Celonis Challenge: Delivery Process Analytics

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  Workspace

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  Analysis Page 1

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  Analysis Page 2

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  Analysis Page 3

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  Answers to Analysis Questionnaire

Inspiration

Using Celonis to apply Process Mining for discovering, monitoring, and improving business processes in an accurate and analytical methods for Pizzeria Mama Mia Delivery System.

What it does

Process Mining gives objective, fact-based insights in delivery process to find relationship between customer satisfactory rating and pizza sale throughput time to identify process issues, reduce anomalies and maximize profit.

How we built it

With data sets provided by Celonis, Pizzeria Mama Mia's Case, Event, and Customer tables were uploaded to Celonis Data Pools, then using Data Modeling tool, we were able to connect different data set in relational dataset. Data was then loaded into the workspace, and we implemented different components, process variations, and KPI's to identify and investigate delivery process.

Challenges we ran into

Different challenges were faced when learning the different components of Celonis and digging deeper into PQL to implement more insightful and complex KPI's and unique components to our process findings.

Accomplishments that we're proud of

Learn Celonis Data Processing techniques and tools to put meaning into data by enabling business owners and managers to fully understand their business process and efficient approaches with automation.

What we learned

Process Mining, Celonis Technology, PQL, and Business Performance and Analytics.

What's next for Celonis Challenge: Delivery Process Analytics

Obtain more details about the phone and online service of the pizzeria. For example, what type of training their employees go through since we noticed a lot of delay and call backs in the online and phone orders. More details like the condition of their scooters could also helps us understand how we can improve the transportation to see if there's also a delay here.

Built With

• celonis