Regulatory Data Governance

Turn regulatory complexity into trusted, governed data.

Regulatory data has become an enterprise asset.

It supports submissions, registrations, labeling, UDI, product information, market access, reporting, digital workflows, analytics—and increasingly, automation and AI.

Yet in many organizations, regulatory information remains distributed across systems, spreadsheets, functions and regions.

Definitions may vary. Ownership may be unclear. The authoritative source may depend on whom you ask. And teams can spend significant time reconciling information instead of using it.

Adroitta helps organizations transform complex regulatory requirements into structured, trusted and governed data capabilities.

From Regulatory Requirements to Enterprise Data

Regulatory requirements often begin as laws, regulations, guidance documents and submission requirements.

But digital systems cannot operate on regulatory language alone.

Those requirements must ultimately be translated into:

data elements → definitions → business rules → ownership → systems of record → controls → processes → evidence

Adroitta helps organizations make that translation.

Where We Help

Regulatory Data Strategy

Establish a clear vision for how regulatory information should be defined, governed, managed and used across the enterprise.

This can include:

Regulatory data strategy
Current-state assessments
Regulatory data operating models
Data capability roadmaps
Regulatory-to-enterprise data alignment
Data governance design

Regulatory Data Standards & Definitions

A trusted data environment begins with a shared understanding of what the data means.

We help organizations establish:

Regulatory data dictionaries
Critical regulatory data elements
Standard definitions
Business rules
Data classifications
Metadata
Taxonomies
Data ownership and stewardship

Data Governance

Governance makes accountability visible.

Adroitta helps define the structures needed to answer fundamental questions:

Who owns the data?

Who maintains it?

Who can change it?

Where is the authoritative source?

What rules determine whether it is complete and accurate?

How are issues identified, escalated and resolved?

The result is governance designed to support the actual lifecycle of regulated information—not governance that exists only on paper.

Data Quality & Traceability

Trusted data requires more than definitions.

We help organizations identify the controls, quality measures and traceability mechanisms needed to strengthen confidence in regulatory information throughout its lifecycle.

Regulatory Data for Digital & AI Readiness

AI increases the importance of data governance rather than reducing it.

Before regulated information can reliably support advanced analytics, automation or AI-enabled workflows, organizations need to understand whether the underlying data is sufficiently defined, governed, traceable and trustworthy for its intended use.

Adroitta helps identify those foundational gaps.

Areas of Particular Expertise

Adroitta brings especially deep experience in medical-device regulatory data, including:

Unique Device Identification (UDI)
FDA GUDID
EU MDR/IVDR and EUDAMED-related data
Global UDI requirements
Regulatory product data
Labeling data
Regulatory master data
Global data requirements
Data dictionaries and taxonomies
Master-data governance
Cross-functional regulatory data processes

Our broader methodology is designed to extend these principles across regulated life sciences.

When This Service May Be Right for You

Consider this service when:

Different functions use different definitions for the same regulatory information
Regulatory data is distributed across multiple systems and spreadsheets
Ownership or stewardship is unclear
Teams spend significant time reconciling information
Global regulatory requirements are difficult to translate into enterprise data requirements
Your organization is implementing RIM, PIM, MDM or other enterprise platforms
Regulatory data quality is limiting automation or analytics
You are preparing regulated data for AI-enabled use cases