Foundation data: You Can’t Govern What You Can’t See

Why This Matters

You can have the best Discovery tool in the world, but if your location data is a mess, the results won't help anyone. Discovery depends on having stable, structured foundation data—companies, departments, locations, users. Yet these are often held in disconnected systems, maintained by different teams, and updated without clear governance.

What happens next is predictable. Discovery pulls in configuration items that can’t be matched. Business rules fail. Service mapping becomes fragile. People stop trusting what they see. And the promise of CMDB visibility fades.

This research focuses on the people and process work required to make Discovery and foundation data useful. It’s not just about credentials or mid server setup. It’s about getting agreement on what data matters, who owns it, how it's maintained, and how other systems plug in.

Research Questions

• What roles are essential to own and maintain foundation data structures?

• How are teams agreeing on what becomes the single source of truth for locations or departments?

• What behaviours, meetings, or approvals help secure buy-in across functions?

• How are Discovery efforts sequenced with CMDB governance and service mapping?

• What happens when foundation data is added manually, and who controls the rules?

• How are successful organisations sequencing CMDB and Discovery rollout?

• What patterns show up in failed or abandoned Discovery attempts?

• How do service mapping and discovery tooling depend on each other?

• Who is responsible for data quality, and how is that responsibility managed?

Scope & Boundaries
In scope: Discovery enablement, foundation data setup and maintenance, data ownership, process alignment
Out of scope: Event management, monitoring tools, and Discovery tools not connected to the ServiceNow platform

Methodology
We will review Discovery project artefacts, CMDB health dashboards, and foundation data governance documentation. Interviews will include platform teams, business owners, application teams, and data stewards. Contributions will be analysed for patterns around trust, ownership, and real-world friction.

How to Contribute
Have you tried to make Discovery land in an organisation where nobody agreed on the location hierarchy? Or inherited a CMDB that no one trusted? Your experiences can guide others. We welcome stories, screenshots, governance decks, and informal lessons. We can keep it anonymised. Contact me via LinkedIn: Laila Edge | LinkedIn

Anticipated Outputs and What Good Looks Like

• A process map for aligning departments around shared foundation data

• Guidelines for who can create or edit location entries, and how to keep them clean

• A sequencing model showing when and how to introduce Discovery and build trust

• Role-based guidance for getting buy-in from data owners and process leads

• Visual models of what good CMDB visibility looks like when foundation data is stable

• Insights on how different departments influence and resist shared data models

• A visual model showing the sequence from foundation data to useful Discovery outcomes

• Clear, role-based guidance for ensuring data quality from the start

• Examples of failure patterns, with early warning signs

• A definition of “mature Discovery” based on platform and process readiness

• Checklist of preconditions for Discovery to deliver value

Status & Timeline
Status: In data gathering and contributor phase
Expected synthesis: January 2026

Insights That Help You Deliver

Independent insights, real-world case studies, and lessons from ServiceNow implementations. Practical, research-backed content to help you build readiness, align stakeholders, and drive adoption.

Email sent once a week. We care about your data in our privacy policy.