Network Optimization Overview for Bulk Commodities

Many organizations suffer from distribution networks that have evolved over time, often morphing based on ad hoc decisions or siloed and/or conflicting viewpoints between sales, operations, logistics, customer service, and finance.  Such evolutions, often made without sufficient data or holistic approaches, result in inefficiencies that add cost and diminish service performance.  Network optimization modeling, scenario analysis, and implementation strategies using best tools and practices are ideal to ensure decisions are data-driven and positively impact customer service and the bottom line.

What is network optimization? Network optimization is the process by which an organization can determine optimal design of a supply chain network that takes into account the myriad of inputs, including transportation costs, distribution site location, inventory levels, and other factors that can influence profitability and customer service.  There are multiple trade-offs to be considered, and complex modeling is usually required to account for all of the variables.

The ultimate goal is for supply chain networks to achieve the most efficient designs with optimal locations and capacities that fulfill customer demand with the lowest possible long-term costs.

Elements of a Typical Network Optimization Solution

A typical network optimization solution includes, but is not limited to:

• Identifying inefficiencies from both  holistic and lane-by-lane points of view
• Modeling network variations  in the no-risk environment of software tools first, before committing to high-stakes capital and operating expenses
• Using network optimization tools to get a complete view of current inventory in the supply chain, evaluate infrastructure, and  develop strategies to serve new customers.
• Developing a thorough understanding of existing and supporting capabilities and capacity before entering or exiting markets

With network solution modeling, organizations can:

• Decide whether to utilize their current assets/sites or assess greenfield facilities and locations to fulfill customer needs
• Evaluate the costs and constraints of existing vs. new infrastructure
• Understand network capacity and, using various demand projections, determine a stable strategy for facility location and size
• Use data to evaluate labor, facility and transportation trade-offs when making facility decisions

Example below illustrates two independently operated companies. After two companies merge, network optimization provides the most efficient network structure.

Aiming to cut costs and maximize profitability, many global and regional organizations have created a complex supply chain footprint. For stakeholders in these organizations looking to make significant tactical and strategic decisions, network optimization is critical.

Approaches and Key Steps in Network Optimization

There are six critical steps in assessing and optimizing a distribution network, regardless of commodity or product:

1. Baseline Development and Validation: Develop a baseline network model that describes the current, existing operating network as a benchmark. The validation process ensures the model can represent at least 90% of the cost and network demand.Through baseline validation processes, companies often find quick wins to make easy adjustments within their operating network. This is also referred to as baseline optimization. Because of the complexity in gathering, validating and cleansing critical data, the baseline development stage typically has the longest lead time.

2. Base Case Development: Once a baseline model is set and validated, future forecast demand and known infrastructure changes should be applied to the model to create a base case model. Depending on business dynamics, the base case model can provide near term beneficial operating results. Based on comparison with baseline and business objectives, organizations can make tactical or strategic adjustments to ensure the business is on the right track.

3. Base Case Optimization: From the base case model, you can see inefficiencies within the network such as material sourced from uneconomical lanes, products distributed from the wrong warehouses and demand fulfilled by multiple, disparate locations. Base case optimization provides the most efficient supply chain without significant changes to existing network infrastructure. Companies should consider resource and capacity constraints in this stage of optimization. Trade-off analysis can be completed when applying different levels of constraints.

4. Scenarios and Hypothesis: This stage of optimization typically goes through the following sequence:
   • Unconstrained greenfield scenario: No capacity and resource constraints, and no existing manufacturing and warehousing locations. Let the model capture least cost infrastructure that can fulfill demand at required service level.
   • Consolidate existing infrastructure by reducing manufacturing and warehousing locations to model cost and service.
   • Expand infrastructure by adding manufacturing or warehousing locations to model cost and service.
   • Relocate existing manufacturing or warehouse locations to hypothetical places to model cost and service; typically combined with consolidation and expansion.

5. Comparisons and Recommendations: List and compare all scenario results generated by the model. Highlight pros and cons, conduct trade-off analysis, and tweak more model scenarios if needed. Provide best-case recommendations to business stakeholders to consider for implementation.

6. Risk Profiling and Implementation Road Map Development: This last step ensures a smooth implementation by detailing an implementation schedule along with potential associated risks and tactics to minimize negative impacts.