When I went to college in the 1980s, I was able to pay most of my way and graduate with just a small loan balance. Today, the average student loan debt is more than $25,000; Americans hold more such debt than credit card debt—$1.2 trillion and $714 billion, respectively, as of last fall.
So while I contemplate taking on a side job as an Uber driver when my second child heads to college next year, I also understand that universities face challenges on multiple fronts. Like many organizations I write about, they’re struggling to streamline operations and at the same time they must innovate to stay competitive—or perhaps catch up.
Some quick numbers: The average annual cost for tuition and fees at a public four-year university in 1985-86 (when I graduated) was $2,918 (in 2015 dollars). In 2015-16, that cost was more than three times higher at $9,410 (and doesn’t include room and board).
Parents, say it with me: Ouch.
Revenues are way up, thanks to more students attending college, but costs are soaring as well. Part of the problem is a facilities-construction arms race to attract the best students. Part of it is increasing and costly regulation. Another big part is the cost of bloated college administrations, according to a 2015 New York Times analysis of the situation. And while enrollment has risen by almost 50% since the mid-1980s, state funding per full-time student has decreased by almost 25%, according to the College Board.
Universities trying to get their arms around this financial picture, across departments and divisions, are finding that they’re stymied by old, heavily customized systems that are inflexible, perpetuate inefficient silos, and cost a lot to maintain.
They’re starting to realize that a couple of little one-off solutions will not get them to where they need to be, says John Curry, director of strategic initiatives in the Higher Education Practice at Deloitte Consulting. “The way to get out of this perfect storm is to address every aspect of it, and reposition the university with respect to the forces blowing at them,” says Curry, who spent more than 25 years in leadership positions at MIT, Caltech, UCLA, and USC before joining Deloitte.
Curry recently took part in a webcast discussion with Mike Gower, executive vice president of finance and treasurer at Rutgers University, and Jeff Henley, Oracle executive vice chairman, about the evolving economic models in higher education and how universities must shift their thinking and operations to thrive—sometimes just to survive.
In an interview before the webcast, Curry offered the following advice for universities looking to rethink their operations.
Focus on the End Game
The impetus for adopting modern, cloud-based financial/ERP systems is often twofold: University leaders realize that their current systems are inefficient and rigid, and they’re faced with an expensive and complex update they want to avoid.
But when exploring options, Curry says, it’s critical to “really think about their vision of what they want to achieve. This is very important, but often not done.”
For example, university leaders might initially say they want systems to do transactions, but what they really want is decision support—the ability to query data and build models with their data. In this time of tight finances and ever-evolving tech-based teaching methods, analyzing the effectiveness of those new methods is critical, and that involves being able to analyze data from systems across the university, not just in one department or function.
Of course, people don’t like change, so university leaders must engage with employees throughout the change process, communicating the greater vision and what it means for them and their departments.
For example, when Boise State University was moving to a cloud ERP system, its finance and administration department worked with employees campuswide to document current business processes and discuss new processes and features. Along the way, they discovered that a particular transaction was being approached 100 different ways, and they were able to communicate how a consistent approach was better for the university and would make employees’ jobs easier.
“The strongest mediator in dealing with change management in an academic setting is very good data,” Curry says. “When the data are incontrovertible—when there aren’t conversations about my data from my system versus your data from your system, but it’s just data, and this is what it says. Here’s the business case, and here’s what we can do to benefit the university, and here’s how it will benefit you. That’s a very different conversation.”
Band-Aids Don’t Work
Curry says he has seen universities try a range of stop-gap measures to address budget shortfalls. Some cut budgets across the board; others cut costs here and there without consulting any data to support their decision—likely because they didn’t have access to data that would help them with these decisions.
“An accumulation of these kinds of cuts over the years has left real imbalances at some universities,” he says. For example, he worked with one university that took the path of cutting its budget across the board—yet some departments had doubled the number of students they educate, while others had lost half of their enrollment. Those student numbers weren’t being linked to budget allocations because university leaders didn’t have the systems in place to connect those dots.
“Ironically, the more analysis that universities do before they modernize their systems—even though they’re modernizing so they can do better analysis—the better off they’ll be because they’ll know what some of the problems are,” Curry says. “Once those are identified, it’s easier to make the case to faculty, to staff, and to various divisions that they need to move toward a systematic reboot.”
Address the Internal Economy
“Every provost knows that psychology departments don't cost as much as electrical engineering,” Curry says. “Engineering needs big, expensive laboratories and equipment. Psychology doesn’t. Yet at many schools, the same tuition is charged for both programs.”
As a result, the programs that are less expensive to run end up subsidizing the more expensive ones—which means that universities that want to grow their engineering programs (which are very popular) should also focus on growing their popular but less-expensive programs such as psychology, he points out.
But for many universities, the inadequacy of their internal reporting capabilities across departments and divisions makes such analysis extremely difficult.
“You need to look at a combination of student data, human resources data, and financial systems data to truly understand the bottom line,” Curry says. “But if you have unintegrated data across those systems, with no comprehensive data warehouse or analytics tool, you can’t study that issue. And you’ve probably got a number of back rooms staffed with people maintaining customizations on systems that won’t talk to each other and won’t give you the answers you need.”
