Transportation Logistics Software for Facility Location

Retailer Identifies Location for Second Distribution Facility

 

This study involves a mid-size retailer operating stores grouped into three main divisions. All three divisions offer an extensive assortment of retail merchandise including both hardlines (toys, health and beauty aids, housewares, furniture, sporting goods, snacks, etc.) and softlines (clothing, accessories, jewelry, etc.).

 

Background

Being a 50+ year old company, the retailer grew through acquisitions but has always operated from their only distribution center in North Carolina. Store deliveries were made with their private fleet. As they extended to the South West, it became obvious that all stores cannot be delivered from the location in North Carolina. Some of the stores were over thousand miles from the distribution center adding to transportation cost in form of driver wages and assets tied up on long hauls. The question then was where the second distribution center should be located.

 

Defining the Needs for a Logistics Optimization Software

The retailer turned to KEOGH Consulting, a Supply Chain consulting provider, for this analysis. Needing a quick turnaround, KEOGH reached out to Paradox to use Paradox Routing Tool (PART), a logistics optimization software. The objective of the study was to identify the candidate location, evaluate reduction in transportation cost, and then weigh it against costs of operating the second facility.

 

Armed with store locations and average week delivery volumes, KEOHG used PART's center-of-gravity model to identify the second facility. The center-of-gravity model works to minimize weighted distance across the network. It conducts an exhaustive search for required facilities and selects those that result in least aggregated product of distance and demand of each store from its assigned distribution center. This analysis led to identifying Birmingham, Alabama as the location for the second facility. With this as the second facility and assigning each store to its nearest distribution center, all stores were within 500 miles from their assigned distribution center and the average distance of store from distribution center was cut in half from about 400 miles to less than 200 miles.

 

Before estimating transportation cost for the new network (two facilities), the retailers' delivery routes were simulated to establish the baseline transportation cost. Delivery routes were built with average weekly shipping volumes. In building the routes, the retailer's operating parameters were defined for the routing engine. Store delivery windows, maximum route time and distance, allowed layovers per route, unload rate to estimate service time at each store, truck capacity were some of the operation specific parameters modeled for the solution along with the standard constraints such as DOT hours of service regulations.

 

Upon locking the location for the second facility, the routing solution for the new network was developed by running the engine with both facilities and revised store assignment.

 

Results

Results from routing analysis included:

  • 44% reduction in annual transportation cost

  • Savings per route- 41% reduction in route time- 43% reduction in route miles

  • 2 fewer routes

 

The retailer and KEOGH Consulting were pleased with the solution and the quick turnaround. The whole analysis took less than a week, discounting the time for data cleanup. It was felt that had they selected a high-end network optimization tool, the model setup itself would've taken a week or two.

 

The job was not done for the retailer though as they now have to evaluate the 44% reduction in annual transportation cost against the annual cost of operating a facility in Birmingham and ROI analysis if they decide to invest in building the facility.

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