Develop a data-driven approach to optimize the warehouse layout by leveraging Association Rule mining
Current Situation: Warehouse agents have reported inefficiencies in the current warehouse layout, leading to increased picking times and fatigue.
These inefficiencies are likely due to inefficient inventory management within the warehouse.Order picking efficiency refers to the speed and accuracy with which workers can select items to fulfil customer orders.
Proposed Solution:
- Utilize the annual sales data to optimize the warehouse layout.
- To identify frequently co-purchased SKUs (Stock Keeping Units) and strategically placing them in close proximity, thereby improving order picking efficiency and reducing fulfilment time.
By analyzing annual sales data, following are identified:
-
Top N SKUs: The products contributing the most to overall sales
Frequently co-purchased SKUs in close proximity to minimize travel distance during order fulfillment.
This information can be leveraged to develop a revised warehouse layout that strategically places high-demand SKUs in easily accessible locations for quicker picking. The expected outcomes include:
- Increased order picking efficiency through reduced travel distances and optimized product placement
- Reduced agent fatigue and frustration by minimizing unnecessary movement.
- Improved customer satisfaction through faster fulfillment times.