Optimizing Store Associate Tasks

$60M in Projected Value Through Smarter Workflows

Operational Scale

2,300+

Stores

Adoption

98%

Adoption

Execution Impact

80%

Task Completion

LinkedIn
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.
Skip to wireframes and flows
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.
LinkedIn
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.
Skip to wireframes and flows
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.
LinkedIn
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.
Skip to wireframes and flows
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.
LinkedIn
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.
Skip to wireframes and flows
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

Led the design strategy for My Day and Store Walk, ensuring a seamless task execution experience for associates.

Partnered with UX Research & Operations to define key behavioral metrics for task efficiency improvements.

Influenced store operations strategy, integrating data-driven insights into feature prioritization and rollout decisions.

Hands-On

Discovery Leadership: Planned and co-facilitated discovery workshops, aligning business and design perspectives.

Iterative Testing & Refinements: Conducted field testing across multiple divisions, validating usability with real associates.

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.

User-Centered Research & Testing:

Conducted multi-division field research, gathering direct insights from associates and store managers.
Worked with UX Research to develop structured feedback loops, ensuring continuous iteration.

Prototyping & Iteration:

Developed and tested low-to-high fidelity prototypes, refining workflows based on usability insights.
Validated that task sequencing and prioritization aligned with real-world store operations.

Behavioral Analytics for Continuous Optimization:

Tracked store adoption rates, identifying stores where workflow refinements had the most impact.

Results & Impact

Enterprise-Wide Scale

2,300+ stores using My Day and Store Walk for task execution.
Enterprise-wide adoption with ongoing refinements based on real store insights.

Labor & Workflow Optimization

$60M in projected value from improved task prioritization and related use cases:
- Product Date Management Tasks
- Rotation and Sanitation Tasks
- Safety Tasks
- Store Walks
- Pickup Directed Work
- Greenrack Conditioning
- Direct Supply Distribution Receiving
- Pallet Scanning
- Night Crew Tasks
- Delivery Issue Reporting
- Cold Chain Compliance Scanning

Task Management & Execution Impact

Store Walks and Schedule Visibility:
- Provided associates and managers with real-time task scheduling, reducing missed or duplicated tasks.
- Improved shift planning and execution accuracy, leading to higher productivity and labor efficiency.
Sanitation, Product Data Management, Rotation, Greenrack Tasks:
- Enhanced visibility into task completion accuracy to ensure compliance with operational standards.
- Achieved 80% task completion through structured workflows.
Shared Tasks with Pickup Department:
- Streamlined coordination for shared stocking and customer order fulfillment tasks, reducing inefficiencies.
- Enabled real-time task reassignment, ensuring priority work gets completed faster.

Supply Chain & Inventory Impact

Pallet Scanning & Truck Delivery Issue Reporting:
- Enabled seamless tracking of pallet deliveries, reducing discrepancies in inventory reconciliation.
- Improved accuracy in truck delivery reporting, ensuring fewer lost or mis-delivered items.
DSD Deliveries & Receiving Tasks:
- Enhanced tracking of Direct Store Deliveries (DSD), reducing errors and lowering overdelivered inventory.
- Allowed for faster identification of shrink sources, reducing revenue loss.

Operational Efficiency Gains

Eliminated manual task tracking, reducing cognitive load on associates.
Improved accuracy of store walks and sanitation audits, ensuring higher compliance.
Enabled real-time visibility for store leaders, ensuring proactive decision-making.

Iterative Loop - Unmet Needs

Advanced AI-Powered Task Prioritization:

Explore AI-driven workflow recommendations, ensuring tasks are dynamically optimized based on store needs.

Enhanced Behavioral Analytics Correlation

Refine analytics to correlate task execution patterns with labor costs and sales performance.

Scalability & Future Enhancements

Roll out predictive task insights, enabling stores to proactively adjust workflows before inefficiencies arise.

Impact Highlights

Operational Scale

4.2 million

pallets

User verified in first 2 months

Loss Prevention

$4 million

loss prevented

Across 8,000 mis-delivered pallets

Adoption

98% of stores

using the Night Crew tool

Adopted Pallet Scanning feature

Optimizing Store Associate Tasks

Optimizing Store Associate Tasks

Optimizing Store Associate Tasks

$60M in Projected Value Through Smarter Workflows

Operational Scale

Adoption

Execution Impact

Key Takeaways

Key Learnings & Strategic Influence

Key Takeaways

Key Learnings & Strategic Influence

Key Takeaways

Key Learnings & Strategic Influence

Key Takeaways

Key Learnings & Strategic Influence

Leadership

Hands-On

How we got there: Design Strategy

Results & Impact

Iterative Loop - Unmet Needs

Impact Highlights

Operational Scale

Loss Prevention

Adoption

My Role & Contribution

Leadership

Hands-On

Problem Statement & Business Context

Solutions

How we got there: Design Strategy

Results & Impact

Iterative Loop - Unmet Needs