Route density benchmarks for fuel distributors: are your trucks full enough?

Why route density varies

Route density in fuel distribution is driven by two variables: how full the tank is when the delivery happens, and how geographically consolidated the stops on a route are. The first variable — tank fill level at delivery — is the one most directly under the distributor's control, and the one most affected by whether fill levels are monitored or not.

In a reactive operation, deliveries happen across a wide range of fill levels. Some customers call early. Some call late. Some are on calendar-based schedules that do not match their actual consumption pattern. The result is a delivery mix where tank utilisation at the point of delivery is highly variable — and the average is lower than it would be if deliveries were timed to actual fill level thresholds. Low average fill level at delivery means more trips for the same total volume. More trips means more kilometres per litre delivered. Route density falls.

What the data shows

Modelling based on real order data from a large-scale diesel distribution operation — using actual delivery records across a regional network — quantified the route density gap between the operation as it ran reactively and how it would run under level-based delivery planning.

The results for diesel distribution: km per cubic metre delivered: 3.50 before → 1.65 after (−53%) — the same volume delivered across fewer kilometres. Total route distance: 10,200 km → 4,800 km across the same delivery period. Tank utilisation: 58% → 72% — deliveries happen at higher fill levels on average. Tours: 89 → 83 — fewer routes required for the same delivery volume. Savings per tank per year: €155 at 80% network coverage.

A separate cross-vertical analysis of FoxInsights partner operations shows a −37% reduction in km per litre delivered across diesel, heating oil, and lubricant distribution accounts. The specific figure varies by operation, geography, and customer mix, but the direction is consistent: level-based delivery planning produces substantially higher route density than calendar or reactive models.

The tank utilisation benchmark

Tank utilisation at point of delivery — the fill level when the truck arrives — is the underlying driver of route density. The data places the reactive benchmark at approximately 58% and the optimised benchmark at 72%. That 14 percentage point gap translates directly into trip frequency.

A tank consistently delivered at 70% fill level needs roughly 30% more deliveries over a year than the same tank delivered consistently at 90% fill level — for the same total volume. Across a network of hundreds of accounts, that difference in trip frequency is the primary determinant of total route distance and logistics cost. Without fill level monitoring, most distributors are operating in the 55–65% utilisation range for reactive accounts.

What improving route density requires

The path from a 58% utilisation model to a 72% model is straightforward in principle: replace reactive or calendar-based delivery triggers with level-based ones. In practice, this means daily fill level data for each tank in the network, a platform that projects delivery timing based on consumption models rather than schedules, and a dispatch workflow that plans from a fill-level service queue rather than a calendar.

The geographic consolidation variable improves as a consequence. When the dispatch team plans from a service queue of tanks approaching threshold, it can group geographically proximate tanks that are ready on the same day. The AI dispatching assistant in FoxInsights combines fill level data, consumption patterns, geographic clustering, and seasonal variation to generate route suggestions — further improving route density beyond what fill level data alone produces.

The cost per litre calculation

Route density improvements translate directly into cost per litre delivered — the metric that matters for distribution margins. If your operation currently delivers at 3.50 km/cbm and your all-in logistics cost per kilometre is known, the cost per litre of that logistics overhead is calculable. The same calculation at 1.65 km/cbm shows what the logistics cost floor is under level-based planning.

For most distributors, the gap between current and optimised route density represents the single largest addressable cost reduction available without changes to fleet size, geography, or customer base. The trucks, the drivers, and the customers are the same. What changes is the information on which delivery decisions are made.