Alerts and Collaboration for Walmart Internal Finance
The problem:
Decisioning is done in silos where access to uniform data and reliance on manual processes leads to being more reactive than proactive, slowing down processes, and reducing accuracy.
The solve:
Build in-product collaboration features such as dynamic alerts/notifications and commenting to centralize financial planning and automate opportunity discovery with internal AI technologies.
⏱️ 27% faster to alert team members of potential data anomalies
✅ 68% task completion fully in-product vs other tools
Quick Context
IBG (Intelligent Business Growth) is a team designing AI-powered financial planning tools within the Walmart ecosystem. The platform spans four interconnected workstreams (A–D), each serving distinct but related needs. Though primarily embedded in Workstream B (business monitoring), the project I worked on was workstream-agnostic — spanning the full platform. My focus was exploring how visual alerts and in-product collaboration could be applied across all workstreams.
Alerts and Notifications
In order to concept out the initial portion of this work, it was necessary to define alerts and notifications and how they should function within our system:
Alerts - Visual cues intended to attract users’ attention to a particular piece of content or UI element that is dynamic in nature. They’re both contextual and conditional.
Notifications - Informational messages that alert the user of general occurrences within our system. Notifications can be tied to alerts or they can be related to some other event.
By labeling these, centering the work around visual alerts, notifications tied to those alerts, and general notifications became key in my initial exploration.
In Situ
Alerts and Severity
Through cross-workstream reviews, it became clear that not all alerts carry the same urgency. Some workflows called for informational indicators rather than action-driven prompts. Severity level was ultimately left to each workstream's designer to define.
Collaboration and Commenting
For collaboration, I distinguished between personal notes and comments intended for others, covering use cases like discussions and action item tracking. The work focused on single comments, threaded replies, and how comments rendered differently across data tables versus visualizations.
