ISO-Compliance-Data-Analysis

A complete notebook-based project on ISO compliance data analysis, featuring anomaly detection, scoring frameworks, forecasting, and executive dashboards for management decision-making

ISO Compliance Data Analysis (2020–2025)

📊 Project Overview

Comprehensive analysis of ISO compliance performance across 4 standards:

• ISO 22000:2018 – Food Safety Management
• ISO 50001:2018 – Energy Management
• ISO 14001:2015 – Environmental Management
• Occupational Safety – Slips, Trips, Falls

Dataset: 3,673 cleaned records across 10 facilities over 6 years Analysis Quality: 98.5% confidence level

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🎯 Key Findings

Metric	2020	2025	Change	Status
Audit Score	64.82%	79.24%	+22.5%	✅ Improving
Compliance Score	67.58%	87.43%	+29.1%	✅ Improving
Incidents/100 Workers	11.8	3.9	-67%	✅ Excellent
Renewable Energy	11.4%	28.79%	+152%	✅ Growing
Safety Training	79.35%	95.59%	+16.2 pts	✅ Strong

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📚 Project Structure

Notebooks (Sequential Analysis)

1. Notebook 1 – Data Loading & Exploration
2. Notebook 2 – Data Cleaning & Validation
3. Notebook 3 – Exploratory Data Analysis
4. Notebook 4 – Trend Analysis & Forecasting
5. Notebook 5 – Correlation & Regression Analysis
6. Notebook 6 – Anomalies & Compliance Scoring

Data Files

• ISO_Compliance_Dataset_2020_2025.csv – Original dataset (3,762 records)
• ISO_Compliance_Dataset_Clean.csv – Cleaned dataset (3,673 records)

Documentation

• EXECUTIVE_SUMMARY_NOTEBOOK.md – Complete analysis summary
• CRITICAL_BUSINESS_QUESTIONS.md – critical questions answered
• ISO_Compliance_Data_Dictionary.md – Column definitions & interpretations

📊 Questions Answered

✅ Q1: Overall compliance health – ARE WE IMPROVING? ✅ Q2: Critical risk areas – WHICH DEPARTMENTS NEED SUPPORT? ✅ Q3: Training ROI – DOES TRAINING REDUCE INCIDENTS? ✅ Q4: Environmental progress – ARE WE MEETING SUSTAINABILITY GOALS? ✅ Q5: Department ranking – HOW DO FACILITIES COMPARE? ✅ Q6: Safety trends – ARE WE BECOMING SAFER? ✅ Q7: Audit findings – ARE WE FIXING ISSUES FOUND? ✅ Q8: Energy management – ARE INITIATIVES WORKING? ✅ Q9: Data quality – CAN WE TRUST THE DATA? ✅ Q10: Correlations – WHAT DRIVES COMPLIANCE? ✅ Q11: Anomalies – ARE THERE UNUSUAL EVENTS? ✅ Q12: 2026-2027 forecast – WHAT SHOULD WE EXPECT?

🔍 Key Insights

Safety Transformation

• Incidents down 35.5% through training investment
• ROI: Every $1 spent on training → $2-3 saved
• On track to beat industry best-in-class by 2027

Department Performance

• All 10 facilities improved 17-22% (2020→2025)
• Production_Facility_A leads at 79.02%
• Three facilities identified for peer mentoring support

2026-2027 Outlook

• Audit Score forecast: 85.56% (on track for 90% target by 2028)
• Incidents forecast: 4.02 (approaching <3.0 target)
• Renewable energy: 36.62% (on track for 50% by 2028

📈 Methodology

• Data Quality: 98.5% confidence (validated through anomaly detection)
• Trend Analysis: Linear regression with R² validation
• Forecasting: 95% confidence intervals on predictions
• Anomalies: Z-score + Machine Learning (Isolation Forest) methods
• Correlations: Pearson correlation with p-value testing

🎯 Skills Demonstrated

✅ Data Engineering (cleaning, validation) ✅ Exploratory Data Analysis (EDA) ✅ Statistical Modeling (regression, correlation) ✅ Time Series Forecasting (trend extrapolation) ✅ Machine Learning (Isolation Forest anomaly detection) ✅ Data Visualization (matplotlib, seaborn) ✅ Business Analysis (ROI calculation, recommendations) ✅ Executive Communication (findings presentation)

📄 License

This project is open source and available for educational purposes.