Data-driven stock replenishment for higher inventory turnover
BeverageCo. struggled with the wastage of its end-of-life products at the central warehouse. In addition to its own products, BeverageCo. also sold third-party products. BeverageCo. assorted its products into seasonal, specialities and sale-to-order segments. Furthermore, these products were often switched from one assortment to another based on their sales. Thus, it would become challenging for BeverageCo. to estimate their optimum inventory level which led to product wastage in many instances or low-service level in some.
600SKUs analyzed for the project
1Economic order quantity tool developed
ERP system uses incomplete historic data to forecast the quantities leading to wastage cost and low service-levels. How to optimise order quantity?
BeverageCo. maintained 500-600 SKUs at its warehouse. The ordering and inventory levels were handled based on ERP, however, this system in many cases used incomplete historic data to forecast the quantities needed for stock replenishment. This led to high wastage cost and low service-levels for many products. Thus BeverageCo. wanted to utilize a data-driven model to predict optimal order quantity of SKUs. The goal of the project was to support the ordering decision by creating a user-friendly tool to determine the optimal size and reorder level.
SCG conducted a three-phase project:
Phase 1 – Map the current process and identify associated challenges
In this phase, the existing stock replenishment process was mapped from order placement to delivery using SIPOC and deployment diagrams. Using these tools, cross-functional flowcharts were developed that described details of the process along with the roles of involved departments and stakeholders. Process mapping helped identify areas of improvement for each stakeholder at each activity level in the replenishment process.
Phase 2 – Segmentation of products based on sales and demand
Once the process challenges were identified, SCG's agile workforce then conducted ABC-XYZ product segmentation based on the products’ contribution to sales and their predictability of demand. Based on this ABC analysis, BeverageCo. products were divided into 3 different groups. For each of these groups a separate replenishment process SOP was developed which included the recommended inventory level and stock monitoring interval.
Phase 3 – Tool creation and user training
In the final phase, SCG's agile workforce created and validated a user-friendly, excel-based EOQ tool with user guide and technical documentation for BeverageCo. The tool highlighted inventory turnover, holding cost and service levels achievable for any selected SKU. The recommended ordering quantities and timing of when to place the order could also be seen in the results sheet. Using this tool, BeverageCo. could make more accurate order replenishment decisions in its warehouse.
SCG’s on-demand workforce provided BeverageCo. with a comprehensive understanding of its replenishment process. In addition, a concrete analysis tool was also provided to aid in accurate replenishment decision-making. This project accelerated progress on BeverageCo.’s inventory optimisation efforts by 6 months.
"We focused on the current state analysis with the objective to identify key areas of improvement. I was impressed by the dedication of the project team to bring outside-in view, to evaluate our concrete business activities and to find out the most essential from the big data elements."
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