Why Strong Data Governance Requires More Than Policy Documents – Bakare

Most organisations have no shortage of data governance policies. The challenge, however, lies in translating those policies into operational systems that consistently enforce them.

Across industries, organisations invest significant resources in developing data governance frameworks, privacy policies, retention schedules, security standards and compliance procedures. While these documents often satisfy regulatory requirements and articulate clear governance objectives, data breaches, compliance failures and governance lapses continue to occur.

According to Bakare, the reason is straightforward: policies establish expectations, but systems determine whether those expectations are enforced.

A policy may stipulate that only authorised personnel should have access to sensitive information, but without properly configured role-based access controls, such safeguards remain ineffective. Likewise, retention policies requiring records to be deleted after a specified period become meaningless if deletion processes are not automated. Similarly, data quality standards cannot improve reporting outcomes if validation mechanisms are absent from operational systems.

Drawing on experience across healthcare, public sector and enterprise environments between 2019 and 2026, Bakare argues that governance failures are often the result of poor implementation rather than the absence of policy.

He noted that the disconnect between governance documentation and technical implementation creates compliance risks, operational inefficiencies, security vulnerabilities and diminished confidence in organisational data.

The challenge, he observed, has become more pronounced as organisations adopt cloud computing, distributed systems, advanced analytics and artificial intelligence, all of which introduce greater complexity into data management.

According to him, governance must therefore move beyond documentation and become an integral part of system architecture.

He pointed to emerging capabilities within modern data platforms—including automated data lineage, schema enforcement, data quality monitoring, access management, audit logging and policy-driven controls—as evidence of a shift towards embedding governance directly into technology infrastructure.

Bakare also urged organisations to consider governance requirements during system design rather than after deployment, recommending that issues such as access control, data quality monitoring, retention management, data traceability and regulatory compliance be incorporated into technology implementation from the outset.

He added that the growing adoption of artificial intelligence further underscores the importance of strong data governance, noting that AI systems depend on accurate, traceable and well-governed data to produce reliable outcomes.

According to him, organisations that successfully integrate governance into their technology architecture will be better positioned to meet regulatory obligations, strengthen data integrity and improve trust in digital systems.

“Policies establish expectations. Systems enforce them. When the two diverge, the system always wins,” he said.