2025 EDUCAUSE Top 10
#1: The Data-Empowered Institution

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Data management, integration, and governance are still challenges, but institutions are making progress. Addressing these fundamentals is empowering leaders to use data and analytics tools to direct precious resources toward investments that are most likely to have an impact on institutional and student success. Most institutions today have budget challenges. Leaders need evidence and guidance to decide which investments are most likely to be effective for students and for the institution. Institutional stakeholders all see a particular problem from different points of view. Data and key performance indicators can help decision-makers come to a unified understanding of how the institution is performing, what it's good at, and where additional investments are needed.

The Promise

Increasing enrollment. Data can help admissions and enrollment leaders understand which students are interested in the institution and identify and reach new prospective students. Data about what students and parents care most about, what the institution is best at, and what the local talent market needs can help staff promote the distinctive institutional characteristics that resonate the most with prospective applicants.

Increasing student success. Real-time analytics can help student success professionals better identify and more quickly intervene with at-risk students. Real-time data also enables ongoing monitoring to verify whether interventions are working.

Identifying and adapting to students' needs. Institutions must work just as diligently at retaining students as they did at recruiting them. Students' needs, expectations, and values are diverse and different from previous generations. Decision-makers need data and analytics to deepen their understanding of their student populations and how institutional services, teaching, and academic programs might need to change to support those populations.

Improving learning. Analyzing students' performance and their learning preferences help faculty to provide more personalized learning experiences. Data can also pinpoint courses where students are struggling the most and where focused investments in course redesign or student support would yield the highest benefits.

Fueling continuous improvement. Interventions and innovations don't always work as planned. Leaders need to be able to connect supports and programs to students' outcomes to know whether changes are actually resulting in improvement. Access to rich, varied data sources throughout the institution can enable decision-makers to see where actions are helping or where they're hurting, and when they need to expand, stop, or change. Measures should be both immediate and long-term.

Optimizing resource planning. Institutional resources are too limited to countenance misallocation. Predictive analytics can help decision-makers anticipate trends and outcomes to forecast enrollment numbers and characteristics, student retention rates, course and credential program choices, demand planning for courses and learning modalities, support service needs, and more. Better data—and information derived from that data—can help institutions more accurately estimate resource needs and develop budgets.

Advancing research and innovation. Institutional data, analytics, and artificial intelligence (AI) capabilities and services can help academic leaders attract and retain the best faculty. Faculty need increasingly powerful computational resources and cyberinfrastructure staff. Institutions can establish core research facilities and programs to help faculty collaborate across disciplines and institutions, make the case for funding, use cutting-edge resources, and jump-start their projects more quickly and cost effectively.

The Key to Progress

Get the staffing and skills mix correct. Staffing data initiatives needn't necessarily require more resources (although that never hurts). Successful tactics include updating existing position descriptions to incorporate new skills, starting with temporary or graduate student workers and, where possible, converting those resources to full-time staff, cross-training staff to safeguard against surges in work or departures, collaborating across teams to ensure efforts are cohesive, and investing in professional development. Managers and faculty can document the ways in which student workers' efforts are contributing to their learning and make the case for awarding credits for students' work.

QuickTakes

This is an existential issue. Institutions that are facing significant enrollment and funding challenges must be the most efficient in resource usage because their existence depends on it. These institutions typically serve students who need extra support and who may lack the resources to get a second chance at college. Existential enrollment pressures and budget pressures are motivating: They hasten alignment, and alignment is a precursor of agility.

Focus. Institutional leaders need to collectively agree on what they want to measure and why. That way, stakeholders can use inevitably limited resources in the best ways possible to create more value.

Data is an institutional asset. To really safeguard and use data, it has to be seen as an institutional asset—a valuable resource that is owned by the institution, not individual stakeholders. It's not easy for people to relinquish the control that comes with ownership and extend the trust required for this paradigm shift. Large, decentralized institutions will struggle with this the most. Cross-departmental collaboration to reach agreement on data priorities and definitions can build a sense of shared ownership in centralized environments.

Invest in data and analytics literacy. Data, analytics, and AI don't make decisions, people do. Anyone at the institution who might use data to make decisions—and that is pretty much everyone—needs to understand how to use and interpret data. They also need to know their responsibilities for data security and privacy.

Prioritize data quality and integration. To optimize the use of data, it's critical to bring many data sources to bear on problems, have a single source of truth, and use resources as efficiently as possible. But it's very difficult to achieve interoperability among systems and to aggregate and analyze complex data from multiple sources. Data leaders should begin by working to ensure that the data is accurate, reliable, and relevant to institutional needs.

Balance openness and privacy. Data openness gives everyone access to all the data they need to plan and manage well and to help students. But too much openness may compromise privacy and security or intellectual property rights. Developing a culture of trust is key to achieving the right balance. A culture of trust requires policies and practices that safeguard people's privacy and data and analytics infrastructure and standards that support those policies and practices.

Foster collaboration across institutions. Institutions that are fortunate enough to belong to a consortium can share common challenges and best practices. They can also move beyond conversations to collaborations to share solutions and skills.

Ask Yourself

• Are we ready to consider data-generated implications that challenge our long-held beliefs about education and student success?
• Does our institution have a strong data culture—a shared understanding, tradition, and narrative around data and its value? Awareness of data cultures is crucial for transformation and achieving fairness and equity.

The Bottom Line

A data-empowered culture can help institutions become and remain future ready, effectively support students, and make strategic decisions that benefit the entire institutional community. For smaller institutions with limited resources, the availability of data and the right analytics tools can be transformative: It's not just about staying competitive, it's about leveling the playing field.

Data Point

Although many institutions seem motivated by avoiding negative consequences like "falling behind," the two most-selected goals of AI-related strategic planning are focused on supporting students: preparing students for the workforce and exploring new teaching and learning methods (64 percent and 63 percent, respectively).^Footnote1

From Strategy to Practice

What You're Saying

"Driving reporting and report creation to the end user is a vital concern in times when staffing dollars are tight, qualified staff are difficult to acquire, and the demand is increasing."

"Historically, we have treated data like an element of risk. We now recognize the great potential to leverage data as an asset."

"AI is worthless without quality data—which is a rare commodity in any organization. So far, we've gotten away with bad, unclean data by building work-arounds."

"We have invested very heavily in PowerBI analytics software and dashboard development. Ironically, we have better success building our own dashboards using PowerBI than purchasing vendor-provided tools."

"What and how can we use data to support academic success and retention of students? If we bring them in as students, what needs to be in place to ensure success even if they are not the strongest students? We are concerned with social and economic mobility."

"People are the lifeblood of our societies, communities, and institutions . . . and data comes a close second! EDU is awash in data, but rarely uses those data to create the information products needed to guide institutional decision-making and foster equitable outcomes and strong success for all learners and for all staff. The crucial importance of having the data estate in order underpins all of the possible futures around sustainability, efficiency, personalization, and any hope of being able to create business value from the use of new and emerging technologies like artificial intelligence."

Solution Spotlights

"For some time, we have been data-rich but information-poor. We've had data available to our deans and other senior leaders, but we have not always had the engagement that we desired across campus with our dashboards. This year, in partnership with the provost, we've kicked off an initiative called the Year of Data, with a goal of better data engagement with campus decision-makers through outreach, education and enhancing our offerings."

Helen Norris, Chapman University

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"We're rebuilding our data infrastructure so that we can reduce the cycle time of getting decisions from data. We're using zero copy data and flexible CRMs to do this."

Roy Lee, New York University

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"We are deploying AI tools in every aspect of university operation, activity, and mission."

Erik Deumens, University of Florida

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"We're building AI-powered academic and research tools for students and faculty that expand across the generative AI compass to include technologies like image generation. Our focus extends to developing AI solutions and integrations that boost staff productivity and reduce inefficiencies. To fuel these innovations, we are working to identify data sources to help drive these solutions and to empower more data-driven decision-making. In addition, there are opportunities to explore ways in which AI can help in organizing and formatting data used in such systems."

Vincent Guerrero, Yale University

What You're Working On

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

Artificial intelligence

• We are leading the country and the world in AI services at scale. Investing in AI models that support student success, access to information, and enhancements in research.
• Modernize academic applications and integrate GenAI capabilities in these applications.
• We have invested in and implemented our AI platform. Now we are working on bringing our data to the platform in a seamless manner.
• We are looking to leverage AI tools like MS Copilot and/or IBM WatsonX or something similar to accomplish all of the above, enabling data-driven decision-making via a business-intelligence platform. We are already leveraging AI to support recruitment/enrollment.
• Looking at ways to leverage co-pilot to create better downward data visualization.
• Created a new AI enablement team to focus efforts and provide real, tangible ROI.
• We have a cross-functional team exploring AI and establishing guidelines for staff, faculty, and student use. We also have a quantitative analysis effort going on and have hired a director in that regard.
• Looking at predictive modeling for retention using AI.
• Investigating using AI to process applications to high grade those that are easier to process and put in line first.
• On-prem open-source LLM service.
• AI to better target student support, establish if students are enrolling in the right program, etc.
• Our Center for Data Science is providing analytics to adjust/validate our processes.

Business intelligence

• Replacing reporting environment with an eye on training an AI model.
• Using SPSS and machine learning to provide predictive analytics to our academic advisors; e.g., predicting success rates of students based on past behavior and outcomes (grade point averages) and course selection for registration (number of credits, course combinations, modality, etc.).
• We are partnering with HelioCampus to provide key data metrics and dashboards for university educators and administrators.
• Investing in Anthology Illuminate.
• Implementing a new SaaS reporting/dashboarding tool (Ellucian Insights) to democratize data across the institution to help inform data-driven decisions.
• Creating a data warehouse, executive dashboards, and improved reporting.
• Power BI Dashboards and data modeling in decision-making.
• We are redefining our analytics reporting to provide end users with the ability to gain access to the data they need when they need it, allowing institutional research to focus on specific reports.
• Aligning strategic plan metrics with assessment standards and converting user stories into requirements for a data-analytics platform.
• Investing in HelioCampus.
• Working with a third-party vendor to create enrollment and student success dashboards to inform leadership in critical decision-making.
• Building a future-focused data platform that enables more citizen-based discovery and insight via smarter tools.
• Working on clean data sources that we are connecting to PowerBI to deliver dashboards and visualizations that support institutional effectiveness.
• Learning about our data and using our data in new ways to build insights and make data-informed decisions.

Comprehensive approach

• We are focusing on developing a 360-degree view of the student and faculty and staff. We are investigating how to maximize existing systems and augment them with AI bots to enhance and personalize services, request fulfillment, and engagement. These efforts cross traditional department silos and require us to think of strategies and efforts that benefit the university as a whole. Functional leads are working with enterprise applications, business analysts, and developers to revamp processes, procedures, and knowledge bases. These efforts align with our institutional plan but are outside of our governance process, requiring us to rethink how we approach digital transformation. We will be successful if we can get access to and use the data we already have in a more systematic way.
• Increasing student success: Implemented a data-driven approach to student retention and graduation, using predictive analytics to identify and support at-risk students. Additionally, the university has invested in chatbots that can answer students' questions, provide academic and career advice, and connect them with relevant services and opportunities.
  
  Winning the enrollment race: Used data and analytics to optimize its enrollment strategies, targeting and attracting prospective students who are most likely to enroll and succeed at the university.
  
  Increasing research funding: Used data and analytics to identify and pursue research opportunities that align with its mission, vision, and values, as well as the needs and priorities of society and the world.
  
  Reducing inefficiencies: Used data and analytics to streamline and automate its administrative and operational processes, reducing costs, errors, and delays.

CRM

• Implementing a full-feature student recruitment/enrollment CRM.
• We're using Salesforce as our CRM which connects to many different tools to help with automation, provide a personalized experience for students, and help us predict enrollment.
• Implemented Salesforce higher education CRM and supporting tools as a campus solution to manage and communicate with prospects to graduates.

Cross-institutional collaboration

• We joined the Unizin consortium to better leverage learning analytics from our LMS.
• Modernizing our current Data Platform Statewide collaborative initiative in data sharing between K–12, community colleges, etc.

Data governance and management

• Developing a single source of data (curated and ready to use). Using this data to generate dashboards at various levels of the university, institution-wide KPIs, divisional and departmental KPIs required for decision-making. A single source of truth is very useful for making decisions to help recruit and retain more students, recruit and retain talent—both faculty and staff— increase research opportunities, and definitely increase efficiency, all of which are fundamental to the growth of the university.
• Focusing on data governance and privacy.
• Working on a data governance policy to ensure alignment of data and accessibility.
• We have a strategic initiative around data governance and are creating committees, a process, and investing in the staff and infrastructure to support this.
• Forming a Data Governance Council to help us integrate different sources of data to improve student retention and graduation rates and increase enrollment.
• We are starting with data governance project version 2.0 after five-plus years of being on hiatus. It has been going well, and we are tackling peak issues like redefining system of record, data access and data management policies, data privacy, etc.
• Establishing a data governance group and developing a data strategy.
• The institution's chief data officer and CIO are partnering on joint governance, streamlining data integrations, and preparing data sources for AI.
• Re-examining data governance; data storage / access; ownership/stewardship; and integrations.
• Looking to create a data governance committee for the campus; develop efficiencies with the data warehouse currently in place.
• Building out data governance, standardizing tools, identifying a single source of truth.
• Established standards. Assuring data accuracy. Sharing data across departments.
• We have integrated several datasets into predictive retention and success models. We expect to automate them more in the future.

Data infrastructure

• We are working on consolidating data. We are planning to go to cloud-based data lakes to facilitate data mining and AI for internal data.
• Implementing a cloud-based data lake to replace our aging, siloed, and difficult to use current tool.
• Investing in data architecture, infrastructure, and technology professionals to modernize our data environment.
• Working on developing an in-house "data lake."
• Moving our data warehouse from Oracle to AWS/Redshift. Adding LMS data and longitudinal to the warehouse.
• We're implementing a new data lake with AI capabilities.
• Consolidating data sources for administrative data and research data. Creating a unified platform that connects with HPC resources.

Data literacy

• Getting users to adopt applications that provide data-informed interventions and measuring outcomes.

Infrastructure

• We have a stable data warehouse, but it is not well positioned to carry us into this new age of AI and LLMs. Our two-year roadmap has us holistically reviewing both our analytics infrastructure and the tools that staff rely on to access this wealth of power. I'm confident that this new modern approach will lead to both an increase in use of the data and a much more data-driven institution.
• Buying new SaaS to help automate and make day-to-day operations more effective. Writing custom automations for time-consuming manual tasks.
• Modernizing data and analytics infrastructure to modern cloud-based solutions to enable ML/AI capabilities to address institutional challenges.

Integrations

• Merging data across administrative systems' silos to identify and investigate themes/issues that are campus-wide, and not specific to one department/system; e.g., strategic enrollment management.
• Building an institutional data space to bring data from different areas together and using conformed dimensions in our analytics.
• We are currently undertaking a use-case driven data-strategy approach—working to define our gaps in capability in both infrastructure as well as integrations, which will help inform our next key initiatives to improve our overall data capabilities and competencies.

Leadership

• Our president has said publicly and privately that we will make data-informed decisions and is supporting the organizational changes, policies, and technologies to support that. It's exciting.
• Newly hired CDO is managing efforts to increase data gathering and showing new importance for data-driven decisions.

Process improvement

• Introduced project management software to staff by creating a project management office. Analytics from software show imbalances in workloads, understaffing in areas, and employees feel acknowledged seeing their work produced quantitatively.
• Making data-informed decisions to help streamline administrative processes for students.
• Aligning business processes and dedicating resources (human, fiscal).

Students, teaching and learning, and student success

• Evaluating Salesforce student success capabilities. Implementing Workday Student, which will focus on enhancing the student experience.
• Implementing Stelic to radically improve how students learn about degree path options.
• We've built our own predictive analytics system to help us surround students who need assistance earlier in their career.
• We are leveraging predictive analytics with proactive nudges to identify students who are struggling in math and then outreaching to the students to get support. We have also built a math AI tutor bot to see if that increases students' ability to learn difficult math concepts.
• The institution is increasing use of traditional predictive analytics to spot potential challenges with individual students sooner and more effectively. While this does involve some AI-centric concepts, it remains based more on more traditional tools.
• Based on the huge set of data from the learning management system and student information system, The university developed a learning analytics dashboard. Expanding this dashboard with a psychodiagnostic screening instrument was the natural next step to help first-year students gain insight into their cognitive abilities. The results from the dashboard are the starting point for conversations, guidance, and support for study coaches to guide students toward study success.
• We recently rolled out EAB solution. Validating the models and optimizing usage will be a priority.
• Personalization of all student communication.
• Recently implemented a software to analyze student data (ZogoTech) and create dashboards for all levels of the college. The state implemented free community college for individuals over the age of twenty-five who have no degree. Using data from ZogoTech and other reporting systems to promote this program. Hired an outside firm to do a formal academic program review to assist the college in getting a clearer handle on where program adjustments may be needed, etc.
• Using data-driven decision-making, we are becoming more efficient in course offerings and scheduling to decrease time to graduate and increase student success.
• More investment in learning analytics and AI professional development and services.
• We are developing software to support our teachers in pedagogical issues and teaching and learning strategies.
• Supporting efforts to enhance data integration and increase decision-making at the point of interaction between staff and students.

Multiple activities

• Revamped data infrastructure, governed data access, on-demand complex reports managed distributed staff.
• Building out a data strategy with a data lake. Implementing Ellucian Insights with SaaS. Piloting AI tools.
• Reorganizing the data and analytics team, establishing data governance, implementing data lakes and data marts and associated processes and practices on data management.
• We recently launched our first unified enterprise data platform on which we will build our insights and actionable knowledge. AI capabilities will be leveraged on top of this data, which is now up-to-date, clean, and accurate.
• While eschewing the idea of a unified data function, we are investing in components that are strategically placed across the institution's organizational units. Our main focus in 2025 will be to put into place fundamental data management and governance, which will better enable our BI (data warehouse) and analytics functions. We have also increased investments in cybersecurity and research computing and data.
• Prioritizing integration of data sources, reporting, and data literacy.
• We have a growing data analytics program that is using the most contemporary tools and technologies in building data dashboards and reports. We are developing a C-suite-sponsored AI strategy for the institution and developing AI chatbots in various areas under the missions of education, research, clinical care, and community engagement. We have also built a cloud-based secure research environment for faculty researchers that has high security of data being used for research and AI tools and LLMs in the environment for use by faculty.
• Partnering with Salesforce to use its Education Cloud CRM offering. Incorporating AI into our IT service-management platform. Early campus introduction of Microsoft Copilot and pilot use of Microsoft 365 Copilot.
• Expanding our course offerings, automating manual processes, focusing on evidence-based, and data-driven decision-making.

Note

1. Jenay Robert, 2024 AI Landscape Study, research report (EDUCAUSE, February 2024). Jump back to footnote 1 in the text.↩

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Deborah Dent is Chief Information Officer at Jackson State University.

James Frazee is Interim Vice President and Chief Information Officer at San Diego State University.

Carrie Shumaker is Vice Chancellor for IT and Chief Strategy Officer at University of Michigan-Dearborn.

Tim Wrye is Chief Information Officer at Highline College.