For complex distribution networks involving large fleets, there are some challenges that seem to grow exponentially as your fleet increases in size. Anyone who runs even a single truck worries about how to deliver all their orders in an efficient way, how to keep fuel costs down, and how to weigh the pros and cons of adding additional capacity—but when you’re running dozens or hundreds of trucks the number of variables impacting these decisions can quickly get out of hand.
Whether you’re running a large number of trucks across numerous, largely autonomous distribution centers or doing all of your planning centrally, it’s easy to feel like the sheer scope of your operations makes the complexity too much to grapple with easily. And if you’re not armed with the right tools, technology, and knowledge, it absolutely can be. Conversely, with the right approach, businesses can overcome large fleet delivery challenges and ultimately simplify complexity, reduce costs.
How? We’re glad you asked…
At this point, the driver shortage is just a fact of life. It’s never going to be easy to hire and retain drivers, and the larger your fleet the more roles you’ll potentially have to fill in a labor market that’s not conducive to making that easy.
In a sense, larger businesses have a disadvantage here: the sheer numbers make hiring that much more challenging.
At the same time, enterprises do have real advantages for attracting and retaining talent—and dealing with the driver shortage more generally. For starters, you can empower drivers across your entire fleet with the tools they need to do their jobs more easily. This can be anything from giving the ability to capture proof of delivery and signatures seamlessly within an intuitive mobile app to providing configurable procedural instructions for dealing with specific delivery use cases (e.g. for service calls or installations that might otherwise require specialized skills).
You can also leverage delivery optimizations tools and techniques—e.g. route optimization—to increase the amount of deliveries you can complete per route per day. When drivers are hard to come by, the ability to deliver more with the driver talent you do have can be a huge boon.
Overcoming Large Fleet Delivery Challenges Around Planning and Orchestration
Like we alluded to above, larger fleets take different approaches to delivery management—i.e. centralized or decentralized approaches. Neither is necessarily better than the other, but it’s important to match your planning style to your processes and technology.
For instance, if you’re letting distribution centers operate fairly autonomously, it’s important to make sure they have the right tools and best practices in place to ensure that deliveries in any part of your network are up to your standards for efficiency and customer service. Here, it’s helpful to be able to gain total visibility into what’s happening in each distribution center even if they’re planning and routing on their own. To make this happen, you’ll want a delivery system that can be adopted at scale and that provides visibility by default. Here, it’s crucial to find solutions that are actually flexible enough to meet the different needs that might crop up in different regions or use cases—otherwise, you run the risk of shadow IT deployments at different branches leading to information and planning silos.
Conversely, if you’re doing all of your routing and planning centrally, you’ll need a solution that’s designed to scale up to arbitrarily many trucks in seconds. There’s nothing more frustrating for enterprise-sized fleets than slow, cumbersome planning processes. Ultimately, scalability for this use case comes down to software architecture. You shouldn’t need to get too into the weeds as a logistics specialist, but it’s important to look for a SaaS-native solution that’s architected to scale up or down seamlessly. Generally, this is something a provider will be able to show off in a live demo.
Fuel costs, driver/technician pay, fleet maintenance, technology licenses, warehouse/distribution center space, office labor costs—it all adds up quickly. And the larger your network is, the harder it can feel to actually do something about it when costs seem like they’re much higher than they should be.
Each of these cost factors can, of course, be tackled individually—through IT consolidation, by finding ways to save time and labor for planners and dispatchers, by making your routes more efficient, by leveraging predictive truck maintenance workflows, etc. But it’s also important to understand and try to tackle costs from a holistic perspective that covers your entire delivery process.
Depending on your industry, cost to service any given customer might include not just delivery but sales follow-up or even merchandising. In these cases, looking at cost optimizations requires you to factor in the impact on each different area. Even in industries where there are fewer touchpoints, you sometimes need a birds-eye-view of your entire logistics operation.
For instance, rather than focusing on optimizations for individual routes, you may want to zoom out and examine the cost implications of bigger changes in your network. How much would it cost to serve customers via a different organization of distribution centers? How might your network benefit if you rethought the way your regions are divided? When you have both descriptive and predictive visibility into your operations, you can figure that out and act on it.
Reporting and Intelligence
Speaking of predictive and descriptive visibility: the larger your fleet, the more complex your reporting and intelligence needs are going to be. We’ve danced around this over the course of this blog post, but most of the challenges we’ve been discussing do come down to data. Specifically, how do you collect the data you need, access it in the right context at the right time, and make smarter decisions based on it?
This is another area where connectivity is key. Solutions that connect every element of your last mile logistics network within a single platform and gather and process data across every touchpoint put you in a position to answer operational questions that might otherwise have been opaque. To make this happen, you need logistics software for fleet management that integrates easily with other solutions from other supply chain and planning touchpoints—but you also need a system that makes it easy to access the right information at the right time. After all, information can go out of date quickly in logistics—even more so when you’re dealing with large fleets and distribution networks. That’s why the ability to pinpoint the right data easily and without switching back and forth between solutions is so crucial.
So far, all of the solutions to these challenges have elided one much larger and more all-encompassing challenge that’s becoming increasingly pressing for large fleet operators: digitization. The kinds of data visibility, planning power, and route optimization capabilities that we’ve been talking about all depend on your ability to tackle one of the most significant large fleet delivery challenges by undertaking a process of digital transformation.
Sure, digital transformation is a little bit of a buzzword. But the basic concept—replacing manual processes with digitized ones, replacing disconnected processes with connected ones, and collecting and analyzing data from across your operation—is an incredibly important one for businesses that want to future-proof their delivery operations.
It’s easy to imagine why this is a stumbling block for large, complicated organizations. When you’re already dealing with a lot of moving parts, making any kind of change can be difficult and might involve a long discovery process. Luckily, digitization isn’t something that has to happen overnight. When you have a roadmap that includes digital transformation for your fleet, you can approach each new technology or operational decision with an eye towards paving the way for a more digitally mature operation.
What does that look like in practice? It’ll depend on the specifics of your business. But, in general, it might mean keeping a few best practices in mind:
- Opt for SaaS deployments rather than on-premise.
- Try to meet the needs of as many stakeholders as possible to avoid shadow IT.
- Prioritize connectivity, visibility, and flexibility.
- Make sure your applications can scale.
- Look out for technologies like AI and machine learning that can transform your data into something exponentially more valuable.
At the end of the day, there’s no one-size-fits-all approach for large fleets. But with the right approach, and the right tools, you can tackle the challenges facing modern delivery organizations head on.