In the bid to make supply chains more efficient, to track goods from raw material to final delivery — and ensure streamlined progression along the last mile — machine learning and other advanced tech can play a pivotal role.
As noted in a blog post featured on Business 2 Community, the overall trend has been one where consumers expect an ever tightening window for deliveries, but logistics are ever more complex.
The shift online is inexorable, and so will the pressure to speed up the movement from factory to consumers’ doorsteps. The critical component is data — the collection of it, the dissemination, and ultimately the actionable insights gleaned from it.
Machine learning helps to automate at least some of the more manual, error-prone functions that occur from order to freight, across various modes of transport, managing inventory (in ways that benefit merchants and have positive ripple effects across supply chains). Logistics hubs and warehouse management improves as a result. Payments can be an integral part of improving logistics, as frequently transactions must be completed before goods move onto subsequent supply chain “links.”
Direct To Consumer Gains Ground
The move to improve supply chains comes as PYMNTS found in recent research, direct-to-consumer (D2C) sales are on the rise, which eats into the traditional brick-and-mortar model of commerce. All categories of spend, from pet food to clothes to food and beverages, saw double-digit declines in physical channels as a point of transaction. This indicates that the traditional inventory management process of stocking retailers’ shelves is on the wane. It also means that the last mile involves trucks, delivery vans, drivers, and, on the horizon at some point, autonomous vehicles. Recent data points (such as from the Port of Los Angeles) show import activity is picking up ahead of anticipation of a busy holiday shopping season, so as the economy rebounds from the pandemic (the latest GDP data were strong, but the longevity may be bumpy).
And, in recent coverage in these digital pages, there’s been no shortage of new solutions underpinned by high tech coming to market to improve supply chains. In one example, SAP SE and Qualtrics, an SAP company, have XM for Suppliers. The solution helps firms secure pivotal supply and use artificial intelligence (AI) to, among other things, find gaps in supply chains. Elsewhere, Amazon’s Smart Shelf, an automated inventory ordering system (based on a wireless scale) for smaller firms, which can help optimize inventory.
At a high level, the Internet of Things (IoT) can help digitize supply chains, modernize them, and give real time insight into where frictions are occurring and how they should be addressed.
In a recent interview with PYMNTS, Niall Murphy, CEO of EVRYTHNG, told PYMNTS in an interview that assigning individual items their own unique identities and data, and tracking it all across the cloud (itself an advanced technology of course), can improve workflows (and payments, too). He told PYMNTS that machine learning can help fill in information gaps and build projections about what is happening on the ground, so to speak, as projects move ever-farther from the raw materials stage toward the final hand-off.
“The more data points we can connect about items as they flow through the supply chain, the more accurate a picture we have about the flow of the overall supply chain,” he said.