IDMP Readiness: Turn Master Data Into an Advantage

Regulators are raising the bar on master data, yet most organizations still juggle

product, substance, and organizational records across dozens of systems. The

result: duplicate work, conflicting submissions, and missed opportunities to

reuse data. IDMP readiness is less about compliance checklists and more about

building a reliable, reusable data backbone.

This playbook turns IDMP readiness into a competitive advantage. You will name a

single source of truth, align with SPOR expectations, stand up a governance

council, and build automation that keeps data accurate long after the initial

remediation.

Why master data mastery matters

Regulatory confidence: Clean IDMP data reduces back-and-forth with EMA and

other authorities, improving review timelines.

Faster submissions: Structured data feeds Module 1, labeling, and lifecycle

variations without re-entering information.

Operational efficiency: Commercial, supply chain, and safety teams rely on

the same information, reducing reconciliation work.

Strategic insight: Trusted data supports portfolio analysis, launch

sequencing, and market expansion decisions.

Step 1: Establish authoritative sources of truth

Identify the system of record for each domain: product, substance, organization,

manufacturing site, and regulatory activity.

Document owned attributes, data standards, and integration points.
Retire rogue spreadsheets or shadow databases that undermine credibility.
Implement change logging and audit trails so users trust the record.

Step 2: Map to SPOR vocabularies and controlled terms

Align each attribute to EMA SPOR lists (Substance, Product, Organization,

Referentials) and regional equivalents.

Maintain mapping tables under version control, including transformation rules

and exceptions.

Monitor agency updates and refresh mappings promptly, communicating changes to

downstream systems.

Validate that translations and local market identifiers remain synchronized with

SPOR codes.

Step 3: Stand up a master-data governance council

Assemble cross-functional leaders from Regulatory, Quality, Manufacturing,

Supply Chain, Commercial, and IT.

Define charter, decision rights, escalation paths, and meeting cadence.
Monitor data quality KPIs: completeness, accuracy, timeliness, duplication.
Approve structural changes (new attributes, code sets) and oversee remediation

projects.

Share dashboards highlighting top issues by market or product so decisions are

data-driven.

Step 4: Implement data stewardship and workflows

Assign stewards for each domain responsible for data entry, review, and issue

resolution.

Deploy workflow tools that capture requests, route approvals, and enforce SLAs.
Integrate validations (format checks, reference lookups) to catch errors at

source.

Provide business-friendly interfaces for affiliates to submit updates while

maintaining central control.

Step 5: Automate data quality monitoring

Configure rules that flag duplicates, missing fields, expired references, and

inconsistent hierarchies.

Use analytics to track KPIs over time and highlight trends by region or product

family.

Create alerts for high-risk changes (new active substance, label change,

manufacturing site updates).

Feed quality findings into the governance council and CAPA processes.

Metrics that prove progress

Core data completeness and accuracy percentages, benchmarked against agency

requirements.

Percentage of submissions reusing approved data without rework.
Turnaround time for data change requests versus SLA.
Reduction in health authority questions related to master data.
Volume of duplicate or conflicting records resolved each quarter.

60-day roadmap

Weeks 1-2: Inventory product, substance, and organization data sources.

Flag conflicts and document pain points.

Weeks 3-4: Define sources of truth per domain, agree on ownership, and map

attributes to SPOR vocabularies.

Weeks 5-6: Launch the governance council, publish initial dashboards, and

prioritize remediation backlogs.

Weeks 7-8: Implement stewardship workflows, automate quality checks, and

communicate new processes to regional stakeholders.

Frequently asked questions

Where do we start? Focus on product and substance data feeding submissions;

these have the highest regulatory impact.

How do we handle affiliate systems? Integrate via APIs or controlled

templates, enforcing the same standards. Provide training and feedback loops.

What tools help? Master Data Management (MDM) platforms, SPOR-ready

solutions, or enhanced RIMS with data governance modules. Tool choice matters

less than process discipline.

How do we sustain momentum? Embed KPIs in management review, tie steward

performance goals to data quality, and celebrate reuse metrics.

Sustain the win

Review master-data KPIs monthly, refresh SPOR alignment when vocabularies change,

and rotate council roles so expertise spreads across regions. Capture success

stories—faster variations, fewer questions—and share them widely to keep the

organization invested in clean data.