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  • Writer's pictureAlex Leigh

Consistency is the higher education data management solution

Consistency is the key to effective higher education data management.


This article explores how institutions can strategically allocate resources year-round to prepare for HESA submissions and outlines best practices for maximising data quality and efficiency through continuous higher education data management solutions and governance.


A laptop on a desk for higher education data management solutions.

 

With HESA’s platform for in-year reporting currently in its current annual cycle, institutions must strategically allocate resources to prepare for data submission. 


Even before in-year returns are mandated, institutions should continue to focus today on year-round on allocating staff and resources to maximise data quality and efficiency.


This article examines the differences in higher education institutions' approaches to data management and outlines how institutions can get the most value year-round from their database management systems, processes and data.


What HESA activities do institutions typically focus on?


Most data management activities within the higher education sector supporting in-year collection focus on the following:


  • Improving student data quality

  • Maintaining hygiene factors to reduce the need for extensive Quality Assurance


This is necessary to meet the current and future HESA collection timelines and within touching distance of best practice data management.


What are the current challenges within higher education data management solutions for the HESA submissions?


Currently, many – if not most – institutions trigger their HESA student return processes in the Spring. 


While there are many differences from institution to institution in how data is cleaned, massaged and made usable, there are common issues in data architecture across the board: 



The quality attributes – completeness, accuracy, validity, and so on – all need work to create a data set that is good enough to meet HESA’s validation.



A team of data management professionals as well as a breadth of non-data roles can be required to work for months to get the data to the required level.


Why do some institutions face more data challenges than others?


No two higher education institutions face identical HESA database administration challenges to the same extent.


What differentiates institutions is how they treat their data year-round, which is effectively the value they place not only on the next return but also on that data set after submission to HESA. 


  1. Some institutions treat post-HESA submission data as a trusted source.

  2. Others forget their HESA data set after submission and move straight onto the next as an administrative task


Institutions in the second category miss out on utilising their datasets for the value they hold for more locally focussed needs (retrospective, current, and future).  


What is the importance of year-round data reuse?


Data collected for one purpose, such as admissions, can be valuable for other scenarios like:


  • Performance measurement

  • Strategic planning (e.g. student number planning)

  • Tactical decision-making. 


However, often, data quality standards for primary uses (like admissions) do not extend to these secondary uses, causing inefficiencies and missed opportunities.


A tangible example: entry qualifications


For example, let’s consider entry qualifications. 


These are incredibly important to admissions staff to ensure offers are made to the right prospective students in line with academic and recruitment targets. The same data is used to derive tariffs, measure course performance, inform tactical and strategic planning, and a host of other scenarios.


However, further data reuse here has typically been seen as ‘someone else’s problem’.


It’s not like people don’t care – colleagues don’t get out of bed aiming to make fellow staff members’ lives a misery as they comb individual entry qualification records for weeks on end – but they are incentivised on what their team needs to do.


This is nuts. It really is. Collecting non-admissions qualifications that affect tariffs is not a huge undertaking. This is different from contacting individual students six months later, which is both extremely costly in time and not great in terms of the student experience. This, though, is often standard practice.


Hence, taking a year-round approach to managing (completing, validating, and ensuring the accuracy of) this data would go a long way toward overcoming the source data not being fit for purpose and the extensive work to get it there.


What is the importance of Data governance?


Data Futures is helping to change this single-use approach to data. Through Data Futures, HESA introduced the concept of Data Governance, promoting:


  • Viewing data as an institution-wide asset

  • Managing data to support short and medium-term goals

  • Encouraging data sharing and comparison across datasets

  • Ensuring that everyone who interacts with data acts as a steward


Why is Data Futures so important?


Crucially, Data Futures defines everyone who touches data as a steward of it, enhancing:


  • Data Utility: Making less data work harder by reducing rekeying and increasing data integration.

  • Accountability: Ensuring staff can find and use data effectively, minimising redundancy and improving data integrity.

  • Data as an Asset: Treating data with the same importance as finance, estates, and staff.


Sure, Data Futures doesn’t eradicate the spreadsheet culture, but it starts to make the case for how that might eventually happen. It stops conversations about whose data is right and starts discussions around what the data means. It provides accountability so staff can actually find data rather than creating yet another copy.


Why try to eradicate data siloes?


Current siloed data management leads to wasted effort and poor outcomes. Understanding the financial impact of poor data quality is crucial.


High-quality data that the entire university can trust and use is vital for operational efficiency and strategic planning.


Why does your institution need data management now?

Despite a HESA delay in any given year, the need to professionalise data management and make data management education a year-round activity remains. 


Quality data is integral to institutional success, facilitating process improvement, better decision-making, improved insights, and richer scenario planning. 


Our regulator may have hit the brakes on moving to in-year returns but we know it’ll be coming……albeit later. As the saying goes, “If you don’t prepare, you will repair”, which we cannot sustain for multiple submissions a year. 


Conclusion

Too many institutions’ approach to the management of their data asset appears to be “we don’t have time to do it right, but we do have time to do it twice”. 


Yet, whether it’s process improvement, better decision-making, improved insights, richer scenario planning or learning analytics – understanding and managing our data as an asset in the same class as finance, estates and staff is foundational.


The question is not “What should we do instead?” but “How can we do more?”


Where can you find support for your data management?

Contact ConnectED today to learn how we can support your institution in developing and implementing a robust data strategy.




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