2024 EDUCAUSE Top 10
#8: Financial Keys to the Future

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The financial positions of many colleges and universities are precarious. Overall, Moody's outlook for U.S. higher education was downgraded from stable to negative for 2023 due to revenue constraints (including tuition and government funding) and inflation.^Footnote1 Like the weather and politics, the financial situation for higher education is a local story. Not every institution is struggling, and state funding for higher education increased 5 percent on average in 2022. But in 28 states, funding is lower than it was before 2008.^Footnote2

Technology leaders must bring about three contributions to improve institutional finances. First, they can help reduce work by using process automation and optimization and by consolidating redundant technologies. Second, leaders can also ensure that institutional technology funds are spent efficiently and effectively. Technology is a cost driver. With inflation have come a series of startlingly large price increases by solution providers. The cost of cloud computing has skyrocketed, in part because cloud storage isn't so cheap when the data stored is increasing almost exponentially. Cybersecurity can help institutions avoid breaches with devastating reputational and financial consequences, but at an increasingly large ongoing cost. Although hiring managers often can't pay market rates for technology jobs, technology staff have some of the highest salaries in institutions.

Perhaps the biggest impact technology leaders can have on institutional finances is providing leadership of data and analytics initiatives to make informed financial decisions and projections, identify cost-savings opportunities, and optimize resource allocation. The factors composing institutional budgets and financial health are expanding, interrelated, and generally becoming more complex. They include enrollment projections, student retention projections, student success, grant funding, and risk and compliance requirements. Financial forecasting and planning involves looking at an expanding set of cross-functional business units and data sources and integrating them to develop dynamic models.

The challenge at many institutions is not that they lack the needed data. It's that the data is more distributed than ever in SaaS solutions throughout the campus, despite ERP systems and other data platforms available to pull the data together. So to develop elegant predictive analytics models, staff first have to find the data and reconcile and integrate it.

Higher education is in a period of turmoil and transformation. Institutions are merging or closing, leaders are looking to make complex changes to the business model, teaching and learning and working models and locations are in flux, the nature and purpose of the campus is being reexamined, athletics income is at risk, climate disasters are increasing, some traditional sources of income are at risk, and student services and experiences are changing. These conditions are calling on leaders to expand their forecasting models and horizons beyond the usual factors and to extend long-range financial forecasting and planning as many as five, eight, and ten years into the future. This is a daunting goal, but it may soon be possible to apply AI and machine learning to financial forecasting.

The Promise

Better data and financial models will improve institutional resilience in the face of escalating changes. Dynamic models can foster planning agility, enabling decision-makers to rapidly adjust projections to account for new information. Many institutions are not far from financial collapse, some are struggling, and others are trying to reinvent and reposition themselves to meet contemporary and emergent needs. Leaders have some tough choices to make and need good data and dynamic models to guide those choices.

QuickTakes

What's your superpower? Institutions facing tough challenges or tough competitive situations may be most open to radical changes. Large, complex institutions may have many more options and resources to apply to the problem. Institutional cultures that foster innovation and change may be able to think most broadly.

Data doesn't make decisions. Tough decisions are tough because the solutions aren't obvious and they're hard to live with. Better data can provide a clear picture, particularly looking forward, to help chart different paths, explore various scenarios, and make informed choices. But at the end of the day, institutional leaders—informed by data and strategic thinking—must use judgment to make the tough choices and choose the best paths forward for their institutions.

Act like business peers. It's time to apply business practices to improve modeling and forecasting—such as doing a landscape analysis, examining demand and supply, and developing sustainability forecasts.

Don't cede leadership to consultants. Consultants can help institutions improve their financial management maturity, but boards and leaders must own the strategy and truly lead the engagement to ensure that the institution benefits going forward.

The Key to Progress

There's no substitute for effective leadership when tough choices need to be made. Leaders must be able to inspire the community, articulate a clear vision for the future, and understand the details, trade-offs, risks, and options well enough to make good choices.

From Strategy to Practice

What You're Saying

"I would love to do something more groundbreaking in this area. We do a great job in negotiating contract to contract. In addition, we have ten-year plans created that allow us to shift away from tech that is no longer viable and plan the offsetting of the software. All of this is deep work. I would love to know if there is another, more radical approach."

"Our area has not received a budget increase in many years despite annual software and service uplifts. We're now faced with larger bills to support and not enough budget to cover everything. Renegotiating with vendors as we renew contracts is one way we're trying to manage costs, but we're also looking at dropping tools we don't use as much pre/post-pandemic."

Solution Spotlights

"Ursinus College is implementing new SaaS enterprise applications (e.g., Oracle Cloud Suite) and working within the HESS Consortium Collective Program on a collaborative model for best practice, a common implementation methodology, and mutual support and inspiration."

Gene Spencer

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"At Northwestern University, we realize that research datasets continue to increase in size due to several factors. As the data landscape evolves, we must continue to develop and provide affordable, accessible, secure, and robust data-storage solutions for researchers and administrators."

Jackie Milhans

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"University of Munster in Germany is developing an on-premises open-source cloud to replace costly proprietary software (e.g., VMware)."

Raimund Vogl

What You're Working On

Comments provided by Top 10 survey respondents who rated this issue as important

Academic analytics

• Investing in an analytics team at the provost office level, separate from the IT teams who are assigned to build the data mart.
• Our BI infrastructure is constantly being extended with new datasets, and there is a project to leverage the data in decision-making within faculties.
• Partnering with Gray Associates for academic program assessment to provide better insight into our programs and directions as a college.
• Using advanced financial analysis and modeling, which include accurate cost centers and costs of individual academic program delivery.
• Using data to assess curriculum effectiveness, streamline pathways, create new certifications and credentials, etc.
• We recently finished an academic program prioritization process to reduce majors and faculty using data. This was a big leap forward for us as an institution—using hard data to make decisions.

Budget/accounting management

• Creating an RCM (responsibility centered management) budget model and using activity-based costing to show financial transparency.
• Implementing heavily data-driven budgets and consequent decisions.
• The university transitioned to activity-informed budgeting that mixes activity-based budgeting with strategic investment decisions from university leadership. Our institutional research and BI team is instrumental in supporting leadership decisions.
• SaaS enterprise applications with built-in analytics. New budget management tools meant to facilitate excellent operations.

ERP

• Evaluating the future of ERP, to make it easier to access data to make informed decisions.
• We are implementing Workday for HR, payroll, and finance to take advantage of enhanced reporting so that we can use the data to drive decision-making in a difficult financial situation.

IT optimization

• Currently undergoing an IT audit (structure, expense, resources, purpose).
• Using financial reporting analysis to augment functional requirements when deciding on priorities and resource allocation; operations data on incidents, problems, and root causes as they relate to change and change approvals; work request metrics to improve service levels, time to implement, time to resolve, and staffing necessary to meet service levels; business impact analysis to determine priorities and funding for systems resiliency investments.
• We purchased a solution to tie our service catalog to our financial system and have developed a process and methodology to articulate the cost of our service offerings.

KPIs and ROI

• Our IRP department is expanding the tools and tying more objectives to institutional KPIs.
• Analyzing existing expenditures and methods for reducing fiscal outlay. Summarizing ROI and TCO for existing technology. Identifying redundancies and eliminating outdated technology.
• Financials is working to provide analysis and justifications that support the institutional vision for enrollment initiatives using KPIs.

And more…

• Our use of predictive analytics allows us to examine previous financial data, detect patterns, and anticipate future financial scenarios. This enables the college to prepare for upcoming challenges, manage resources effectively, and make intelligent decisions based on data-driven insights.
• Developed data model and analytics that provide university leaders trend analysis to assess instructor load, efficiency of scheduling, revenues, expenses, and margins by college, major, course, etc.
• Developing new tools to analyze course/program resource allocation and ROI.
• We will lean on data to decide what to throttle and what to propel faster in terms of institutional investment.
• We have consolidated enterprise application services and included two new departments: Data Engineering and Data Management (DEDM) and Academic Business and Performance Analytics (ABPA).
• An annual project collaboration between IT and academic affairs to advance our data warehouse capabilities, onboard new areas of the institution so data is unified in one stream, and continue to expand the data-informed culture of the campus.
• New School of Data Science that collaborates with the community on numerous projects.
• The campus is currently undergoing what we call Financial Sustainability Task, and it involves reviewing all campus budgets and procurement processes. Every new purchase and every addition of new FTE has to go through a review committee.

Notes

1. Jason Sussman and Larenda Mielke, "2023 Credit and Capital Markets Outlook for Higher Education," KaufmanHall (website), January 27, 2023. Jump back to footnote 1 in the text.↩
2. Helen Huiskes, "State Support for Higher Ed Continues to Rise, yet Public Colleges Still Face Headwinds," Chronicle of Higher Education, May 25, 2023. Jump back to footnote 2 in the text.↩

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Mike Dieckmann is Associate Vice President and CIO, Florida Polytechnic University.

Carolyn Lightfoot is CIO, Office of Information Technology, Lee College.

Ioannis Salmatzidis is Director of IT, Aristotle University of Thessaloniki, Greece.