【Consulting Case】Restaurant (4) : Breakdown by Periods

Recap

In the following posts, I will illustrate how the processed data were used for internal analysis, particularly to extrapolate information necessary to set up future operational strategies.

 

2020/07/14 - [Research & Analysis/Financial Modeling] - 【Consulting Case】Restaurant (3) : Monthly Snapshot

2020/07/13 - [Research & Analysis/Financial Modeling] - 【Consulting Case】Restaurant (2) : Exploratory Analysis

2020/07/13 - [Research & Analysis/Financial Modeling] - 【Consulting Case】Restaurant (1) : Accounting 

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Hourly Sales

The next analysis is sales breakdown by more granular periods: weekday and hour. Based on the transaction-level data, pivot table was created. This pivot table was then used to create pivot charts with multiple filters.

 

By Product Group

 

By Product

 

For both tables, the user can filter to (1) Month, (2) Category (Type) and (3) Product:

 

 

Using these charts, we were able to identify interesting patterns where customers in 5pm, 6pm, and 7pm, respectively, had distinct tastes throughout the observation period.

 

 

Sales by Weekday

Other time period we explored was at weekday-level. Though this may be obvious and intuitive, we confirmed the sales to be significantly higher on saturdays, with long upper tail on Sundays. A takeaway was that the sales during Sundays were typically lower than expected.

 

 

 

In the next post, we will continue discussing how external data (daily temperature) was used to analyze external factors were impacting the sales.