Transportation Management System
Legacy TMS and the Cost of Failed Deliveries
Jul 31, 2025
5 mins read

Imagine this: a planner signs off on the 9 a.m. dispatch schedule. By noon, three routes are stalled, two orders are missed, and one VIP customer is calling support. The plan was solid, until reality showed up.
This is how the first attempt delivery rate (FADR) quietly crumbles for retailers, e-commerce businesses, and CEP companies. And FADR, more than any other metric, reflects the real-world maturity of a logistics operation. When it drops, so do margins, customer trust, and operational sanity. Not because failures are unpredictable, but because legacy TMSs pretend nothing changes.
Let’s talk about where deliveries really go wrong. And why your TMS might be the silent killer.
The quiet cost of missed deliveries
In a recent survey by McKinsey1, respondents rank on-time delivery more important to their experience (CX) than fast delivery. About 50% of them track the order status just to make sure they arrive when promised.
That’s why a failed delivery hurts more than it seems. Sure, you might pay for a redelivery. But the real cost is compounding.
Miss a delivery window and you break a service-level agreement (SLA). That means fines, refunds, or customer support escalations.
Make a loyal customer wait or wonder, and suddenly they aren’t loyal anymore. A Sage Journal study2 found that delayed or missed deliveries increase the time it takes for a customer to buy again. It often kills the next purchase entirely. Every failed delivery quietly chips away at customer lifetime value (CLV).
Then there’s the operational mess. Reattempts clog up capacity, drivers waste hours, orders stack up in warehouses, and support teams drown in tickets. It’s like a domino effect, and your logistics team is stuck cleaning it up every time.
And yet none of this is new. Everyone in logistics knows delivery failures are bad. The real question is: why do they still happen?
Missed deliveries aren’t a last-mile problem
Failed deliveries aren’t just a last-mile issue. It doesn’t happen only because something went wrong on the road. In reality, many failures are set in motion much earlier. Often before dispatch. Sometimes even at checkout.
Here’s how it plays out:
| Before the van rolls | After the van rolls |
| Customers aren’t shown meaningful delivery slots they can actually commit to. | The customer wasn’t home, and the driver didn’t know. |
| Delivery preferences aren’t captured or passed downstream. | Traffic delays make an on-time delivery impossible, but the system doesn’t react. |
| Routes are locked hours or even days before real-world variables come into play. | A vehicle is unavailable, or a driver calls in sick, and now a time-sensitive order is just… sitting. |
| Support teams reschedule deliveries, but the changes never make it to the dispatch logic. | No one’s monitoring SLA risk in real-time, so issues are discovered after they’ve already become problems. |
Traditional TMS can’t resolve the above issues because they weren’t built for dynamic variables. The system assumes the plan will go perfectly. And when it doesn’t? The delivery fails. The customer churns (lost LTV). And the team scrambles. That’s not what modern logistics demand.
Must-haves for a modern TMS for high FADR
A modern TMS should be able to withstand the dynamic nature of last-mile delivery. It should effectively plan for contingencies on the go, without any delay. In practical terms, it should have the following features.
Lock in deliveries before they fail
Customers should be able to choose the delivery date and time based on their convenience. A seamless checkout process with such a feature will drastically reduce no-shows during delivery. Dispatchers can be rest assured that the order has not failed from the start. And it improves FADR, operational efficiency, and predictive resource planning.
Locus Delivery Linked Checkout (DLC)
(For a deeper dive into how Locus handles customer-preferred time windows and helps clients improve FADR, check out our whitepaper: Customer-Preferred Delivery Time Windows.)
Detect SLA risks before they become churn
Route planning should take in possible variables, and thus plan ideal routes for scheduled, dynamic, and recurring fulfillment models. The TMS should be able to auto-assign on-demand orders or at-risk SLAs to best-suited drivers in the vicinity. For this to work, on-ground exceptions, like traffic, have to be analyzed real-time.
Route planning engine that optimizes routes for time, distance, and over 180 variables
Both the above features ensure high FADR while giving peace of mind to all the stakeholders in the supply chain process.
Modernize where it’s due
We live in a time where retailers and CEPs have packages that chase customers. The goal is simple: deliver smarter, faster, and on the first attempt. That’s why the most forward-thinking logistics and supply chain leaders aren’t waiting for the next failure to make a change. They’re upgrading before the cracks turn into churn. If you’re ready to see how Locus can help your team deliver smarter, faster, and on the first attempt, book a demo with us today!
References
- McKinsey 2024 Voice of Consumer Survey (McKinsey Insights)
- Sage Journal: The Effect of Delivery Time on Repurchase Behavior in Quick Commerce – Alice Harter, Lucas Stich, Martin Spann, 2025
Anas is a product marketer at Locus who enjoys turning complex logistics problems into simple, clear stories. Outside of work, he’s usually unwinding with a book or catching a good movie or series.
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