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A US-based multinational manufacturer operating across 100+ countries saw its annual logistics costs rise to more than $1 billion by 2022 as post-pandemic volatility, unstable transport rates, and ineffective routing put growing pressure on its global network. Rather than returning to business as usual after the worst of the pandemic, the company chose to redesign logistics as a resilience capability.
The manufacturer’s problem was not isolated to freight inflation alone. EY says the business was running with static annual sourcing strategies, a decentralized operating model that limited visibility across business units, a large and fragmented set of contracts across air, land, and ocean transportation, and weak reporting around shipments, costs, and compliance. In parallel, the company lacked the updated analytics needed to support faster and more informed decisions.
The intervention: move from fragmented logistics management to a centralized transformation program
In 2022, the company launched a logistics transformation with EY structured in three phases. The first phase focused on a rapid-response logistics tower to build visibility, trust, and immediate savings. The second focused on strategic sourcing opportunities across transportation modes and support for negotiations with key providers. The third focused on building long-term capabilities for operational excellence. EY says the company delivered over $300 million in savings in 15 months through this effort.
The early work targeted fast savings first. EY benchmarked the company’s transport spend and found it was overpaying across ocean, air, and over-the-road transportation. In the second half of 2022 alone, the logistics-tower effort delivered $50 million in savings, supported by freight analytics, vendor tracking, and tighter oversight of contracts and spend.
Where the structural gains came from
The biggest operational shift appears to have come from simplifying the provider landscape and standardizing how transport was managed. In North American over-the-road trucking, the manufacturer had been working with about 200 transportation service providers, each with separate contracts and inconsistent pricing across business units. Routes were not optimized, truckloads were underutilized, and vendor relationships had become unnecessarily complex. EY says the provider base was reduced from about 200 to the low 100s, helping the company move toward more strategic carrier relationships.
This matters because the transformation did not stop at sourcing savings. EY says the company also improved how it structured and used logistics data, enabling stronger analytics across a more agile supply chain, better compliance, and stronger support for sustainability efforts. The result was not just lower spend in a declining rate environment, but a more adaptable logistics foundation.
The strategic lesson
This case is useful because it shows that large logistics cost problems are rarely solved by renegotiating rates alone. The manufacturer’s real issue was a combination of fragmented governance, poor visibility, too many provider relationships, and limited analytics. Once those were addressed together, savings followed. EY reports the final result as a 15% reduction in logistics costs across trucking, ocean, and air transportation modes.
The broader takeaway is that supply-chain agility is often built through operating-model redesign, not just digital tools or procurement pressure. In this case, centralized visibility, cleaner provider architecture, better analytics, and a playbook for future disruptions created a more resilient system than the one the company had before. That last sentence is an inference based on EY’s description of the transformation and outcomes.
Why this case matters
For global manufacturers, freight volatility is no longer a temporary problem to absorb and move past. It is a recurring stress test of how well the network is designed. This case suggests the companies that respond best are not just negotiating harder with carriers. They are rebuilding logistics as a coordinated capability across modes, providers, data, and decision-making. That final point is an inference grounded in the case details.
