Discovery to Optimize.
Gated, not hoped.
Discovery, Design, Build, Deploy, Optimize. Nothing moves forward until the gate is met and operations signs it.
We spend the two weeks on the floor with your operators and supervisors. You get a read on where connectivity and master data actually stand, what the losses cost per year, and which site should go first.
Shopfloor walkthroughs
Gemba walks with operators and supervisors, on every shift pattern you run.
Maturity assessment
Connectivity, data quality, process discipline, and readiness across candidate sites.
Value-case framing
What the program is worth, in operational terms an Operations Director will defend.
Lighthouse selection
We score candidate sites on complexity, connectivity and readiness, then agree the shortlist with operations.
Master data decides what the system can do for the next decade. In these four to six weeks we model equipment, materials, BOMs, recipes and lot logic to a level an engineer can build from directly.
Functional requirements
Documented to the level needed for build — screens, rules, exceptions, integrations.
Master-data design
Modeled once at the lighthouse site so wave two doesn't need a redesign.
KPI definition
Every KPI gets a written formula and a data source before anyone builds a screen.
Architecture & template
We fix the integration contracts with ERP and the machines now, so Build has nothing left to negotiate.
Your chosen platform configured against the spec, machines connected, ERP integrated — and tested with real production data before anyone calls it done.
Platform configuration
Core template built and configured on TrakSYS or AquiWeb — workflows, screens, events, quality.
Machine connectivity
We pull the tag list during Design, so connectivity work starts on day one of Build.
Enterprise integration
ERP, LIMS, WMS, CMMS — bidirectional, with master-data alignment.
Test with real data
Full order-to-genealogy runs on a copy of last month's production.
Go-live is an operational event, not an IT event. We commission line by line, train at the station, manage MES validation requirements where applicable, and stay through hypercare until the site runs without us.
Commissioning
Line-by-line cutover with rollback criteria defined before we start.
Operator training
At the station, on live orders, on each crew's own shift.
Go-live support
Floor presence through the first full production cycles, every shift.
Hypercare
Daily triage, same-week fixes, and a weekly adoption number pulled from the system's own transaction logs.
Once the system is live, the loss tree is real and daily management has something to run on. Improvements made here go back into the global template under change control, so wave two starts from a better version than wave one did.
OEE & loss routines
Daily management run off losses the machines attributed themselves, at the minute they happened.
Continuous improvement
Kaizen cycles fed by execution data, with every action tracked to close in the system.
Template evolution
Improvements flow back into the global core under change control.
AI enablement
Once the event and genealogy data is clean enough: decision support, root cause, prediction.
Roughly twelve weeks
to a live first site.
That's a lighthouse factory of typical complexity. Your real timeline depends on how much connectivity already exists, what state master data is in, and how many systems need integrating. Wave sites after the first run faster because the template is proven. Discovery gives you the real number.
Adoption is the deliverable.
A configured system nobody uses is a failed project with good documentation. We measure operator adoption, not just uptime.
We stay until it runs without us.
Hypercare ends on evidence, not on a date. The exit gate is a site that no longer needs us in the room.
Honest gates, even when it hurts.
If a gate isn't met, the phase isn't done, and we'll say so on the steering call. Slipping a week beats living with a broken master-data model for a decade.
Every program starts with a 30-minute conversation.
One operational pain point, an honest read on what it would take to fix it. If we're not the right fit, we'll say so.