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Why is everyone talking about HESA Data Futures?

Since 1994, every Higher Education Institution (HEI) in the UK has been required to report on student-level data to regulators. The data collected is vast and varied, and includes, for example, the student’s highest qualification when they joined the institution, their parent’s occupation and their study pattern/location. Historically, there have been minor annual updates to the data specification and field definitions, but the Higher Education Statistics Agency (HESA, now part of Jisc) Data Futures programme, taking effect from this academic year (22/23), marks a significant change in the scale and frequency of the statutory reporting requirement.

  • Compared to the 21/22 academic year, there is a much broader scope around the type of data and the level of information that HEIs are required to collect and report, including over 80 new, or significantly changed data fields for the 22/23 academic year.
  • From 24/25, there is a requirement to report data much closer to the date of collection: twice-annual collections will be introduced in 24/25 and in later years near-live reporting will be implemented.

These changes must be adhered to by UK higher education providers (including private sector), with some variations for providers outside England. This demands the re-defining of business processes, clear governance, robust student record management, and well-understood data structures.

Why is Data Futures so important?

HESA data is the central source for the collection and dissemination of statistics about UK higher education. It is used by the Office for Students (OfS) to understand individual providers’ performance, improve access and participation, ensure prospective students have reliable information, and to understand trends and risks at a sector level. The HESA data return is a regulatory requirement for HEIs, with late or poor-quality data potentially impacting funding and reputation.

The Data Futures programme presents a great opportunity for HEIs to proactively review data management processes to continue to enhance quality, consistency and accuracy. This will ultimately enable better data insights to support decision makers in driving a better student experience.

When do HEIs need to start thinking about Data Futures?

In brief: now!

HEIs need to adhere to the Data Futures specification return from the 22/23 academic year, with a final return due to be submitted to HESA in October 2023. Initially the return will be annual, to allow HEIs to adapt to the new model. Two data collection points will be introduced from the 24/25 academic year, with an aim to deliver close to real-time reporting and data sharing in subsequent years.

Data Futures may require significant changes in the end-to-end “record to report” process: from collecting new data (e.g. individual campus addresses, external PhD supervisors), through to mapping existing data to new HESA definitions, working with data owners to improve data quality, and adapting processes and controls to ensure an accurate return.

What do HEIs need to think about to successfully deliver Data Futures?

There are a number of key areas that HEIs should be thinking about to ensure a successful delivery of the Data Futures return. These include: processes/systems for collecting new data; resource capacity; technical skills for any system/logic changes; communications to data owners; data quality/validation and data governance.

1. Challenging timeline for 22/23 and beyond
  • There is a short and challenging timeline for 22/23, including over 80 new or significantly changed fields which may not have been collected previously. For example, it is now a requirement to report the student IDs and engagement numbers from a partner HEI where they have a collaborative learning arrangement.
  • HEIs need business analyst skills to determine how this data will be collected and to develop processes to ensure accuracy and completeness. This includes developing detailed field-level plans, which then need to be prioritised, resourced, communicated, monitored and delivered.
  • Data engineering skills are required to work at pace to collect, integrate and transform student record data from different sources and systems, using a range of tools.
2. Data quality and integrity
  • A successful return is underpinned by high quality data. HEIs should consider how to develop an efficient data validation methodology & compliance model to achieve this.
  • HEIs should maintain detailed data lineage documentation explaining how data for HESA has been derived and how to adapt these to the new (and emerging) HESA requirements. This includes ensuring that data is consistent across each record and can reconcile to underlying systems and between data sets, using analytics tools such as the HESA data validation toolkit.
  • HEIs may need to liaise directly with HESA to ensure correct interpretation of the requirements, particularly for more complex learning arrangements (e.g. distance learners or unusual study patterns).
3. Clear governance and ownership
  • The data required by HESA spans the entire student lifecycle. There needs to be effective data governance to ensure that a culture of valuing high quality data at source exists.
  • HEIs need to agree and communicate who the data owners are across multiple data sets in the organisation, and what the governance and sign-off processes will be.
  • There needs to be clear standards for data documentation across the HEI. It is important to ensure there is a data mapping and lineage is clearly documented.

Are you prepared for HESA Data Futures? To find out or for more support, please get in touch for a Deloitte HESA Readiness Assessment or a discussion with the any of the contacts listed below.

This is the first in a series of HESA Data Futures blogs from Deloitte – look out for more!