Transforming Enterprise Service Management with Employee Self-Service Technology A Case Study at Mölnlycke Health Care

Abstract

Digitalisation initiatives have become vital for companies seeking to maintain a competitive advantage and Self-Service Technology (SST) has emerged as a popular solution. While much research has been conducted on customer SSTs, this thesis concentrates on analysing internal employee SSTs. Through the identification of key factors and proposing strategic recommendations for organisational improve- ment, the aim is to provide valuable insights into how to increase adoption and optimise usage of employee SSTs. Ultimately, leveraging this technology seeks to enhance Enterprise Service Management (ESM), a key process in digital strategy. It also explores the potential integration of Artificial Intelligence (AI) technology to elevate this process. Research has been done through a case study at Mölnlycke Health Care, a medical solutions company in Gothenburg, Sweden. Employing an abductive approach and conducting 32 semi-structured interviews with identified stakeholders, employees, and external actors, the study yielded broad insights with multiple organisational implications. To ensure comprehensive analysis, empirical findings were integrated with theoretical models from technology adoption, change management, knowledge management, and literature on AI. The empirical results identified seven factors influencing the adoption and usage of employee SSTs. The factors identified at Mölnlycke can, to varying degrees, be linked to those found in the literature, suggesting that they are not unique to this context. Moreover, the findings underscore the need to build a robust organisa- tional foundation to ensure harnessing the full potential of the technology, while emphasising a user-centric approach. Effective implementation and maintenance require dedicated resources for developing clear strategies and fostering continuous improvement efforts. Additionally, integrating AI technologies such as AI-powered search engines or chatbots offer promising opportunities to enhance performance of employee SSTs and ESM.