Running a ten-wheeler at half capacity burns margin on every kilometre — yet many Bangladesh depots default to largest available truck because “it is free now” or because warehouse loaded early without volume plan. Under-utilization hides in daily habit until route profitability review reveals lanes that never cover diesel, let alone fixed cost.
Right-sizing is not always smaller vehicle — sometimes it is combining stops, deferring partial load until second cut-off, or refusing dispatch that fills cube but not weight for dense cargo. Load planning connects fleet desk, warehouse, and commercial pricing — not warehouse alone.
Measure fill rate consistently: tonnage, volume, or pallet count versus capacity — pick one primary metric per cargo type and track weekly. Without measurement, utilisation debates stay subjective.
Warehouse management systems and fleet dispatch often live in separate silos — a daily ten-minute stand-up between warehouse shift lead and dispatch supervisor prevents “truck is here but load not ready” partial dispatch. For cement and bulk cargo, weight bridge data should feed load confirmation before gate release; cube-only planning fails for dense product. Commercial team needs visibility into average fill achieved when negotiating next season rates — ops data is sales defence against underpriced lanes.
Under-utilisation often peaks Monday and post-holiday when warehouse backlog clears unevenly — anticipate with staggered vehicle call-up rather than sending full fleet to gate at once.
Define load types and vehicle class matching rules
Publish which cargo fits which vehicle class — ops should not guess each morning under client pressure. FMCG cartons, cement bags, reefer pallets, and machinery each have mapping document updated when fleet mix changes.
Dispatch override above class requires supervisor code and reason — overrides tracked weekly reveal client or warehouse pressure patterns.
- Cargo category to vehicle class matrix posted at dispatch
- Override log reviewed weekly with commercial impact
- New client lanes assessed for class fit before first trip
Measure fill rate and partial load frequency
Weekly report: average fill percent by route template and vehicle class. Templates below threshold two weeks trigger redesign — combine stops, shift cut-off, or reprice. Partial emergency dispatches counted separately; high count indicates warehouse schedule problem.
Combine compatible stops and clients
Same zone, compatible product (no cross-contamination), same temperature band for reefer — combination rules reduce partial loads without heroic dispatcher memory. Commercial must approve client mix where contract exclusivity applies.
Coordinate warehouse cut-off with fleet plan
Late loading forces small emergency trucks because client window cannot wait for full load build. Loading schedule is fleet problem — joint daily plan between warehouse supervisor and dispatch reduces split shipments.
Right-size return and backhaul legs
Do not send large unit empty to fetch small next load if smaller vehicle can backhaul economically. Backhaul opportunity board visible to dispatch — empty return km ratio KPI supports this habit.
Price contract lanes for actual utilisation achieved
Commercial quotes assuming full load while ops averages sixty percent fill erodes margin permanently. Rate review uses achieved fill data — not theoretical truck capacity on proposal slide.
Load planning meeting cadence
Daily fifteen-minute load review between warehouse and dispatch before morning assignment — today’s outbound volume, vehicle class plan, known partial risks. Weekly fill rate review names bottom three route templates for redesign. Commercial invited monthly to see fill trend — supports rate conversation with data.
Photograph or system-capture load height at gate for dispute when client claims under-delivery — load proof protects operator and client alike.
Commercial proposal template should include expected fill band — sales cannot promise dedicated ten-wheeler at full load rate if ops history shows seventy percent on similar lane. Fill honesty at sale prevents margin argument at month-end.
Warehouse incentive tied to ready load by cut-off — small bonus for pick team meeting dispatch window reduces partial emergency dispatch that destroys fill rate.
Common mistakes to avoid
Purchasing larger fleet because “we always need capacity” without fill analysis — often need better planning, not more metal. Blaming drivers for partial loads caused by warehouse pick sequence. Another mistake is combining incompatible cargo for fill rate — product damage costs more than empty km saved.
Do not ignore weight limit while maximising cube — overloading creates compliance and safety risk disguised as utilisation win.
Simulate fill rate impact before adding vehicle to fleet — if current routes average fifty-five percent fill, new truck may repeat pattern unless load rules change first. Capacity purchase without planning discipline duplicates under-utilisation.
Quick action checklist
- Publish cargo-to-vehicle-class matrix at dispatch desk
- Track weekly fill rate by route template
- Review override log and partial emergency dispatch count
- Align warehouse cut-off meeting with dispatch daily
- Flag route templates below fill threshold for redesign
- Include achieved fill in commercial rate review data pack
- Monitor empty return km ratio alongside fill rate
Depot gate weighbridge integration where available — declared load weight before departure feeds fill rate analytics automatically instead of estimated cube guess from dispatcher visual check alone.
Monthly leadership review of fill rate by sales region — underpriced lanes with chronic low fill trigger commercial repricing conversation backed by ops data not anecdote.
Reject informal load override without supervisor code — casual overrides erode fill discipline faster than warehouse delay.
Fill rate target published per route class gives dispatch clear goal beyond informal bigger truck habit.
Improve utilisation with load and dispatch tools on logistics transport solutions, or request a demo. Operator utilisation gains appear in case studies.