Internship / Assignment: Process Mining for Sales Patterns in POS Software

Internship/ Assignment: Applying Process Mining Techniques to Uncover Sales Process Patterns in Point of Sale (POS) Software (Period Continuous) – WO / University

About the assignment

This assignment explores the application of process mining methodologies to analyse event data from Point of Sale (POS) software systems. Process mining is a powerful tool for discovering, monitoring, and improving real processes by extracting knowledge from event logs readily available in today’s information systems. By focusing on a POS system, the student will engage in a practical investigation to uncover the underlying sales process, identify bottlenecks, and suggest improvements to enhance current software architectures. The foundation of process mining and its core principles can be explored further at the Process Mining Group website (www.processmining.org/overview).

Objectives

• Understand Process Mining: Understand process mining concepts, including discovery, conformance, and enhancement of software architectures.
• Data Handling: Learn how to extract, transform, and load data (ETL) from POS systems for process mining analysis.
• Process Discovery: Utilize process mining tools to discover the actual sales process as it is executed and recorded in the POS software.
• Analysis and Optimization: Identify process bottlenecks, deviations, and inefficiencies. Propose actionable insights for process optimization.
• Practical Application: Apply theoretical knowledge in a practical context, enhancing skills in data analysis, process improvement, and critical thinking

Methodology

• Literature Review: Students may start by reviewing existing literature on process mining techniques and their application in retail environments, including foundational knowledge from the Process Mining Group.
• Data Acquisition: Obtain operational data from a POS system. This dataset should include event logs capturing sales transactions, product returns, and customer interactions.
• Data Preparation: Clean and preprocess the data to fit the requirements of process mining tools, including defining case IDs, activities, and timestamps.
• Process Mining Analysis: Use process mining software (e.g., ProM (https://promtools.org/), Celonis (https://www.celonis.com/) to conduct the process discovery phase and generate process models from the event logs. Perform conformance checking to compare the discovered process models with any predefined process models (if available) or standard business practices. Report and Recommendations: Compile findings into a detailed report that outlines the discovered sales process, issues identified and proposes recommendations for architecture optimization.

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