Updated February 2026
A delivery fails, and the driver takes the blame. It's an easy assumption—they're the last person to touch the package, after all.
But the real culprit usually entered the system hours or days earlier. Wrong addresses, missing apartment numbers, outdated contact information—these data errors doom deliveries long before a driver pulls up to the curb. In this article, you'll learn why data quality matters more than driver performance, which types of errors cause the most failures, and how to fix problems at the source.
Why drivers are not the real cause of failed deliveries
When a package doesn't arrive, the driver usually gets blamed. But here's what the data actually shows: roughly 22% of delivery failures happen because of incorrect or incomplete address information entered at checkout. That's before a driver even sees the order.
Think about it this way. A driver receives an assignment with an address, a time window, and maybe some delivery notes. If any of that information is wrong—a missing apartment number, an outdated gate code, a disconnected phone number—the driver is set up to fail before they leave the depot.
This matters because it shifts where you look for solutions. Instead of focusing on driver training or adding more vehicles to your fleet, the real leverage point is upstream. Fix the data flowing into your delivery system, and you fix a huge portion of your failed deliveries.
What types of data errors lead to delivery failures
Delivery data errors are gaps or inaccuracies in the information used to plan and execute a shipment. These errors sneak in at various points—during checkout, when orders transfer between systems, or when information simply gets stale over time.
Let's break down the most common types.
Incomplete or incorrect addresses
Address problems cause more delivery failures than any other single factor. A typo in the street name, a missing suite number, or an old zip code can send a driver to the wrong location entirely.
High-rise buildings are especially tricky. A driver might find the right building but have no way to reach the actual recipient without a unit number. Rural addresses with non-standard formats create similar headaches when systems can't interpret them correctly.
Missing or outdated contact information
When something goes sideways during a delivery, the driver's backup plan is to call or text the recipient. If that phone number is disconnected or the email bounces, the driver has no way to resolve the issue on the spot.
Here's something that surprises a lot of businesses: contact information decays fast. People switch phone numbers, move, and abandon email accounts more often than you'd expect. Without regular validation, contact data becomes unreliable within just a few months.
Unclear or conflicting delivery instructions
A note that says "leave at door" doesn't help much when a building has four entrances. And when one system says "signature required" while another says "safe drop authorized," the driver has to guess which instruction to follow.
These conflicts typically pop up when data lives in separate systems that don't talk to each other. The warehouse might see one set of instructions while the driver's app shows something completely different.
Wrong time windows and availability data
Scheduling a delivery for Tuesday at 2 PM when the recipient works until 6 PM guarantees a failed first attempt. Without accurate availability information, even a perfect address won't prevent a "not home" exception.
Plans change too. A recipient might have been available on Tuesday when they placed the order, but their schedule shifted. If there's no way to communicate that change, the original time window—now wrong—stays locked in the system.
The true cost of poor delivery data quality
Failed deliveries cost more than just the price of a second attempt. The financial impact spreads across operations, customer relationships, and how people perceive your brand.
Redelivery and return expenses
Every failed attempt triggers a chain of costs. The driver returns to the depot. The package gets rescanned and rescheduled. Customer service fields an inquiry. Failed deliveries cost retailers an average of $17.20 per order, and during peak seasons when capacity is already tight, these costs compound quickly.
Return-to-sender packages hit even harder. The item travels backward through the network, requires restocking or disposal, and the original sale often disappears entirely.
Customer churn and brand damage
A failed delivery breaks a promise. And broken promises stick with customers. Research consistently shows that shoppers are far less likely to order again from a retailer after a delivery failure—and that likelihood drops further with each additional bad experience.
The ripple effects extend beyond individual transactions too. Customers tell friends, post on social media, and leave reviews. One data error can snowball into lasting reputation damage.
Wasted driver time and fuel
Drivers who spend time hunting for incorrectly listed addresses or making repeat trips to inaccessible locations aren't completing new deliveries. This inefficiency cuts into the number of successful stops per route and burns extra fuel.
Over time, these frustrations also contribute to driver burnout and turnover. Yet another hidden cost that traces back to data quality rather than driver performance.
How to identify data quality issues in your delivery operations
Before you can fix data problems, you have to spot them. Several patterns signal that data quality—not driver performance—is behind your delivery failures.
Here's what to watch for:
- High rate of "address not found" exceptions: When drivers consistently report they can't locate addresses, the issue likely sits in your address data, not your routing.
- Frequent customer complaints about missed or late deliveries: If customers report problems even though packages left on time, the disconnect often traces back to inaccurate delivery information.
- Drivers regularly flagging unclear or missing instructions: Frontline feedback reveals data gaps that don't show up in system reports.
- Spike in return-to-sender packages: A sudden increase in undeliverable shipments usually points to systemic data problems rather than one-off incidents.
Tracking these metrics over time shows whether data quality is trending better or worse—and helps you prioritize which data sources deserve attention first.
Best practices for improving address data quality
Fixing delivery data takes intervention at multiple points in the order lifecycle. The most effective approach catches errors before they enter the system and creates ways to correct them when they slip through.
Validate addresses at checkout
Real-time address verification tools compare what customers type against postal databases. These tools flag potential errors, suggest corrections for typos, fill in missing postal codes, and confirm that an address actually exists—reducing address errors by up to 40%.
Checkout is the ideal moment to catch these errors. The customer is right there, engaged and able to confirm or correct their information. Once an order enters fulfillment, fixing address problems becomes much harder and more expensive.
Require complete recipient contact information
Collecting a phone number—not just an email—gives drivers a direct line to recipients when issues come up. A quick call can clarify a confusing delivery instruction or confirm someone is home for a signature-required package.
For high-value shipments, consider asking for a backup contact method. If the primary number doesn't work, having an alternative prevents an automatic failure.
Allow consignees to update delivery preferences
A consignee is the person receiving a delivery. Giving consignees the ability to change their delivery instructions after an order ships dramatically reduces failures caused by changed circumstances.
Platforms like Koorier give consignees real-time control over their delivery experience. Recipients can update access codes, specify safe drop locations, or adjust delivery windows as their plans change—even while a package is already in transit.
Connect systems to eliminate data silos
When order management, warehouse, and delivery systems don't communicate, data conflicts emerge. The shipping label might show one address while the driver's app displays another. Delivery instructions might exist in the order system but never reach the carrier.
Integration ensures that a correction made in one place flows everywhere. When a customer service rep updates an address, that change automatically appears on the driver's device.
How real-time visibility reduces delivery issues
Visibility turns delivery management from reactive to proactive. When shippers and recipients can see what's happening as it happens, they can step in before small issues become failed deliveries.
Here's how real-time tracking helps:
- Shippers catch exceptions as they emerge: Instead of learning about a problem after the fact, operations teams see issues develop and can act immediately.
- Recipients can respond to problems in the moment: A notification that a driver can't access the building gives the recipient a chance to share the gate code before the driver leaves.
- Drivers receive corrected data mid-route: When a customer updates their delivery instructions, that information reaches the driver right away rather than sitting in a queue until tomorrow.
Koorier's control center provides this level of visibility. Shippers get a comprehensive view of every delivery while consignees receive real-time updates on their shipments.
Build a smarter delivery operation with accurate data
The path to fewer failed deliveries doesn't run through driver training programs or route optimization software. It runs through data quality. When the information flowing into your delivery operation is accurate and complete, performance improves across every metric.
Start by looking at your current data processes. Where do errors enter the system? Which data sources go stale fastest? What feedback loops exist to catch and correct problems before they cause failures?
Then look at technology that validates information at the source, keeps systems in sync, and gives everyone—shippers, drivers, and recipients—visibility into what's actually happening.
The drivers aren't the problem. The data is. Fix the data, and the deliveries follow.
Ready to see how better data drives better deliveries? Request a shipping quote or explore how Koorier can optimize your shipping operations.
Author & Authority
By Avinash Anand
Logistics analyst with 25+ years of experience in Canadian last-mile delivery optimization.
About Koorier
Koorier is a Canadian logistics technology company specializing in regional last-mile delivery networks and real-time delivery visibility for retailers and enterprises.
Frequently asked questions about delivery data and failed deliveries
What is a delivery error?
A delivery error happens when a shipment can't be completed as planned. Common causes include wrong addresses, unavailable recipients, or missing information. While drivers often get blamed for these failures, the root cause typically traces back to inaccurate data that entered the system long before the delivery attempt.
How can shippers fix a failed delivery before it reaches the customer?
Real-time tracking platforms let shippers monitor exceptions as they happen. When an issue pops up—say, a driver reports an inaccessible location—the shipper can push corrected information to the driver or contact the recipient directly. This often resolves the problem before a second attempt becomes necessary.
What are the most common causes of delivery failures?
Incomplete addresses top the list, followed by missing contact details, incorrect delivery instructions, and outdated recipient availability information. These data problems account for a much larger share of failures than driver errors or vehicle breakdowns.
Can customers update their delivery information after an order ships?
Yes. Many modern delivery platforms—including Koorier—let consignees modify their address, delivery instructions, or preferred time window even while an order is in transit. This flexibility prevents failures caused by circumstances that change after the original order was placed.
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