Pizzeria Order Fulfillment Process Analysis

Process Analysis Dashboard
Process Analysis Overview: Happy Path (most frequent process path)
Process Analysis Overview: Throughput Times
Process Analysis Overview: Bottlenecks
Process Conformance Overview
Conformance Process Model
Process Deviations
Optimized Order Fulfillment Process
Data Structure

Inspiration

We really enjoyed the ability to perform complex data mining techniques without hard coding. This gave some of our inexperienced team members the ability to participate and make meaningful contributions without coding.

What it does

This dashboard provides an interactive process analysis for the Pizzeria owners. With this tool, the owners can examine how their processes might be inhibiting their profits and causing lower customer ratings.

How we built it

We started by thoroughly examining the reason why Pizzeria Mamma Mia is seeking help: low customer ratings, and negative profits on deliveries. When considering these problems, we brainstormed potential factors that might be contributing to the problems from both the perspective of the customers and the business owners.

Factors potentially contributing to low ratings:

taste of food
temp of food
speed of service
cost of meal
convenience of ordering
delivery times

Factors potentially contributing to low profits

high cost / cost factor
low sales
day of week
customer type (maybe older folks order more than teenagers?)
automation of processes

From here, we were able see that many of these factors could stem from the overall ordering process. This is where we focused our analysis.

Challenges we ran into

Using this new software posed some challenges. There was a large learning curve to understand the results of our input. We did feel that we could have hard-coded some of the analysis to provide the Pizzeria with a more robust analysis. Even so, we chose to keep our analysis maintained within the software provided in order to avoid challenges with integration of outside work.

Accomplishments that we're proud of

We are really proud of the interactivity of our project. There are four clickable buttons that link to our written findings and recommendations as well as three other process analyses we created using Celonis software. Additionally, we added a selection dropdown menu that allows the user to filter on process variants to examine how each of the processes are different.

What we learned

This project gave us an opportunity to explore process mining without the need for hard coding machine learning techniques. We learned that business processes can often be messy, and this can cause other aspects of the business to suffer. Optimizing processes is the first step in improving customer satisfaction and profits.

What's next for Pizzeria Order Fulfillment Process Analysis

In the future, we would like to take what we've accomplished using the Celonis software and hard code these findings. This way, we can understand the backend processes used by the Celonis software to perform the machine learning tasks that give actionable insights.