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Only connect - bringing together the people and the systems

The panels at Data Matters 2026 shone the spotlight on the sector view and experience with data - from celebrating successes and sharing lessons learned to overcoming challenges and interrogating legacy systems and processes.

A panel of four speakers sitting on a stage.

James Hodgkin, head of analytics, Jisc, introduced the panel discussion ‘data foundations for understanding student engagement’ and introduced colleagues from organisations spanning the various stages of applying learning analytics to student engagement data, from piloting to building, to re-evaluating, to wide-scale transformation and next steps to embedding in the ways of working and organisational culture.

All representatives had commonalities alongside distinct and unique ways of working within their organisational drivers and strategy.

We've selected some topline themes from the conversation, but for the full and diverse discussion watch the unedited panel recording on our Data Matters 2026 channel.

Wrangling data streams and systems

With any data transformation programme comes the job of interrogating the data available and the systems holding it.

Legacy has evolved into a term that carries an amount of foreboding. We recently published Tackling technical legacy in UK higher education: a strategic imperative, a report highlighting the scale and impact of technical legacy across the sector.

Nick Moore, director of information technology at Birmingham City University, opened the conversation considering the weight of legacy systems and highlighting the importance of the audit process ahead of any planning for successful future activity:

"…where we came from was a fantastic focus on the student great variety of practice but not a lot of commonalities to build on. So that is what we've been trying to do: fix the foundations of particularly the technology so that we can actually harness the power of something like data as an institution."

Catherine Murray, director of planning at Queen Mary university London, added that sometimes it isn’t a lack of systems but an overwhelming richness of sources and storage in need of streamlining for consistent, coherent next steps:

"We've got about five attendance monitoring systems. That's down from a larger number, where we have 20 platforms that we use for assessments.

We've had to do a lot of work wrangling that data into a shape that means that we can present to the university in a consistent way."

But the panel agreed, securing and agreeing the vision and mission across teams and workstreams before the direct work to catalogue and review the systems and processes is the strongest indicator for success.

Change – and success – doesn’t exist in isolation

What was clear from the discussion was that acknowledging and accommodating the initial work is a key part of a change project, as well as focusing on the future benefits.

Bringing people along with you on the journey and understanding how their challenges align with your requirements mitigates the risk of launching another silo that competes with existing ways of working.

As Catherine said,

"We've doubled in size and as we grew our attrition was increasing. So there was definitely a driver to reduce that, and we have seen in the last five years student dropouts reducing by one and a half percent or so each year. So there is a real financial value to [learning analytics]."

The motivation or underlying reason for managing and transforming data streams shares an ambition across organisations, not least how to start improving student experience through data. But engagement has to work from both sides of the learning experience to be a long-lasting, useful change.

Dr Mary Cornelius, educational development and innovation manager at the university of Suffolk, spoke about the unexpected benefits reaped by their programme:

"…what we did was not just focus on improving the data quality for the typical compliance reasons and all that…what we did in the background was work quite closely with teams across the organisation, particularly our research team … and they've actually built a level four retention project which is now in its third year of running and we've been able to save more than a million pounds in retained tuition fees … we raised the stakes of the data and helped our organisation understand this is the importance of good clean data and what we can get out of it."

Nick agreed, saying:

"What the pilot has shown is that there are lots of people who haven't had that good practice who really want it. So there is a real draw from across all the different schools to want to be able to support their students and get the data and connect the systems together."

The discussion also dived into why this work is so important, predictive versus descriptive analytics, the unexpected opportunities along the way as well as what success looks like.

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