Case Studies > Unearthing Profitability via Cost to Serve Optimization

Unearthing Profitability via Cost to Serve Optimization

Company Size
1,000+
Region
  • America
Country
  • United States
Product
  • anyLogistixTM
Tech Stack
  • Supply Chain Design and Optimization
Implementation Scale
  • Enterprise-wide Deployment
Impact Metrics
  • Cost Savings
  • Productivity Improvements
Technology Category
  • Analytics & Modeling - Predictive Analytics
  • Functional Applications - Enterprise Resource Planning Systems (ERP)
Applicable Industries
  • Agriculture
  • Chemicals
Applicable Functions
  • Logistics & Transportation
  • Warehouse & Inventory Management
Use Cases
  • Inventory Management
  • Predictive Maintenance
  • Supply Chain Visibility
Services
  • System Integration
  • Training
About The Customer
For over 100 years, Tessenderlo Group, a 1.6B € diversified industrial organization, has been delivering world-class products and solutions around agriculture and bio-residuals. Presently, the organization operates at more than 100 locations across the globe, including 15 production plants and over 100 distribution terminals. Tessenderlo Group is known for its commitment to innovation and sustainability, providing essential products and services that support the agricultural sector and contribute to environmental conservation. The company has a strong presence in North America, where it has experienced significant growth and expansion.
The Challenge
As the population of a market increases, so does the demand for agriculture products. In North America, Tessenderlo has enjoyed steady organic growth since its inception. However, growth does not come without its challenges. With constraints in their network becoming more evident, Tessenderlo recognized transportation asset availability, accessibility of transport modes, production capacity utilization, and operating costs needed to improve. Presented with this daunting task, Tessenderlo quickly realized it was in their best interest to hone in on these challenges by creating a practice dedicated to Supply Chain Analytics.
The Solution
In order to rapidly get their Supply Chain Analytics capabilities off the ground, the Tessenderlo North American team selected anyLogistixTM as their primary Supply Chain Design and Optimization platform given the exceptional customer service and rapid time-to-value for solutions. The initial project Tessenderlo tackled was to optimize the cost-to-serve for two of its core product offerings. These products were produced and distributed out of multiple plant locations, creating complexities around competing production resources, available storage, and transportation assets. With the guidance of the anyLogistixTM team, the Tessenderlo Supply Chain Analytics practice decided on the following approach: Create a baseline scenario model to best understand the current state of the supply chain with a key focus on plant capacity utilization, production costs allocation, transportation spending, and terminal distribution costs. Run a series of scenarios to identify an array of optimal methods to serve end customers. The primary objective was to uncover how asset utilization and associated costs (plant, production, storage, transportation, etc.) varied when shifting production and distribution among the various plants. Review the top 10 scenarios with the Tessenderlo key stakeholder project team to validate the results and decide on the most appropriate future state scenario to implement.
Operational Impact
  • By utilizing the anyLogistixTM platform, the Tessenderlo team achieved the insight and confidence needed to properly redeploy their production and distribution strategy for the two products in North America.
  • The project team will march forward taking a similar approach on the remainder of Tessenderlo’s products and network challenges to identify further opportunities for savings.
  • To ensure continued success and maximize ROI of optimization-driven Supply Chain transformations, the organization plans to leverage the anyLogistixTM platform capabilities on a recurring basis to maintain a pulse on operations while also validating optimization findings.
Quantitative Benefit
  • Savings identified by the project were approximately $1.4MM USD annually.

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