Insights Dashboard

The first visual ops tool for Target Last Mile

Insights Dashboard gave operations teams a shared map for market health. Before this, pay, store coverage, delivery surge, and order density were hard to see together. The dashboard put those signals in one place. Operations teams across 12 sortation centers used it daily to see what was happening across stores, routes, and metros.

What I built

The app was a Streamlit and Plotly product backed by Snowflake data. It let operators filter by business line, shopper experience, metro, zone, retailer, store, and date, then move between detailed and aggregated views.

• Order-level maps for delivery status, promo pay, incentive pay, store locations, shopper homes, and customer locations.
• H3 grid views for order density, on-time performance, pay, delivery lateness, cancellations, returns, and reschedules.
• Aggregated maps and tables by store, zipcode, retailer, zone, metro, route, hour, day, date, and week.
• TLMD-specific views for route coverage, driver supply, vehicle class, active status, and last-delivered recency.
• Redis-backed session state so operators could move between pages without rebuilding every selection.

Shipped in phases

The product grew from a spatial app into a production operations tool. The shipped work added Redis-backed state, deployment infrastructure, H3 geospatial density views, Snowflake-backed KPI tables, TLMD support, and driver supply workflows.

Why it mattered

Operations could finally see the same market story in one tool. Pay exposure, store coverage, last mile delivery surge, and order density were no longer separate pulls or static reports. They were visual, explorable, and tied to the same operational filters people used to make decisions.