Across every industry, there’s buzz about artificial intelligence (AI), machine learning (ML), automation, optimization engines, and other advanced technologies. But what do these terms mean for the logistics industry? Will self-driving trucks ever be a reality? What exactly is a data cloud? Should we be excited or scared by the possibilities created by today’s rapid technological innovations?
If advanced technology intimidates you, consider that the exponential pace of innovation we’re seeing today is not new. Other industries, like aerospace, have experienced similar flashpoints, which created enormous benefits. As this World Economic Forum article points out, it took 2.4 million years for humans to use fire for cooking. But only 66 years passed between the Wright brothers’ first flight and the first moon landing. As supply chain professionals, we’re in an age of extreme innovation that’s thrilling, but not unprecedented.
At Blue Yonder, we believe every logistics stakeholder should be excited about advanced technologies like AI. But we understand the confusion, and there are some great questions out there. So, let’s take a few minutes to define some of the most common terms related to managing logistics via advanced technology.
Transportation management system (TMS). Let’s start with the basics. A TMS is software that collects data and tracks the processes associated with moving goods, both inbound and outbound, and across all modes of transportation including rail, air, surface, and sea. By replacing manual processes and paperwork with software, logistics teams are digitizing complex transportation functions to increase visibility. They can see and manage, in real-time or near real-time, what is happening, at every node in the network. They can gather and analyze data across the end-to-end logistics network to monitor for problems, as well as improve service and cost outcomes. In addition, some very select TMS solutions like Blue Yonder’s TMS can dynamically optimize routing based on factors like service levels, cost, empty miles, and driver schedules and optimize load build. Blue Yonder’s TMS also links directly to leading visibility partners to increase end-to-end insights. TMS adoption is growing rapidly for manufacturers, retailers and logistics service providers (3PLs, 4PLs and 5PLs) — as well as the carriers they partner with. Today, the worldwide TMS market is growing at 14.8% annually and is expected to reach $31.18 billion by 2030. This growth is driven by both the increasing complexity of logistics operations and the improved accessibility of TMS software thanks to software-as-a-service (SaaS) models — in which the software is accessed over the internet and includes both hardware and services.
Warehouse management system (WMS). A WMS is a software platform that collects real-time information on all the moving parts of a distribution center (DC) regardless of size — whether it’s manned, fully automated or even a dark DC, equipped to handle inventory based on systems commands. The WMS allows logistics teams to see the status of orders, inventory, labor, robotics, physical assets, trailers…the list goes on. If it’s part of the warehouse, it’s captured and reflected in the WMS. Thanks to dashboards and reports, managers can see what’s happening now, anticipate what’s coming and avoid disruptions. They can measure performance aspects like on-time fulfillment and picking efficiency, leveraging those metrics to optimizewarehouse processes. WMS revenues will increase from $2.75 billion in 2022 to $7.30 billion by 2030, reflecting an annual growth rate of 13.2%.
Automation. While TMS and WMS platforms enable data gathering, monitoring and communication, automation takes a more active role in accomplishing work. By relying on robotics to pick products and move them around the DC, companies can eliminate labor- and time-intensive processes, freeing human resources for more strategic tasks. Edge technologies — includingrobotics, wearables and camera-based yard management systems — empower associates with the technology they need to complete jobs quickly and accurately, while also making their work easier. Touchless transaction systems reduce manual touch points for data entry in both the warehouse and transportation management functions — improving the speed and efficiency of activities like picking and load-tracking, while also reducing mundane tasks and improving employee satisfaction.At Blue Yonder, we’re excited about the growing use of decision automation such astask management solutions in the logistics arena, where software is used to prioritize jobs, assign resources and manage disruptions — autonomously, with no human intervention. Today’s automation solutions aren’t aimed at eliminating humans, but elevating their contribution to a more strategic role, maximizing both their value and their job satisfaction.
Artificial intelligence (AI). While AI seems scary and futuristic, it’s becoming commonplace. AI simply means relying on software to perform learning, problem solving and decision processes that have historically been associated with the human brain. Across the logistics function, AI is becoming an imperative. In the face of constant disruptions, today’s logistics networks and distribution systems are simply too large, fast-moving and complex to manage effectively via only human cognition and analysis. Machine learning (ML) is a subset of AI, and it enables software to become continuously smarter. An example of ML is when yard software learns to better identify trailer numbers through the help of human operators. As the system learns, dependence on human instruction diminishes, and the system grows faster.
Optimization engines. In defining a resolution for an exception or disruption, optimization engines can find the best possible solution far faster than human analysts by exploring tens of millions of possible actions and outcomes, based on rules set by both the organization and industry best practices. These rules target optimal cost and service outcomes, but also recognize and honor constraints. Decision-support algorithms automatically and autonomously identify the best resolution to achieve pre-defined outcomes such as speed, cost or sustainability (or, more typically, the best balance of these). For example, a network-modeling engine might physically move products closer to actual demand to reduce freight costs and CO2 emissions, while also improving delivery speed. A load-building engine will figure out the best way to create fuller, more cost-effective truckloads. Mode-selection engines suggest the best way to actually move products — for example, by full truckload, less-than-truckload, parcel, air, ocean, or rail. Autonomous trucks may not be quite ready for prime time, but increasingly software is routing and re-routing those trucks, and making other critical decisions, in real time. Equipped with AI and ML capabilities, software-based optimization engines also can scan the logistics network for issues, then, in many cases, automatically resolve them based on pre-defined rules. All optimization engines rely on accurate, real-time data streams from across the logistics network.
Data clouds. Companies can no longer rely on static databases to make the right decisions. Instead, they need access to multiple real-time data streams, both internal and external, to monitor changing conditions and pivot immediately. Data clouds provide a single platform that integrates internal data across various systems — including Blue Yonder’s WMS, TMS and OMS solutions — with third-party streaming sources like news and weather. Data clouds eliminate siloes and latency, creating an agile logistics environment in which everyone shares the same real-time perspective, and AI-enabled engines can make the best possible choices. Via its partnership with Snowflake, Blue Yonder makes it easy and seamless for customers to combine the power of its software with the insights of the world’s leading data cloud for business.
Beyond the Buzz
AI, ML, automation, and optimization are more than just buzzwords at Blue Yonder. These advanced technologies form the foundation for our industry-leading logistics solutions — including WMS and TMS solutions that have positioned Blue Yonder as a Leader in three Gartner Magic Quadrant reports1 covering Supply Chain Planning, Transportation Management Systems and Warehouse Management Systems. And we’re investing over $1 billion in research and development over the next three years to ensure that our solutions continue to represent the leading edge in AI, ML and other capabilities.
From retailers and manufacturers to logistics service providers, thousands of companies run on Blue Yonder software every day. Learn how Blue Yonder can help take your logistics capabilities to the next level by contacting us today.
Source:
1 Gartner, “Magic Quadrant for Supply Chain Planning Solutions,” Pia Orup Lund, Amber Salley, Tim Payne, Janet Suleski, Joe Graham, Caleb Thomson, 2 May 2023; “Magic Quadrant for Transportation Management Systems,” Brock Johns, Oscar Sanchez Duran, Carly West, 28 March 2023; “Magic Quadrant for Warehouse Management Systems,” Simon Tunstall, Dwight Klappich, Rishabh Narang, Federica Stufano, 8 May 2023.
