Franchise Data Analysis

Company Profile : Franchisor of beauty salons

Business Challenge : Company wanted to be able to :

• Analyze the rate at which occupancy increases of new stores during ramp-up
• Analyze growth / reduction in key expense categories over time
• Compare the performance of stores and franchises using key performance indicators
• Determine if there are any seasonal patterns in move-ins / move-outs

Solution : Metric-X developed a data warehouse using our RentViewer analytics platform.

The data warehouse contains data from the Rent Manager property management system. Using the API, data is extracted from Rent Manager, and is organized for analysis before being loaded into the data warehouse. The data warehouse contains several million General Ledger transactions, as well as data on franchises, stores, unit types.

In addition to the data obtained from the Rent Manager property management system, new data was defined :

• A calendar table to identify the weeks since start of operations of any store (1 being the first week of operations). So, for example, a comparison can be made to view the occupancy of any store in its 10th week of operation.
• A chart of accounts “translator” to enable common reporting even though most franchises used different chart of accounts
• A “Unit Size” table to identify the rentable capacity of each unit
• A “Customer” table that contains information such as how long each customer has rented at any of the stores

Benefits :
The data warehouse is the foundation for flexible data analysis and fact-based decision making. Benefits include :

• Reveals real insights through flexible, visual analytics (insights that are hard to uncover through spreadsheet style reports)
• Provides ability to ask “any question” about franchise operations without having to compile multiple Excel files and do one-off data analysis
• Helps the define key performance indicators (KPI) based on past performance and differences in store size, geography and other variables
• Enables identification of outliers and misclassified transactions so that further data cleanup can be conducted
• Does away with bulky Excel files

Tools:

• RentViewer by Metric-X
• Tableau Desktop
• Rent Manager API
• Microsoft SQL Azure