Watermelons & Pumpkins | Brenden Cavazos

Context or Challenge

The programs required coordination across merchandising, forecasting, sourcing, suppliers, transportation, distribution operations, and inventory teams. Conditions changed frequently due to crop availability, order-generation issues, forecast movement, constrained regions, holiday peaks, and seasonal buy-down requirements.

Observation

Success depended on four teams -- Merchandising, Grocery Supply Chain Operations, Transportation, and Data Science Forecasting -- acting on one shared plan instead of four separate ones. Owning that shared visibility, and the cadence that kept it current, was the highest-leverage role in the program.

Insight

For volatile programs, the orchestration layer is a product in itself: cadence, intelligence, decision context, escalation, and a shared view of what changed.

My Thinking

I built a governance approach around the program lifecycle. The focus moved from pre-season planning, to peak readiness, to in-flight recovery, to controlled inventory transition into the next season.

What I Built or Led

I coordinated weekly executive communications, business-intelligence reviews, readiness planning, forecast discussions, operational risk escalation, and cross-functional alignment for both Walmart and Sam's Club. The readiness cadence below shows how that alignment actually ran, week to week, across every team involved.

Featured Capability: Cross-Functional Readiness Cadence

Runs a roughly ten-week cross-functional cadence connecting Merchandising, Grocery Supply Chain Operations, Transportation, and Data Science Forecasting so seasonal volume never lands on any one team all at once
Partners with Merchandising and the Replenishment Manager to smooth order creation into distribution centers over time, protecting receiving windows instead of congesting them with a single large surge
Partners with Data Science Forecasting roughly three weeks before shipping to build a trailer-and-driver capacity plan from validated order volume, sized to each facility's confirmed maximum throughput
Designed and delivered facility-specific, generative-AI-powered enablement dashboards -- built from direct user research with 10+ operators -- reaching more than 150 grocery supply chain operators with a daily capacity and ship/inbound/outbound view tailored to their facility
Runs a final readiness check one week before shipping, then monitors inventory flow in-season and escalates for added trailer or driver capacity the moment a facility falls behind

Seasonal Readiness Cadence & Collaboration Model

In generalized terms, the season runs on a fixed cadence rather than a single hand-off. Six weeks before shipping, Merchandising and facility operators align on total volume and maximum capacity. From there, orders are smoothed into distribution centers, an outbound trailer-and-driver plan is built with Data Science Forecasting, and every facility receives a tailored, generative-AI-built enablement view before the season starts. Every phase names the teams that must be in the room -- because in a program this size, the orchestration itself is what protects the supply chain.

Across a generalized roughly ten-week cadence, six phases run in sequence, each naming the teams that must align: kickoff and capacity alignment (Merchandising and Facility Operations), order smoothing and forecast validation (Merchandising and Grocery Supply Chain Operations), outbound capacity planning (Transportation and Data Science Forecasting), facility-specific generative-AI enablement reaching 150+ operators, a final readiness check where all four teams align, and in-season monitoring and escalation. — A recurring, roughly ten-week cadence connecting four teams -- collaboration is the mechanism here, not a side effect.

Execution and Adoption Strategy

The program used recurring communications, shared playbooks, milestone reviews, operator enablement, forecast-change visibility, and escalation of operational constraints. The approach adapted as the primary risk shifted across planning, supply, capacity, system stability, and end-of-season inventory.

Business Impact

Supported planning and governance for 862,659 watermelon bins and 15,975 full truckloads of product
Supported planning and governance for 394,422 pumpkin bins and 6,574 full truckloads of product
Supported readiness across Memorial Day, July 4, and Halloween demand windows
Helped connect summer inventory buy-down with fall seasonal launch readiness
Reached 150+ grocery supply chain operators with facility-tailored, generative-AI-built enablement dashboards, informed by direct user research with 10+ operators throughout the season

Key Takeaway

“In complex seasonal programs, cross-functional alignment is one of the most scalable forms of risk mitigation.”

Capabilities Demonstrated

Enterprise program management
Executive communications
Business intelligence
Seasonal strategy
Risk management
Cross-banner coordination
Lifecycle planning
Generative AI enablement
User research