Project Case Study: LCBO Supply Network Analysis
Investigate the Impact of Various Warehousing Strategies
The Liquor Control Board of Ontario (LCBO), a provincial Crown corporation with headquarters in Toronto, Ontario, Canada, is one of the world’s largest buyers and retailers of beverage alcohol that offer more than 20,000 products annually to consumers and licensed establishments.
LCBO approached Visual8 to develop a Supply Network Simulation model of its entire LCBO supply-network that would provide a fast and user-friendly simulation tool that would generate graphical and informative reports.
After an initial Supply Chain simulation model project phase, a more detailed operational model of LCBO’s supply chain system was expanded using the previous high-level simulator.
The Supply Network Simulation model would investigate the operational and financial impact of various warehousing strategies for the product supply to the current and planned LCBO stores. The warehousing-distribution system would allow for the analysis of various components of the supply network and assess the complex interactions between them.
Using SIMUL8 software, Visual8 expanded upon a previous LCBO warehouse operations simulation model into a more detailed operational model of the LCBO supply network. The model accounted for a range of operating issues related to warehousing and product distribution across the supply chain including the extended range of products and the individual management, and handling of the products through the supply chain network. Resources are modeled as a constraint on operations at receiving, put-away, picking, packing and shipping.
The Supply Network Simulation represented a number of factors that affect the supply chain including:
- Working rates,
- Resource availability,
- Shifts and labor costs, including overtime.
An evaluation of the costs including labour (with overtime), inventory carrying, and shipping, as well as operational reports on resource utilization and inventory levels over the course of the simulation were generated for assessment.
The tool provided a more accurate recommendation on inventory levels through a higher resolution of products than the group levels defined within the initial project. This provided a wider range to assess seasonal or promotional effects on supply costs and inventory levels.
The supply-network simulation provided a user-friendly interface that allowed the users to easily configure and test various scenarios and policies. Using actual and projected demand data, segregated by product categories, seasonal periods, and geographical store locations, the simulation provided valuable insight into current and future state scenarios.
The supply-network simulation tool provided the flexibility to address a wide range of scenarios such as:
- Increasing the number and type of stores,
- Changing the storage capacity, handling rates, and location of the supplying warehouses, and
- Assessing the method of supply, which included the introduction of sub-warehouses in the field for cross-docking product to local stores in a particular region.
The potential cost-savings of 10-15% in productivity improvements and reduced operating costs were realized in the supply network simulation model.