Deadhead Repositioning Decisions: What a Small Fleet Should Measure

Research question: Which evidence helps a small trucking fleet decide whether an empty repositioning move improves the next-load opportunity, rather than merely adding miles to a dashboard?

Why empty miles need a decision record

An empty move can be sensible when it places equipment near a known pickup, protects a committed customer, or returns a driver toward home. It can also be a poor choice when the next load is speculative, the timing is uncertain, or the move consumes available hours and fuel. A deadhead percentage alone cannot explain the decision. This report studies the quality of the decision record, not profitability, a lane quote, or a forecast of freight rates.

The research unit

Use one completed trip leg as the unit and choose a period that includes both accepted and declined repositioning opportunities. For each leg, record origin, destination, equipment type, loaded miles, empty miles, dispatch timestamp, pickup window, known next-load status, fuel and toll observations where available, driver hours constraints, and the reason for the move. Keep the original dispatch record and distinguish an estimate from a final result.

For each decision, compare the information available at decision time with what became known later. This prevents hindsight from making a reasonable choice look foolish or a lucky outcome look like a sound process. Calculate empty-mile share and time-to-next-load only for records with defined endpoints. Report missingness, canceled loads, and out-of-network work separately.

Three kinds of evidence

Operational evidence describes what happened: the truck departed empty at a stated time, covered a stated distance, and arrived within or outside a window. Commercial evidence describes what was known: a confirmed tender, a broker conversation, a customer commitment, or an unverified board posting. Resource evidence describes constraints: remaining driver hours, equipment fit, maintenance status, and planned home time. Mixing these categories creates a false appearance of certainty.

A dispatch support specialist can assemble the decision packet, compare the planned and actual sequence, and flag missing assumptions. The fleet owner or authorized dispatcher decides whether a move is acceptable. A clerical record should not become a guarantee that a future load will materialize or an instruction that compromises hours-of-service compliance.

A decision matrix with humility

Classify repositioning opportunities as confirmed next load, probable opportunity with named evidence, exploratory move, or return/home move. Then record the alternative that was available: wait, remain in place, decline, or seek a local load. The useful question is not “did the truck earn more?” when the necessary cost and revenue data are absent. It is “did the record show why this move was chosen and what risk was accepted?”

For a monthly review, show loaded miles, empty miles, empty-mile share, hours between delivery and next pickup, canceled or changed opportunities, and fuel or toll data coverage. Avoid publishing an industry benchmark from one fleet. A high empty-mile share may reflect equipment relocation, customer commitments, or a seasonal lane pattern. Context is part of the result.

External sources and what they cannot prove

The Bureau of Transportation Statistics publishes freight transportation data that can frame national movement patterns but cannot predict a specific carrier’s next load (BTS Freight Transportation). The Federal Highway Administration discusses freight planning and network performance at system level, useful context for route constraints rather than a local dispatch answer (FHWA Freight Management and Operations). The Federal Motor Carrier Safety Administration’s hours-of-service rules define important driver-time constraints that must remain in the decision record (FMCSA Hours of Service). None of these sources supplies a lane rate, a guaranteed tender, or a profitability result.

A narrow pilot

Test a single rule: no discretionary repositioning is marked “confirmed” unless the packet contains a named load, pickup window, equipment fit, and an authorized source. Compare the completeness of decision records and the number of last-minute reversals during the pilot. Do not assume fewer reversals mean better financial performance; that requires a separate cost and revenue analysis.

Weather, customer changes, driver preferences, deadhead definitions, and fuel-price movement can alter the result. A small fleet may not have enough comparable lanes to make a fair before-and-after comparison. Keep the method transparent and allow a reason code for exceptions. If a driver reports a safety or hours concern, that concern takes precedence over an optimization target.

Limitations

Future-load information is often incomplete, and dispatch conversations may not be retained. Telematics can measure distance but not the commercial reason for a move. Cost allocations can also be arbitrary when a truck serves multiple trips. These limitations make the record valuable precisely because it exposes assumptions. They also prevent a local study from being marketed as a universal rate or margin benchmark.

The study should preserve the decision snapshot even when the result is favorable. A later load acceptance can make an exploratory move appear preplanned, while a cancellation can make a documented commitment look irrational. Keeping the original evidence and the later outcome in separate fields is the simplest safeguard against hindsight bias and gives the fleet a fairer basis for improving dispatch judgment.

Evidence-led conclusion

The best deadhead study explains the decision using evidence available at the time: next-load certainty, timing, equipment fit, driver constraints, and alternatives. Broad freight and safety sources provide context, but only the fleet’s preserved dispatch records can show whether its decisions were legible and reversible. Measuring the decision process first gives a small carrier a safer improvement target without promising a future load, rate, or financial outcome.