The First-Attempt Delivery Rate: A Key Metric That Decides Last-Mile Profitability in 2026

Why First-Attempt Rate is the Profitability Metric

Last-mile teams track a lot of numbers, but if you had to pick one that most directly moves profit, it would be the first-attempt delivery rate: the share of deliveries completed on the first try. The reason is simple economics. A delivery completed on the first attempt costs what you planned for it. A delivery that fails and has to be attempted again costs roughly double, and it drags a chain of other costs behind it. So the first-attempt rate is not just an operational quality metric; it is close to a direct read on last-mile unit economics.

Last-mile delivery accounts for 41–53% of total logistics/shipping cost.

For a Head of Logistics under peak-season cost pressure, that makes it the highest-leverage number on the dashboard. On-time rate tells you about reliability, deliveries per hour tells you about throughput, but first-attempt rate tells you how much of your delivery spend is being wasted on second and third tries. This post breaks down why a failed attempt is so expensive, models what even a modest improvement is worth, explains why first attempts fail, and covers the levers that lift the rate.

Why a Failed First Attempt is So Expensive

A failed first attempt is not one cost; it is several, stacked. The redelivery is the obvious one: the same stop has to be routed, driven, and attempted again, consuming capacity that could have served a new order. Around it sit the extra fuel and mileage of the repeat trip, the driver time, the warehouse handling of the returned or held item, and a customer-support contact as the recipient asks where their order is. There is also the harder-to-count cost: a customer whose delivery failed is a less satisfied customer, and in competitive categories that erodes repeat business.

Gartner finds 96% of customers who have a high-effort experience become disloyal (vs 9% for low-effort).

Put a number on the direct portion and it lands at roughly $17 per failed first attempt once redelivery, wasted mileage, and handling are counted (OrangeMantra). That is per failed attempt, before the softer customer-experience costs. It is worth noting that widely quoted first-attempt failure rates (often cited in the 8 to 20% range) come from vendor and aggregator estimates rather than rigorous research, so treat the rate as an industry estimate and benchmark your own; the per-attempt cost is the more reliable anchor.

Also Read: Best Last-Mile Logistics Provider Near You: Checklist

The Cost Model: What a Few Points Are Worth

The reason first-attempt rate decides profitability is that the cost compounds with volume. A simple, illustrative model shows the scale.

Take an operation running 10,000 deliveries a day (an illustrative figure, substitute your own volume). At an 85% first-attempt rate, 1,500 deliveries fail the first attempt each day. Lift that rate by 10 points to 95%, and only 500 fail, 1,000 fewer failed attempts a day. At roughly $17 per failed attempt, that 10-point improvement is worth about $17,000 a day in avoided direct cost. Across a year of operations, that is in the range of several million dollars, from a single metric moving 10 points, and before counting the customer-experience and capacity benefits.

McKinsey finds consumers now rank on-time reliability above speed, and would rather wait than have an order arrive late.

The numbers scale with your own volume and starting rate, and the point holds at any size: because every avoided failure removes a doubled cost, first-attempt improvement is one of the highest-return efficiency moves in last-mile. (The volumes and rates here are illustrative; the $17 per-attempt cost is the sourced input, and any operation can run the same arithmetic on its actual figures.)

Why First Attempts Fail

The encouraging part is that most first-attempt failures are not random; they trace to a handful of fixable causes. Addresses are inaccurate or poorly geocoded, so the driver arrives at the wrong point or cannot find the location. The customer is not home, because the delivery came without a usable time estimate or notification. The timing is wrong, arriving when the recipient could not receive it. Communication is missing, so the customer had no chance to adjust or prepare. And sometimes the route sequencing put the stop at a time that made success less likely. Each of these is addressable, which is why first-attempt rate is a lever rather than a fixed cost of doing business.

Also Read: The Best 3PL for Last-Mile Delivery Efficiency: Why Your Tech Stack Is the Real Differentiator in 2026

How to Lift First-Attempt Success

Four levers move the rate, and they map directly to the failure causes.

• Address intelligence and accurate geocoding. Resolving and correcting addresses so the driver arrives at the right point removes a large category of failures before the route is even built.
• Predictive ETAs. Accurate, dynamic ETAs let recipients know when to expect delivery, which is the single biggest driver of being home to receive it.
• Proactive customer communication. Notifications that tell the customer the delivery is coming, and let them react, convert would-be failures into successful handoffs.
• Window-aware routing and sequencing, with real-time adaptation. Planning against the windows the customer can actually receive in, and re-optimizing when the day slips, keeps deliveries arriving when someone is there to take them.

None of these is exotic; together they are what separates an operation that quietly absorbs a high failure rate from one that keeps it low.

How Locus Improves First-Attempt Rate

Locus improves first-attempt rate by attacking those causes in the plan and the execution. As the world’s first agentic TMS, it applies address intelligence and accurate geocoding so stops resolve to the right location; it generates predictive, dynamic ETAs from live route progress; it drives proactive customer notifications off that same operational data rather than as a bolt-on; and it plans window-aware routes across 250+ real-world constraints, re-optimizing in real time so deliveries keep arriving when the recipient is there. Because the communication and ETAs are driven by the actual dispatch and routing decisions, the customer-facing signals stay accurate rather than drifting from what is happening on the road. Locus runs this across operations in 30+ countries and 1.5B+ deliveries, and its route intelligence holds G2’s #1 position for Route Planning.

The effect is fewer failed attempts from the same fleet, which flows straight to the cost model above. (Any first-attempt-rate figures specific to your operation should be measured against your own baseline; the improvement comes from removing the fixable failure causes, not from a universal benchmark.)

What This Means for a Head of Logistics

If you are looking for the single highest-return number to improve in last-mile this year, first-attempt rate is the strongest candidate, because it sits closest to unit economics and because its failures are fixable. Benchmark your own rate, run the cost model on your real volume to size the prize, diagnose where your failures come from, addresses, timing, communication, and attack those with address intelligence, predictive ETAs, proactive communication, and window-aware routing.

Also Read: Route Optimization Software vs Last-Mile Platform 2026

Do that, and a metric that was quietly inflating your cost-per-order becomes one of the clearest levers you have on last-mile profitability. It is one number, and it decides more than any other.

Learn more, visit locus.sh.