Role

Data Analyst

Industry

Energy | Economic Development

Duration

2 weeks

View Live Dashboard

Project Overview

This project analyzes electricity consumption and system losses across African and MENA countries, focusing on per-capita usage, income-level disparities, electricity loss rates, and long-term trends.

Using World Bank data in Excel, raw multi-year energy records were transformed into a structured analytical model that reveals where electricity access is constrained, where inefficiencies persist, and how income and region influence energy outcomes.

Process & Methodology

Data Cleaning & Transformation (Excel Power Query)

  • Unpivoted year-based columns into a time-series format

  • Removed blank and inconsistent records

  • Standardized country names and classifications

  • Enriched missing income-level data to ensure accurate segmentation




Data Modeling & KPI Development (Power Pivot / DAX)

  • Built a structured data model using Country, Region, Income Level, and Date tables

  • Resolved filter inconsistencies by aligning fact and dimension tables



Developed KPIs for:
  • Electricity consumption per capita

  • Electricity loss rate (% of output)

  • Income-level and regional averages

  • Year-over-year and long-term trends



Visualization & Insight Design (Excel Dashboards)

  • KPI cards for consumption and loss metrics

  • Ranked bar charts for top countries by latest-year loss rate

  • Income-level comparison charts

  • Regional maps (darker shade = higher loss and consumption)

  • Long-term trend lines for electricity performance

Business Questions
  • How does electricity consumption vary across income levels and regions?

  • Which countries record the highest electricity loss rates in the latest year?

  • How do system losses differ by income group and region?

  • How large is the gap between MENA and Sub-Saharan Africa?

  • What long-term trends indicate improvement or stagnation?




Key Insights & Findings

  • Consumption Inequality: Per-capita electricity consumption is concentrated in high- and upper-middle-income countries, while low-income countries consume significantly less.

  • Loss Rate Concentration: High electricity loss rates are concentrated in a limited number of countries, highlighting infrastructure and efficiency challenges rather than demand alone.

  • Regional Disparities: MENA consistently outperforms Sub-Saharan Africa in both consumption levels and grid efficiency.

  • Misleading Averages: Regional averages are skewed by a few high-performing countries; country-level analysis provides a clearer picture of energy access gaps.

  • Trend Patterns: Electricity outcomes show long-term improvement, but growth remains uneven and volatile in lower-income economies.

Recommendations

  • Prioritize grid efficiency improvements in high-loss countries

  • Track per-capita consumption alongside loss rates for balanced evaluation

  • Segment energy planning by income level and region

  • Use trend analysis to identify stagnation and recovery periods

Expected Impact

  • Clear visibility into electricity access and efficiency gaps

  • Stronger evidence base for infrastructure investment decisions

  • Improved support for energy and development policy discussions


Electricity Consumption & Loss Analysis

Electricity Consumption & Loss Analysis

Electricity Consumption & Loss Analysis

Assessing regional, income-based, and efficiency disparities
Assessing regional, income-based, and efficiency disparities

Assessing regional, income-based, and efficiency disparities

Role

Data Analyst

Industry

Energy | Economic Development

Duration

2 weeks

Project Overview

This project analyzes electricity consumption and system losses across African and MENA countries, focusing on per-capita usage, income-level disparities, electricity loss rates, and long-term trends.

Using World Bank data in Excel, raw multi-year energy records were transformed into a structured analytical model that reveals where electricity access is constrained, where inefficiencies persist, and how income and region influence energy outcomes.

Process & Methodology

Data Cleaning & Transformation (Excel Power Query)

  • Unpivoted year-based columns into a time-series format

  • Removed blank and inconsistent records

  • Standardized country names and classifications

  • Enriched missing income-level data to ensure accurate segmentation




Data Modeling & KPI Development (Power Pivot / DAX)

  • Built a structured data model using Country, Region, Income Level, and Date tables

  • Resolved filter inconsistencies by aligning fact and dimension tables



Developed KPIs for:
  • Electricity consumption per capita

  • Electricity loss rate (% of output)

  • Income-level and regional averages

  • Year-over-year and long-term trends



Visualization & Insight Design (Excel Dashboards)

  • KPI cards for consumption and loss metrics

  • Ranked bar charts for top countries by latest-year loss rate

  • Income-level comparison charts

  • Regional maps (darker shade = higher loss and consumption)

  • Long-term trend lines for electricity performance

Business Questions
  • How does electricity consumption vary across income levels and regions?

  • Which countries record the highest electricity loss rates in the latest year?

  • How do system losses differ by income group and region?

  • How large is the gap between MENA and Sub-Saharan Africa?

  • What long-term trends indicate improvement or stagnation?




Key Insights & Findings

  • Consumption Inequality: Per-capita electricity consumption is concentrated in high- and upper-middle-income countries, while low-income countries consume significantly less.

  • Loss Rate Concentration: High electricity loss rates are concentrated in a limited number of countries, highlighting infrastructure and efficiency challenges rather than demand alone.

  • Regional Disparities: MENA consistently outperforms Sub-Saharan Africa in both consumption levels and grid efficiency.

  • Misleading Averages: Regional averages are skewed by a few high-performing countries; country-level analysis provides a clearer picture of energy access gaps.

  • Trend Patterns: Electricity outcomes show long-term improvement, but growth remains uneven and volatile in lower-income economies.

Recommendations

  • Prioritize grid efficiency improvements in high-loss countries

  • Track per-capita consumption alongside loss rates for balanced evaluation

  • Segment energy planning by income level and region

  • Use trend analysis to identify stagnation and recovery periods

Expected Impact

  • Clear visibility into electricity access and efficiency gaps

  • Stronger evidence base for infrastructure investment decisions

  • Improved support for energy and development policy discussions


View Document

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Adewale Idowu Victor

Copyright 2025 by Adewale Idowu Victor

Designed and built in Framer by me, combining data analytics expertise with design thinking for clear, impactful storytelling.

Adewale Idowu Victor

Copyright 2025 by Adewale Idowu Victor

Designed and built in Framer by me, combining data analytics expertise with design thinking for clear, impactful storytelling.

Adewale Idowu Victor

Copyright 2025 by Adewale Idowu Victor

Designed and built in Framer by me, combining data analytics expertise with design thinking for clear, impactful storytelling.

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