Sales & HR Analytics Dashboard

Project Overview

In this project, I designed and built an end-to-end interactive analytics dashboard to help a company understand its sales performance, workforce structure, and revenue drivers at a glance.

The goal was not just to visualise data but to answer real business questions that leadership teams typically ask:

Where is our revenue really coming from?
Which products and regions drive growth — and which underperform?
How is our workforce structured in terms of salary, retention, and gender balance?
Where can data guide smarter strategic decisions?

This project demonstrates my ability to translate raw data into insights that non-technical stakeholders can immediately use.

Tools & Skills

Power BI (data modelling, DAX, interactive dashboards)
Business analytics & KPI design
Data storytelling & visual design
Sales, HR, and revenue analysis

Key Insights Delivered

Sales Performance Analysis

Total revenue of £185M, broken down by product category, country, and year
Clear identification of highest-revenue products (e.g. Graphic Design & Executive PA)
Detection of lowest-performing products, highlighting opportunities for optimisation or discontinuation
Comparison of sales value vs. quantity, uncovering pricing and demand patterns

Geographic Revenue Breakdown

Revenue concentration analysis across UK, Pakistan, Kenya, and Kuwait
Immediate visibility into high-performing and underperforming markets
Supports decisions around market expansion and regional investment

HR & Workforce Analytics

Workforce overview with 384 employees
Gender distribution analysis (55% male / 45% female)
Employee retention insights, showing an 85% retention rate
Salary distribution and averages by function, revealing:
- Pay disparities across departments
- High-cost roles and potential optimisation areas

Why This Project Matters

This dashboard is designed exactly how decision-makers think:

Simple, clean visuals
High-level KPIs for executives
Drill-downs for analysts and managers

Instead of static reports, stakeholders can interactively explore the data, filter by year, country, or category, and instantly see the impact.

This project reflects how I approach data science and analytics:

Not just building models or charts — but delivering clarity, insight, and business value.

How I’d Take This Further

If this were a real business deployment, the next steps would include:

Forecasting future revenue using time-series models
Customer or product segmentation to improve targeting
Attrition risk modelling for HR
Integration with real-time or automated data pipelines