Data Governance for manufacturers. Lineage from MES to BI, plant-floor data quality, regulatory traceability, and Copilot-safe metric definitions.
Material master, equipment master, BOM, and supplier hierarchies typically run as a separate MDM workload (Stibo, Informatica, or Salesforce Data Cloud depending on the stack). We build the analytics-side governance that integrates with the MDM source of truth.
Classified spend, clean supplier master, and contract metadata are the prerequisites. The work usually takes 3 to 6 months to land cleanly before any AI procurement tool produces reliable category recommendations.
First useful phase (top 20-30 assets cataloged, owners assigned, quality SLAs defined) lands in 90 to 150 days. Full enterprise rollout typically 18 to 30 months across plants and functions.
No. Documents without operational enforcement do not change behavior. The work is the operating model: named owners, defined SLAs, monitoring posture, and the change-management pattern that prevents drift. The documents follow from the operating model.
Time-to-trust for new analytical use cases, time-to-resolution for data quality incidents, and the metric-consistency rate across downstream consumers. We instrument these from day one of the engagement.
, and the data and AI work we ship is designed to hold up under their review.