Analysed existing inventory management and manual reordering practices to identify operational inefficiencies.
Conducted detailed discussions with product category managers to understand category-specific requirements and reorder criteria across different product types.
Applied scientific, data-driven methods to calculate optimal reorder points and reorder quantities, factoring in supplier lead times, demand variability, and minimum display quantities.
Designed and implemented an automated inventory replenishment system for locally procured SKUs.
Integrated the automated reordering solution with existing procurement software to enable real-time updates and ensure seamless adoption.
Implications
67% reduction in manual workload, with automated SKU-level reorder recommendations saving time and reducing operational costs.
Optimised inventory management, preventing stockouts and reducing overstocking, improving capital utilisation and product availability.
Enhanced supplier management, with automated ordering improving transparency and strengthening supplier relationships.
Improved operational performance, as streamlined procurement enabled consistent product availability and improved customer experience.
High-volume automation, with thousands of SKUs reordered daily, minimising manual intervention and improving order accuracy.
Reduced opportunity loss, as timely reordering of high-performing SKUs lowered daily sales losses and improved revenue capture.