Business Process Management and Business Process Automation: A Case Study in the Luxury Industry

In the current business environment, characterized by rapid transformations and increasing competitive dynamics, the efficiency and reliability of business processes play a pivotal role in sustaining performance and value creation. Business Process Management (BPM), which aims at discovering, analyzing, redesigning, optimizing and monitoring business processes, is thus a strategic lever for organizational agility and long-term competitiveness. The study explores the theoretical foundations and key methodologies of BPM, investigating its integration with Business Process Automation (BPA) and the transformative potential of automation in business process improvement. A specific focus is devoted to Robotic Process Automation (RPA), an emerging technology in the BPA landscape that enables the automation of structured, rule-based tasks. The analysis critically examines both the opportunities and limitations associated with its implementation and also explores the transition to Intelligent Process Automation (IPA), as a natural evolution of RPA which leverages Artificial Intelligence to address processes characterized by greater variability and decision-making complexity. The thesis proceeds with a case study within a company in the luxury industry, focusing on the closing macro-process, identified as critical due to its time and resource consuming nature. The aim is to optimize selected subprocesses involved in multiple functions. The current state of processes is reconstructed through expert interviews, workshop-based discovery sessions, and targeted process mapping activities. As a result of an in-depth analysis, several inefficiencies and multiple options for addressing them are identified, while a comprehensive gap analysis supports the design of an optimized future state, specifically addressing the identification of processes best suited for automation. By integrating a structured methodological framework with empirical evidence, the thesis provides actionable insights into how organizations can leverage process management and automation tools to enhance performances, particularly in complex, time-sensitive, accuracy-critical and resource-demanding processes.