Alex-Mutua/Water-project

In this project we try to Optimize Revenue Management for Sustainable Water Distribution: QUATECH Senegal's Customer Data Analysis to Address the Decline in Water Development Fund Revenues # Optimizing Revenue Management for Sustainable Water Distribution ### QUATECH Senegal – Customer Data Analysis ## Overview This project analyzes the decline in **Water Development Fund (FDE)** revenues at QUATECH Senegal despite increasing water production. A **data-driven approach** is used to uncover key drivers of revenue decline and support strategic decision-making. --- ## Problem Statement Why are FDE revenues decreasing despite increased water production and high payment compliance? --- ## Objectives - Segment subscribers based on **consumption and payment behavior** - Analyze **billing and payment trends** - Identify key factors driving **FDE revenue decline** - Build predictive models for **revenue estimation** --- ## 📊 Dataset - **Size:** 1.14M records, 23 features - **Period:** 2014 – 2019 - **Region:** Saint-Louis (Region 4) - Includes: - Consumption (cubage) - Billing & payments - Customer category (Private/Admin) - Financial metrics (FDE, VAT, FNE) --- ## Data Preprocessing - Renamed variables for clarity - Converted date and monetary fields - Handled missing values (`PAY_DATE` retained for delay analysis) - Removed extreme anomalies (outliers in FDE) - Encoded categorical variables - Feature engineering: - `PAYMENT_DELAY` - Time-based features --- ## Key Insights - FDE revenue **peaked in 2017**, declined sharply after - **94.5% pay on time**, but revenue still drops - **Administrative customers consume ~87.5%** of water - Revenue concentrated in few regions: - Bakel (**52.6%**) - Foundiougne (**13.5%**) - Birkelane (**12.1%**) - Average payment delay ≈ **30 days** --- ## Methodology ### 1. Exploratory Data Analysis (EDA) - Trend analysis (FDE over time) - Payment behavior analysis - Regional contribution analysis ### 2. Dimensionality Reduction - **PCA** to identify key behavioral patterns: - Axis 1 → Consumption & billing - Axis 2 → Payment behavior ### 3. Modeling - Regression Models: - **Ridge** (best performance) - Lasso - …