For many delivery operations, a delivery exception—like minor damage, a wrong item, or an access issue—immediately results in lost revenue. Why? Because the driver often has to leave before your support team has a chance to successfully intervene. This time lag turns a recoverable issue into a costly return or a frustrating redelivery.
When leading retailers and distributors learn how quickly the delivery orchestration software market is growing, they tend to have one of two reactions.
With fuel prices top of mind for anyone who runs even a small number of trucks, it’s all too easy to scramble for quick cost cutting measures. Economizing on software spend, trying to fit just one more order onto routes that are already full, cutting corners on delivery execution: they’re all on the table, but they’re all ultimately shortsighted.
If you’re one of the logistics leaders at a building supplies distributor, you don’t have time for theory—you need practical ways to manage logistics more effectively. This means removing uncertainty, increasing visibility, and keeping customers happy and connected. All while minimizing delivery costs.
On some level, your delivery customers want the same thing that they’ve wanted since time immemorial: fast, attentive delivery service at a reasonable price point and a minimum amount of hassle.
AI-powered chatbots can be a useful tool for answering simple customer questions—but are they really the be-all and end-all of AI for customer delivery experience?
Successful logistics businesses are obsessed with their customers. One of the most important things to your average VP of Logistics is the delivery experience being offered to the end customer—whether that’s a consumer working on a home improvement project or an overworked general contractor who needs to keep their job site on schedule.
Maybe you’re in the market for a new last mile logistics solution and you’re wondering how to factor AI into your decision making process. Maybe you’re thinking about enabling the AI-powered features in your existing platform. Or maybe you’re trying to layer in AI workflows on top of the technology you’re already utilizing—either way, it’s critical to make sure that your AI capabilities can actually scale.
When it comes to deploying AI in an operational setting, a gap is starting to appear between ambition and reality. More than a quarter of leaders say that fewer than half of their AI pilots are ultimately scaled to production, and 75% of people say that leadership underestimates the difficulty that comes with scaling AI projects.
If you’re a building materials logistics lead, you know how much depends on the quality of your scheduling. When you’re scheduling and routing mostly by hand and over the phone, every day can feel like a logic puzzle—and matching up the right drivers and assets to the right orders based on your customers’ needs and their existing work schedules is a lot more taxing than your average sudoku.