Network Modeling and Optimization: Building Stronger Customer Service Levels with Cost-Effective Supply Networks
From source of supply to delivery of product to the customer – the supply chain journey starts with a simple request that often leads to unexpected complexity and expense along the way. Customer demands for on-time performance and customizable delivery options are increasing every year. Profit margins are under constant pressure as costs creep up across the global, complex supply networks. Further, the lack of visibility and insights for controlling costs can result in rising operational expenses that challenge the bottom line.
Is your supply chain creating the value you expect? Improving customer service levels while reducing costs is a great formula for improving the customer experience and profitability, but you need to understand how altering one variable in the network equation may impact one or all of the others. Higher service levels can come with higher end-to-end network costs necessary to maintain those levels. Consider a company evaluating how to reduce the shipping distance from a supply location to a customer. They may need to add stocking locations, for example, and that translates into additional operational costs for incremental warehouse locations and inventory. The question that’s critical to answer is: Are the additional costs worth the increased service levels?
Understanding supply chain performance requires deep visibility into your network, and a comprehensive understanding of whether specific changes under consideration will improve service levels and reduce costs, or just increase cost without driving optimized delivery performance and supply chain agility.
That’s why Network Modeling and Optimization is so important. It helps you to answer business-critical questions such as:
- Is our network footprint aligned to provide the right service level to our customers?
- How can we ensure that products are stocked at the right locations across multiple distribution centers?
- Are we aligning our customers’ requirements with the right supply chain solutions to meet their requirements and build their loyalty?
Network Modeling and Optimization for the Real World – A Molex Case in Point
To further illustrate the essential nature of Network Modeling and Optimization, let’s look at how our own global logistics team evaluated optionality around Molex’s supply chain hub network. With 18,000 suppliers, and 80+ plants in 38 countries, Molex is a tremendous example of global supply chain complexity. And, as we drilled in to explore our the full extent of our network, wehad significant origin and destination pairs, transiting east to west to make product available to customers in multiple locations. We wanted to understand if our supply chain network was aligned to our customers’ needs. We wanted to gain a deeper insight into whether our products were stocked at the right locations and what logistics cost were incurred when they were not. And we wanted to evaluate if multiple supply chains hubs were necessary, or if we could accomplish our desired service level with just one.
We modeled the options with some key assumptions. For example, in one scenario, we assumed a state where we eliminated a supply chain hub and reconfigured our entire network. In an alternative option, we ran our entire network through a single hub to assess how it would impact our customer service levels. We also considered risk levels, including a scenario where disruption at a single hub had the power to impact the network –- and how to mitigate it.
We also developed a model that identified potential hubs where we should consider relocation. The model demonstrated the impact of these relocations, answering questions such as what is the cost impact of moving the supply chain’s center of gravity closer to a specific customer? And what are the corresponding impacts to reducing shipping timeframes? The result was highly informative. We gained a clear vision of the financial impact of operating with one supply chain hub, two supply chain hubs, etc., as compared to utilizing our broad baseline network.
The insights were revealing. We determined that the potential improvement in service levels, potential relocations, coupled with the associated cost did not create significant benefit to justify the change. Why? While moving a hub closer to our customer would reduce the distance, the overland distance from the west coast port where the product was delivered would be greater. So, the efficient optimization of cost vs. benefit called for no change. Our models also identified potential risks to customer service levels if we experienced a disruption in our relocated hub. As a result, changing the Molex network in this particular case was not justified. To assess similar scenarios for different customers, the same process was considered.
It all Comes Back to the Customer
Molex’s network modeling and optimization efforts all map to the same bottom line: How can we meet customer expectations by improving service levels, agility and cost across the supply network? Business to Business (B2B) professionals expect the same service levels they receive in their personal lives, demanding higher “personalization” and more agile supply chain solutions. To win, organizations must respond with a customer-centric supply chain that can provide optimized networks that create unparalleled flexibility, speed, agility, resilience and real-time response to disruption.
Network Modelling and Optimization is simply essential for companies trying to stay competitive in today’s global economy. This is why Molex has invested in systems, knowledge processes and subject matter experts to support Network Modeling and Optimization — as a foundational supply chain capability.