InfoPlanning Data Failure2026-06-20
FAILURE: Capacity plans become mathematically correct and operationally wrong when constraints are stale
Current planning signals emphasize plan-for-every-part, production capacity, maintenance optimization and constraint-based planning. These systems remain exposed when labor, maintenance, tooling, material or yield assumptions are not refreshed and owned.
Why it matters
A planning engine can optimize only the constraints it receives. Stale assumptions can produce a technically valid plan that cannot be executed.
What leaders should monitor
- parameter age and effective dates;
- named owners for capacity constraints;
- modeled versus demonstrated capacity;
- manual overrides and local calendars;
- maintenance and tooling changes not reflected in APS or ERP.
Sources: Caterpillar and DecisionBrain.
The Dataleo angle
The affected decision is how Capacity Planning, Planning Parameters and Master Data change the operating workflow. Value requires verifiable data and constraints, explicit business ownership and measurable outcomes; the principal failure mode is adopting or automating the signal without changing the underlying decision.