Product Manager

Merchandise Planner Execution

Turning complex reconciliation work into recommendations a merchandise planner can review, approve, and act on in minutes.

The problem

Merchandise planners keep store assortments aligned across three sources: what the store is told to set, what downstream systems are told, and what merchants say the store should carry. When those sources disagree, merchandise planners reconcile them manually.

A single case can take a full day to resolve, and much of the decision-making relies on tribal knowledge that can take months to develop.

What I did

Tested the assumption first. Leadership believed store reset projects were the biggest source of misalignment. Using BigQuery, SQL, and Claude, I analyzed billions of rows across approximately nine enterprise systems and discovered that most misalignment accumulated during everyday maintenance activities, outside of store reset projects entirely.

Reset the strategy. Based on the findings, we focused on day-to-day assortment maintenance, an area fully within our team’s control, with fewer dependencies and enough volume to validate improvements quickly. We selected product drops as the first pilot because they represented the largest source of misalignment and were trending in the wrong direction.

Prototyped the workflow with AI. Using Claude, my merchandising domain knowledge, and existing training resources, I codified tribal knowledge into approximately 95 business rules and built a rules-engine prototype. The experience provides merchandise planners with a single recommendation they can approve, adjust, or dismiss, creating a more consistent and scalable decision-making process.

Responsible AI

I validate AI-generated outputs before they reach users by re-running key metrics directly in BigQuery, reviewing results with engineering partners, and keeping rules in draft until merchandise planners provide feedback.

That process surfaced an AI-generated metric that incorrectly treated “every system agrees a store should not carry an item” as less valid than “every system agrees a store should carry it,” which would have distorted both reporting and recommendation logic.

Where it stands

A pilot involving approximately a dozen super-user merchandise planners is currently underway, representing an opportunity that could eventually support roughly 120 merchandise planners.

Success will be measured through reduced misalignment, lower merchandise planner effort per case, and at least 90% of recommendations being approved as-is.

Senior Business Analyst

New Store Readiness

Helping new stores open with the right products in the right place at the right time.

The problem

Opening a new store requires coordination across Merchandising, Store Environment, and Supply Chain. Limited visibility into assortment readiness and inventory gaps created risk that stores would open with missing products and incomplete assortments.

At the time, new stores were opening with an average of more than 2,000 out-of-stock SKUs.

What I did

Built visibility into the problem. I designed reporting, analytics, and communication processes that surfaced assortment readiness, inventory risks, and execution gaps before stores opened, enabling teams to take action earlier.

Connected teams and processes. I coordinated efforts across Merchandising, Store Environment, and Supply Chain, ensuring issues were identified early and ownership was clear.

Created a feedback loop. I worked closely with merchant teams to understand recurring challenges, improve engagement with the new-store process, and continuously refine reporting based on user needs.

The challenge

The work required aligning multiple organizations with different priorities and timelines while maintaining visibility into thousands of products moving through the opening process.

The impact

New-store in-stock performance improved to 99%, while out-of-stock SKUs at opening fell significantly from prior store openings.

The reporting and communication processes became core operating tools for new-store teams, helping drive consistent in-stock performance while improving visibility, accountability, and execution across future store openings.