Today’s logistics teams are operating in an environment characterized by uncertainty on three fronts. Customers’ needs and expectations are constantly changing. The available talent pool of drivers, warehouse associates and other employees is small, which creates staffing volatility. And their operating conditions are extremely challenging and unpredictable, from skyrocketing fuel costs and tariffs to blocked shipping lanes and ongoing geo-political conflict.
Minute by minute, logistics providers are asking themselves: What do customers want? Do I have the resources to meet their needs? And can I do so profitably and sustainably?
The extreme volatility of the last two years, which continues today, has starkly demonstrated the need for logistics professionals to monitor real-time conditions across the extended end-to-end value chain, recognize and broadly communicate any changes, and respond immediately in a synchronized, orchestrated manner. The bad news is that older technology solutions and outdated workflows, based on manual handoffs and organizational siloes, no longer support the necessary level of speed and collaboration required by the current environment.
There is good news, however. A new generation of advanced solutions, enabled by artificial intelligence (AI) and machine learning (ML) – has created new supply chain models and new work processes that are purpose-built for today’s extreme uncertainty. These intelligent, strategy-driven solutions help the entire end-to-end value chain enact a fast, coordinated response not only across functions but also across multiple trading partners.
These advanced solutions support real-time monitoring and the ingestion of incredible volumes of real-time supply chain data, which allows logistics teams and other stakeholders to see disruptions at the earliest possible opportunity. Just as important, they connect the end-to-end value chain digitally, so all partners can participate in a shared response. Supported by best-in-class optimization engines that exceed human cognition, they consider every possible response to the disruption, weigh trade-offs and multiple priorities, and — often autonomously — execute the right strategic response across warehouses, fleets and other logistics assets.
Real-time, end-to-end connectivity is the key to truly mitigating disruptions and ensuring that the response is both strategic and profitable. It creates visibility, transparency and accountability across functions and trading partners. The logistics team is not left to struggle alone to mitigate disruptions, but instead acts as part of a unified effort to achieve the best possible service and cost outcome for all trading partners.
This might sound too good to be true, especially to companies still using outdated tools and manual processes. And it’s a far cry from the panicked, on-the fly decisions many logistics professionals were making in 2020 and 2021 — which, unfortunately, were not always profitable. But I can assure you that every day the world’s leading logistics teams are relying on advanced AI- and ML-enabled solutions to maximize both service levels and profit margins, even in the face of the most extreme volatility.
I’ve seen firsthand the very different levels of success companies have achieved over the last two years, which is largely based on the ability of their technology solutions and work processes to combat extreme uncertainty in market demand, available resources and external conditions.
Cases in Point: The Real-World Value of Digitalization
A North American retail customer operates over 1000 stores as well as multiple distribution centers (DCs) in the US. The retail customer completes close to 100,000 store deliveries per year, working with both an import and domestic vendor base. According to its Director of Logistics, the company digitized its freight order management system, creating two-way integration with its existing digital transportation management system (TMS). The company moved from a clunky domestic routing portal, with no routing restrictions and no SKU-level vendor routing, to an intelligent, connected digital system that features a user-friendly interface, as well as SKU-level routing and reporting. Vendor routing restrictions based on weight and volume, as well as vendor-driven bill-of-lading creation, support greater efficiency, compliance, cost control and responsiveness to exceptions.
Digitalization also enables this retailer to optimize its entire logistics network across stores, vendors and DCs. Manual, slow and inaccurate processes have been replaced with automated, optimized practices in such areas as loading, sequencing, inbound order management and cross-docking. Instead of basing key logistics decisions on assumptions, it optimizes its logistics operations based on real-time data about costs, service levels, capacity and other constraints. Real-time access to carriers via a single platform helps this retailer maximize agility and further optimize its transportation spend.
Manufacturers, retailers, and third-party logistics providers can all benefit from digitized logistics. With nearly $21.3 billion in revenues, Bayer Crop Science distributes agricultural products to customers around the world. Johnny Ivanyi, Global Head of Distribution Operation, mentioned in a supply chain and logistics conference that the company is using its advanced TMS to achieve real-time inventory visibility for both warehousing and shipment tracking across its extended carrier network. Advanced analytics help Bayer Crop Science identify exceptions, make fact-based decisions, and respond rapidly. Across the supply chain, increased connectivity with partners is helping to build trust and strengthen relationships. Automation and greater process efficiency are improving reliability, customer service levels, sustainability and cost-to-serve.
Automated bidding events, improved load planning, route optimization and other transportation enhancements support higher service at a lower cost, with a reduced environmental impact. Across 65 countries, Bayer Crop Science is standardizing its processes and adopting best practices. The company is targeting a number of benefits as a result of its digital logistics initiative, including a 3% annual savings in its transportation spend.
Greater Resilience: The Real Value of Connectivity
After two years — and counting — of supply chain volatility, it’s clear that disruption is here to stay. Increasingly, success depends on companies’ ability to manage, and even master, ongoing exceptions and unexpected surprises.
In their attempts to master volatility, it’s important for companies to recognize that no disruption takes place in a vacuum. Just as disruptions affect every part of the extended value chain, that entire chain must participate in executing a response that maximizes outcomes for every participant. Gone are the days when an event is merely a “logistics problem” that must be solved by only the logistics function.
Executing a collaborative, orchestrated response depends on creating real-time connectivity across the value chain via advanced technology. While AI, ML, control towers, data science, predictive analytics and other capabilities are readily available today to help identify and strategically manage disruption, it’s up to each organization to attain these advanced solutions and make the commitment to fully leverage them.
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Terence Leung is Senior Director, Solutions Marketing at Blue Yonder. He has a keen interest in digitalization and the value it generates throughout the supply chain. In this role, he leads his organization to drive thought leadership and go-to-market strategy for supply chain and logistics solutions. In addition, he works with customers to understand requirements and drive best practices in the digital journey.
Prior to joining Blue Yonder, Terence was the leader in product marketing and value engineering at One Network. Previously, he was in leadership positions in industry management at Savi Technology and solutions and management consulting at i2 and Deloitte Consulting respectively. Terence holds an MBA from the University of Texas, Austin and an Electrical Engineering degree from MIT.
