Capacity in logistics is never one number. It is a moving combination of drivers, vehicles, time windows, route conditions, and operational constraints. If this is ignored, plans look good only in theory.
Article series: Dispatch → Cash Flow
Definitions
Definition: Capacity buffer
Intentionally unallocated capacity (often ~10–15% depending on season and job type) reserved for volatility: weather, driver absence, incidents, and urgent priority shifts. Without a buffer, plans degrade into daily firefighting.
Definition: Plan vs execution
A basic control loop that compares plan with reality over time (what should be done vs what is done) and highlights deviations and causes — not just “how much was planned”.
Why capacity plans fail
A common mistake is converting weekly demand directly into fixed daily allocation. In reality, conditions shift daily, weather, driver absence, urgent customer changes, loading constraints.
Practical capacity control model
Plan across horizons (day, week, rolling 14 days).
Separate must-deliver commitments from flexible windows.
Maintain an exception buffer by season and job type, usually around 10-15% of capacity.
Track plan-vs-execution, not just planned volume.
How to handle priorities
Priority needs formal logic. If one urgent order changes the plan, teams should see exactly what was displaced and how SLA exposure changes, often within the next 24-48 hours.
Where custom development and AI help
Custom solutions are often useful for:
what-if dashboards for scenario testing
prioritization rules balancing margin, SLA, and availability
alerts for overload and deadline risk
AI can support delay probability signals, but decision rules should remain transparent and accountable.
Operational takeaway
Capacity planning is not a static spreadsheet target. It is a dynamic control system built for uncertainty.
Recommended next reads
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