Store Fulfillment Workflow

Discovery research to identify store fulfillment associate picking strategies and pain points and map picking journeys. Product recommendations were made to improve picking efficiency by reducing cognitive and physical load, reduce associate turnover, and improve customer satisfaction. Led to the business decision to redesign the store fulfillment app to align with associate behavior.

Why It Maters

The store fulfillment team is responsible for picking customer orders for delivery and in-store pickup for both do-it-yourself and professional customer bases. These orders can include numerous item types, from small tools and hardware to building materials and lumber. Associates have described their role in fulfillment as overwhelming and they often rely on non-fulfillment associates for help. Additionally, understanding associate mental models and pain points for picking and fulfilling orders is essential for optimizing the workflow. Addressing the gaps in the fulfillment technology will improve associate job satisfaction and the order fulfillment experience for customers downstream.

Business Obectives

Reduce turnover by improving associate job satisfaction.
Reduce cancellation rate by improving customer satisfaction
Increase overall fulfillment LTR (likelihood to recommend) by improving timeliness in order fulfillment.

Research Method

Conducted stakeholder interviews with design, product, and business operations to understand questions and assumptions (e.g., that associates "cherry pick" which orders to pick to avoid large/bulky orders) and align on objectives and research plan.

Contextual Inquiry at 3 different stores.
- Stores also varied in population density (urban v. suburban), sales volume (mid-volume vs. high-volume), and team structure (number of associates on shift).
- Spent 2 full days per store with fulfillment associates, team leads, and department supervisors of varying tenure (2 months - 20+ years) to fully immerse in the environment and build rapport
- Stores chosen were based in 2 different regions, across 3 different districts to control for leadership directives on fulfillment strategies.

Data Analytic Approach

Used ChatGPT to identify high-level themes in transcripts.

Identified trends in picking strategy, including impact of seasonality and time of day.

Conducted affinity mapping to cluster common themes, including pain points and workarounds.

Used anonymized, direct quotes from associates to convey sentiment and tell the story of order fulfillment through the eyes of associates.

Developed individual and summated picking journey maps to illustrate how the current technology is inconsistent with associate mental models and strategies for efficient order picking.

Developed a network map to highlight the "favor economy" fulfillment associates develop and rely on to perform their job functions across store departments.

Insights & Deliverables

Insights:

The store fulfillment app is designed for associates to pick and stage a single customer order at a time, resulting in an inefficient workflow requiring associates to walk several miles per shift across the store.

Associates click in and out of orders to manually sort and batch to reduce walking and pick multiple orders at once, staging and sorting these orders later.
- Revealed that the "pick time" metrics used to capture store fulfillment performance do not account for deviations from single-order picking and are inaccurate for stores employing other picking strategies.

Associates organize items across multiple orders by department to reduce walking.
- Sorting through orders, while reducing walking, creates increased cognitive demand with associates proactively creating mental plans to pick orders efficiently.

The assumption that associates "cherry pick" which orders to work was nuanced and not purely explained by associates avoiding large orders. During times of high-stress, associates cherry pick orders to serve as many customers as possible in a short amount of time.

Fulfillment associates help customers in-aisle and handle customer pickups, resulting in large amounts of task-switching, requiring a dynamic and flexible experience. This increases cognitive demand because associates must mentally track what tasks are incomplete, in progress. and complete.

Deliverables:

Research report including findings, insights and actionable recommendations was presented to stakeholders.

Journey map showing 2 individual associate picking journeys to illustrate how associates batch and zone pick and why. This also included time on task.

Network map illustrating which associate roles fulfillment relies on and for what (e.g., cashiers for help picking, sales floor specialists for help finding items in specific departments.

Recommendations

*Research contributed to the business decision to redesign the fulfillment team app.

Aligning the app technology with associate picking strategies, including allowing batch picking and zone picking, while still providing flexibility to pick by single order when situations warrant (e.g., large lumber orders).

Showing optimal picking route through the store and surfacing department information earlier to aid in planning and reduce travel through the store.

Given the amount of task switching required in this role, add indicators for associates to flexibly move in and out of flows and track what tasks they left off on.

Use plain language and include in-app help for new and non-fulfillment associates to learn on the job with minimal training.

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