Final Analysis Report
Final Analysis Report: Delivery & Pickup Performance Analysis
Table of Contents
1. Executive Summary
Overview of the project objectives and scope
Key insights and findings from the dashboards
Summary of recommendations
2. Introduction
Background and purpose of the project
Business challenges and objectives addressed
Importance of data-driven decision-making
3. Methodology
Data sources used (Delivery and Pickup datasets)
Data preprocessing and cleaning steps
Tools and technologies used (Power BI/Tableau, Python, SQL, etc.)
4. Dashboard Analysis & Key Insights
4.1 Delivery Dashboards
Dashboard 1: Delivery Performance Overview (On-time delivery, SLA compliance)
Dashboard 2: Customer Satisfaction Analysis (Delivery success rate, customer ratings)
Dashboard 3: Cost & Efficiency Analysis (Cost per delivery, fuel efficiency)
Dashboard 4: Issue Resolution & Delays (Resolution time, delays frequency)
4.2 Pickup Dashboards
Dashboard 5: Pickup Performance & Efficiency (On-time pickup, courier performance)
Dashboard 6: Pickup Cost Analysis (Cost per region, pickup efficiency)
Dashboard 7: Courier Utilization Analysis (Utilization rate, average orders per courier)
Dashboard 8: Service Benchmarking (Delivery & pickup combined metrics, revenue insights)
5. Key Trends & Observations
Patterns in delivery delays and SLA breaches
Pickup efficiency and courier allocation issues
Cost variations across different regions
Correlation between customer satisfaction and on-time performance
6. Business Recommendations
Route optimization strategies to improve efficiency
Workforce allocation improvements for better courier utilization
Issue resolution automation to reduce delays
Demand forecasting using predictive analytics to optimize delivery scheduling
7. Conclusion
Final summary of findings
Expected impact of implementing recommendations
Next steps for continuous improvement
8. Appendices
Additional visualizations and charts
KPI calculation methods
Data dictionary
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