data-analytics-portfolio

Logistics Operations Dashboard

Business Problem

Logistics operations teams need fast visibility into delivery performance, returns, and cash-on-delivery (COD) risk in order to take timely action.

This project demonstrates how operational data can be transformed into a simple dashboard for daily decision-making.

Dataset

Order-level logistics data including:

City
Delivery time (hours)
Delivery status
COD amount

Tools Used

Excel (data cleaning, pivot tables, pivot charts, dashboard)

Dashboard Overview

Logistics Dashboard

The dashboard provides a one-page view of key operational metrics:

Average delivery time
Total COD amount
Orders by delivery status
High-risk vs low-risk COD orders
City-level filtering using slicers

Key Insights

Average delivery time indicates moderate delays that require monitoring.
Returned and delayed orders represent direct revenue and operational risk.
A significant portion of COD value is associated with high-risk orders.
City-based filtering allows operations teams to identify problem areas quickly.

Business Recommendations

Prioritize follow-up on high-risk COD orders to reduce revenue loss.
Investigate cities with higher delays or returns.
Use this dashboard as a daily operations monitoring tool.
Expand the dashboard with trends over time for proactive decision-making.

Conclusion

This project reflects real-world logistics operations analysis, combining data cleaning, KPI tracking, and visual reporting to support business decisions.