Skip to content

Chann2512/Financial-Performance-Analysis

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

3 Commits
 
 
 
 
 
 

Repository files navigation

📊 Financial Performance Analysis Dashboard

📌 Overview

This project analyzes financial performance using a structured P&L dataset to identify profitability drivers, cost inefficiencies, and business risks across multiple business lines.


🧩 Business Context

A multi-sector company in the Sports & Health industry aims to:

  • Maintain sustainable profitability
  • Optimize cost structure (COGS & Opex)
  • Allocate resources efficiently

The company experienced significant profit volatility, especially a sharp decline in mid-year performance.


❓ Problem

Profit dropped significantly despite relatively stable cost levels.

Key questions:

  • What caused the mid-year profit decline?
  • Which segments are underperforming?
  • Is the company scaling efficiently with revenue?

🔍 Analytical Approach

1. Data Modeling

  • Designed a star schema
    • Fact table: 580 financial transactions
    • Dimension tables: Calendar, Group, Subgroup, KPI, Ratios
  • Structured data to support full P&L analysis (Revenue → Net Profit)

2. Data Processing (SQL)

  • Cleaned and validated raw data
  • Joined fact and dimension tables
  • Aggregated metrics by time, business line, and cost category
  • Calculated key metrics:
    • Revenue, COGS, Opex, Profit
    • Profit margins and cost ratios

3. Analysis Flow

Step 1: Trend Analysis

  • Analyzed revenue, expense, and profit over time
  • Identified seasonality: Q1 peak → Q3 trough → Q4 recovery

Step 2: Cost vs Revenue Behavior

  • Compared revenue decline vs cost reduction
  • Evaluated cost rigidity and operating leverage

Step 3: Business Line Performance

  • Compared performance across:
    • Sportswear (main contributor)
    • Equipment (declining trend)
    • Nutrition (low efficiency)

Step 4: Cost Structure Deep Dive

  • Analyzed:
    • COGS: Labor, Materials, Shipping
    • Opex: Marketing, Payroll, R&D
  • Identified key cost drivers impacting profit

Step 5: KPI & Efficiency Analysis

  • Evaluated:
    • Opex ratio
    • Gross & Net margins
    • ROI on Marketing, R&D, Payroll

📊 Key Insights

  • Profit dropped 87% due to revenue decline and cost rigidity
  • Costs remained largely fixed despite falling revenue
  • Nutrition segment showed low ROI and inefficient spending
  • Revenue highly concentrated in Sales (~80%) → concentration risk
  • Q4 recovery shows strong operating leverage potential

💡 Recommendations

  • Reallocate resources from low-ROI segments (Nutrition)
  • Optimize Opex (Marketing, Payroll)
  • Improve cost flexibility to scale with revenue
  • Diversify revenue streams to reduce dependency

📈 Result

Identified key drivers behind an 87% profit decline and proposed strategies to improve margin potential from 8% to 30%+.


🛠 Tools & Skills

  • SQL (data cleaning, transformation, aggregation)
  • Data Modeling (Star Schema)
  • Power BI (dashboard & visualization)
  • Financial Analysis (P&L, margins, cost structure)

📷 Dashboard Preview

Dashboard


🔗 Live Dashboard

👉 View on Power BI

About

No description, website, or topics provided.

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

 
 
 

Contributors

Languages