and a small handful of people with exceptionally high salaries.
  • Bonus Information – The salary information I pulled looked only at base salary and not bonus.  I tried to incorporate the bonus data, but it looked off.  In 2012, REIS was only recently getting off the ground and I believe they may have had some input errors during that year.  Without bonus data, investment bankers, who are grouped under finance, show a significantly lower compensation level than what they actually receive in total.
  • Accepted versus Received Offers – The current data set only tracks accepted offers, not all offers received.  While this has the possibility of skewing the data, it probably wouldn’t have a huge effect.  It’s likely that accepted offers correlate with received offers within any particular industry.
  • Supply versus Demand – For any specialization to have a high number of offers is driven by both student interest as well as recruiter interest.  Therefore, if recruiters only supply a few jobs within a category, the number of students ending up in that role will likely be very low as well.

I’ll run this analysis again for the Class of 2013 and hopefully the data will improve in that iteration.  One key thing missing from this data is how hard it was to get a particular job.  Essentially, the job offers as a percentage of the overall interest level.  While this will be impossible to calculate definitively, I may be able to find a good proxy.

{ 0 comments… add one now }

Leave a Comment

Previous post:

Next post:


Related pages


how to create a vlookup function in excelhow to create bar graph in excel 2010how to create formulas in excelhide formula in excel 2007how to get rid of duplicates in excelw4 allowances calculatorcollege library uclagreater than or equal to symbol in excelexcel generatorsucla book storegaussian distribution function excelexcel costing templateexcel 2007 formulas and functionstrue false formula in excelif isna vlookup functionexcel sheet vlookuphow to create a bell curve in excel 2007quotations in exceldownload microsoft powerpoint 2010 free trialexcel match two columns of dataamazing excel tricksvlookup in excel step by stephow to use hlookupshortcut for checkmark in excelstacked horizontal bar chartexcel task management templatehow do i create formulas in excelwhat is a vlookup function in excelvlookup formula for excelexcel compare two lists and return differencesvlookup based on two conditionsexcel continuous numberingconverting adobe to exceltrue false excel formulaexcel chart min max averageexcel match formulafind and delete duplicates in exceltick mark symbol wordhow to choose random numbers in excelucla anderson mba tuitionkey excel formulasinterview padfoliocreate bins in excelexcel currency formatms excel formulas vlookupvlookup 3 columnsnest if statements in excelvlookup excel 2003commonly used formulas in excelfree trial microsoft office 2007 download full versionucla gpa neededvlookup return multiple valuescreate a histogram in excel 2010how to insert macros in excelvlookup 2 valuesisna meaninghow does vlookup work in excel 2007how to use hlookuphow to learn vlookuptch worksheetsnesting formulas in excelexcel cell format customexcel cse formulaframeworks for case interviewsifs in excelexcel count arraymicrosoft excel lookup functionms excel histogramthe goal by eliyahu goldrattwhat is the purpose of macros in excelapproximate matchtracking sheet in excelvlookup usagestandard deviation bell curve excelforecasting tools in excelexcel formula match
\n