The Pizza Sales data was made available as a challenge by Maven Analytics, providing two CSV files, one containing the sales data and the other more detailed information about the pizzas (such a ingredient list).

Client: Plato’s Pizza, a Greek-inspired restaurant in New Jersey

Context: Transactional data from the past year has been collected but underutilized

Objective: Use data to identify opportunities to boost sales and improve efficiency

Key Questions:

Busiest days and times

Number of pizzas made during peak periods

Best and worst-selling pizzas

Average order value

Seating utilization (15 tables, 60 seats)

Note: Additional insights beyond these questions are welcome

For the Maven Pizza Challenge (2022), I took the role of a BI Consultant hired by Greek-inspired Plato’s Pizza, based in New Jersey. The goal was to use their 2015 sales data to put together a report to help the restaurant find opportunities to drive more sales and improve operations.

On a single-page dashboard, the following information is available, with a descriptive analysis below.

Busiest days and times? 

• Fridays are busiest, during lunch hour (12:00-14:00)

How many pizzas are being made during peak hours?

• Lunch Peak: From 12:00-14:00, 19 pizzas are made on average per hour, and a total of 13 189 were made over the course of the year during that time.
• Dinner Peak: From 17:00-19:00, 16 pizzas are made on average per hour, and a total of 10 628 were made over the course of the year during that time.

Best and worst-selling pizzas?

• The best-selling pizza was The Classic Deluxe Pizza, while The Thai Chicken Pizza generated the most revenue.
• The worst selling and lowest revenue generating pizza was The Brie Carre Pizza.

Average order value?

• On average, customers spent $38.31 per order placed.

How many customers do we have each day?

• An average of 60 customers placed orders at Plato’s Pizza every day, with an average of 2 pizzas per order.

How much money did we make this year, and can we identify any seasonality in the sales?

• Plato’s Pizza made $817,860.50 during the year of 2015.
• Several days saw an extraordinary rise in sales, of which the 3^rd and 4^th of July (Independence Day/weekend) contributed to $3443 and $3864 respectively, 50%-68% above the average daily sales of $2300.
• Another busy day took place on the 15^th of October, garnering an incredible revenue of $4320 (88% above average sales)
• The busiest weekend bringing in the best sales of the year was Thanksgiving and Black Friday, with a whopping combined sales of $8828 – 92% above average daily sales.
• Despite the success of Thanksgiving, July outperformed all the months and ended strongly with a total revenue of $72,558. 1935 orders were placed and 4392 pizzas consumed. 

Additional insights (with additional visuals not on the main dashboard) were required to suggest business decisions to improve operations and to reduce costs and waste. The problem areas below will be systematically identified, followed by the development of integrated solutions to address all identified challenges.

How well is seating capacity utilized? (15 tables and 60 seats)

Are there any pizzas we should take off the menu, or any promotions we could leverage?

Seating Utilization vs Capacity

Seating capacity is under-utilized. While the lunch and dinner peak hours reach 60%+ capacity on the busy days (Thursday, Friday, Saturday), other days only see an average of 30%. Less busy times of the day perform worse. Only a few days during the year saw a 100% capacity during peak hours.

Utilization has been calculated using the following method:

• Order_ID is a unique identifier for each order placed by a table
• Plato’s Pizzas stated that they have 15 tables available (60 seats in total)
• Within the orders table, a timestamp is recorded once an order has been placed in the POS system.
• A simple DAX formula to divide total orders by 15 is used, and with a matrix visualization the orders are then further divided into their hourly groups. This gives us a percentage of utilization during each hourly bracket.
• Thus Utilization rate = orders per hour divided by tables available.

Ingredient Utilization, Slow Sellers, Wastage

Cost of sales data is not available, so the overall analysis of Plato’s Pizzas focuses on total revenue. However, by examining the ingredient usage patterns, we can infer cost-efficiency and potential waste.

The number of ingredients used per pizza, relative to the total pizzas sold and revenue generated, provides insight into how well individual pizzas performed in terms of ingredient utilization. This helps highlight opportunities to streamline recipes, reduce excess usage, remove slow and poor performing items from the menu, and improve overall profitability.

A great example of a well performing pizza is The Pepperoni Pizza. Though only 11^th on the list for highest revenue, this pizza has been 4^th on the top seller list (2418 pizzas made), which makes it a highly sought after item. Lower revenue reflected is merely because of the lower selling price of the pizza – it only contains 2 ingredients other than the standard mozzarella cheese and tomato sauce after all.

Perfect utilization is further illustrated with the Pepperoni Pizza when you consider the 2 ingredients used: Pepperoni and Mozzarella cheese.

Of the 32 pizzas on the menu, Pepperoni and additional Mozzarella cheese are used on 5 other pizzas as well, which translates into fast moving ingredients and zero wastage.

The opposite is true for The Brie Carre Pizza.

Both the worst seller (490 pizzas for the entire 2015) and bringing in the least revenue ($11,59K), this pizza is a perfect example to dissect further for cost saving opportunities.

It utilizes an amount of 6 ingredients, of which 4 items; Thyme, Pears, Brie Carre Cheese and Caramelized Onions are only used for this pizza.

The other 2 ingredients are better utilized, Garlic, used on 19 other pizzas, and Prosciutto, only used on one other pizza.

Additional ingredient utilization and cost analysis would be needed for precise savings calculations, but the findings above clearly indicate actionable steps for Plato’s Pizza to increase revenue, improve profit margins, and reduce waste.

Suggestions to improve seating utilization, improve operations and reduce wastage.

• Run time-based promotions during slow hours to increase foot traffic such as happy hour deals, late lunch specials, early bird dinners discounts etc.
• Run social media campaigns and flash promotions tied to specific hours (e.g. “4PM Frenzy!”)
• Partner with local businesses or schools – offer corporate lunch discounts for nearby offices after the lunch rush or create after-school snack specials for students.
• Improve ambience or events during off-peak – offer a co-working friendly environment with free Wi-Fi, host trivia games, open-mic nights etc.
• Consider reducing wait staff during slow hours, especially between 09:00-11:00, and after dinner from 22:00-00:00.
• Leverage holidays and special events to boost marketing efforts and highlight best sellers and high-margin pizzas for increased visibility and sales.
• Consider adjusting the menu by removing slow-moving items, particularly those that require ingredients not used elsewhere, to reduce costs and wastage, and improve efficiency.

This is how I approached the project