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Design Your Transportation Network to be a Competitive Advantage

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Many supply chains are the product of history, developed over time as a company grows with expanding product lines and emerging markets. In larger successful companies supply chains can grow to enormous complexity, encompassing billions of dollars in assets and cemented by deeply ingrained processes.

If an organization continues to gain market share, acquires other companies and strengthens its brands, there may be an assumption that the supply chain and transportation network, while not perfect, are functioning to an acceptable degree of efficiency. But what if it’s not a great supply chain? What if it’s simply an optimized version of an inefficient supply chain? For most transportation and logistics professionals, this is a challenging question to answer because it requires visibility into the full supply chain network and the balancing of numerous performance metrics, including service, cost, complexity, sustainability, and risk.

How can you design a transportation network that can achieve its full potential? Only through computations that isolate your legacy infrastructure and model the data with a ‘what if’ freedom. Transportation optimization is a rapidly-growing analysis approach that enables companies to create digital “models” of their end-to-end supply chains to evaluate new strategies and identify break-through performance improvements.

Define Efficient Routes, Reduce Landed Cost, Optimize Mix and Mode, and Test Service Levels

Using advanced algorithms, you can define transportation routes to minimize the cost of inbound or outbound shipments, while considering realistic cost and constraint structures. This helps answer the question, “what happens to transportation routes when the network design is changed?”

LLamasoft® Supply Chain Guru® transportation optimization enables you to baseline existing routing strategies and test new strategies to predict actual costs and service levels. Create optimal daily, weekly, monthly or quarterly plans to define optimal distribution routing. Supply Chain Guru enables you to model your entire supply chain network, incorporating alternative transportation options and key variables such as cost, time, capacity and delivery parameters. Identify your optimal transportation plan based on total costs and service constraints.

Transportation Optimization Delivers Tangible Business Benefits

The following are a few real-life examples of how businesses are using transportation optimization to achieve lower costs, better service, and more efficient operations

Challenge Legacy Transportation Networks Is you best option to optimize ‘as-is’ or to re-engineer a new network? Test the effects of new modes or product flow patterns. Evaluate importing through new ports or adding cross-docks. Answer these questions with concrete data and visual references.
Determine Lowest Overall Landed Cost Incorporate inventory, sourcing, production, service levels and other constraints to understand true lowest landed cost solutions for your global transportation network.
Identify Optimal Mode Mix Test and understand trade-offs for ocean vs. air, TL vs LTL, or rail vs. road given your global supply chain network flows and costs, and scale the model to include all required SKUs and shipments.
Create More Efficient Routings Locate backhaul or continuous move opportunities, or consolidation of both inbound and outbound shipments to reduce empty miles and labor requirements. Choose from various vehicle sizes and carriers and consider multiple cost types related to distance, stops, subcharges and discounts, driver time and overnight hauls.
Model Asset Utilization Against Service Metrics Identify the most efficient use of your vehicles, or containers, by modelling and optimizing the transportation as it relates to customer service.
Design a More Sustainable Transportation Network Calculate the emissions associated with as-is and new transportation network strategies or optimize the network to achieve a specific reduction target while also meeting performance criteria.
Balance the Trade-offs Between Service & Cost Using scenarios in transportation optimization to understand the cost impact of delivering within strict delivery windows and identifying the opportunity cost associated with relaxing these constraints.

Network Optimization and Transportation Optimization Working Together

What effect would changes in your supply chain design have on your transportation strategy? Network optimization on its own is very useful to identifying high-level costs associated with transportation. However, it only uses average costs and shipment sizes with no concept of multi-stop routes and cannot answer the question of how routes might change when the network changes. Transportation business problems can range from basic route design including multi-stop, backhaul, and cross dock consolidation configurations, cost-to-route calculations, fleet sizing with asset mix, and mode selection. The two technologies complement one another. Using transportation optimization you can verify the route efficiency of network sourcing allocations outputs. Additionally, transportation optimization’s outputs can help in calibrating lane based costing allocation for network design. Network optimization is the right tool for evaluating sourcing, production or inventory decisions but is even more powerful when used in tandem with transportation optimization. The following are examples of how transportation and network optimization can be used together.

Prove Optimal DC-to-CustomerAssignments Determine the optimal assignments of DCs to customer or retail locations to achieve the lowest cost solutions that still meets service level targets. Rebalance assignments as new customers or stores are added to the network
Evaluate Network Footprint and Greenfield Locations Identify the optimal structure and footprint of distribution, production, or sourcing sites or use advanced greenfield technology to find the ideal location for new facilities.
Model Warehouse Capacity Against Service Metrics Using NO you can model warehouse capacity and optimize with the transportation network to ensure optimal service metrics.

Business Case Examples

Optimizing Logistics Network Helps Shipping Company Meet Commitments and Save Millions

A large shipping company had an organically grown distribution network of more than 154 terminals. The network had never been fully optimized, and what optimization had been done was primarily around their 9 a.m. service delivery guarantee, even though only about 2 percent of their order volume was attributed to this service. In addition, margins can be tight in the logistics business as customers naturally look to save money. Their management wanted to see if they could optimize their network to lower their costs and still deliver the same high level of value and service for which the company was known.

Together with LLamasoft, the shipping company’s supply chain team used Supply Chain Guru to gain perspectives on the network from several different angles. The team developed a baseline model of the existing network, then developed the model across several time horizons: 3, 5, and 10 years. Through this, they ran over 100 different scenarios that examined existing nodes, with an eye toward right-sizing footprint and optimizing location, plus 23 potential greenfield locations. They also looked at the potential impact of changing the mode of transportation between nodes, e.g., adding rail lanes between locations where it was available.

To further optimize the transportation, they did a detailed analysis of several delivery changes including:

  • Using subcontracted shippers for some shipment types.
  • Changing the delivery time requirements for some of their offerings.
  • Shipping in two waves, sending the early AM deliveries out first.

By optimizing transportation alone, they could save as much as $12 million CAN. In addition, the model demonstrated that the organization could close as many as thirty of its nodes without impacting delivery commitments. In total, the project showed a potential savings of $18-27 million CAN.

Land O’Lakes Uses LLamasoft Transportation Optimization for Acquisition Rationalization and Outbound Shipment Consolidation

After conducting a large acquisition, Land O’Lakes needed to model the impact of integrating the new product line into its existing network versus using the acquired company’s existing network footprint. Traditional network optimization would allow Land O’Lakes to see where additional or reduced products would be necessary, but wouldn’t allow them to see the impact of combining these two networks on the company’s consolidated outbound transportation. In addition, in a separate Land O’Lakes division, about 80 percent of products are made and distributed locally, and the remaining 20 percent are made and transferred to other facilities, then distributed to customers. The company wanted to capture the ‘cost-to-service’ of the latter products and analyze the effect of using regional distribution centers to service these items on outbound shipping.

Land O’Lakes used LLamasoft transportation optimization and simulation modeling in conjunction with network optimization to approach these network challenges. They created multiple scenarios to compare the effects of alternate network configurations. Land O’Lakes also conducted regional transportation modeling analysis for the other division by building six separate models to baseline local facilities.

With more modeling projects still in progress, Land O’Lakes has identified a scenario for consolidation which would reduce outbound cost by 20 percent per pound. While fluctuations occur due to the state of the current distribution pattern, Land O’Lakes can cite between six and 10 percent in transportation cost savings by simply adjusting order patterns.

Why LLamasoft?

Supply Chain Guru provides a digital model of your supply chain, enabling you to evaluate alternate sources, routes, transportation modes, or production processes that may be required to meet your desired services levels. You can introduce disruptive events into the model to better understand the robustness of your supply chain. From the optimized model results, you can make informed decisions about the nature and timing of supply chain network design alterations

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