The UK is a global leader in higher education, a sector that generates more than £30 billion of revenue for the UK economy. Like most other sectors of the economy, higher education is driven by data. From maintaining student records, managing payments, curating staff and student schedules, to confidential research and funding data, the challenges faced can be daunting.

Feeling the effects of the global pandemic and with declining funding and increasing costs, higher education institutions face some challenging times ahead. Expert data management, in both the administrative and academic sense, is now essential.

However, UK universities have a data problem. Well, if we are being honest, it’s far more than one.

Fractured data landscapes, inconsistent policies, and an institutional reticence to prioritise back office spending over investment in faculties are preventing universities from realising the value of their data, or even meeting their regulatory obligations.

Higher education institutions have an enormous amount of personal information contained within their data stores. From student bank details to their vulnerabilities, addresses to family histories, this data creates a significant burden as well as opportunity.

With new requirements on data, such as the GDPR and the upcoming HESA Data Futures submissions, bearing down on IT departments and admin teams across higher education, the time is very much here for data fundamentals to come front and centre in senior leadership team discussions.

Expertise in data management, throughout the college or university, can make a significant difference in maintaining the safety of students and the success of the institution as a business.

A New Approach Is Needed

Like their private sector counterparts, universities need to modernise their approach to data management. Focused investment is needed on data governance and quality; the foundation stones of efficient processes, data science and MI reporting. Structured data governance, with accountability and responsibility baked-in at all levels, is the first step in improving, and then transforming data into a valuable asset.

Whilst the business case may be hard to justify in terms of outright ROI, the consequences of inaction are more compelling. In 2018, data from a training conference not being properly governed led to a £120,000 fine issued to a London-based university, which would have undoubtedly been higher had it been calculated post-GDPR.

Specialists Over Generalists

In these rapidly changing times, CIOs are increasingly turning to specialist SMEs to bring new thinking, cutting-edge technology, and high responsiveness to revolutionise university data use in cost-effective packages. Industry disrupters are proving that specialists trump generalists every time.

Smaller expert providers can give clients the close relationships which allow them to tailor solutions to their needs and, in partnership with them, to produce game changing data innovations.

Targets Need To Be Ambitous

With pressure coming on tuition fees and remote delivery essential, universities need to do more than meet the demands of the day. 99% quality still means one in every hundred students experiencing issues with data, which, in an increasingly competitive marketplace, with active, tech-savvy ‘customers’, can be the difference in the all-important League Tables and leave a mark on an institution’s reputation.

Understanding data assets and maintaining and leveraging them correctly is not only the key to unlock cost savings and realise efficiencies across BAU, but to also open new streams of revenue and research. If data is ‘the new oil’, refining it through good governance, enforced quality and robust process is the only way to turn it into the fuel which will power universities forward from the digital dark ages to a data-driven future.

Applying The Theory

The implementation of a design and solution for HESA Data Futures and Student Planning and Forecasting at a Sunday Times top 10 UK University.

Our client, like many other universities in the UK, are under increasing pressure to do more for less. In particular, a fragmented and poorly understood data estate meant that meeting the requirements of HESA Data Futures, or improving the quality of their Student Planning and Forecasting, was a daunting and seemingly unachievable task within the timeframe they had been set.

HESA Data Futures

The HESA Data Futures requirements for 2021/22 forwards, mark a step-change in the obligations for universities to report student data, and a major test of institutions data management and reporting capabilities.

IntoZetta were engaged initially to help the university understand the scale of the problem they face. Using our field-tested method for data archaeology we were able to quickly establish the 20 systems that were potentially required in scope to meet the new HESA requirements (ranging from the core student management tool – Banner, to SAP systems, to desktop items such as spreadsheets and Access databases) We also identified more than 30 required data items which were not currently captured by the University.

After implementing the IntoZetta software, we completed a full data dictionary for the required items, including identifying lineage, documenting transformation or derivation logic, and mapping the data flows between systems in IntoZetta Governance. From there, we were able to utilise the flexibility of the IntoZetta data model to provide a repository for the data items not currently captured, allowing the requirements to be met, whilst a long-term solution was built into the core Banner system.

The second major hurdle for the University was the requirement to provide point-in-time submissions, removing the opportunity for a lengthy period of data quality assessment and cleansing. By ingesting the data quality rules from the HESA specification into IntoZetta Quality, we were able to provide a daily assessment of data quality issues.

This allows the University to target, with precision, areas of data in which the quality was below the required standard. Over 1000 quality rules are executed on an ongoing, daily basis, and as a result the university can now maintain their standards in an efficient and cost-effective manner.

Finally, we were also able to build a bespoke process to map the University’s data to the HESA DF standard, including transformations of codes, calculations of certain fields and on to the generation of the XML submission itself. This process greatly simplifies the existing BAU process and allows us to produce a submission on an ad hoc basis, in turn allowing the institution to submit to HESA as they wished.

This solution currently supports the as-is, annual HESA submission and is ready to support Data Futures from Go Live.

Student Planning & Forecasting

Similar to the challenge of HESA, the University also face issues with accurately planning and forecasting their student numbers, due to the fragmented and unreliable nature of their data (including 20 students who had a different name depending on which system you looked at!).

By ingesting all the data required for planning and forecasting, we were able to provide a rounded view of data quality and, within IntoZetta Governance, define an organisational structure for the management of this data going forward. We worked with the university to identify the right number of data participants, such as ‘Owners’ and ‘Stewards’, define their accountability and responsibility, and then identify and document the individuals to hold these positions.

This governance structure, allied to the output of the IntoZetta Quality rules, allowed the University to monitor the progress of data cleanse, rate the performance of the teams involved, and – most importantly – deliver improved data to the planning and forecasting system.

IntoZetta was configured as the data repository for the chosen planning and forecasting solution, and was able to ingest, model, aggregate and extract all the required data, in the format required by the tool. This approach saved hundreds of thousands of pounds when compared with the alternative of having those changes made in Banner directly.

Our detailed analysis of the processes involved in planning and forecasting also highlighted several inefficiencies and inconsistencies in them. Together with BA’s from the university, we were able to design new, leaner processes, delivering improvements in performance across the piece.