Enhancing Pallet Receiving & Cold Chain Compliance – $8.4M+ in Shrink Reduction
Operational Scale
4.2 million
Pallets
Loss Prevention
$8.4 million
Shrink
Adoption
98% stores
Enterprise-wide
Key Takeaways
Operational Scale: 4.2 million pallets verified in the first two periods.
Loss Prevention: Forecasted $8.4 million in shrink reduction.
Adoption: 98% storewide adoption of pallet scanning functionality.
Implemented a real-time scanning solution that improved pallet verification accuracy, reduced shrink, and increased operational efficiency across enterprise stores.
The UX Problem
Store associates lacked a real-time verification method, leading to errors and inefficiencies.
The lack of tracking visibility disrupted supply chain operations.
The Business Impact
Overstocking of incorrect inventory, increasing shrink risk.
Workarounds where store leaders sold misplaced inventory, causing financial losses.
Store associates previously relied on paper load sheets to verify pallet deliveries, leading to a manual and error-prone process that caused:
Problem Framing (Empathize & Define)
Early Explorations & Trade-offs
Manual Scanning for pallets with missing barcode label → Simple but still required associate effort.
Unload and stage time estimates to help associates better assess their productivity.Storage ID for better accountability of cold chain pallets
Design & Execution (Prototype & Decision-Making)
Challenge Overcome: Driving Adoption
Initial Barrier: Store associates were hesitant to change workflows, citing time constraints and unfamiliarity.
Solution: working with SMEs and store leaders to conduct in-store pilots, refining user training materials and the UX to reduce scanning friction and adding audio cues for real-time correction without slowing down work.
Outcome: The adjustments led to 98% adoption, surpassing expectations.
Design & Execution (Prototype & Decision-Making)
Final UX/UI Screens & Walkthrough
Design & Execution (Prototype & Decision-Making)
User Feedback & Testing Rounds
3 rounds of usability testing revealed the need to track and quantify missing pallets.
Post launch user feedback surfaced the need to use pallet data to inform nightly stocking strategies.
Behavioral analytics insights identified gaps in scanning compliance.Iterative Loop - Unmet Needs (Iteration & Impact)
Key Learnings & Strategic Influence
Leadership in Change Management:
Drove alignment between design, operations, and supply chain teams to ensure adoption.Scaling & Future Considerations from User Research: Explore ways to dynamically update BOH using verified delivery data and automate claims.
Leadership Contribution
Facilitation Coaching: Coached Product Designers in facilitating alignment workshops with business owners.
Democratized Research: Created opportunities for all design team members to conduct field research, regardless of their direct involvement.
UX Research Collaboration: Partnered with UXR to develop study guides for both discovery and post-launch feedback, ensuring insights drove iteration.
Hands-On Contribution
Discovery Leadership: Planned and co-facilitated discovery workshops, aligning business and design perspectives.
Supporting Role: The team asked me to remain engaged throughout problem-solving, and refinement phases, leveraging my expertise in store operations and behavioral analytics.
How we got there: Design Strategy
Fast-track Alignment: Focused on problem framing and gaining shared alignment during Discovery phase, by facilitating fast-track alignment, design workshops.
Tight Collaboration with UXR: Worked closely with research teams to ensure that design decisions were grounded in user insights.
Prototyping & Iterative Testing: Validated the scanning experience early and often with:
Store associates (primary users).
SMEs & Business Owners to ensure feasibility and operational alignment.
Results & Impact
Operational Scale: 4.2 million pallets verified across P1 and P2.
Loss Prevention: 8,000 mis-delivered pallets identified, preventing $4 million in product loss across P1 and P2. $8.4M total business case target by P13.
Adoption & Engagement:
98% of stores using My Day adopted Pallet Scanning.
74% of pallets now scanned via My Day, surpassing the 70% goal.
Process Improvements:
Over 10,000 pallet issues submitted, improving Distribution Center workflows.
Identified top issue: missing pallet stickers, prompting corrective actions.
Iterative Loop - Unmet Needs
Cold-Chain Pallet Tracking Needs Work: Behavioral analytics revealed that users rapidly mark all pallets as “moved into cold room”, casting doubt on tracking accuracy.
Expansion Areas:
Missing Pallet Tracking: Developing tools to track and quantify missing pallets.
Automating BOH (Balance on Hand) Updates: Exploring ways to dynamically update BOH using verified delivery data.
Optimizing Credit Submission Process: Investigating ways to automate claims, reducing store workload.
Enhancing Stocking Prioritization: Utilizing pallet data to inform nightly stocking strategies.
Distribution Center Collaboration: Using insights to drive long-term operational improvements.
Impact Highlights
Operational Scale
User verified in first 2 months
Loss Prevention
Across 8,000 mis-delivered pallets
Adoption
Adopted Pallet Scanning feature