Embedded engagement

WTP Data Quality & Migration Support

Duration 6–12 months
Commitment 3–4 days/week
Delivery Model Embedded PM / Data quality lead
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  • Kader Datakwaliteit-aligned assessment
  • KDE identification and DRI profiling
  • Remediation programme management
  • Migration specification and testing
  • Parallel run coordination
  • ISAE 3402 alignment and sign-off support

Why data quality matters now

DNB's supervision expectations and Pensioenfederatie's Kader Datakwaliteit are raising the bar. Poorly managed data doesn't just slow transitions — it creates audit friction, delays sign-off, and puts funds at compliance risk. We fix this at the source.

Why data quality determines transition success

WTP transitions are complex enough without data surprises. Most pension administrators inherit years of accumulated data inconsistencies — inconsistent ABO formats, missing ISAE 3402 validation trails, incomplete KDE mappings, incomplete DRI profiling. These gaps surface when it's too late: during parallel runs, UAT, or worse, during sign-off.

DNB's heightened focus on data governance and the Pensioenfederatie's Kader Datakwaliteit have fundamentally changed what "ready for transition" means. It's no longer enough to have data that technically migrates. You need a documented baseline, a clear remediation narrative, and ISAE 3402-aligned governance.

We've managed this from both sides. We've seen what happens when data quality is ignored — missed sign-offs, extended parallel runs, post-live reconciliation crises. And we've seen how hands-on data quality leadership turns potential blockers into managed risks.

What we deliver

Baseline Assessment

Kader Datakwaliteit-aligned assessment of your current state. We identify data issues, categorize remediation priority, and establish a baseline for progress tracking.

KDE Identification & DRI Profiling

Map your Key Data Elements against scheme rules and regulatory expectations. Profile Data Responsibility Indicators to clarify who owns remediation — fund, administrator, or custodian.

Remediation Management

We don't just document problems — we lead remediation execution. We prioritize fixes, track progress, manage dependencies with fund and administrator teams, and adjust scope based on regulatory timeline pressure.

Migration Spec & Testing

Define mapping rules, handle exception workflows, and lead UAT. We ensure migration logic captures remediation decisions and tests confirm data quality gates are met before parallel run.

Parallel Run Coordination

Oversee data reconciliation between legacy and new systems. Manage reconciliation variance workflows, escalate anomalies, and build the sign-off evidence file.

ISAE 3402 Alignment & Sign-off

Document governance decisions, remediation rationale, and control execution. Build the audit trail that satisfies your auditors and DNB's expectations for data governance rigour.

Our approach

Data quality work is inherently embedded. It requires daily interaction with your teams, custodians, and the migration programme. We embed as a data quality lead or project manager, sitting in your transition office, leading data remediation as a work stream, and building governance as we go.

1

Discovery & Baseline

Walk through your current data landscape. Document known issues, data ownership, and existing controls. Establish a Kader Datakwaliteit-aligned baseline.

2

KDE Identification & DRI Profiling

Map Key Data Elements to scheme rules and DNB expectations. Profile data responsibility. Clarify what must be fixed, by whom, and why.

3

Remediation Execution

Lead remediation as a dedicated workstream. Prioritize, execute, and track fixes. Manage stakeholder alignment when remediation scope changes.

4

Migration & Parallel Runs

Ensure migration logic captures remediation decisions. Lead UAT and parallel run reconciliation. Build the sign-off evidence file in real time.

5

Sign-off & Handover

Consolidate governance evidence. Prepare for auditor and regulator scrutiny. Handover operational data quality governance to your team.

Who this is for

Pension administrators and funds with known or suspected data quality issues. If your last data audit flagged material gaps, if you're uncertain about KDE completeness, or if you're approaching WTP transition with data governance anxiety — this is the engagement for you.

This isn't for funds with gold-standard data governance. It's for administrators and funds who recognize that data quality is a transition blocker and want to fix it before it becomes a compliance liability.

We embed as your data quality lead. You should expect daily collaboration, direct access to your teams, and a shared commitment to making data quality progress visible and measurable.

Frequently asked questions

How does your assessment align with Kader Datakwaliteit?
We use Kader Datakwaliteit as our baseline framework. We assess your current state against the framework's governance, data ownership, and quality dimensions. The result is a baseline and roadmap that maps directly to Pensioenfederatie expectations — and gives you evidence for DNB conversations if needed.
Do you work with our administrator's systems, or ours?
Both. Data quality spans administrator systems (membership, contribution records), custodian systems (holdings, valuations), and your own fund systems (accounting, reporting). We work across all three. This is why data quality is a transition programme role — it's inherently cross-organization. We coordinate the remediation dependencies between fund, administrator, and custodian.
What does ISAE 3402 alignment mean in this context?
Your service provider (administrator, custodian) has ISAE 3402 controls in place. During remediation and migration, we document how data quality decisions are governed, how exceptions are handled, and how controls are executed. This evidence feeds into your audit process and gives your auditors confidence that data governance is intentional, not accidental.
What if our data quality is really poor? Will 6–12 months be enough?
Depends on scale. If you have systemic issues (e.g., decades of incomplete KDE data), 6–12 months of embedded leadership can manage remediation in parallel with transition planning. If you discover severe issues late (e.g., during migration UAT), timelines compress. We scope this upfront. If poor data quality emerges mid-engagement, we escalate and adjust, potentially bringing in additional capacity or recommending post-live remediation workstreams.

Ready to get your data transition-ready?

Data quality isn't theoretical. Let's assess your baseline and build a remediation roadmap that fits your timeline.

Schedule a Consultation