Enhancing Pallet Receiving & Cold Chain Compliance – $8.4M+ in Shrink Reduction

Pallet Scanning Functionality

Pallet Scanning Functionality

Pallet Scanning Functionality

Impact Highlights

Operational Scale

4.2 million

4.2 million

4.2 million

Pallets

Pallets

Pallets

User verified in first 2 periods

Loss Prevention

$8.4 million

$8.4 million

$8.4 million

Shrink

Shrink

Shrink

Forecasted on mis-delivered pallets

Adoption

98% stores

98% stores

98% stores

Enterprise-wide

Enterprise-wide

Enterprise-wide

Adopted Pallet Scanning feature

My Role & Contribution

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.

Problem & Context

Store associates previously relied on paper load sheets to verify pallet deliveries, making the process manual and prone to errors.

Operational Challenges: Pallets were frequently unloaded at the wrong store, leading to inefficiencies such as:

  • Wasted time returning misdelivered pallets to trucks.

  • Overstocking of incorrect inventory, leading to potential shrinkage.

  • Store leaders resorting to selling misdelivered inventory, creating an unstructured workaround.

Business Impact: Lack of real-time tracking and verification caused significant disruptions in store operations and supply chain visibility.

Solutions

Real-Time Feedback Integration:

  • Implemented immediate visual and audio feedback when a pallet was mis-delivered.

  • Designed a seamless issue-logging process for misplaced pallets, reducing manual errors.

Phase 2 Enhancements:

  • Integrated behavioral analytics to refine usability and determine which feature areas no longer needed investment.

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.