Operational Bottleneck Analysis & SLA Optimization

Report Link: https://app.powerbi.com/view?r=eyJrIjoiZDNkODdhZjctYjliMC00YWRmLWFkNGEtM2NjYTM5ZjU3YWEwIiwidCI6ImY2MjdlMjJlLWNmNzItNDlhOC05MmZjLTZjNmIwMThmNTg3MiJ9

Project Overview

This project was developed as part of an MBA in Data Analytics & Business Intelligence 360°. The main goal was to identify operational bottlenecks in a simulated manufacturing company (Xperiun), focusing on process delays, sector performance, and financial impact.

Business Objectives

• Improve operational efficiency
• Reduce order cycle time
• Enhance customer SLA performance
• Support data-driven decision-making

Data Sources

The analysis was based on operational system data, including:

• Orders
• Production process flow
• Departments and workstations
• Employees
• Materials and product complexity

Key Insights

• Actual execution time frequently exceeds standard time, especially in:
  • Machining
  • Cutting
  • Welding
• Recurrent issues such as:
  • Operator unavailability
  • Machine breakdowns
• High-complexity and heavy-weight orders account for most delays and rework

Proposed Improvements

Based on the analysis, the following actions were recommended:

• Strategic resource reallocation
• Feasibility analysis for new machine acquisition
• Workforce optimization, prioritizing critical departments

Deliverables

• Interactive dashboards developed in Power BI
• KPIs for monitoring operational delays and bottlenecks
• Visual insights to support management decision-making

Tools & Technologies

• Power BI
• Data Modeling
• DAX
• Business Intelligence concepts
• Process analysis

Project Structure

• /powerbi: Power BI dashboard file (.pbix)
• /docs: Dashboard screenshots
• /data: Sample or anonymized data (optional)

📎 Notes

This project uses simulated data for academic and portfolio purposes.