Enrollment Nerdery

A place to collect my thoughts on data analysis within Enrollment Management. Dare I call it Enrollment Science?

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My Thoughts on Enrollment Science


Enrollment Science is my attempt to relate the emerging role of Data Scientists to Enrollment Management Divisions within Higher Education.  Let’s get real.  Higher Ed is BIG business, and it’s about time that we start to embrace advanced techniques (i.e. the methods industry has been using for many years now) in order to be more efficient.  We need to think differently about how we run our organizations, and in my opinion, it starts with the principles of Enrollment Science.


Over the last few weeks, I have begun tagging posts on Twitter with the hashtag #emsci.   It’s about time that I discuss what I believe to be Enrollment Science. As far as I can tell, this post introduced the notion that:

Data is the new oil

That was back in 2006. In 2012, this Forbes articleseemingly struck a chord.   The concept of “Data Science” has been gaining tracking ever since.

What is #emsci all about?

At the end of the day, there is both an art and a science when it comes to Enrollment Management, the term coined by Jack Maguire.   As an industry, not only do we collect an immense amount of data internally, but we report extremely detailed information to a wide range of external audiences.  Outside of public companies listed on stock exchanges, no other industry is required to publicly expose this level of data.  It’s about time that we begin to use these datasets more effectively.   I am calling this Enrollment Science, a play off the wildly over-used term, Data Science.

Enrollment Science

Drew Conway famously used the venn diagram below to describe the skills required of today’s data scientist.   It’s not surprising that the emphasis on leveraging data would make it’s way to higher education.  NACAC recently hinted at the growing importance of Enrollment Scientists…..

Aside from communications, #DataAnalysis most critical skill for senior level #admissionjobs @NACAC http://t.co/lxhYE8B8PJ #emchat #edchat — NACAC (@NACAC) July 30, 2014

To be fair, the application of analytical techniques to solve business problems within higher ed is not new, and a number of vendors have been providing these services for some time now.  However, we rarely have “Big Data” in Enrollment Management, but I will talk about that in future posts.  Most of us who analyze Enrollment Management problems barely have Medium Data.  However, what we do have is disparate data.

Enrollment Science

In this post, I want to discuss the relationship between Data Science and Enrollment Management. I contend that Enrollment Scientists:

  1. Have both educational and practical experiences dealing with scientific method
  2. Are capable with one or more programming languages that are executed on the command line.  I will come back to this in a moment.  If you prefer Linux environments to Windows, you are well on your way to being an Enrollment Scientist.  The key takeaway is that dirty data does not scare you, and you rarely believe that “manual” data cleaning is the correct approach.  If your data operations staff are cleaning things manually, there is a good chance your process can be improved.
  3. When it comes to discussing advanced methodologies and the results from these approaches, Enrollment Scientists are able to synthesize the key facts to a non-technical audience.  I believe this skill to be the hardest of them all.

To put it simply, I  believe that Enrollment Scientists are capable of understanding the strategic reasoning behind a problem, can hack together datasets that come in a variety of shapes and sizes, and are able to effectively communicate the “so what” behind the results to senior leadership. Basically, Enrollment Scientists are the intersection of IT, Analytics, and Management.

 Technical Tools of the Trade

As referenced above, predictive techniques are just one tool in the Enrollment Scientist’s toolbox.  The items below are the skills that I believe are critical to the success of an Enrollment Scientist.

 What’s Next?

Outside of Tableau, all of the skills and software listed above are free, as in, free beer.  Even Tableau has Tableau Public, but there are usage limitations,  Nonetheless, everything you need to be effective within Enrollment Science is (basically) free.  Of course, it takes time to hone these skills, many of which can not be learned from a text book, but the efforts will pay off in spades. Enrollment Science is no longer a luxury, but a necessity in order to compete in today’s rapidly changing higher education landscape. From here, I aim to highlight how easy it is to get started within Enrollment Science.  I am very passionate about this topic, so I hope to share that passion with you.  My aim is to introduce you to the tools listed above, and apply advanced techniques to datasets that you already have in-house. Today, Enrollment Management divisions are asking increasingly complex questions.  Luckily, industry (i.e. for profit companies) have proven that we can leverage data to improve our position in the market, so it’s about time we get better at data within Enrollment Management.

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