Definitions
Metrics disagree
ERP, CRM and reporting each count differently.
Services · Enterprise AI · Data & analytics
Data foundations, analytics and production AI — delivered into the workflows where someone acts on them.
01 — Challenge
Definitions
ERP, CRM and reporting each count differently.
Timing
The window to act already closed.
Delivery
A dashboard nobody opens mid-process.
Ownership
Quality, monitoring and retraining undefined.
Another dashboard inherits the same disagreement.
02 — Method
Who calls it, how we measure better.
Integration, quality, lineage, access.
Lightest method that answers it.
Where the team already works.
Monitoring, controls, feedback.
The difference between a model that runs and a decision that changes.
03 — Platform
A forecast that stops at a dashboard asks someone to go and find it.
04 — Analytics
What happened?
Why did it happen?
What is likely next?
What should we do?
05 — MLOps
Versioned. Same values train and serve.
Reproducible, lineage tracked.
Metrics, slices, fairness.
Registry with signature and deps.
Shadow → canary → full.
Drift and business outcome.
Drift- or schedule-triggered.
06 — RAG
Skipped most often: re-ranking and citation binding.
07 — Governance
Person does the work. System records it.
System suggests. Person decides every time.
System drafts. Person approves before effect.
System acts in bounds. Person samples, handles exceptions.
Self-monitors, escalates outside limits.
08 — Agents
Task arrives.
Decompose into steps.
Call a tool or API.
Read the result.
Continue, replan or escalate.
Step limits and cost ceilings matter as much as the gate.
09 — Effort
Which is why readiness comes before use-case selection.
10 — Failure modes
Data without a use case
Technically sound, commercially unanswerable.
Use case without data
Convincing in the room, blocked everywhere else.
The method exists to avoid both: decision first, readiness second.
11 — Capabilities
01
Prioritise use cases before the engineering starts.
02
Governed pipelines across ERP, CRM, cloud and operations.
03
One set of definitions behind every dashboard.
04
Anticipate, then evaluate the options.
05
Models that survive contact with production.
06
Unstructured information made usable.
07
Assistants grounded in approved sources.
08
Image and video intelligence in real conditions.
12 — Use cases
Supply chain
Sales, inventory, promotions and capacity in one model.
Risk
Signals that precede failure or delay.
Customer
Segmentation and churn from joined-up data.
Documents
Claims, contracts and invoices routed automatically.
Knowledge
Answers grounded in approved repositories.
Workflow
Forecasts and alerts inside ERP and planning.
13 — Engagement
Data, governance and use-case viability.
One decision, proven end to end.
The governed foundation and its pipelines.
We run, monitor and retrain in production.
What changes
SharperPlanning works from a model of what is coming rather than a record of what happened.
FasterOne agreed set of definitions removes the reconciliation cycle before every meeting.
EarlierRisk and exceptions surface while there is still time to act on them.
FAQ
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Start with the business problem. We can identify where data modernization, analytics or production AI creates credible value — and how that value gets measured.