This section focuses on how I use Excel to analyze operational performance, identify inefficiencies, and uncover opportunities for process improvement and revenue growth.
Each case study demonstrates how structured data analysis can support better business decisions and improve performance across key areas such as sales, demand, and operational workflows.
Business Problem:
Limited visibility into ride demand patterns, revenue drivers, and operational bottlenecks
Approach:
Analyzed ride data using Excel to identify demand trends, customer behavior, and revenue distribution
Key Insight:
Peak demand periods and specific locations were under-optimized, leading to missed revenue opportunities
Impact:
Provided actionable insights to improve pricing strategy, driver allocation, and operational efficiency
Uber operates a high-volume ride-hailing service across major UK cities. However, leadership lacked clear visibility into demand patterns, revenue drivers, and operational inefficiencies, limiting their ability to optimize performance in a competitive, time-sensitive market.
This analysis provides an executive-level view of ride activity, focusing on demand trends, customer behavior, revenue distribution, and operational bottlenecks impacting performance and customer experience.
Business Problem:
Limited visibility into regional sales performance and product profitability
Approach:
Built an Excel-based dashboard analyzing revenue, product categories, and regional trends
Key Insight:
High-revenue regions were underperforming in profitability due to cost inefficiencies
Impact:
Enabled identification of improvement areas to optimize pricing and operational strategy
BikeGear Solutions operates as a multi-regional retail and distribution company with a diverse product portfolio across several markets. As transaction volumes and operational complexity increased, leadership faced growing challenges in maintaining clear visibility into performance drivers.
Despite strong revenue generation, there was limited insight into regional performance, product profitability, and demand patterns, making it difficult to identify inefficiencies and optimize decision-making.
To support strategic planning and sustainable growth, the organization needed to move beyond basic reporting toward data-driven performance intelligence that could uncover actionable insights and guide business decisions.
Limited visibility into regional performance and product profitability made it difficult for leadership to make informed decisions.
Built an Excel dashboard using Power Query and Pivot Tables to analyze revenue trends, product categories, regional performance, and customer segments.
High-revenue regions were underperforming in profitability due to cost inefficiencies, while revenue was heavily concentrated in a few product categories and customer segments.
Enabled identification of profit gaps and supported data-driven decisions on pricing, operations, and growth strategy.
Data Commerce Solutions operates across multiple regions and product categories. As operations scaled, leadership lacked a clear, unified view of performance, limiting their ability to optimize revenue and profitability.
Across these projects, I consistently focus on identifying inefficiencies, improving performance visibility, and translating data into actionable business decisions.