Saturday, May 25, 2024
HomeSourcingWhy Automating The City Center-Mile is Key for Quick and Predictable Deliveries...

Why Automating The City Center-Mile is Key for Quick and Predictable Deliveries • Let’s Speak Provide Chain

At Argo AI, we believe enabling fast and predictable deliveries begins upstream in a pivotal segment we’ve dubbed the urban middle-mile. This new delivery space has emerged in response to convenience culture – consumer expectations for rapid, inexpensive and predictable deliveries. We hear from retailers and logistics providers that they are actively decentralizing their supply chain, or planning to, in an effort to store goods closer to the consumer, all to enable faster deliveries and greater fulfillment optionality. This trend has created urban middle-mile use cases – such as warehouse-to-micro-fulfillment-center deliveries and store-to-store inventory rebalances – at a time when the supply chain is already stretched.

Autonomous vehicles (AVs) could play a key role in shaping the urban middle-mile. Here’s how:

Deploy AVs on-demand across urban middle-mile routes to enable faster deliveries.

The emergence of urban middle-mile deliveries can add logistical complexities, introducing more routes and on-demand dispatching requirements. Many retailers and logistics companies are feeling the impact of driver shortages. More than one-third of shipping companies report that their biggest problem is finding qualified drivers, which impacts costs for both shippers and customers. Some retailers are pulling associates off sales floors to drive products to other stores, yet this clearly isn’t sustainable. Instead, as businesses decentralize their inventory to enable faster delivery times, AVs can be deployed on-demand to fulfill customer needs without disrupting business operations. Automating the repetitive urban middle-mile routes could allow businesses to scale their delivery operations to meet rising demand.

Surface actionable data insights to plan, predict and optimize urban middle-mile logistics.

As companies explore urban middle-mile deliveries, data insights could enable them to optimize overall fleet performance and utilization. Current and potential customers say that they often lack clarity about where their products are when they leave one facility and before they arrive at the next, and that they rarely have actionable insight into the root cause of delivery delays or missed delivery windows. The urban middle-mile requires greater logistics flexibility, and to enable this, businesses will need transparency to both predict and respond to disruptions. Our autonomous, connected vehicles generate precise positioning data and delivery status updates, providing businesses with real-time information, as well as historic averages and trends, to optimize delivery schedules, maintain adequate inventory levels, plan efficient routes, and more.

Argo’s autonomous vehicles operating on urban middle-mile routes can enable retailers and logistics providers to meet the emerging fulfillment demands of their customers. The Argo Autonomy Platform already operates across a variety of use cases, powering fleets in multiple cities across two continents, with more locations to come. If you are interested in learning more about collaboration, get in touch at


Let's Talk Supply Chain Why Automating The Urban Middle-Mile is Key for Fast and Predictable Deliveries 1 Lehren is the Director of Business Development at Argo AI, a global autonomy company on a mission to make the world’s streets and roadways safe, accessible, and useful for all. Lehren leads the team responsible for driving Argo’s go-to-market strategy through first-of-kind strategic partnerships. Prior to Argo, Lehren worked at Google in their technical program management organization. She has a Bachelors from UCLA, and started her MBA at Wharton before leaving to join Argo.

BtoB Central Staff
BtoB Central Staff
Btobcentral is dedicated to business news.


Please enter your comment!
Please enter your name here
Captcha verification failed!
CAPTCHA user score failed. Please contact us!

Most Popular

Recent Comments

We use cookies to give you the best online experience. By agreeing you accept the use of cookies in accordance with our cookie policy.

Close Popup