Assessment 01 · Operational truth
Factory Data Reliability & Operational Truth Assessment
Determine whether production, downtime, quality, historian, MES, ERP and related operational records can be trusted, explained and reconciled.
What we examine
Focused enough to act on.
The exact scope is shaped during pre-engagement. The assessment is designed around the operating question, not a fixed technology checklist.
- Critical production and operational records across relevant systems
- Timestamp, identity, lot/batch, state, quantity, quality and event consistency
- Historian, MES, ERP, QMS/LIMS, SCADA or database evidence paths where in scope
- Master/reference data alignment and system-of-record assumptions
- Known manual corrections, reconciliation workarounds and reporting dependencies
- Sampling of selected evidence chains from source event to reported outcome
What you receive
Decision-ready outputs.
Deliverables help leadership, engineering, operations and technology teams agree on the current state and the next move.
Operational truth traced from source event to reported outcome.
Where records reconcile, where they do not, and why.
Data-quality and ownership risk with severity and evidence.
Priority failure modes and root-cause hypotheses.
Near-term containment and structural actions, sequenced.
When this is useful
Common signals.
These patterns indicate where the assessment is likely to pay for itself.
- Production reports regularly require manual correction
- Downtime differs between systems or teams
- Lot, batch, genealogy or quality evidence is difficult to defend
- Historian and MES data disagree
- ERP quantities do not reconcile to operational records
- AI or analytics programs are planned but source-data trust is uncertain
What happens next
Turn disagreement into a defensible evidence model.
An assessment can stand alone or become the baseline for architecture, remediation, implementation, training or ongoing assurance.