TARGET SMART WAREHOUSE
Designing Jetson, an operational platform that connects warehouse equipment, data, and people across a national network.
Sole UX designer for Automation Intelligence.
Jetson supported Target’s middle-mile operations across more than 50 warehouses. Each facility brought its own combination of automation, equipment, vendors, workflows, and local needs.
As the sole UX designer on Jetson’s core team, I worked with Product, Engineering, and Operations to understand those differences, identify recurring needs, and shape tools that could work locally while supporting a more consistent platform across the network.
Supported four site activations, including two new warehouse concepts, with scheduled go-live dates to meet.
Prototyped workflows implemented in warehouses.
More than 30 modules delivered through Workday.
Two Target Together Demo Days and two UX Automation lectures for leadership.
One warehouse, multiple connected systems. Equipment, software, and people share the same physical environment but operate under different constraints.
Commissioning verified installed automation on-site, checking physical equipment responses against software signals and Jetson interface states. Activation was also a named rollout phase and team, with a scheduled go-live date to meet.
Define scenarios and expected equipment behavior.
Observe how conveyors and automation respond on-site.
Verify that displayed states and signals match what happens.
Document issues, correct gaps, and check again.
The Activation team worked through the Activation phase toward a scheduled go-live date. Commissioning findings, interface fixes, and operational readiness had to align with that milestone.
Conveyors, sortation, storage, robotics, and automated assets physically move material through the building. Each facility uses a different combination.
Controls, warehouse software, telemetry, reporting, and the Jetson application must form a useful operational picture even when the underlying sources differ.
Operations, Maintenance, Engineering, and Leadership need different levels of detail from the same environment. Responsibility shifts with the task and urgency.
Select a case study to explore the problem, field perspective, investigation, and design response.
“I made my own Excel spreadsheet to consolidate the 20 apps I have to access for information.”
Sites differed in equipment configurations, workflows, and local solutions. A feature useful in one building could be unsuitable elsewhere.
Separate shared operating concepts from site-specific rules, while giving proven local solutions a path toward supported capabilities.
See the Material Flow case study“We only have 30 minutes to fix something before it becomes critical.”
Teams could see developing conditions without knowing whether someone was responding, who was responsible, or how much time remained to intervene.
Connect signals with state, ownership, context, and the next useful decision rather than merely surfacing an alarm.
See the Signal Visibility case study“Everyone has a different idea of what this means.”
The same metric or condition could mean different things to Operations, Engineering, and Leadership. A result without contributing factors was easy to misinterpret.
Make definitions and component measures visible beside the result; support appropriate detail and decisions for each role.
See the OEE & Learning case studyAcross Material Flow, Signal Visibility, and OEE & Learning, the challenge wasn't simply making more operational data available. It was connecting equipment behavior, local practices, and system information so different teams could make sense of the same environment. Each investigation approached that challenge differently: reconciling shared and site-specific needs, making physical signals actionable, and turning performance metrics into understandable decisions. Together, they demonstrate an approach to warehouse automation grounded in how people actually operate, maintain, and improve these systems.
I worked across design tools, industrial automation software, technical documentation, delivery systems, and site validation.
Ignition Gold Certified 2023–2026, working within the constraints of operational software and equipment signals.
Modeling workflows and building reusable interaction patterns.
Mapping dependencies, equipment behavior, and exceptions.
Collaborating with engineering and teams responsible for commissioning.
Turning observations, surveys, and field tests into product decisions.
Exploring where AI could support complex, role-aware operational workflows.
