Piece'a Pizza 2022 Operational Report
About this project
My first portfolio project, done on December 12, 2022 and entirely through Excel.
This is a year's worth of sales data from fictitious pizza place Piece'a Pizza. In this project, I played the role of a BI analyst that had been hired to find insights and recommendations in their 2022 transactional data in order to increase sales and efficiency in 2023.
Recommended analysis questions from Maven Analytics were:
- How many customers do we have each day? Are there any peak hours?
- How many pizzas are typically in an order? Do we have any bestsellers?
- How much money did we make this year? Can we identify any seasonality in the sales?
- Are there any pizzas we should take of the menu, or any promotions we could leverage?
As my first unguided project, I stuck mainly to these analysis questions, though as I gain business acumen, I would like to more critically consider what other data and measures would be beneficial to report on in future projects.
Considering my end-user (the business owners), I kept my report high-level, making usage of KPI cards for measures such as total sales and orders. These were paired with a simple line chart to provide context into seasonality and peak month sales. Although not written in my recommendations, I would encourage Piece'a Pizza to track Y-O-Y changes in future reports.
Peak days and hours were tracked with a column chart and table (though I could not figure out a way to easily remove clutter from the conditionally-formatted table in Excel).
Top and bottom 5 pizzas were displayed in a similar less-is-more fashion. I would suggest to the business owners that it could be beneficial to track the cost of making pizzas so that profit and revenue and cost could be compared in future reports.
Finally, my recommendations were listed:
Investigate cause for bottom 5 pizza sales performance.
Information-gathering will help determine Piece'a Pizza's plans regarding these underperformers. Does the recipe need to be adjusted? What do customers find unappealing about this pizza (or in contrast, what do customers find more appealing about other products?) Does it need more marketing? Does it need to be scrapped altogether?Test bundling of underperformers with high-performing pizzas.
Classic strategy to more quickly push out underperformers and bring more attention to them. It would be beneficial to track changes in transactional data specifically for these underperformers in order to evaluate the effectiveness of the campaign.Focus staffing/stocking for peak days and hours. Business hours can be changed from 11AM to as early as 10PM.
Consider increased marketing of delivery during colder months.
Created by: Mars Huynh | Data Analyst
