The Retention Formula

During the years I worked in public higher education in the US overseeing enrollment, I spent a lot of time trying to “track” students. While enrollment encompasses a broad range of operations and strategic planning, one of the trickiest areas was retention. If you work at a university and have attended a presentation about retention, the one question that is always asked is “Why do students leave?” As anyone in the retention and advising field will tell you, this is not an easy question to answer. There is no single answer or obvious cause. Solving the retention puzzle almost always involves locating quantitative and qualitative data and then using a good bit of anecdotal evidence to draw conclusions.

The equation for improving retention seems easy enough: P + R = M

P =Problem, or the cause for stop-out

R =Response, or the strategic tactic

M= More students, or increased retention

Of course, identifying the problem and then executing a response are both equally challenging endeavors. In my professional experience, I was often the recipient of anecdotal information for attrition causality. For example, faculty often pointed to academically unprepared students. In turn, I have spoken to students who leave because they don’t feel connected to or supported by their assigned academic advisor, or because there is a single professor from whom they will need to take the majority of their programmatic courses and they feel unable to forge a strong bond. I have also been asked by top-level executives what actions professional or academic advisors carry out to prevent students from stopping out. Meanwhile, student support staff will often point to a lack of stable housing or food insecurity as reasons students are forced to leave school.

Amidst the passive finger pointing there are multiple truths, but in order to fully understand why students leave college, it is important to look at data—both nationally and at one’s own institution. National data does support some of the anecdotal reasons for declining or lower-than-anticipated retention numbers. According to the National Student Clearing House Research Center, in 2018, only 75.9 percent of first-time college students persisted until at least Fall of 2019 across universities studied within the United States. That number significantly drops as students progress, with only about 58% of students graduating with a degree from a 4-year university from start to finish.

According to multiple sources, the top reasons students drop out are financial (consistently the number one reason), students are not prepared for the academic rigor of college life, unhappy with their college experience, lack of support structure when it comes to family or housing, and well… just life in general.

However, as senior leaders of Enrollment Management understand, when the executive team or the board of trustees wants to know why the retention rate is lower than the national average and how the SEM team plans to turn it around, pointing to national data only goes so far. What is needed is reliable, consumable data that all stakeholders can understand from the Finance/Budget team to the on-the-ground professional and/or academic advising team. Awareness of the likely causes is a good place to start, but they must be demonstrated to be the case at one’s own college or university before leadership is willing to invest in the proposed solutions.

Gaining access to reliable and understandable data isn’t always that easy, however. If your institution—like many I have encountered—does not have a strong data governance team or data source, your first inclination might be to invest in retention and persistence software. There are dozens of these on the market today and new ones seem to pop up all the time. Retention software often uses a combination of LMS and SIS data to predict which students are most likely to drop out, and then offers solutions for helping those students with the resources they need. Learning Management Systems are also attempting to enter this market with lots of analytics being introduced with each update.

There is an additional disconnect between Admissions and Enrollment stages that can pose problems for tracking students. Admissions finds and nurtures prospective students all the way through the conversion stage using a CRM that integrates with an institution’s SIS. The retention software that is subsequently purchased also integrates with the CRM and collects the data originally submitted from the CRM. This might be great when it comes to collecting the type of raw data contained in the SIS or ERP System, but there is usually very little connection linking the student to all of the interactions they have had up to enrollment. Once they are enrolled and their tuition paid, they are handed off to the advising team or to a faculty advisor and start all over again forging new relationships and relaying important contextual information about their economic and personal situations.

Unfortunately, when a student suddenly disappears from the radar and is classified as a stop-out, the executive team sees only the number—not the student who needed emergency surgery during midterms that put her too far behind or the student who’s housing situation fell apart causing him to drop out and find work. The executive team also rarely sees or knows about all of the staff and faculty that worked with the student before they left. But all of those touch points are important in understanding the big picture as well.

In short, there is so much more to that singular number indicating stop-outs vs. graduates vs. retained. In my experience, most provosts, deans, VPs, and Presidents do not have the ability nor the bandwidth to figure out how to navigate retention software to find the problem.

What I love about FAST Student is that it measures, analyzes, and stores all of the information that all of the stakeholders require. FAST provides the ability to track and communicate with students from application through graduation. It allows for the retention and advising staff to communicate with advisees and document touchpoints, academic progress, and actions take toward retaining them. FAST houses dashboards that upper-level administrators and Board members can check out on a daily basis to monitor retention and graduation (and all things enrollment). It also allows managers and supervisors to track employee engagement with students. FAST can even produce reports to help the SEM and academic teams run a variety of correlative analyses for initiatives like identification of courses in which students are most likely to do poorly, which advisors have the highest attrition rates, or at which points in the student life cycle they are most vulnerable to leaving the institution.

Perhaps what we really need is a retention formula rather than an equation. Equations are all about finding the answer–in this case the answer must be improved retention. Formulas, on the other hand, are much more about showing us how things are related to one another. Perhaps a formulaic approach to retention looks something like this instead:

(Qualitative Data + Quantitative Data + Anecdotal Information) * Analysis = A Broader Understanding of Institutional Retention Trends

Simplified it’s another way of saying:  (a+b+c)d = x

In short, retention is rarely a problem with a single solution. A better way to think of it is to locate the available information and data, conduct an analysis of that data, and aim to achieve an understanding of retention trends. Once the bigger picture is more clear, develop a plan of action aimed at suturing the most severe retention bleeds and to addressing any additional gaps. Make sure the plan is measurable and actionable, assign action leaders, and agree on deadlines. And no matter what–remember to regularly review the data to make sure your action plan is working and make changes as you progress through the plan.