Turning statutory reporting risk into sustainable data governance

A large, multidisciplinary university was managing regulatory data scrutiny while transitioning to a new student-records environment. Its statutory reporting process relied on manual intervention and off-system activity, making it harder to identify data-quality issues early, demonstrate clear accountability and maintain an auditable route from source data to final submission.

The brief

Our client had developed an off-system proof-of-concept using source data from its student records system and the regulator’s coverage and quality requirements. Strive Higher was asked to develop this into an approach that could support the immediate statutory submission while creating a foundation for wider data governance. The priorities were to:

• Reproduce the required statutory reporting logic and generate a compliant final-format file,

• Identify data-quality issues earlier through repeatable validation and reporting,

• Clarify accountability among data owners, data stewards, system custodians and data users,

• Reduce dependence on undocumented, manual and reactive processes, and

• Create methods, controls and governance assets that could be reused across other returns and data domains.

Our approach

Rather than designing an abstract governance framework, we used statutory student reporting as a practical test of how governance needed to operate. Working alongside reporting, business and technical teams, we helped the university:

• Embed assurance within the data flow. Regulatory coverage and quality requirements were translated into repeatable validation, with exceptions surfaced earlier and an auditable route maintained from source data to submission output.

• Clarify ownership and escalation. Responsibilities were distinguished across data owners, data stewards, system custodians and data users, creating clearer routes for decisions and issue resolution.

• Create reusable controls and assets. Definitions, business rules, quality rules, authoritative sources, issue logs and assurance points were documented for application beyond the initial return.

• Connect governance to existing work. The approach was aligned with established reporting cycles, forums and workflows, supporting its transition into business as usual.

• Prepare for wider adoption. The proof-of-concept informed recommendations for an operating model, institutional data domains and a wider community of practice.

Outcomes

The proof-of-concept demonstrated that the selected methodology and tools could reproduce the required statutory logic, provide data-quality reporting earlier in the reporting cycle and generate a final-format output that met the regulator’s submission requirements. Furthermore:

• Automation and repeatable validation reduced manual intervention and improved processing efficiency.

• Data-quality issues became visible earlier, enabling more proactive investigation and remediation.

• Roles, controls and escalation needs became clearer across business and technical teams.

• A repeatable approach was established for additional returns and data domains.

• The institution gained a stronger basis for auditable, quality-assured statutory data that was not dependent on a single student-records system.

From proof to capability

The work showed how an immediate regulatory requirement could become a controlled environment for establishing ownership, testing assurance processes and building governance around the realities of institutional work. The next stage was to embed that capability through a defined target operating model, prioritised controls for high-risk data, agreed institutional domains and owners, and governance integrated into business-as-usual processes.

For universities replacing student records systems or strengthening statutory return assurance, the case study demonstrates a practical route from reactive reporting activity to more sustainable institutional data governance. If you’d like support with similar challenges, get in touch. We’d welcome a conversation.