When you’re advocating for a new initiative, having compelling and accurate data at your fingertips is essential. Senior leaders at colleges and universities increasingly expect that HR will ground strategic initiatives in data, whether you’re making the case for more competitive pay, hiring more hands and minds to share the workload, or enhancing the employee experience.
CUPA-HR’s DataOnDemand — powered by data from more than 1,000 institutions — offers the information to fuel an institution’s most critical strategic initiatives. While many HR teams use their DataOnDemand subscription for compensation benchmarking, its value extends far beyond setting base pay. DataOnDemand is a powerful resource for supporting compliance, gaining senior leadership buy-in and advancing institutional priorities.
We asked higher ed HR leaders at six institutions how they use their DataOnDemand subscription to support a range of HR projects that go beyond setting base pay. They shared how DataOnDemand can be used to:
- Create data-backed budgets
- Conduct strategic workforce planning
- Prepare federal Labor Condition Applications
- Create a career framework and compensation structure
- Assess employee turnover
- Benchmark hiring metrics, such as time to hire and time to fill
Higher ed HR leaders share how they use DataOnDemand for a wide range of HR functions, from creating budgets to benchmarking hiring metrics.
Creating Data-Backed Budgets
With DataOnDemand, HR leaders at institutions of all sizes can plan and advocate for their compensation budgets with data-backed justifications. We spoke with leaders at three institutions currently using DataOnDemand for budgetary planning.
Considering Past Increases
“Over the past five years, detailed data has become increasingly important to strategic-decision making at our institution,” said Jacob Lathrop, the assistant director of Talent and Strategic Partnerships at Michigan State University.
Each year, Michigan State, a large public research university, budgets for pay increases for non-unionized employees. Michigan State HR uses DataOnDemand’s Trend Reports to determine the percentage pay increase they will propose for non-unionized employees. (Unionized employees’ pay is negotiated through collective bargaining.)
Tracking Salary Trends Over Time
DataOnDemand Trend Reports provide data on actual percentage changes in pay that occurred within a two-year span. You can find data on changes for individual positions, a group of positions, or for all positions in a survey (e.g., the Administrators Survey). With Trend Reports, you can also see salary increases for past years, helping you understand how salaries changed within many two-year spans — essentially tracking yearly salary increases over time. While final increases will depend on factors like budget availability, knowing how your peers have increased salaries in the past can help you plan for future increases and assess your market competitiveness.
Planning With Future Salaries in Mind
CUPA-HR also provides members-only forecasts of future salary increases that can be used in conjunction with other data during budget planning. Statistical forecasting uses past salary increases to predict future increases for typical years and for years when there are severe budgetary restrictions, such as the Great Recession and the COVID-19 pandemic.
We suggest using a mix of actual past increases and projected future increases to create a budget for increases, but the right mix comes down to compensation philosophy, goals and preferences.
Reviewing Individual Positions for Competitiveness
The budgeting process looks somewhat different at Northwestern College, a small private college in Iowa. Each year, HR arrives at a proposed compensation budget by reviewing each individual position at their institution for market competitiveness and internal equity. Once they know the adjustment they’d like to make to each position, HR uses them to create a detailed compensation budget for the following year.
Adjusting for Market Competition and Internal Equity
To understand what adjustments are needed for each position to maintain market competitiveness, Northwestern College HR uses DataOnDemand’s Multi-Position Reports to pull market data on many positions at once. HR uses several peer groups depending on the position. After they develop a plan for adjustments to maintain market competitiveness, they review roles for internal equity. Finally, they present their data-based budget for pay adjustments to other institutional leaders.
“It’s so much easier to discuss what we should do with the budget if we have data to back it up instead of it just coming from me,” said Mindy Stichka, Northwestern’s director of human resources.
HR also directly shows vice presidents how the pay of each employee in their area or division compares to the market — a tailored approach that demonstrates their budget was based on detailed, data-driven planning.
“It’s so much easier to discuss what we should do with the budget if we have data to back it up instead of it just coming from me,” said Mindy Stichka, Northwestern’s director of human resources.
In years when budgets are particularly tight or scrutinized, having employee-level data helps Northwestern College prioritize budget dollars toward positions that are particularly out of step with the market. “DataOnDemand helps us advocate for our employees,” Stichka said.
Budgeting With Data Dashboards
Franciscan University of Steubenville, a small private university in Ohio, also uses DataOnDemand for budget planning throughout the year. A key focus of Franciscan is ensuring that competitive compensation, both base pay and employee benefits, is funded during budgeting cycles and prioritized during other institutional planning.
“Our leadership is very interested in data-based human capital planning, and support gets stronger every year,” said Bill Thomas, executive director of human resources. Leadership values the opportunity to readily see how compensation at Franciscan University of Steubenville compares to its peers not only during planning meetings, but throughout the year.
Benchmarking With an Internal Data Dashboard
Franciscan maintains an internal dashboard that compares their institution to their peers on 30 different factors, including compensation, benefits and other human capital metrics. The dashboard is leadership’s main source for compensation benchmarking information throughout the year. The dashboard is updated regularly with the latest data from the university and its peers.
“We are constantly using the dashboard and asking ourselves whether we are behind, meeting or ahead of market,” said Thomas. Franciscan University of Steubenville sources much of the peer data for the dashboard from CUPA-HR’s workforce surveys and includes data from the Integrated Postsecondary Education Data System (IPEDS).
The dashboard also includes data on benefits and employee experience sourced from CUPA-HR’s Benefits, Employee Experience, and Structure (BEES) Survey. BEES provides data on traditional retirement, healthcare, tuition, and paid time off benefits, as well as insight into employee experience initiatives such as flexible work arrangements, professional development, and employee performance evaluations. Be sure to familiarize yourself with CUPA-HR’s data use agreement before building a dashboard with this data.
Strategic Workforce Planning
One of the many challenges that HR leaders face is getting workforce size right — a delicate balance between the realities of an institution’s finances and the realities of workload. What constitutes a “just right” workforce size changes over time, due to factors like growth in student enrollment, shifts in strategic priorities, or changes in institutional offerings or focus.
In addition to staffing ratios, DataOnDemand offers department size reports and our brand-new area size reports to help you compare headcounts within specific positions or an entire area at your institution to those of your peers.
Rightsizing the Workforce
Loyola University Maryland, a medium-sized private institution, recently adopted a strategic plan that emphasizes operational excellence as a guiding light. They’re now undertaking an initiative that includes reviewing their organizational structures to understand how the size of their workforce compares to their higher education peers.
Benchmarking Staff Ratios
Loyola’s Office of People and Culture relied on DataOnDemand’s Turnover, Staffing Ratios, and Comparison Group Characteristics Report to understand how they compared to their peers in terms of staffing ratios and full-time equivalency (FTE), using four years of data. This report is included with any subscription to DataOnDemand and provides staffing ratios such as number of FTE faculty per 100 FTE students and number of FTE staff per 100 FTE students. The Office of People and Culture also reviewed general FTEs for HR, faculty, students and staff.
Using a combination of DataOnDemand and additional outside data, the Office of People and Culture concluded that their staffing levels in some departments were high in comparison to their peers. These data were presented to a committee that will provide recommendations to leadership on rightsizing the workforce. The project is still ongoing, but, ultimately, leadership will make final decisions on any staffing changes that could help bring Loyola into closer alignment with their peers’ staffing levels, increase the efficiency of their workforce and strengthen their financial resilience.
Planning for Strategic Workforce Increases
Over the past 10 years, Kennesaw State University, a large public university in Georgia, has grown its student enrollment by 55% — from approximately 33,000 students to 51,000 students. While an enrollment surge is a good problem to have, such a sizeable increase in students poses a challenge to smooth daily operations if the workforce remains unchanged.
“We knew that we needed to grow the workforce,” said Karen McDonnell, vice president and chief human resources officer. “The story was there, but we didn’t have any data to defend our own gut senses.”
Before using DataOnDemand, Kennesaw State’s HR team had signs that their workforce needed to grow to keep pace with new service realities. There was simply too much to get done and not enough employees to share the load. But beyond anecdotal information and the team’s intuitions, they had no concrete data to advocate for a larger workforce or give voice to how severe the problem had become. “We knew that we needed to grow the workforce,” said Karen McDonnell, vice president and chief human resources officer. “The story was there, but we didn’t have any data to defend our own gut senses.”
KSU turned to DataOnDemand to get concrete data on how their staff size compared to other institutions. DataOnDemand’s Turnover, Staffing Ratios, and Comparison Group Characteristics Report provides staff-to-student ratios, faculty-to-student ratios, and HR-staff-to-all-staff ratios for the peers that a user chooses. They began their investigation by exploring ratios for all institutions but eventually refined their peers in partnership with a consulting firm for an apples-to-apples comparison of staff sizes.
Making the Case for Workforce Increases
The results were clear. Kennesaw State University’s faculty-to-student ratio was far lower than the ratios of its peers. For staff, the mismatch was striking: they needed to double staff to meet their peers’ typical staff-to-student ratio. HR needed three times the headcount to meet their peers’ HR staffing levels.
Once HR had the data in hand, they used it to model workforce planning and budget needs and started sharing the data with university and system leadership. They also created a long-term strategic plan of how, over time, Kennesaw State could grow its workforce to required levels. Once leadership saw the data, they quickly began supporting efforts to grow the size of Kennesaw State University’s workforce.
“Now that we have the data, it’s been straightforward to get the support from leadership that we need for workforce planning and growth,” said McDonnell.
“Now that we have the data, it’s been straightforward to get the support from leadership that we need for workforce planning and growth,” said McDonnell. Though far from finished, the growth of Kennesaw State University’s workforce has already had positive impacts. Staff workloads, particularly those of HR, have improved, and a recent survey found that 93% of Kennesaw State employees were satisfied with HR.
Preparing Labor Condition Applications
At the University of Michigan, a large public research university, the office of Faculty and Staff Immigration Services prepares and manages the immigration process for all employees. Several application types, such as H-1B visas and PERM-based green card applications, include a wage requirement that is in part based on the prevailing wage. The prevailing wage can be based on a number of sources, including external wage surveys. When relying on external wage surveys, the prevailing wage is the weighted average — or, in the absence of a weighted average, the median — pay of other workers with similar roles within the geographic area of intended employment.
Using Trusted Sources for Prevailing Wage Determinations
Making prevailing wage determinations is particularly challenging in higher ed due to the limited availability of data. That’s why David Muusz, the associate director for Faculty and Staff Immigration Services, relies on CUPA-HR data: “We regularly use DataOnDemand on Labor Condition Applications because CUPA-HR data is often more realistic and comprehensive than other data sources.” DataOnDemand’s Prevailing Wage Reports are specifically designed to meet the Department of Labor’s requirements for this purpose and provide data as quickly as possible.
The Office of Foreign Labor Certification accepts CUPA-HR data as a reliable source. A step-by-step tutorial for using Prevailing Wage Reports can be found here.
Prevailing Wage Reports provide the exact statistics requested by the Department of Labor (DOL) and easily allow the user to demonstrate that the prevailing wage is based on the smallest possible geographic area that returns sufficient data. The report also includes all documentation of CUPA-HR survey procedures necessary to accompany a labor application. DataOnDemand Prevailing Wage Reports can be used directly in Labor Condition Applications without further review with the DOL and may also be used for official prevailing wage requests in the PERM context. External consultants who prepare Labor Condition Applications can be granted access to an institution’s DataOnDemand subscriptions.
Creating a Career Framework and Compensation Structure
Until recently, Kennesaw State University had no uniform job descriptions or formal compensation philosophy. They typically hired at whatever the budget was for a position, regardless of experience or background of the applicant. HR struggled to meet KSU’s current workforce needs without a clear compensation strategy — let alone meet demands as student enrollment rapidly grew. Employees lacked clarity on how they could grow their compensation and career at KSU.
In response, Kennesaw State launched a multi-year initiative to create a compensation philosophy and formal career framework for their staff. The career framework established job descriptions, each organized within newly created job families, and formal salary grades. Each position at KSU is now assigned a formal position description, a job family and a level, which translate into a salary grade.
To establish their new pay structure, Kennesaw State and their third-party consultants used market data and peer compensation data. DataOnDemand’s Multi-Position Reports allowed them to obtain pay data on many positions at once. With peer data in hand, they aligned all employees with a competitive salary grade. No employees received a pay reduction during the project, and some employees received an initial adjustment to ensure market competitiveness.
Kennesaw State employees now have a clear guide for growing their career and compensation, and HR is better able to meet the workforce needs of today and tomorrow.
Benchmarking Employee Turnover
For the past few years, Loyola University Maryland has monitored employee turnover as part of broader workforce analytics efforts. The Office of People and Culture tracks voluntary, involuntary and overall turnover for faculty and staff, and conducts exit interviews. At least once per year, the team reports top turnover reasons and turnover rates to key stakeholders, including the budget committee and the compensation and benefits committee.
Loyola also tracks how their turnover compares to their peers. DataOnDemand’s Turnover, Staffing Ratios, and Comparison Group Characteristics Report helps the team obtain benchmarking data on voluntary, involuntary and overall turnover.
Each year, the People and Culture team show key stakeholders whether Loyola is below, above or equal to peer benchmark data for turnover. They also synthesize exit interview data with turnover benchmarking data to develop recommendations for how to reduce turnover or continue to beat their peers in terms of turnover.
Turnover benchmarking data is foundational for Loyola’s compensation and benefits recommendations and for supporting other strategic retention initiatives. Lately, Loyola University Maryland has outperformed their peers on employee turnover.
If you’re looking to start benchmarking turnover at your institution, Georgeann Burton, director of compensation and HR operations at Loyola, has this advice: “Just start! It doesn’t need to be overly complex. Start by looking at overall turnover, then begin to drill down further as needed. This data can help determine and support strategic retention initiatives for your organization.”
Benchmarking Hiring Metrics
As part of a new recruitment marketing initiative, Michigan State University recently started tracking hiring metrics, which provide a measure of the efficiency of their hiring processes. They now track two key metrics: time to fill, the number of days it takes for a candidate to accept after a job is posted; and time to hire, the number of days it takes for a candidate to accept a job offer after they apply. Understanding internal time-to-fill and time-to-hire metrics is useful in seeing how efficiency in processes improves (or degrades) over time.
MSU also wanted to know how their hiring metrics compared to their peers. University leaders who came from outside higher ed often brought metrics from their previous industries that didn’t reflect the reality of higher ed’s specialty hiring.
Michigan State HR turned to Benefits, Employee Experience, and Structure (BEES) DataOnDemand. BEES DataOnDemand provides time to fill and time to hire by employee type (for example, tenure-track faculty or exempt staff) for the peers that institutions choose. Using BEES data, HR leaders at Michigan State showed senior leadership that they were generally doing well on hiring metrics relative to their peers.
Insights from DataOnDemand Experts
Although the experts we interviewed use DataOnDemand for a variety of purposes, they all agree it’s critical to rely on data when making strategic decisions — and for getting leadership buy-in. “I don’t think we can bring forward any major initiative without having data behind it,” said Jacob Lathrop, assistant director of Talent and Strategic Partnerships at Michigan State. “Leadership not only desires but expects that data will be incorporated into all strategic decisions.”
The case studies here are just a starting point. As you explore ways to use DataOnDemand to enhance your decision-making, consider this advice from our experts:
- Clearly define your goals. Take the time to dive deep and carefully define the goal(s) of the project or decision. What must you accomplish? What would be nice to accomplish? Clearly defining your desired outcomes can help you choose the best data to advocate for a decision and in turn measure its impact.
- Don’t be afraid to start small. If you haven’t used data or DataOnDemand for strategic decision-making yet, the best way to build a foundation for future success is to start with a small project that has a simple goal in mind. For instance, imagine your institution is considering changing limits on employee tuition benefits, and the goal is to decide whether to increase the limit or not. You could consult BEES Survey data to determine your peers’ tuition benefit limits, and whether your limits align with your peers. Once you’ve gained experience with the procedures behind using and advocating for smaller decisions with data, you can apply those skills to larger decisions and initiatives.
- Truly understand your peers. A common thread throughout our data users’ experiences is the importance of understanding who their peers are and sharing with stakeholders why the peers they chose are appropriate for the decision or initiative. Take the time necessary to show senior leadership why your data is an apples-to-apples comparison for the current project.
About the Author: Melissa Fuesting, Ph.D., is an associate director of research at CUPA-HR.
Citation for This Article:
Fuesting, Melissa. (2026, July). Beyond Base Pay: How DataOnDemand Informs Strategic Decisions at Colleges and Universities. https://www.cupahr.org/resource/beyond-base-pay-how-data-on-demand-informs-strategic-decisions-at-colleges-and-universities/. CUPA-HR.
Special Thanks:
Special thanks to the following experts for the interviews and feedback that made this article possible: Georgeann Burton, Jacob Lathrop, Karen McDonnell, David Muusz, Sharon Sherlock, Mindy Stichka, Bill Thomas and Kristi Yowell.
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