How Many Drops Should One Van Do in a Day?

Somebody in every growing distributor eventually asks it: how many drops per van per day should we be doing? It usually surfaces just before a bigger question — do we need another vehicle? — and the honest answer to the first is that no universal number exists. An urban convenience round doing two-minute doorstep handovers and a rural foodservice route doing twenty-minute cage deliveries can both be running well at wildly different drop counts.

What does exist is a method: build the benchmark from your own geography, drop profile and day structure, compare what your routes actually achieve against it, and only then decide whether the constraint is vehicles — or the way the existing ones are being used. This article walks that method with a worked, clearly illustrative example, then lists the density levers worth testing before buying another van.

Why the benchmark must be yours

Drops per van per day is the output of five inputs, and every one of them is specific to your operation:

• Customer density — minutes of driving between consecutive stops, which is geography and routing, not effort.
• Dwell time — minutes at the door, driven by drop size, access, paperwork and whether payment is collected.
• Day structure — loading, vehicle checks, depot departures, breaks and end-of-day duties all come out of the same shift.
• Stem mileage — the unproductive run from depot to first drop and back from the last.
• Service model — a pre-sold delivery drop, a van-sales visit with selling time, and a delivery-plus-merchandising call are different jobs wearing the same word.

Borrowing another operation's number — or a figure from a vendor's brochure — imports their five inputs and tells you nothing about your own. The comparison that matters is internal: modelled capacity versus actual performance, route by route.

Build the capacity model

The arithmetic is deliberately simple — and it is only the time ceiling. Actual feasible drops are the lowest of several ceilings at once: time capacity, vehicle volume and weight, legal driving and duty hours, customer time windows and any product or vehicle constraints. Build the time model first because it is the easiest to measure, then check which ceiling binds:

Now put the model next to reality. If the route plans 23 and completes 18, the gap has a location: late departures eating the window, dwell running past the assumption, failed drops consuming stops without producing them, or a sequence that turns 7-minute hops into 12-minute ones. Each has a different owner and a different fix — a second van does not repair those underlying causes, and may only mask them.

The density levers to pull before buying a vehicle

1. Sequence the stops properly. Ordering stops well — and respecting time windows while doing it — directly attacks the inter-stop drive number. On many routes it is one of the larger levers available — measure before assuming.
2. Spread the time windows. When many customers insist on the same morning slot, the plan fills with waiting and backtracking. Renegotiating even a handful of windows can unlock stops the model says are feasible.
3. Attack dwell. Payment collected digitally rather than counted, paperwork signed on a device rather than filled in, the load arranged in drop order so the driver is not excavating — minutes per stop, times twenty stops, is a stop or two per day.
4. Cut the failure rework. A failed drop consumes a full stop cost and produces nothing, then consumes a second stop later as a redelivery. Reducing failures is a density lever wearing a service-quality costume.
5. Question the stem. Route boundaries drawn years ago often make two vans cross each other's territory daily. Redrawing route areas — or resequencing which days serve which zones — shrinks unproductive mileage without touching the fleet.
6. Check the load, not just the map. Vehicle capacity and weight can cap a route before time does; if the van cubes out at 19 drops, the time model is answering the wrong question.

Only when the modelled capacity is genuinely being achieved — and demand still exceeds it — is the extra vehicle the right answer. At that point the same model prices the decision honestly: the new route's feasible drops, its stem, and the density dilution of splitting territory.

Where RouteMagic fits

RouteMagic gives this method its two missing ingredients: a plan built on real constraints, and actuals to compare it against. The Route Planner sequences stops with capacity and weight gauges per vehicle, respects delivery time windows and vehicle attributes, and shows route time, distance and capacity before dispatch — while the optimiser does the sequencing arithmetic across whole fleets. On the road, Route Monitor tracks planned versus actual as the day unfolds — geofenced arrival detection and route history give you evidence for the dwell and drive assumptions instead of guesses — and route and driver reporting turns the model-versus-actual comparison into a standing report instead of a one-off spreadsheet. The result is the vehicle decision made on evidence: you buy the van when the data says the current ones are genuinely full.

Conclusion

There is no industry answer to drops per van per day — treat external benchmarks as context, not targets. What there is instead is a short piece of arithmetic — productive window divided by the average minutes per stop — that turns the vague question into a measurable one for each of your routes. Build it with measured inputs, compare it with actual completions, and the gap tells you whether your constraint is vehicles or utilisation. Work the six levers first: sequencing, window spread, dwell, failure rework, stem mileage and load limits are all worth testing before committing to a vehicle, its driver and its standing costs. Then, if demand still outruns modelled capacity, add the van with a clear conscience and a costed plan for it. This week's version of that work is simple: time one route's real day — departure, every arrival and departure, return — and see how wide your blue bar actually is.