This is the story of how one of the nation’s largest food distributors turned post-acquisition complexity into synergy with help from Sophus Technology’s advanced network optimization platform.
Organic Expansion
After decades of growth, the company had become a household name in food service and distribution. Its operations stretched from coast to coast. Products sourced from suppliers and producers flowed through a maze of mixing centers, regional hubs, and distribution centers before reaching restaurants, grocery chains, and retailers nationwide.
Acquisition and Overlap
Acquisitions are common in the food industry, often helping companies expand their regional reach. But in 2021, this company underwent its largest acquisition ever—merging with another major national distributor.
When the merger was finalized, executives quickly realized that two massive distribution networks—each built independently over years—were now stacked on top of each other. The result: significant overlap in facilities, redundant lanes, and unbalanced regional coverage. Some regions were overserved, while others remained strained.
“We had situations where two trucks—one from each legacy company—were delivering to the same customer on the same day,” one executive recalled. “That’s when we knew we needed to take a hard look at the network.”
Consolidating such a vast, multi-tiered system, however, was far from simple. The network had complex dependencies:
- Certain suppliers and producers were required to ship through specific DCs due to food safety and labeling regulations.
- Others were restricted by cold-chain requirements or DC capacity limits.
- And most critically, service levels could not drop—restaurants and retail partners depended on daily or even same-day replenishment.
Let’s bring in Network Optimization!
Facing pressure from the board to deliver post-merger synergies, the company turned to Sophus Technology, known for its supply chain decision intelligence.
The mission was simple in principle but complex in practice:
Reimagine the entire U.S. network footprint—reduce redundancy and cost—without compromising service reliability.
The scope was massive, encompassing thousands of nodes:
- National and regional suppliers,
- Dozens of mixing centers and distribution hubs,
- Hundreds of thousands of transportation lanes and modes (from refrigerated to dry freight)
- Thousands of customer delivery points across the United States.
Data came from multiple systems—ERP, transportation rate tables, and historical order and shipment records. Using the Dastro ETL engine, Sophus integrated, cleansed, and transformed these datasets efficiently
Then with a solid data foundation in place, the SophusX network optimization engine went to work—running millions of potential configurations to identify the most efficient combination of facilities, flows, and inventory levels.
Each scenario incorporated dozens of real-world constraints:
- Which suppliers could serve which DCs,
- Storage compatibility,
- Labor and handling costs,
- Regional transportation rates and modes, and
- Minimum service levels and lead-time guarantees.
Sophus’s optimization model went beyond cost-cutting—it balanced cost, capacity, and service, ensuring that the final recommendations were not just efficient, but operationally achievable.
The Science of Simplification
What set Sophus apart was its ability to transform a chaotic network into a visual, data-driven “digital twin.”
Executives could literally see on an interactive map how each facility contributed to the overall network, how closing or consolidating a site affected costs and delivery times, and how inventory would flow under different demand conditions.
Through dozens of scenario runs, the Sophus and client teams jointly explored practical questions:
- What if we expand mixing capacity in the Midwest instead of building new cold storage in the Southeast?
- How much could we save by rerouting shipments directly from mixing centers to key retail customers, bypassing regional hubs?
Each “what-if” scenario was tested against the current baseline, ensuring that every decision was grounded in measurable trade-offs—not assumptions.
After weeks of analysis and validation, a clear pattern emerged: the company was operating nearly 20% more facilities than necessary to maintain its service levels. Redundant hubs in several regions could be merged or repurposed, freeing up capital and reducing transportation miles—all without affecting on-time deliveries.
The Results: $20 Million in Annual Savings
When the final recommendations were presented to the executive board, the numbers spoke for themselves:
- $20 million in annual logistics and operating savings identified across the network.
- A roadmap for an optimized facility footprint, outlining which plants and DCs to retain, expand, or consolidate.
- Smarter inventory placement, reducing excess stock in low-demand regions while improving availability near high-demand zones.
Perhaps the greatest outcome was clarity—for the first time, the company had a transparent, data-backed view of how its supply network operated as a single, interconnected system.
“Before Sophus, our decisions were based on local experience and instinct,” said one vice president. “After Sophus, we were making enterprise-wide decisions backed by hard data and visual insights.”
A Roadmap for Dynamic Growth
The Sophus roadmap didn’t just optimize costs—it gave the company a blueprint for the future.
It showed how the network should evolve as demand shifts, new customers are added, or product categories expand. It identified which sites could serve as flexible hubs during seasonal surges and which locations should be prioritized for automation or expansion.
In essence, the company’s supply chain transformed from a static structure into a living, adaptable network.
Today, Sophus continues to partner with the company—enabling its team to instantly simulate the impact of market changes, new contracts, or logistics disruptions and make proactive, data-driven adjustments.
From Complexity to Confidence
In a world where food supply chains face constant volatility, continuous network optimization has become essential.
By combining advanced analytics with practical business insight, Sophus helped this food distributor achieve exactly that—agility with confidence.
The $20 million in identified savings was impressive, but the real victory was cultural. The company now approaches every decision—warehouse renewals, transportation contracts, customer onboarding—through the lens of data-driven design.
About Sophus Technology, Inc.
Sophus Technology, Inc. is a global leader in AI-powered supply chain decision intelligence, helping enterprises design, optimize, and manage their end-to-end networks. From production to distribution, Sophus empowers businesses to make smarter, faster, and more sustainable decisions through its advanced optimization and analytics platform, SophusX.
