Founder and CEO of Arkestro, the leading Predictive Procurement Orchestration platform.
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In recent years, the logistics industry has invested heavily in last-mile capacity, the final leg of the customer-facing supply chain. A recent study estimated this “last mile” niche of the logistics market alone will grow from $25 billion to $72 billion by the end of 2025. “Last mile” in a traditional retail supply chain typically entails moving products from a retailer’s distribution center to a physical store. But in the past decade, the rise of e-commerce and direct-to-consumer supply chains has upended that model, creating a scramble for last-mile logistics capacity across the United States, capable of delivering packages to every consumer’s residential address instead of a smaller network of retail locations.
For companies like Amazon and other e-commerce-based businesses that don’t rely on physical storefronts, last mile is a vital element of their customer experience. However, the last mile also tends to be the most laborious and expensive part of a delivery’s logistics costs, with its numerous stops and low drop sizes. For this reason, retailers, distributors and e-commerce pure-plays are constantly seeking ways to increase speed and efficiency, with Amazon Same-Day and 2-Day Delivery setting the pace for operational tempos across the entire supply chain.
During the height of the recent supply chain crisis, attention shifted to port congestion and especially long delays for unloading container ships. Since then, the backlog of ships and unloaded goods has mostly returned to healthier pre-Covid-19 levels (e.g., the Port of Los Angeles just recorded its most productive month ever). What doesn’t get as much attention, however, is the pesky middle mile—that intermediary leg of the supply chain where products are unloaded from docked ships, moved to port terminals and placed onto trucks and trains to travel to retailers’ distribution centers. Middle-mile logistics is ripe for speed and efficiency improvements, and it’s crucial to know what in this arena may be causing delays and what this may be costing you.
Many enterprise customers rely heavily on third-party logistics (3PL) platform providers to manage the warehousing and transportation needs of the middle mile, which include the costs of port operations, customs, trade compliance, stevedores and drayage providers. These providers, who often serve many enterprise customers simultaneously, can quickly become overwhelmed for any number of reasons, including labor shortages, weather-induced delays and congestion during peak times. When such a provider or one of their sub-contractors becomes overwhelmed, orders can be delayed and expediting fees can spike, leading to added costs and eroded margins.
Many 3PL providers are beginning to leverage AI and machine learning in a plethora of use cases to manage highly complex supply chains and maximize middle miles, ranging from automated warehouses to autonomous pallet packing to predictive yard management and logistics network optimization and more. Even still, because different embedded elements of these middle miles are controlled by different providers, the cost elements are opaque to teams who support supply chain operations. How do long wait times for truckers at ports impact logistics costs? What are the benefits of using a provider that offers an automated warehouse? Procurement teams often don’t have enough cost element data to determine the risks that poorly managed middle miles can pose to overall supply chain performance.
This means that as digital technology becomes more ubiquitous, enterprise procurement teams will need to be very mindful of the way logistics are procured. As the procurement of last-mile logistics is set to increase, enterprises will also increasingly be rethinking how they buy services and components of their middle miles, ranging from warehousing to specialized services. And just as AI and ML can help manufacturers with the procurement of their direct goods—quickly surfacing preferred supplier and predictive prices based on multiple attributes like quality, availability and cost—so too can retailers, distributors and e-commerce groups benefit by identifying the ideal middle mile providers and cost structures based on the relevant context-sensitive variables.
More specifically, here’s how AI and ML can help in procuring middle-mile logistics:
• Real-time programmatic flagging of lead time changes: An enterprise customer may have had a traditionally good experience with a particular provider, but it becomes critical to programmatically identify exceptions and surface them to decision-makers in real time. If a preferred provider offers a longer lead time than usual, this is a clear sign the provider may be overwhelmed and if engaged now, the enterprise customer may wind up at the end of their line. Real-time exception monitoring can help enterprise customers avoid going with a constrained lane and provide recommendations on the next best option.
• Tier 2 cost structure visibility: If a commonly used logistics provider’s costs suddenly change, such aberrations should also be automatically flagged, giving organizations the chance to ask the provider “why?” and gain insight into Tier 2 cost structures. Providers are able to deliver a detailed breakdown of costs that may include fees associated with late deliveries, weekend deliveries and demurrage fees. When enterprise customers are proactively made aware of this information, they can make changes to improve scheduling and capacity plans.
• Supporting faster procurement cycles: When a procurement cycle can be graded against a predictive target without human intervention, the overall procurement process becomes much smarter—and faster. Rather than issuing requests for logistics services one at a time, these cycles can be automated and executed in parallel, effectively enabling enterprise customers to lock in scarce capacity for the right market basket of logistics lanes at once.
One main reason why Amazon is so successful in the middle mile is that it has visibility into all of the cost components that make up port and warehouse operations. Such tight visibility undoubtedly played a role in helping it be first-to-market with Same-Day and 2-Day delivery. Amazon is also deriving savings on middle-mile costs that can ultimately be passed to end customers, furthering its competitive advantage.
For retailers, distributors and other e-commerce players who may not have this luxury, an approach to the procurement of middle-miles logistics that leverages predictive models can offer leverage to control costs in a fast-moving environment.
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