How Optimizing Network Flows Can Improve Growth Plans
The lessons learned at this stage can help to avoid missteps before the network has to handle higher product volumes.
Latest NewsHoneywell rebrands Intelligrated business in latest step of integration process Sharpen Your Competitive Edge with B2B Managed Services Lanetix Launches Collaboration Suite in Response to Digital Disruption NextGen Supply Chain: The new look of supply chain automation Ports address climate change More News
Latest ResourcePlan. Manage. Recover. The power of risk management and resilience. Savvy supply chain managers are putting risk management at the top of their to-do lists, planning for the recovery following inevitable disruptions.
Editor’s Note: Every year, 40 or so students in the MIT Center for Transportation & Logistics’ (MIT CTL) Master of Supply Chain Management (SCM) program complete one-year thesis research projects. The students are early-career business professionals from multiple countries with 2 to 10 years of experience in the industry. The research projects are sponsored by and carried out in collaboration with multinational corporations. Joint teams of company people, MIT SCM students, and MIT CTL faculty work on real-world problems chosen by sponsor companies. In this monthly series, we summarize a selection of the latest SCM research. The researchers for the project described below, Ann-Marie Chopyak and Haotian Lee, developed an optimization model for a distribution network for their MIT Supply Chain Management Program master’s thesis. The sponsor was a company in the garment rental business, and the project was supervised by Dr. Bruce Arntzen, Executive Director, MIT Supply Chain Management Program. For more information on the program, visit http://scm.mit.edu/program.
Optimization models are commonly used to identify cost efficient network flows. This tool is especially useful for modelling complex flows, for example when various products move through a distribution network via multiple paths and transportation modes.
But companies should also be aware of how optimization models can show the possible impact of business growth on network efficiency before embarking on expansion plans. The lessons learned at this stage can help to avoid missteps before the network has to handle higher product volumes.
Focus on cost
The MIT CTL researchers built such a model for a uniform rental company. The company’s largest segments are rental, first aid & safety, and facility services. Two of these divisions use less than truckload (LTL), while the third ships by truckload (TL.) Additionally, one of the LTL segments uses an intermediary distribution center (IDC), while the other bypasses this point and moves directly to the regional distribution center. The TL category also bypasses the IDC.
The objective of the research project was to minimize distribution center (DC) and transportation costs. DC costs consist of fixed operating costs, variable handling and holding expenses, and opening/closing/expansion costs. The company’s transportation team worked with their largest carriers to obtain lane rate information for new and existing lanes. All rates were based off corporate discounts that were in force as well as historical volumes that could potentially be switched to the new lanes.
In order to account for network flow and capacity, suppliers were grouped into three main regions and customers were separated into 17 regions. Historical volumes were calculated for each region. The DCs helped to analyze annual flows through respective facilities.
Possible growing pains
The optimal solution proposed a network that used fewer company operated facilities. Another recommendation was to establish DCs in new locations to realize transportation cost savings. Transportation rates proved to be a sizeable factor in all model iteration outcomes and, as volume increased in certain iterations, variable rates became more influential.
This outcome highlights the importance of accurately projecting the growth of a company and the location of that growth, before making changes to the current network. For example, given current demands, the model suggested closing some facilities to achieve efficiency. But when the demand was increased by 10 percent and 20 percent to represent the actual growth rate, these same facilities were opened up again and expanded.
Shifts in supply or demand volume in certain regions will likely influence where a DC should be located. Therefore, additional ports or supplier regions should be considered in building a network that will support the future growth of the company. Additionally, if sales are expected to increase, then potential DC variable costs should also be a crucial consideration in making a final DC opening or closing decision.
Additional cost and demand analyses are required to reflect the future state of the business and show the optimal distribution model for the company moving forward.
About the AuthorPatrick Burnson, Executive Editor Patrick Burnson is executive editor for Logistics Management and Supply Chain Management Review magazines and web sites. Patrick is a widely-published writer and editor who has spent most of his career covering international trade, global logistics, and supply chain management. He lives and works in San Francisco, providing readers with a Pacific Rim perspective on industry trends and forecasts. You can reach him directly at [email protected]
Subscribe to Supply Chain Management Review Magazine!Subscribe today. Don't Miss Out!
Get in-depth coverage from industry experts with proven techniques for cutting supply chain costs and case studies in supply chain best practices.
Start Your Subscription Today!