Enhancing Fast Food Franchise Analytics Through Microsoft Power

Alexander Amlani

Data Visualizer
Data Analyst
Data Engineer
Figma
Microsoft Power BI
SQL
Introduction
Our client, a US-based fast food franchisee with 11 stores, grappled with a significant data analytics challenge. Each week, the client had to manually collate data from various spreadsheets to perform an analysis. Due to the effort involved and time constraints, he was limited to conducting only a weekly analysis.
The Challenge
The client needed an efficient, automated solution to streamline data collection and enable more comprehensive and frequent analysis. The goal was to eliminate manual collation and bring all the data together into a uniform platform that would allow historic analysis and time-based comparisons.
The Solution
To address this challenge, we created a dynamic Power BI dashboard that compiled all the client's data into one cohesive database, allowing for historical analysis. This provided the franchisee with an overview of his business performance over time, facilitating the identification of trends and patterns that were previously obscured due to disjointed data.
One of the standout features of this dashboard was its dynamic time-intelligent analysis. This feature enabled a flexible switching between Current Full Month vs Prior Full Month, Month-to-Date (MTD) vs Prior MTD and Prior Year MTD, Current Week vs Last Week to Date and Last Year Week to Date, and Year-to-Date (YTD) vs Prior YTD. This flexibility offered the client an unprecedented ability to track and compare performance over various timeframes.
To quickly benchmark stores' performance, we incorporated bullet charts, providing an intuitive visual aid for comparison against selected targets. We also implemented conditional formatting in the table view, allowing for faster analysis of data by highlighting key performance indicators and changes.
The Impact
With the introduction of the Power BI dashboard, the client gained comprehensive access to historic data and could perform complex time-intelligent analyses with ease. The manual collation of data was eliminated, enabling the client to analyze performance more frequently and in greater depth. The visual aids and conditional formatting further enhanced the speed and ease of analysis.
Conclusion
This case study highlights the transformative power of Microsoft Power BI in data analytics. The client was able to shift from manual, time-consuming analysis to automated, detailed, and dynamic analytics. This transition resulted in more accurate, timely, and actionable insights, ultimately improving the client's ability to make data-driven decisions for his fast food franchise
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