Automating Business Process to Enhance Organisational Efficiency and Productivity: Using Academic Intervention at Salford Business School as a Case Study

Chen, Yun; Han, Kate; Seager, Charlotte

Abstract

Organisations, particularly large ones with multiple stakeholders involved in their business processes, frequently face challenges related to process efficiency and productivity, leading to wasted resources, time, and effort, ultimately reducing overall output and performance. These issues can stem from poor workflow design or a lack of automation. Higher Education Institutions (HEIs) are no exception. For example, in academic interventions, current process models often fail to account for the complexity of the organisational context. At Salford Business School, Academic Personal Tutors (APTs) play a key role in academic intervention to support student success, by monitoring student activity and intervening when necessary. However, manually consolidating data from various platforms is time-consuming and limits the team's ability to focus on personalised student support. This paper presents an ongoing project aimed at optimising processes by utilising AI-driven data analysis, automation, and the Microsoft ecosystem for process modelling and data integration. In this developing paper, we will discuss the preliminary work we have completed on the project and outline the plans for its future development.

• Presentation Conference Type: Conference Paper (published)
• Conference Name: UKAIS2025: Shaping the Future of Academia: The Impact of AI on Teaching, Research, and Scholarship
• Acceptance Date: Jan 8, 2025
• Publication Date: Jan 8, 2025
• Deposit Date: Jan 9, 2025