The primary objective of the project was to enhance operational efficiency by reducing the average picking time for orders and minimizing FEFO losses, thereby increasing our revenue.

The current manual picking system causes a significant time wastage for pickers who struggle to locate items without clear information on their placement. This inefficiency not only results in a breach of the First Expiry First Out (FEFO) principle but also increases order fulfillment time. Hence there was a need for a streamlined solution to enhance overall system efficiency.

As the lead designer, I orchestrated a cross-functional collaboration with product, development, QA, and business teams. My responsibilities included crafting the design strategy, aligning user needs with business objectives, and ensuring a seamless integration of an intuitive and efficient digital picking flow.

In navigating the intricacies of the project several constraints shaped our approach to ensure successful implementation.

Resistance to change among the picker workforce might affect the adoption of the new system. A comprehensive training program and effective communication strategies are necessary.

The new UX solution must seamlessly integrate with the existing warehouse management system, considering potential challenges in data transfer and compatibility.

We simplified the flow to cater to a user base with limited education, prioritizing straightforward design over intricate visual aesthetics patterns typically employed to engage customers.

To enhance item location efficiency within the warehouse, we introduced a sophisticated solution by implementing an algorithm with advanced batching logic. This algorithm intelligently combines orders based on factors such as order distances and promised delivery times, resulting in the creation of an optimized picklist.

To guide pickers through the warehouse in the most efficient manner, we devised an optimal pick path derived from the batched orders. To ensure adherence to this path and minimize potential deviations, we made a strategic design choice: presenting pickers with only one product at a time. This focused approach aims to prevent distractions and deviations from the optimized path, ultimately contributing to a significant reduction in picking times and a streamlined order fulfillment process.

In the course of user testing, it became evident that during peak hours, pickers were less likely to rely heavily on visual cues from the screen, instead opting for a rapid scanning approach.

Recognizing that traditional visual error notifications might go unnoticed in such scenarios, we devised a solution by introducing an additional audio cue to alert pickers of any anomalies in the workflow. This auditory feedback ensures that pickers are promptly notified of issues, even when their visual attention is limited, contributing to a more effective and error-responsive system.

During our research phase, it became apparent that pickers lacked real-time awareness of inventory updates, leading to potential disruptions in the picking process. To mitigate this challenge, we implemented a solution where pickers could mark a packet as 'not found,' triggering our algorithm to suggest an alternative packet from a different bin without deviating from the picker's designated path.

If no alternatives were available, the system automatically alerted the hub manager. He would then investigate. If he is able to find the product physically, he reallocates the product into the system. This proactive approach aimed to achieve near 100% order fulfillment, minimizing cancellations.