01
Workflow first
Model the journey, state changes and operator handoffs before introducing prediction.
CASE STUDY / LOGISTICS
Put logistics decisions inside the workflow.
The design connects shipment and event data to workflow state, prediction, operational decisions, exceptions and visibility. AI is one component of that operating flow.
THE OPERATING PROBLEM
Logistics execution is a chain of decisions.
Load creation, pricing, dispatch, route choices, ETA changes, documentation and exception handling are interdependent. The platform has to preserve that context across handoffs.
02
Decision support
Use prediction where it can inform ETA, route, load or exception decisions.
03
Exception management
Surface deviations early and route them into the appropriate operational response.
AI INSIDE THE DECISION
Prediction only matters when the system knows what happens next.
01Workflow state
02Relevant data
03Prediction
04Action / exception
CONTEXT TRAVELS
Prediction is part of the operating flow.
The prediction is useful only when it has workflow context and a defined path into the next operational decision.
01
Data
Shipment, event and operational inputs enter a common decision flow.
02
Workflow
Current state defines the context for decisions and prediction.
03
AI
Prediction supports a defined operational decision rather than sitting beside the workflow.
04
Orchestration
The decision triggers the next action, escalation or exception path.
05
Visibility
Operators see the state, exception and required response in one operating view.
SEE THE SYSTEM
Follow the context from data to operational response.
The case study traces how data moves through workflow, prediction, orchestration and exception handling.
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