You've done your research and are now convinced that an advanced analytics solution is a must-have for your enrollment office.
How do you convince others at your institution that this purchase is an investment—one that will pay dividends for years to come?
In this blog, I outline steps to build your case to invest in advanced analytics for strategic enrollment management (SEM).
Advanced analytics, specifically predictive analytics, what will likely happen, and prescriptive analytics, what can you and your team do to change the likely outcome, hold the greatest potential to achieve enrollment goals effectively and efficiently.
Additionally, advanced analytics hold the greatest potential to demonstrate return on investment to university leadership quickly.
That is, advanced analytics enable you to move from approval and implementation to measurable results in a short time frame, which provides the evidence you need to submit and receive approval for other recommendations for SEM investments.
After reading this post, you may want to read my two-part blog (part 1 and part 2) on the four-step method I have found successful in garnering institutional investment in SEM.
You should know your institution’s strengths, weaknesses, points of distinction, etc., and have a good sense of your market and the dynamics affecting that market in the short and long term.
However, here are some links to help you see your markets in the future and build your case for investment.
As I wrote above, increasingly advanced analytics are being used more and more across every sector of our society, so you can count on many of your academic and administrative leadership colleagues having knowledge and appreciation of advanced analytics.
Within the context of the EM challenges now and through the rest of the decade, you can rely upon that many, if not all, of them being allies in your campaign to gain investment for advanced analytics to support enrollment goals, particularly tuition revenue goals.
My experience has been that deans of business and engineering schools and academic leaders with STEM backgrounds have been some of the strongest supporters of investment in analytics, but with the proliferation of advanced analytics in so many fields, you may find your allies anywhere.
Among your fellow administrative leaders, increasingly, you’ll find the CIO, CFO, director of IR, and budget officers, willing allies who will not only support your recommendation but may also provide additional insights to support building your case.
The most powerful way to gain acceptance for an advanced analytics solution to support EM goals is by revealing how the tool will deliver a return on investment (ROI).
To gain approval for an investment in predictive analytics to support student success, including a new staff position to manage the process, I showed that, given our average net tuition revenue per student, we only needed to retain 16 more students to the following academic year across all 18,000 undergraduates.
With the deans of engineering and business leading a discussion about the necessity for us to leverage advanced analytics, I won approval easily.
Here are some examples of how advanced analytics can deliver ROI by increasing net tuition revenue after aid and optimizing resources. I want to provide you just a few examples. There are many more!
Advanced analytics models allow you to understand price sensitivity for individual students because they consider many more variables than simple financial aid leveraging models, which consider two variables, academic profile and the family’s expected family contribution (EFC).
Financial aid leveraging matrices based on academic profile and EFC create cells with a significant number of students. The assumption is that the students in the cell have identical price sensitivity, which is not the case.
By considering many more variables, including behavioral variables that you can get from a CRM, you’ll be able to understand each individual’s price sensitivity and optimize your aid strategy and maximize net tuition revenue (NTR) after aid.
For instance, it is April 15, and it looks like you will fall 50 students short at census. On average, every student brings in about $20,000 of NTR. So those 50 students translate to a deficit of $1M in revenue for the following budget year.
With advanced analytics, you identify 100 students that, if awarded an additional $1,000 in aid, you will increase the student’s likelihood of enrollment enough to exceed your enrollment target by about 50 students.
You will also move the institution from a projected deficit of $1M in NTR to almost $1M over the NTR goals – a $2M swing.
In the same instance as above, it is April 15, and your advanced analytic platform projects that you will not achieve your enrollment or NTR goals.
As we did above, with advanced analytics, you can analyze how to invest the minimum amount of aid necessary to meet and exceed your goals. Or, even better than investing in more aid is prioritizing and focusing your recruitment and communication resources on the right students at the right time to increase the likelihood they will enroll.
Advanced analytics can reveal that it isn’t always about financial aid; you can identify individual students where you can significantly increase their likelihood of enrolling through a specific recruitment or marketing tactic.
You can identify which students whose probability of enrolling will increase the most by attending your admitted student day event.
Then you can coordinate a high touch campaign, or award travel vouchers, to get those students to campus, or during these days, conduct a VIP virtual admitted student day for those select students.
In this case, you will move the enrollment forecast from a deficit in enrollment and NTR to exceeding your goals with no additional financial aid spend.
By the way, advanced analytics provide the ability to optimize your resources at any time in the funnel from first contact to graduation, i.e., prospect => inquiries => applicants => admits => deposits => enrolled student => retention => persistence to graduation.
Don’t forget to invite the colleagues who support your move to advanced analytics to the meeting when you present your proposal.
Move quickly, and you will see the ROI and improve resource utilization.
Repurposing my own budget resources, I went from contract on February 1 for a predictive and prescriptive analytics platform to improve selectivity and yield through financial aid and non-financial aid tactics to implementation on March 15.
Over the next 45 days leading to May 1, we were able to leverage the advanced analytics platform for real impact. The platform proved to be instrumental in our ability to exceed our headcount, NTR, quality, diversity, and residency goals. We calculated that the platform had helped us exceed our NTR goal.
I was able to move quickly because my team had fully bought in and I had met with key colleagues, made my case for advanced analytics, and secured their support.
If your institution depends upon undergraduate tuition as the primary source of revenue, as most institutions do, talking to administrative colleagues about NTR and expected ROI should resonate. Key partners include information technology and institutional research.
As NACUBO, AIR, and EDUCAUSE state in their joint statement on the importance of advanced analytics, “A sense of urgency is critical as institutions commit to using data analytics.”
Advanced analytics improve decision-making and promote the nimbleness institutions need to survive and thrive.
As higher education leaders, enrollment managers must step forward boldly with a clear understanding of the current and future EM environment and the many associated challenges.
They must also articulate the absolute criticality of investing in and implementing predictive and prescriptive analytics to achieve institutional admissions and student success goals.
I think these steps offer a framework that will help you get the support to invest in advanced analytics at your institution. If you have any questions or would like to talk more about building your case, contact me at firstname.lastname@example.org.