Key points:
- Data is the foundation of agility and the key to sustained progress
- Why education leaders must highlight their people
- How small colleges can build a data-driven enrollment engine that lasts
- For more on higher education data use, visit eCN’s Campus Leadership hub
Education leaders are facing one of the most challenging decades in recent memory: Budgets are tightening, enrollment–both domestic and international–is declining, and grants and state funding are down. And yet, expectations for personalized learning, operational transparency, and institutional innovation have never been higher.
CIOs face mounting pressure to sustain progress as students expect tailored experiences, boards demand accountability, and faculty rely on digital tools that require constant upkeep. The question is no longer how to do more with less–a phrase many education leaders find discouraging–but rather, how can institutions do more with what they already have?
To keep pace with these expectations, institutions must leverage their existing people, technology, and processes to enable smarter decisions and faster pivots when needed. In doing so, data becomes the foundation of agility and the key to sustained progress.
The operational agility advantage
The ability to pivot swiftly sets leading institutions apart in today’s rapidly changing landscape. Whether adapting to enrollment fluctuations, new regulations, or breakthrough technologies like agentic AI, operational agility gives schools the flexibility to move with purpose rather than react to disruption. Building this agility depends on three interconnected pillars: process, technology, and culture.
- Process agility: Streamlining workflows
In an environment that demands rapid change, many educational institutions continue to rely on outdated processes, which can become significant obstacles. Improving process agility starts by rethinking how data moves through daily work:
- Automation can streamline manual workflows, allowing staff to focus on value-added tasks. In addition to increasing productivity, retention rates increase when employees feel more fulfilled by the tasks they’re doing.
- Analytics can map where bottlenecks occur, like in form digitization or approval chains.
- Departments can gain independence by accessing shared insights rather than waiting for static reports.
By updating processes, leaders can monitor performance in real time and reconfigure operations before issues escalate, turning adaptability into a repeatable habit rather than a crisis response.
- Tech agility: Building a strong infrastructure
Technology alone doesn’t make an institution agile; the right data infrastructure does. When data flows seamlessly across finance, enrollment, academic, and HR systems, institutions can operate as one, not in a collection of silos. For example:
- Predictive analytics can forecast the impact of declining enrollment rates before they happen.
- Scenario modeling can help administrators test multiple outcomes and “what-if” scenarios before reallocating limited resources.
- AI-powered assistants enable staff to query data directly and in a conversational manner.
This isn’t about adding more tools–it’s about making existing technology smarter and more collaborative.
- Cultural agility: Empowering continuous learning
When ChatGPT and similar platforms entered classrooms, it reshaped academic culture almost overnight. Faculty, students, and administrators had to adapt rapidly to new ways of learning and working. That same adaptability now needs to extend beyond AI to every part of institutional life. A truly agile culture is one where:
- Faculty use analytics to continuously improve learning outcomes.
- Staff view experimentation as progress, rather than risk.
- Leaders invest in data and AI upskilling so employees can augment their expertise and feel confident applying data to their work.
By empowering their existing workforce to become data-literate, every team member becomes a data-driven problem solver.
Doing more with what you have
The real story of transformation isn’t about cutting back, but about unlocking capacity. Processes that are agile enough to change course mid-semester, technology that adapts alongside new questions, and a culture that sees data as an enabler, not an audit trail.
When those elements work together, institutions can:
- Identify emerging trends in enrollment or funding.
- Repurpose existing resources to meet new student needs.
- Maintain continuity amid uncertainty–all without requiring massive new investments.
AI and analytics help institutions uncover hidden capacity–whether that’s reallocating resources, spotting at-risk students sooner, or revealing new ways to deliver impact with existing teams.
The future: From data-driven to data-dynamic
In the coming years, the most resilient education systems will be those that master the art of doing more with what they have. They will train their workforce to collaborate with AI and analytics, build cultures where insight drives experimentation, and pivot processes instantly in response to changing student or funding realities.
Operational agility isn’t about cutting costs; it’s about amplifying capability. By aligning processes, technology, and culture around agility, institutions stop reacting to change and start shaping it. That’s the promise of becoming truly data-dynamic: an institution that continuously learns, connects, and evolves.
Tom Scurlock is VP of SLED Sales at Qlik Federal. Scurlock leads Qlik’s State, Local and Higher Education practice across the U.S., where he is responsible for revenue, strategy, and customer success. With a people-first leadership approach, Scurlock works closely with public sector leaders and partners to modernize systems, prepare for the impact of AI, and ensure data investments drive lasting public value.
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