Practical solutions to a complex problem
Aligning your supply chain’s design with your business goals and strategy is key to your organization’s profitability but not a trivial computational exercise. The volume of data required and the complexity of the calculations grow exponentially with the size of the operation.
At Technologix we have been modeling and optimizing supply chain designs for the past 25 years. We have supported dozens of projects in a consultative role and implemented numerous fully integrated applications used for both design and ongoing planning purposes.
Opti-Net™, our advanced planning and optimization modeling platform, consistently generates valid and sound solutions without taxing its users with hours upon hours of data manipulation and related 'behind the scenes' tasks.
That is why our very first client is still our client 25 years later.
Questions our projects will answer:
What is the optimal combination and configuration of plants, suppliers and warehouses?- Do we need to add new facilities? If so, when? Where? What type and size?
- Do we need more production capacity? If so, when? Where? Which Lines?
- Is our current sourcing strategy sound?
- How profitable are our markets and products?
- How re duties and tariffs affecting us?
- What congifuration and policy changes are needed to support our new omni-channel strategy?
- How does our service level target impact costs and margins?
Case Study
Optimizing a Large Agribusiness Network
Nutrien (previously Agrium) is a major retail supplier of agricultural products and services in North America, South America and Australia and a wholesale producer and marketer of all three major agricultural nutrients and a supplier of specialty fertilizers in North America.
The organization was searching for a strategic supply chain network modeling tool and commissioned Technologix to implement an earlier version of the Opti-Net™ platform.
The Agrium supply chain optimization system became one of our most successful and long-standing solutions. The actual mathematical model was relatively large, incorporating roughly 6,000 shipto destinations, over 60 plants and warehouses, 20,000 demand records, 45,000 customer freight lanes, 100,000 decision variables and 500,000 coefficients.