Logo Lanfrica
  • Accueil
  • Atlas
  • Analyses
  • Documentation
  • Sign in

© 2026 Lanfrica. Tous droits réservés. Tous les droits d'auteur des ressources affichées sur le site Web Lanfrica appartiennent aux détenteurs de droits d'auteur d'origine, sauf indication contraire explicite.

Muhammad-Ahmad-Y/Nigeria-Disco-s-Revenue-Analysis

Domaine:

socioeconomicenvironment and energy

Type de record:

dataset
Créateur:
Muh
Hôte:
An analytical deep-dive into Nigeria's power distribution sector, highlighting critical revenue leakage and performance disparities across DisCos with a strategic focus on optimizing KEDCO's collection efficiency. # Nigeria DisCos & KEDCO Loss & Revenue Recovery Analysis **Author:** Muhammad Ahmad Yusuf ## Project Overview This project is a comprehensive data analysis and business intelligence solution evaluating the operational and commercial performance of Nigerian Electricity Distribution Companies (DisCos), with a deep-dive focus on the **Kano Electricity Distribution Company (KEDCO)**. By leveraging 2025 performance data, this analysis investigates energy losses, billing efficiency, revenue collection performance, and Aggregate Technical, Commercial and Collection (ATC&C) losses. The primary goal is to benchmark nationwide DisCo performance, identify the major drivers of revenue loss across the value chain, and highlight specific operational bottlenecks within the Kano region. ## Dashboards ### 1. National DisCos Overview *Provides a macro-level view of all Nigerian DisCos, comparing Billing Efficiency, Collection Efficiency, and ATC&C Losses.* ### 2. KEDCO Specific Performance *A localized deep-dive into KEDCO's specific revenue recovery challenges, highlighting the severe disparity between billing capabilities and actual revenue collection.* ## Data Sources & Methodology * **Datasets:** Energy Billed & Received, Revenue Billed & Collected (Values in Billions of Naira - ₦). * **Methodology:** * ETL processes performed in Power Query (Unpivoting, Data Cleansing, Time-Series Structuring). * Relational Data Modeling in Power BI. * Custom DAX measures engineered for calculating Efficiencies, Revenue Losses, and Variances. ## Key Findings: National DisCos Overview * **The Nationwide Revenue Gap:** Across all DisCos, out of ₦3.64 Trillion in Energy Received and ₦3.0 Trillion Billed, only ₦2.32 Trillion was collected. This translates to an industry-wide **Billing Efficiency of 81.94%** and a **Collection Efficiency of 77.65%**. * **Total National Revenue Loss:** The sector suffered a massive ₦1.33 Trillion in lost revenue. Notably, this loss is split almost evenly na …

Visit

github.com