Operations KPI Reporting Automation

This project demonstrates an automated Python workflow for factory production, workforce, and operational KPI reporting.

Business problem

Production managers need to monitor planned output, actual output, defects, downtime, labor productivity, overtime, absenteeism, and headcount across production lines and shifts. Manual Excel reporting is repetitive and can hide performance issues.

Solution

The automation reads daily factory operations data, calculates weighted KPIs, and generates management reports by month, production line, and shift.

Synthetic data

• Reporting year: 2025
• Daily line-shift records: 2,190
• Production lines: 3
• Shifts: 2
• Planned factory headcount: approximately 960 employees

All data is synthetic and does not contain real company or employee information.

KPIs

• Plan attainment
• Defect rate
• Availability
• Output per employee
• Overtime rate
• Absence rate
• Monthly production trend

Input

data/raw/factory_operations_2025.xlsx

Outputs

output/
├── validated_operations_data.xlsx
└── operations_kpi_report.xlsx

Run locally

python -m venv .venv
Set-ExecutionPolicy -Scope Process -ExecutionPolicy Bypass -Force
.venv\Scripts\Activate.ps1
python -m pip install -r requirements.txt
python -m pytest
python run_report.py

Project structure

operations-kpi-reporting-automation/
├── data/
│   ├── raw/
│   └── reference/
├── output/
├── src/
├── tests/
├── screenshots/
├── run_report.py
├── requirements.txt
└── README.md

Business value

The workflow replaces repetitive factory KPI reporting with a reusable process that produces consistent monthly, line, and shift-level management reports.