Normalized OEE across plants — so debates start from a shared definition of availability and performance.
— TYPICAL TIMELINE
8–14 wk
— TEAM SIZE
3–5 ppl
— STARTING POINT
Plant data audit
— DELIVERS
Shift dashboards
WHAT WE FOCUS ON
Domain depth, not template playbooks.
Supply chain, quality, and shop-floor intelligence — from sensors to decision dashboards.
TYPICAL SCENARIOS WE SOLVE
The shapes of work we keep seeing.
Challenge & how we help
SCENARIO / 01
OEE and downtime truth
— Challenge
Downtime reasons are inconsistent; OEE debates stall because each plant measures differently.
— How we help
Normalized time-series and batch logic, downtime root-cause views operators trust, and shift dashboards aligned to a single definition of availability and performance.
SCENARIO / 02
Supply disruption response
— Challenge
Forecasts break when suppliers slip and alternate sources are invisible until stockouts hit.
— How we help
Supplier performance analytics, scenario planning prototypes, and integrated visibility across tiers where your data allows — pragmatic, not theoretical.
SCENARIO / 03
Quality and traceability
— Challenge
Recalls and audits are expensive when batch genealogy lives in ad hoc spreadsheets.
— How we help
End-to-end traceability data models, quality analytics, and reporting that support both continuous improvement and regulator-ready evidence.