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18 November 2025 at 14:14:40

Data Tangle Interview 1:
Jo Knott

Interview #1 of 12 our Data Tangle research project. Jo Knott- Director of Student Information and Planning at University of Hertfordshire.

Alex Leigh

September 10 2025

4 min read


Introduction

This is interview #1 of 12 for our Data Tangle research project.

Interviewee: Jo Knott

Institution: University of Hertfordshire

Role: Director of Student Information and Planning

Processes in scope: Student data management, HESA Student return, Data Quality reporting and remediation.


Summary of discussion

A summary of the issues and solutions discussed
A summary of the issues and solutions discussed

The main data issues we discussed were:

  • Operational data quality thresholds do not meet all use cases leading to point of use data cleansing

  • Ownership of data is fragmented and/or not well understood

  • Difficult/time consuming outputs are often not valued

  • System integration is patchy leading to re-keying and duplication

  • Cost of poor data management is not a metric anyone is or attempting to track.

  • Data outputs – especially some dashboards – are not universal with push back on whose data is correct.

 

Pragmatic solutions in place include:

  • Design the HESA process outside the Student Record System. Explain the importance of it and be really transparent about what needs to happen and when.

  • Manage access to student data reporting so it’s easy for anyone to get the data they need, and add context to ensure they understand what they are getting

  • Deploy tools where they add most value (Alteryx and Tableau)

  • Engage with other institutions on best/good practice so no reinventing the wheel for sector wide processes.

  • Provide context for how data is processed and visualised through data handbooks and roadshows. Be honest about progress and how much there’s still to be done.

  • Make explicit links between university objectives and data outputs (e.g. TEF, league tables) and tell better “data stories”

 

Our final takeaway

Something we don’t see enough of are specific data quality objectives embedded in role descriptions. This has measurably improved the quality and efficiency of improving the HESA Student Return.


 

Summary and next interview

Issues around data quality are not a surprise. What’s not are the way institutions respond with pragmatic and practical solutions, fixes and work arounds. That is the reality within the constraints the sector is working in.


The way we’re thinking about this is “We can’t be perfect, but that doesn’t mean good isn’t worth trying for!”


Next time we’ll be discussing the issues and insights of an ex-Director of Planning.


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