CMDB Excellence
A CMDB nobody trusts is worse than no CMDB at all.
Every downstream service -- incident routing, change impact, cost allocation, AI -- relies on accurate configuration data. When it's wrong, everything built on top of it is wrong too. We assess, model, remediate, and govern.
The real problem
It's not that you don't want a good CMDB. It's that nobody could show you where to start.
CMDB is one of those things where the theory is well understood and the execution consistently fails. Not just for the organisations trying to run it -- for the consultants trying to implement it too.
The barrier is usually the same: CSDM feels abstract until you see it mapped to something you actually recognise. Once you see your services, your stack, your teams reflected in a model, the path forward becomes obvious. Getting there is the hard part.
We built an AI-assisted approach that produces that model fast -- grounded in your deployed stack and your context, not a generic diagram. It's how we get organisations unstuck quickly, and it's how we get buy-in from teams who've been sceptical of CMDB projects before.
Why CMDB projects fail - The same four problems, every time.
Understanding why your CMDB is unreliable is the first step to fixing it.
- No data model before Discovery ran. Discovery finds everything. Without a model deciding what matters and why, it fills your CMDB with noise. The CI count grows; the trust doesn't.
- No ownership of CI lifecycle. Data goes stale the moment a server is decommissioned and nobody updates the CMDB. Governance is what keeps data accurate between projects.
- CSDM felt too abstract to start. The Common Service Data Model is well-documented but hard to apply. Most teams can't see how it maps to their services -- so they don't start at all.
- No dedicated config manager. CMDB needs ownership. Most organisations don't have a config manager, so it drifts by default. We hold that function as part of the service.
Our approach - Assess. Model. Remediate. Govern.
In that order, every time. The sequence matters -- you can't govern what you haven't modelled, and you can't remediate what you haven't assessed.
01
Assess
Platform maturity assessment against ServiceNow best practice. We find what's unreliable, what's missing, and what's creating noise downstream -- in incidents, changes, and AI features that depend on clean data.
02
Model
AI-assisted CSDM service modelling in the context of your deployed stack and your services. Not a generic diagram -- a model that resonates with your teams and reflects how you actually deliver.
03
Remediate
CI class hierarchy design, data model rationalisation, Discovery configuration, and reconciliation rules. We fix the structure first so the data has somewhere clean to land.
04
Govern
Governance framework with CI lifecycle ownership, ongoing quality metrics, and a remediation playbook your team can follow. A CMDB without governance returns to chaos -- we prevent that.
AI-assisted service design
A CSDM model that reflects your reality.
Most CSDM modelling still happens the traditional way -- whiteboarding sessions, offline design work, and separate review meetings before a diagram exists anyone can react to. Ours works differently: the model is produced in the context of the services your team already owns, so you can visualise it instantly instead of waiting on the workshop cycle.
That matters at scale -- when there are 1,600 services to model, producing concepts instantly instead of one whiteboard session at a time is a large time saving. When the model reflects the services your teams run every day, agreement comes faster and implementation follows.
What's delivered
- Platform maturity assessment against ServiceNow best practice
- AI-generated CSDM service model in context of your deployed stack
- CI class hierarchy design and data model rationalisation
- Discovery agent configuration and reconciliation rules
- Governance framework with CI lifecycle ownership
- Ongoing quality metrics and remediation playbook
- Monthly CMDB review (included in Platform Excellence retainer)
FAQ - Common questions.
Things people ask before they start a CMDB engagement.
- Our CMDB is a mess. Where do you even start?
- With an assessment. We need to understand what's there, what's reliable, and what everything downstream depends on. The assessment gives us a prioritised remediation plan -- we don't touch data we haven't understood first.
- What makes your CSDM approach different?
- We model in context. Our AI agent produces a CSDM diagram grounded in your deployed stack and your services -- not a blank template. When the model reflects what your teams actually recognise, it's far easier to get buy-in and move forward.
- We don't have a dedicated config manager. Is that a problem?
- It's very common. Governance is part of what we deliver -- we establish the framework, the ownership model, and the review cadence. For clients on the Platform Excellence retainer, monthly CMDB review is built in so the data stays reliable over time.
- How does CMDB connect to AI features in ServiceNow?
- Directly. AI triage, Now Assist, impact analysis, and cost allocation all depend on accurate CI data. A CMDB nobody trusts means AI features nobody trusts. Getting the data right is the prerequisite for AI that actually works.
- Can we start with CMDB and move to Platform Excellence later?
- Yes. CMDB Excellence is a standalone engagement. If you later want ongoing architecture support, CMDB governance is already built into the Platform Excellence retainer.
Ready to make your CMDB trustworthy?
Start with a platform assessment. We'll tell you exactly where your CMDB stands, what's causing the unreliability, and what a realistic fix looks like.
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