University Website Data is Everywhere, Insight is (almost) Nowhere. The CDO’s Job for 2026:
Imagine living in a hi-tech home where everyone owns a smartphone, yet no one can quite figure out where the light switch is. You see it in larger organisations that have invested heavily in tech, only to find themselves navigating yet more systems, dashboards, and even more logins than they had five years ago.
University Website Data. Visibility is Job #1
There is a special kind of frustration that comes from knowing something should be relatively simple, yet watching it become more and more complicated.
A University’s website data is one of those somethings.
And you see it in many industry sectors. Recently, I saw it up close and personal in Higher Education.
Economist Robert Solow once observed that you could see the computer age everywhere except in the productivity statistics. It was a critique of a world that had embraced technology faster than it had learned to extract value from it.
At the Digital Universities UK 2026 event, it was suggested we may have arrived at a modern version of Solow’s frustration. University website data is everywhere. Dashboards are everywhere. Systems are everywhere. But insight, the kind that reveals itself in good time to make a difference; that kind of insight is hard to find.
Keith Rozelle has spent three decades in complex B2B sales and advisory roles, from City of London boardrooms to fast-growth SMEs. He now works with leadership teams on sales strategy, reputation, and how complex commercial decisions really get made.
At last week’s Digital Universities UK event at the National Conference Centre, the conversation was not about whether universities value data. That question has long been settled. The more interesting question, and the one that surfaced repeatedly, was what happens when data exists everywhere, but actionable insight remains just out of reach?
The Illusion of Progress Through Volume
There is a persistent belief across sectors that more data leads to better decisions. It is an idea that feels intuitive, and for that reason, it is rarely interrogated.
Higher education has followed that path with enthusiasm. Over the past decade, universities have expanded their digital estates at pace. Website platforms, customer relationship management systems, virtual learning environments, engagement tools, marketing automation, analytics dashboards. Each addition has been made with a clear and rational purpose.
The result is not a lack of capability. It is an abundance of it.
Yet abundance brings its own complications. As highlighted in the post-event analysis, universities are actively trying to understand behaviour, intent and risk across the student journey, but still face gaps between website activity, CRM records and operational follow-up.
That gap is not about effort. It is about connection.
Growth Without Coordination
It would be easy to characterise this as a failure of strategy but that would be unfair.
The expansion of digital capability across higher education has been largely well-intentioned. Institutions have responded to changing student expectations, increased competition, and mounting financial pressure. Investment has been made where it was needed, often at speed.
The more accurate framing is that growth has outpaced control.
Different departments have adopted tools that suit their immediate needs. Faculties have built their own digital environments. Marketing, recruitment, student support and academic delivery have evolved in parallel rather than in lockstep.
Over time, this has created digital estates that are functional, but fragmented.
The systems work. The data is captured. The reports are produced.
But the journey is not always visible.
The Data Exists. Visibility, However, Does Not.
An economist friend of mine once made a point that has stayed with me the longest time.
We do not necessarily need more data. We need the right data.
In higher education, the situation is slightly different.
The right data often already exists. It is captured across websites, CRMs, engagement platforms and operational systems. The issue is that it rarely appears in the same place, at the same time, in a form that allows teams to act with confidence.
This distinction matters.
Because it shifts the conversation away from collection, and towards interpretation.
Universities are not starting from zero. They are surrounded by signals. What they lack is a joined-up view.
The Rise of Proxy Thinking
In the absence of that joined-up view, something fairly predictable happens. Teams rely on proxies to enrich their understanding of what’s happening “under the hood.”
Clicks become a signal of interest. Logins suggest engagement. Time on page hints at intent. These measures are not meaningless. They offer direction. They provide clues. But they are just fragments.
When those fragments are treated as a complete picture, the risk is not that universities are guessing. It is that they are making decisions with a level of confidence that underlying data does not support.
As the report makes clear, many institutions are still relying on these proxy measures precisely because deeper visibility across the journey is not yet available.
That is not a criticism. It is a reflection of the environment.
But it does introduce an element of risk.
From Observation to Action
One of the more encouraging developments discussed at the event was a shift from passive reporting towards active intervention.
Keele University’s work on engagement-led retention offered a clear example. By drawing on behavioural data across multiple systems, they are beginning to identify students at risk earlier and trigger support in a more timely way.
This represents a meaningful step forward.
It suggests that universities are moving beyond dashboards and towards decision-making that is informed by real-time signals.
Read: Why SMEs Don’t Buy Apprenticeships
Yet even here, the limitations remain visible.
Where the underlying data is incomplete or disconnected, intervention is still shaped by what can be measured, rather than what is fully understood.
It is progress, but it is not a revolution.
Governance. The Quiet Constraint
It is tempting to frame this as a technology problem. In reality, governance plays an equally important role.
Sessions focusing on web platforms and digital experience highlighted a familiar challenge. Universities must balance central oversight with local autonomy. They need consistency without stifling innovation.
That balance is difficult to achieve.
Too much control, and progress slows. Too little, and fragmentation accelerates.
The result, in many cases, is a digital estate that has grown organically, without a clear mechanism for unifying insight across the whole journey.
Governance, in this context, is not about restriction. It is about alignment.
Without it, even the most capable systems struggle to deliver coherent outcomes.
AI, With Its Feet on the Ground
Artificial intelligence was, unsurprisingly, part of the conversation. What stood out was not the level of excitement, but the level of caution.
Universities are exploring AI through the lens of trust, student confidence and academic integrity. There is an awareness that technology must support, rather than undermine, the learning experience.
This grounded approach is instructive. It suggests that the sector is less interested in novelty and more focused on practical value. Tools that can scale support, improve feedback, and reach underserved students are welcome. Those who introduce uncertainty or risk are approached carefully. In that sense, AI becomes part of the broader challenge.
Another source of data. Another layer of potential insight. But only valuable if it connects meaningfully with what already exists.
A More Commercial Lens Emerging
Alongside these themes, there is an important shift in how universities are thinking about their activities.
The move towards employer-led education, modular programmes and lifelong learning reflects a more commercial mindset. Institutions are exploring new revenue streams and new forms of engagement. This has implications for data.
In a more commercial environment, understanding intent and timing becomes critical. Decisions are not just academic anymore; they are operational and financial, too.
Fragmented data, in this context, is more than just an inconvenience; It is a fundamental constraint.
The ability to see and act on the full student journey has become a point of Distinctiveness.
The Practical Implication: Universities don’t need more systems, or even more data. Universities need better connections to what already exists.
When website behaviour sits separately from CRM records, recruitment and conversion teams lack context to act on. When engagement data is isolated, support arrives too late. When governance is inconsistent, insight does not scale.
These are not dramatic failures; they are tiny, persistent frictions which eat away at conversion rates.
The Longer-Term Consequence
The pressures facing higher education are well understood. Financial constraints, changing student expectations, and increased competition all shape the environment.
In that context, the ability to act on data quickly and confidently is not just an operational benefit. It is a strategic one.
Institutions that can connect their data effectively are better positioned to respond. Those who cannot may find themselves reacting more slowly, with less certainty.
The difference is not always visible in the short term but becomes clearer over time.
A Question Worth Considering
If the data already exists across the student journey, what would change if it could be seen clearly, in one place, at the moment it matters?
Not retrospectively. But in time to act.
And Back to the Beginning
It is easy to mistake complexity for progress. More systems. More dashboards. More capability.
But as any household full of disconnected devices will tell you, complexity without transparency rarely delivers.
Higher education is not short of ambition, nor is it short of data. The goal now is whether it can bring those pieces together in a way that supports the decisions already made.