From recommendation to outcome, in real operations
Each story follows one difficult decision through ConstraintFlow — the context it required, how it was evaluated, how people stayed accountable and what the outcome taught the operational model. Numbers appear only once they are verified and customer-approved.
- Context
- Decision
- Action
- Outcome
- Learning
Cross-site scheduling at a multi-plant packaging manufacturer
An 11-plant packaging network placed orders across sites using experience and spreadsheets, with no shared view of the true landed cost — setup, run and freight — of running an order at one plant versus another.
ConstraintFlow was deployed on the customer's own cloud and validated on live orders against the customer's expert schedulers before go-live. Every recommendation is tracked — accepted, adjusted or rejected, with reasons — and compared against what the floor actually executed.
Results are published here once verified and customer-approved: setup hours avoided · schedule acceptance rate · execution variance · throughput impact · customer commitments protected.