- The ERP planning-actuals gap — where production plans assume theoretical capacity but actual production runs at real capacity — is the single biggest source of schedule misses and cost overruns in manufacturing.
- AI bridges this gap by feeding real production performance data back into ERP planning logic, replacing theoretical assumptions with actuals.
- FactoLake connects to SAP, Oracle, and other major ERPs without replacing them — adding real-time shop floor intelligence to systems manufacturers already have.
Your ERP thinks your machines run at 100% efficiency. Your plant knows they don’t.
ERP production planning modules calculate schedules, material requirements, and capacity utilisation based on standard times and theoretical machine speeds. These numbers were set during system implementation, possibly years ago, and rarely updated as machines age, products change, or staffing fluctuates.
The result: ERP says a production run should take 8 hours. Shop floor reality says 11. The difference is the planning-actuals gap — and it’s the root cause of most delivery date misses, overtime cost surprises, and inventory discrepancies that manufacturing businesses experience.
AI’s role in ERP integration isn’t to replace the planning logic. It’s to feed real performance data into that logic so plans reflect factory reality.
Simply connecting shop floor data to ERP without cleaning and contextualising it first creates worse planning, not better. Raw machine data without production context (which order, which product, which shift) is noise in an ERP planning model. The integration layer matters as much as the data.
What AI+ERP integration actually delivers
Accurate capacity planning: ProdIQ continuously updates actual OEE by machine — giving ERP’s capacity planning module real available capacity numbers rather than theoretical ones.
Real-time schedule feedback: When FactoMES detects that a production order is running behind, the ERP production schedule can be updated automatically — without waiting for an operator to manually report the exception.
Demand-driven maintenance scheduling: MaintIQ predictions can be surfaced in ERP as planned maintenance work orders, enabling capacity planning to account for upcoming maintenance windows rather than discovering them during scheduling.
The integration approach
FactoLake provides the bidirectional bridge between shop floor systems (SCADA, MES, PLCs) and ERP systems (SAP, Oracle, Microsoft Dynamics). Shop floor actuals flow upward to correct ERP planning assumptions; ERP production orders and demand signals flow downward to drive MES scheduling.
Frequently Asked Questions
FactoLake includes pre-built SAP connectors for PP, PM, and QM modules that cover the most common integration scenarios. Complex SAP landscape configurations (multi-plant, multi-ERP) benefit from SAP expertise during design, but the integration itself doesn’t require custom ABAP development.
No — the integration reads from and writes to ERP via standard APIs. It doesn’t modify ERP core configuration or run processes inside the ERP system itself.
When AI-derived real capacity differs significantly from ERP standard capacity, the system flags the discrepancy for human review rather than silently overwriting ERP values. Standard times in ERP are updated through a controlled change process, not automatically.
Related: SCADA vs MES vs ERP · AI + MES · AI Agents for Production Planning