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POL · Policy Management

Data policies mapped to every obligation

We write and rationalise data policies, standards and procedures, map them to the regulations you are subject to, and embed classification, privacy and retention rules into everyday controls.

The challenge

Policy estates grow by accretion. Each new regulation adds a document, and soon nobody knows which rule applies or how compliance is evidenced.

  • Overlapping policies written by different functions, with contradictory requirements.
  • No traceability from regulatory obligations to the controls that satisfy them.
  • Classification schemes exist but are not applied to data, so protection is inconsistent.
  • Retention schedules are defined but not enforced, creating both privacy and legal-hold risk.

What we deliver

Policy Management

Policy hierarchy

A clear policy → standard → procedure structure with ownership, review cycles and plain-language drafting that people can follow.

Regulatory mapping

A traceable obligations register linking each regulatory requirement to policy statements, controls and evidence.

Data classification

A classification scheme for confidentiality and criticality, with tagging rules applied in your catalogue and platforms.

Privacy by design

Personal data inventories, records of processing and privacy controls integrated with governance workflows.

Retention and disposal

Retention schedules translated into enforceable rules, with legal-hold handling and defensible deletion.

Attestation and assurance

Annual attestation workflows, control testing and reporting to risk committees and the board.

Regulations and standards we map to

  • UK GDPR
  • EU GDPR
  • BCBS 239
  • DORA
  • Solvency II
  • CCPA
  • NDPR
  • ISO 8000

Outcomes you can measure

Outcomes you can measure

40%

fewer policy documents after rationalisation, with no loss of coverage

100%

of in-scope regulatory obligations traced to a policy statement and control

1 register

of obligations, controls and evidence replacing scattered spreadsheets

Related case study · Illustrative engagement

Rationalising data policy across a public body

A national public sector agency · Africa

41%

fewer policy documents

Twenty-seven overlapping data policies were consolidated into a clear hierarchy mapped to national data protection law, with a costed three-year roadmap.

Read the case study

FAQ

Frequently asked questions

What is the difference between a data policy, standard and procedure?

A policy states intent and principles, a standard sets measurable requirements, and a procedure describes the steps to meet them. Keeping the layers distinct makes documents shorter and easier to maintain.

How do you map data policies to regulations such as GDPR or BCBS 239?

We build an obligations register that breaks each regulation into discrete requirements, then link each one to the policy statement, control and evidence that addresses it.

Do you cover African and Middle Eastern data protection laws?

Yes. Alongside UK and EU GDPR we regularly map to Nigeria's NDPR and Data Protection Act, South Africa's POPIA and the data protection laws of the UAE and Saudi Arabia.

How should data classification be implemented?

Keep the scheme to four or five levels, apply it at domain or dataset level first, automate tagging where possible and link classification to concrete handling rules.

How often should data policies be reviewed?

At least annually, and whenever a material regulatory, organisational or technology change occurs. We set up review cycles and attestation so this happens by default.

Discuss your priorities with a practitioner

A 45-minute working session, no sales deck. You will leave with at least three actionable recommendations.

Book a consultation Email us: info@crestqa.co