Service
Service
Data & CRM Strategy and Advisory
A roadmap your finance team can defend.
Most Salesforce and AI roadmaps fail on sequencing rather than ambition. We align the direction, order the work by dependency and evidence, and put a business case behind it that survives contact with a budget review.
- Sequenced by dependency
- Costed, including consumption
- Operating model included
- Written for a budget review
Advantage:
Tangible Outcomes
Agentforce · Data · Salesforce
Almost every organisation we meet already knows roughly what it wants from Salesforce and AI. What is missing is the order — which foundation has to exist before the visible thing can work, and what each step costs to run once it is live.
We work through the current estate, the constraints nobody wants to raise, and the dependencies between the things on the wish list. The output is a sequence, a cost, and an operating model for who owns what afterwards.
Scope
How we advise
Current-state assessment
An honest read of the estate: what works, what is held together by one person's knowledge, and which assumptions are no longer true.
- Platform, data and integration review
- Technical debt and single points of knowledge
- Process reality versus documented process
- Constraint and risk register
Opportunity shaping
Turning ambitions into candidate initiatives with enough definition to be compared — scope, dependency, effort and expected effect.
- Candidate initiative definition
- Dependency mapping
- Effort and complexity sizing
- Comparable scoring across initiatives
Business case and consumption cost
A case that includes what the thing costs to run — credits, licences, support — because that is where roadmaps quietly break.
- Benefit baseline and measurement plan
- Build cost and run cost separated
- Credit and licence implications
- Sensitivity on the shakiest assumptions
Sequenced roadmap
A dependency-ordered plan with decision points, so the programme can be stopped or redirected at known moments rather than mid-build.
- Dependency-ordered phasing
- Explicit go / no-go decision points
- Foundation work made visible, not hidden
- Realistic capacity assumptions
Operating model and governance
Who owns the platform, who approves change, how agents get reviewed, and what the team needs to be able to do without outside help.
- Ownership and decision rights
- Change control and release cadence
- Agent review and approval process
- Capability gaps and hiring or upskilling
How an advisory engagement runs
Step 1
Listen
Interviews across business and technology to surface the real constraints and the disagreements worth resolving.
Step 2
Assess
Review the estate, the data foundation and the current commitments against what the ambition requires.
Step 3
Shape
Define and score candidate initiatives, map dependencies, and cost both build and run.
Step 4
Agree
Land the sequence, the decision points and the operating model with the people who have to deliver it.
What good looks like
What you get from advisory work
An agreed sequence
Work ordered by dependency and evidence, with the foundation work visible rather than assumed.
Run cost in the case
Consumption and licence cost included from the start, so the business case still holds in year two.
Named risks
The constraints and dependencies stated plainly, including the ones that are politically awkward.
Clear ownership
Decision rights and platform ownership settled before delivery starts, not negotiated during it.
Decision points
Defined moments to continue, redirect or stop, with the evidence each one needs.
A plan that can change
A roadmap built to be revised as evidence arrives, rather than defended past its usefulness.
Bring us the roadmap you cannot get agreement on.
A short advisory engagement usually resolves the sequencing argument faster than another round of internal workshops.