Logistics Industry Trends and Digital Transformation

For an industry associated with old tech - trains, trucks, ships, planes, etc. – logistics has become something of a poster child for innovation in recent years.

The development of logistics services, also referred to as supply chain management, dates to ancient Greece and Rome and evolved during the Middle Ages to incorporate supply systems, roads, and warehouses. The World Wars of the first half of the 20th Century contributed significantly to further development of logistics processes, given the need to mobilize and move soldiers, supplies, and vehicles, and gave rise to today's multi-modal approach.

While the market for moving goods from place to place has been on the road to digital transformation for some time now, the global pandemic and the various supply chain disruptions that followed have put logistics operations in high gear, accelerating emerging technology adoption among companies in the space and helping the vertical as a whole serve as an example of how the likes of machine learning, big data analytics, robotics, IoT, battery-electric technology and robotic process automation (RPA) can enable a whole new way of doing business.

Critical drivers for the digital transformation of the logistics industry tend to be sector-specific and range from fuel efficiency to operator and vehicle safety to labor shortages to advances in electrification. That said, perhaps the biggest motivation behind the recent technological overhaul of the logistics space is something all industries can likely relate to increased cost savings. With that motivation in mind then, let’s look at some of the key technologies currently re-shaping the logistics landscape as we know it, as well as some of the innovative companies making such a revolution possible.

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Logistics industry trends: machine learning

Perhaps the most transformative of technologies to upend the industry in recent years, machine learning has emerged as the logistics professional’s crystal ball – and for many reasons. In fact, it seems no part of the supply chain has gone untouched by the virtual clairvoyance enabled by this technology. Whether its warehouse management systems bringing new efficiencies (Fulfilld, CognitOps), freight shipping fulfillment services (Zuum), fleet management  (Azuga, Avrios), shipping estimates (Onfleet, Shipup), or last-mile delivery (Interplai, Elite Extra, Wise Systems), the influence of machine learning on modern logistics operations cannot be denied.

Logistics industry trends: big data analytics

Often deployed in concert with technologies like machine learning and IoT, big data analytics can give logistics professionals a better handle on the big picture by operationalizing the information they already have on-hand or are currently gathering. Incorporating traffic, fleet, and other GPS-derived metrics with real-time monitoring of goods movement can provide logistics professionals with valuable insights. Supply chain-specific use cases for big data analytics include route optimization (OptimoRoute, Routific), perishable goods management (Procurant, Turvo), weather forecasting (Everstream Analytics), and vehicle diagnostics (KeepTruckin, Omnitracs).

Logistics industry trends: robotics and supply chain management

The potential for autonomous robots to bring innovation and significant cost savings to the supply chain cannot be understated. The influence of robotics has already been felt across the entirety of the logistics industry, thanks to the technology’s ability to bring increased speed and accuracy to warehousing and manufacturing operations, expand access to dangerous, non-human-friendly working environments, and work alongside humans (6 River Systems, Fetch Robotics, Boston Dynamics). And that’s likely just the tip of the iceberg as, going forward, autonomous robotics promises to permeate supply chain management in even more innovative and exciting ways.

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Logistics industry trends: Internet of Things (IoT)

In terms of vertical application, there are few industries as ripe for disruption by IoT as logistics. The crux of the IoT proposition – to harness the power of data accessible via the remote monitoring and management of connected devices – seems almost tailor-made for logistics processes, where everything is in a state of pretty much constant motion. To that end, key, supply-chain-oriented applications of IoT include inventory tracking (Lowry Solutions, Wiser Systems), location management (Datablaze, Blume Global), drone-based delivery (Flirtey, Flytrex), advanced driver assistance features (AImotive, Mobileye), and fully-autonomous vehicles (Waymo Via, Embark Trucks).

Logistics industry trends: electric vehicles

While, to date at least, the industry has only really dipped its collective toe in the autonomous vehicles space – public opinion on self-driving cars, trucks, and the like is currently such that it may be a while before we see this technology meaningfully integrated into the supply chain – battery-electric vehicles are already making an impact on the logistics sector. Between the lower emissions, the reduced maintenance, the increased reliability, and the potential for significant fuel cost savings, modernizing shipping fleets is something of a no-brainer. However, there are also barriers to entry. Not only are the acquisition costs currently high, putting the infrastructure in place to support electric fleets can be as complex as it is expensive. Still, given the many upsides, several companies are looking to get it in on the market opportunity, not just those associated with the major automakers (Rivian, Nikola, Arrival, Workhorse, Bolt Logistics, etc.).

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Logistics industry trends: Robotic Process Automation (RPA)

Already in use across a wide range of industries, RPA technology automates routine business processes, which helps to lower costs, increase efficiency and boost productivity. The time-sensitive nature of the logistics business makes it an ideal target for RPA deployment. Currently, RPA is being used to enhance the effectiveness of everything from shipment scheduling, including shipment scheduling and tracking (EdgeVerve, Keymark), invoice processing and collection (RPA Labs, Kofax), and inventory tracking (Aspire Systems, Flobotics).

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