Being in charge of last-mile delivery can feel a little like being Sisyphus. (You’ve probably heard the story, even it doesn’t immediately ring a bell.) He’s the guy in Greek mythology who rolled a giant boulder up a mountain every day, only to almost reach the top and have it hurtle to the bottom. The next day, he did it all over again.
Now imagine the mountain gets a little higher every day—in the same way the bar for last-mile delivery is constantly being raised. Then, a higher-up asks if you can chisel away at the boulder (aka your costs) while you’re rolling it up the mountain every day. Maybe we’re taking a little poetic license here, but it’s similar to the scenario most supply chain and operations execs face every day. And much like Sisyphus’ task, it can feel impossible.
For example, in a single day, you may be expected to do last-mile delivery, as well as omnichannel to Amazon, big box stores, small retailers and same- or next-day direct to consumers. At the same time, while delivery windows keep getting smaller and smaller, you’re being asked to lower costs.
If you’re in charge of a two- or three-shift facility, you’re likely to feel even greater pressure because your material handling fleet is a top three to five cost for your company. That means your work likely comes under even more scrutiny and pressure. The good news is that while the challenge is larger, so is the potential pay-off.
If your company has a number of different facilities, one of your biggest frustrations is probably fragmented service solutions. The different cost and efficiency data you’re getting from each facility doesn’t allow you to chip away at your cost. This divergent data makes it hard -- if not impossible -- to implement overall best practices that can lead to cutting costs.
It’s difficult to design a process for implementing universal best practices when you aren’t comparing apples to apples. In fact, with fragmented service solutions, you aren’t even comparing apples to oranges. If you have multiple facilities running different kinds of operations with different service set-ups, it might be more accurate to say that you’re comparing apples to oranges to lemons to limes to pears to blueberries. And that system just doesn’t allow you to maximize efficiencies and minimize costs.
The way to solve these issues—so your comparison is apples to apples—is to implement a national service solution. This allows you to get consistent data across all facilities, while still allowing for different equipment as needed. And we all know that consistent data is the “secret sauce” that allows you to implement best practices across all your facilities.
Ultimately, how you choose your fleet’s system and equipment—and decide who maintains and deploys it—determines a significant portion of the cost and effectiveness of your being able to meet your last-mile delivery goals.
Why does a national service solution work? When it comes down to it, there are five reasons it can cut costs and improve productivity:
1. Optimized Data - With a national service solution, you get consistent data to analyze costs and efficiency. Plus the freedom to choose the equipment you want for every application based on that data.
2. Universal Best Practices - With a national service solution, you can be certain that you’re implementing consistent best practices for all equipment and for all facilities. You can choose and then put into place best practices for every aspect of material handling: from reach trucks to pallets to storage, and then deploy those best practices nationally with the same service model and same cost structure everywhere.
3. Improved Productivity - A national service solution drives productivity improvements. Even if you take cost out of the picture, the fact is, your company will either move product effectively or it won’t. A national service solution simply makes you a more efficient and productive company when it comes to moving product.
4. Consistency - A national service solution allows for the same service model and the same cost structure in all facilities.
5. Reduced Costs - When you have consistent data, you can use that analysis to drive optimization over time. And that has a significant effect on cash flow because you’re driving optimization for a top three to five cost.