People analytics: The underutilized tool to help higher ed HR leaders meet talent goals and reduce costs
A quick start guide for HR and institutional leaders to overcome people analytics barriers
January 5, 2024, By Liliana Loosbrock, Senior Research Analyst
As colleges and universities collect more and more data, leaders are using insights to make critical business decisions, such as analyzing student success data to identify at-risk students or using enrollment data to manage course and program offerings. However, after interviewing over 65 higher education leaders, EAB discovered that most institutions overlook valuable employee data. Most only use employee data for baseline compliance reporting and miss opportunities to improve recruitment and retention for staff and faculty.
People analytics is the collection and application of employee data to improve business outcomes. It can help anticipate turnover and retirements, save money on sourcing candidates, and identify engagement opportunities for staff and faculty. HR and executive leaders can no longer afford to ignore their employee data; the cost is simply too high.
Progressive higher ed HR teams are beginning to use employee data to estimate cost savings and convince institutional leadership to invest in talent initiatives that work:
-
ÂŁ400K
spent on low-ROI staff recruitment activities at a large international institution
-
$100M
worth of encumbered funds due to vacant roles being open for up to 10 years at a large public institution
While some skeptics view people analytics as an added expense, these institutions prove it can be a cost-saving technique. To overcome common barriers and fully realize your people analytics capabilities, see EAB’s advice outlined below for both executive and HR leaders.
Barrier #1: Lack of trust in institutional data processes and systems
Many leaders are skeptical of their HR unit managing inherently messy employee data. They are often wary of data insights due to the large number of shadow systems and untrained users. Further, cabinets are more likely to trust historically data-driven units like institutional research over traditionally administrative units like HR. In turn, some cabinets do not use employee data at all beyond compliance purposes.
This skepticism prevents leaders from using directionally correct employee data, which sufficiently detects trends despite not being perfectly recorded, to inform decisions. Leaders must acknowledge the inherently messy nature of employee data and learn to act on what they already have access to, even if it’s imperfect.
Solution: Establish uniform standards for employee data collection and presentation
Cabinet: To understand what data you currently track and decide what metrics you want HR to monitor in the future, invite the CHRO to present data and updates about people and workplace culture on a biannual basis. Ask them to only present data and trends that correlate with strategic talent goals, such as hiring and promoting more internal candidates or increasing racial diversity in leadership positions.
HR: Instead of looking for the perfect data visualization tool, start with the data collection and analysis resources you already have, like Excel. Centralize disparate employee data across units into a central location managed by HR. To build trust with campus leaders, be upfront about data errors and uncertainty, explain methodologies, and outline how to use employee data going forward.
Barrier #2: Disconnect between employee data and decision making
Presenting data can become a check-the-box activity when not accompanied by a recommendation or explanation of a trend. When HR does have the opportunity to present data to the cabinet, they often only present broad or general statistics such as overall turnover.
Without additional direction on what units, roles, or groups of staff are most impacted, campus leaders cannot identify problems or plan solutions. Data without recommendations or assigned next steps limits the ability of campus leaders to improve processes and track success metrics.
Solution: Highlight the financial risks of making talent decisions without people data
Cabinet: Instead of relying on speculations or hearsay, employee data should inform conversations about and investments in talent. Before a decision is made to scale up or down a talent initiative, such as cutting an unused benefit or adding a young leaders program, review HR’s analysis of the potential benefits and cost savings associated with change. To ensure HR has the data to track the performance and financial success of talent decisions, hold divisional leaders and deans accountable for reporting feedback and progress.
HR:Â When presenting employee data to the cabinet, highlight no more than three to four campuswide trends. When presenting to unit leaders, focus on trends that diverge from campuswide data, such as a unit turnover rate that is much higher than the university average. Distribute these findings and recommendations informed by the following questions:
- How does this trend impact different units, roles, or employee groups?
- What is the financial risk of not taking action based on our data? Can we quantify it?
- What other data do we need to diagnose the root cause of this problem?
Barrier #3: Constrained capacity for HR to analyze data
The above solutions ensure you collect and report only on necessary metrics. Yet, without the time and expertise to conduct thorough analyses and provide recommendations, you cannot realize the potential cost savings of people analytics.
Given chronic HR staffing shortages, overextended teams, and a lack of technical skills in HR, institutions must focus on cost-effective ways to conduct people analytics. In fact, a dedicated people analytics team is not strictly necessary—efforts should encompass the collective effort of experts both in and outside of HR to help leaders make quicker and more accurate decisions.
Solution: Until HR can build skills and capacity, source data analytics and visualization skills from the existing campus community
Cabinet: Invest in and facilitate collaboration between institutional research, IT, finance, and HR for talent projects that involve several different types of data.
HR: Look outside HR for potential capacity and skill for individual projects, including analytics graduate students and institutional research staff. As HR units automate activities, such as benefits coordination, plan to reallocate time to people analytics.

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