Through the long months of the pandemic, Latin America’s confined populations waited and waited on the products they’d ordered online. Having embraced e-commerce during the pandemic to an unprecedented degree, a region registering 37% growth in retail e-commerce found itself still enduring woeful wait times for non-essential and essential goods alike. As demand for same-day/next-day deliveries spiked, locked-down populations felt the pangs of the region’s formidable geography, sprawling urban landscapes, and onerous traffic all the more acutely.
The problem, of course, is nothing new. The region has always lagged behind Europe and North America in logistics technology and delivery speed, with the final leg of products’ journeys proving agonizingly long. However, the urgency of the issue has never been greater. Latin America (LatAm) is the fastest-growing e-commerce market in the world and consumers are clamoring for greater efficiency.
READ ALSO: A new perspective on mobility solutions through Mobility as a Service
The choke point in Latin America’s last-mile logistics is as much the antiquated coordination and routing processes still used by delivery companies as it is intractable infrastructure. Meanwhile, the long-awaited fix to Latin America’s last-mile logistics will come in the form of cutting-edge artificial intelligence (AI). By taking the right steps, businesses of all sizes can leverage AI to create vastly more efficient, intuitive and predictive logistics networks. Here’s how.
LatAm’s Delivery Problem
If on-demand courier platforms like Colombian last-mile delivery service (and unicorn) Rappi offer a glimpse of what is possible, the efficiencies of a select few belie just how painfully ill-equipped the region still is for fast deliveries. In Mexico, half of all deliveries are made within seven days and 70% within two weeks. Meanwhile, last-mile delivery obstacles have seriously hindered vaccine distribution across the region.
A huge part of the problem is thanks to the fact that the vast majority of LatAm delivery companies still rely on rudimentary coordination and routing processes. For example, many still track deliveries using pen and paper and manual dispatchers. They also contract with independent drivers since it’s less expensive than maintaining a fleet of their own vehicles. Of course, this can create serious inefficiencies and cause substantial delays.
For those few companies trying to update the old ways of doing things, the topography of the region of course comes with its own set of unique challenges. For instance, the continent’s urbanization rate is around 80%, which is statistically higher than other regions globally. Plus, the preference for trucking over rail results in many streets within large cities locked in near-perpetual traffic jams.
The lack of companies operating at a scale large enough to meet consumer demand paired with non-existent optimization processes means that, in most places, same or next-day delivery is unavailable. For the region to catch up with the rest of the world, an algorithmic overhaul of decades-old processes cannot come quick enough.
Visibility From Retailer To Customer
It’s AI that will be uniquely capable of cutting through the gridlock to deliver a solution to the region’s logistics woes. AI algorithms allow companies to cut time and costs by automatically finding the most efficient routes possible. Unlike the majority of current deliveries, where dispatchers select routes without knowing the real-time road conditions or drivers take it upon themselves to find shortcuts, machine learning works to remove any of the guesswork.
Construction delays, traffic accidents, and driver capacity are just some of the obstacles that can be evaded in real-time when logistics decisions are forced through an algorithmic sieve. With an intelligent software solution in place that acts on new information, each stage of the logistics node can be connected to another seamlessly and efficiently, allowing for visibility from the retailer to the customer.
Applying AI becomes all the more powerful when used in conjunction with so-called “dark stores” – that is, urban fulfillment centers established in commercial buildings that are organized and optimized for the rapid retail fulfillment of online orders. These spaces are located in strategic urban points to break down the journey from distributor-to-doorstep. With this flexible distribution network in place, smart order planning and tracking can work to provide a transparent overview that both merchants and their customers benefit from. The result is deliveries that can move across the urban landscape along the path of least resistance, something that is badly needed to combat the region’s famously chaotic streets.
READ ALSO: Amazon: the giant’s awakening in Brazil
Three tips to integrate AI
Logistics services that mesh their fleet management and route planning processes with AI are met with several benefits including reduced costs, faster transportation, seamless inventory tracking, reduced fossil fuel emissions, and enhanced productivity. Better yet, businesses of all sizes can leverage AI as the technology becomes more widely distributed, meaning that even small companies can partner with an AI-powered last-mile service provider without having to build out the system from scratch.
Those LatAm companies who want to integrate AI into their last-mile delivery offering should consider a few things. First, upon integration, companies should develop a proof of concept (beta test) at an operational and technical level to see how the system works for their current operations. This small-scale test should focus on integrating AI into systems where optimization isn’t in crucial need of a complete overhaul, and where the old way of doing things can be hybridized at first to boost efficiency.
READ ALSO: Back to the future: Via’s innovation strategy is all about the company’s legacy
Second, once you’re up and running, try considering a controlled pilot in a single city to scale up your new operations. As you get used to the new way of doing things and progress from the basics, the true benefits of AI become apparent as the time saved on rote processes by machine learning frees up staff to utilize their creativity to solve more complex business problems. Third, the final stage in AI integration would be national deployment and implementation of your new system based on the lessons learned.
It’s clear that now is the time to play catch up for last-mile logistics in LatAm. As the e-commerce economy grows and numerous players emerge to meet the needs of a new retail paradigm, delivery companies must act now to follow in their footsteps. Sketching out routes in paper and pen, however, no longer cuts it. Companies across the continent must embrace the moment and leverage technology to make their logistics networks more efficient, intuitive and predictive. Empowering consumers with a service that is faster and cheaper has been a long time coming.