I built a clean, automated logistics KPI dashboard to help e-commerce operations teams monitor shipment performance, identify root-cause issues, and improve weekly fulfillment accuracy. This dashboard showcases my ability to translate raw shipment data into clear operational insights, using structured metrics, exception categorization, and visual reporting.

Provide a centralized view of weekly shipment performance

Track on-time delivery rate, transit trends, and customs delays

Categorize delay reasons and exceptional cases for root-cause analysis

Build an easy-to-read dashboard suitable for internal updates or stakeholder reporting

Support future expansion for multi-warehouse or multi-country data

Defined core KPIs: Total Shipments, On-time Delivery Rate, Average Transit Days, Delay / Exception Cases, Return Rate

Standardized definitions to keep reporting consistent across teams and time periods

Cleaned and structured shipment data (country, carrier, date, exception reason)

Grouped delay reasons into operational categories for clear diagnosis

Built automated charts showing shipment volume trends and on-time % fluctuations

Added summary sections to highlight operational stability and vendor-related delays

Designed layout for management-ready weekly reports (PDF or Google Sheets)

Created a repeatable weekly template

Ensured that new data can be dropped in without breaking formulas or charts

Prepared a clear user guide so teams can maintain, edit, or expand the dashboard in future

A clean, readable KPI dashboard suitable for weekly operations review

Clear visibility into delays and performance trends

Improved transparency for fulfillment partners and internal operations teams

Google Sheets（data cleanup, formulas, charts）

Microsoft Excel（KPI table formatting）

Notion（documentation）