COLLEGES USUALLY RELY on marketing, alumni networks, and positive
word-of-mouth to attract new students, but what if predictive
analytics could do a better job of creating the perfect match between
students and universities? And what if advanced analytics could help
schools develop better processes for increasing enrollment, reducing
attrition, and improving job prospects for graduates?
These questions were considered in October at the inaugural Advanced
Data Analytics Summit hosted by the University of Pittsburgh
in Pennsylvania and Othot, a Pittsburgh-based provider of advanced
analytics for higher education. During the two-day summit, representatives
from U.S. universities shared how they are using advanced
analytics to grow their enrollment, maximize tuition revenue, and
improve overall performance.
Keynote speaker Jaime Casap, education
evangelist at Google, discussed
the factors that Generation Z will bring
to the education equation in the future.
Specifically, he noted that members of
Generation Z are willing to give information
about themselves as long as an
experience is meeting their expectations.
He added that schools can use
analytics to create the educational programs
that these students are seeking.
Other education and technology experts
offered their own insights, which resulted
in four key takeaways:
1. Most schools are paying attention
to the aggregate, when they need to
focus on the individual. Students don’t
decide to attend colleges in cohorts
of 4,000; they decide one by one. To
increase conversion rates, colleges have
to ask the right questions; then they can
let data indicate the right tactics that
human admissions officers can use,
such as telecounseling, to engage with
individual students.
2. Schools are losing students they
shouldn’t be losing. Even before they
step on campus, students send myriad
behavioral signals that let colleges know
they might not stay. Schools need to pay
attention and respond proactively, or
those students will be gone by midterms.
John P. Campbell, vice provost of West
Virginia University in Morgantown,
said, “The goal should be to identify
early signs that can enable early interventions,
so that you can re-recruit your
freshmen to become sophomores.”
3. Advanced analytics can help
create a more meaningful definition of
student success. Schools can’t merely
consider graduation rates; they must
focus on the entire lifecycle, from
admissions to retention to graduation
to post-graduation success. A whole
host of factors influence why students
choose schools and complete degrees,
and universities must support students
holistically, not just academically. For
instance, the smartest student won’t graduate if she can’t pay tuition, so
schools must understand and respond
to each student’s financial situation.
Advanced analytics allow schools to
ensure that students are in the programs
that suit them best and that they are
receiving the support that will help them
through academic, financial, and personal
difficulties. As Marc Harding, vice
provost for enrollment at the University
of Pittsburgh, pointed out, “Analytics
is the art and the science of acting in
the right moment” in ways that nudge
students toward desired outcomes and
away from negative ones.
4. Data alone won’t drive the change. The people using the data influence the
outcomes at every stage, from admissions
through graduation. According to
Jamie Hansard, executive director of
undergraduate admissions at Texas Tech
University in Lubbock, “Data-driven
decision making is about empowerment.
What does the data tell you?”
One final insight came from Andy
Hannah, CEO of Othot. He is also an
adjunct professor of entrepreneurship
and analytics and an entrepreneur-in-residence at the University of
Pittsburgh. He noted that data will be
valuable only if leaders can utilize the
insights to improve outcomes—for
students as well as schools.