The schedule changes frequently, variance causes remain disputed and decisions arrive after capacity or material has been lost.
EMS Industry suite
How to connect ERP, production, quality and maintenance without disrupting the plant
Build decision continuity across demand, materials, capacity, execution, quality, maintenance and cost.
For: Industrial, plant, production, maintenance, quality, finance and IT leadersWhat to clarify before discussing a solution
How can feasibility and variance become reliable without overloading shop-floor reporting?
The answer does not lie in an isolated feature: it is built by connecting rules, actors, data and evidence.An industrial flow governed by useful events, a consistent data model and deployment waves compatible with plant cadence.
Four decisions to make before configuration
These decisions make the scope testable and prevent structural choices from being discovered during the project.
Set the useful planning horizon and granularity
The decision must specify the rule, its owner, the required data and the evidence used to accept it.
Define the minimum declarations that explain variance
The decision must specify the rule, its owner, the required data and the evidence used to accept it.
Choose the batch genealogy that is genuinely needed
The decision must specify the rule, its owner, the required data and the evidence used to accept it.
Connect maintenance and production schedule through criticality
The decision must specify the rule, its owner, the required data and the evidence used to accept it.
A readable end-to-end flow
Scope is not a list of modules. It is a chain of events, ownership and decisions.
1Demand and schedule
2Materials and capacity
3Execution and WIP
4Quality and traceability
5Asset reliability
In the first scoping
- One representative flow and its useful variants
- Authoritative events and minimum data
- Roles, decisions and escalation times
- Acceptance criteria and baseline measurement
To sequence in waves
- Additional sites, activities or populations
- Rare variants that do not condition the pilot
- Automations whose rule is not yet stable
- Advanced dashboards after source reliability
To decide explicitly
- Set the useful planning horizon and granularity
- Define the minimum declarations that explain variance
- Choose the batch genealogy that is genuinely needed
- Connect maintenance and production schedule through criticality
From direction to measured improvement
- 1Navigator
- 2Personalised review
- 3Scoping workshop
- 4Wave-based deployment
- 5KPI measurement
Each stage produces a decision or evidence reusable in the next. Deployment remains business-led and verifiable.
Measure to decide, not to fill a dashboard
Every KPI needs a definition, a source, a cadence and an associated decision.
KPIFormulaSourceDecision
OEEAvailability × performance × qualityMachine time, speed and qualityTarget the dominant loss rather than a symptom
Schedule adherenceOrders completed as planned ÷ planned ordersSchedule, orders, declarations and disruptionRebalance capacity, materials and sequencing
Work in progressValue or quantity of open production ordersOrders, consumption and declarationsReduce waiting, queues and immobilisation
Scrap rateScrapped quantity ÷ quantity producedProduction, inspections and quality causesAddress root causes by product and operation
06 · Business scenario
A pilot centred on one product family
- Situation
- A plant has rich but separate planning, production, quality and maintenance data. Meetings are spent reconciling figures.
- Approach
- One representative product family becomes the pilot scope. Teams align bills of material, events, variance causes and decision routines before extending the model.
- Target outcome
- Management focuses on actionable losses and expansion relies on a proven model.
Useful answers before the first discussion
01Where should we start in practical terms?
Choose a representative scope spanning “Demand and schedule” and “Materials and capacity”, then document one normal case and one frequent exception. The first flow should be important enough to matter but contained enough to observe end to end.
02Do all existing systems need replacing?
No. Scoping starts with decisions, authoritative events and ownership. It then determines what should be retained, integrated, replaced or simply better governed, wave by wave.
03What data should be prepared before a workshop?
Prepare a few real cases, the volumes shaping the operation, the main variance reasons and the sources used to measure OEE. The quality of examples matters more than the quantity of documents.
04How should the right pilot scope be chosen?
Choose a scope with an available owner, accessible data, a meaningful exception and a measurable outcome. Avoid both an overly simple case that proves nothing and an overly broad scope that dilutes learning.
05How can scope changes during the project be limited?
Make assumptions, interfaces, variants, exceptions and acceptance criteria explicit. Every new request can then be classified: essential to the wave, suitable for a later wave, or outside the objective. Discussion focuses on impact rather than intuition.
Next step
Turn this guide into a personalised review
Complete Navigator to position your context, then use the review as the starting point for a scoping workshop.
- 1Navigator
- 2Personalised review
- 3Scoping workshop
- 4Wave-based deployment
- 5KPI measurement
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