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

Sammanfattning

Digitalisation initiatives have become vital for companies seeking to maintain acompetitive advantage and Self-Service Technology (SST) has emerged as a popularsolution. While much research has been conducted on customer SSTs, this thesisconcentrates on analysing internal employee SSTs. Through the identification ofkey factors and proposing strategic recommendations for organisational improve-ment, the aim is to provide valuable insights into how to increase adoption andoptimise usage of employee SSTs. Ultimately, leveraging this technology seeks toenhance Enterprise Service Management (ESM), a key process in digital strategy.It also explores the potential integration of Artificial Intelligence (AI) technology toelevate this process.Research has been done through a case study at Mölnlycke Health Care, a medicalsolutions company in Gothenburg, Sweden. Employing an abductive approach andconducting 32 semi-structured interviews with identified stakeholders, employees,and external actors, the study yielded broad insights with multiple organisationalimplications. To ensure comprehensive analysis, empirical findings were integratedwith theoretical models from technology adoption, change management, knowledgemanagement, and literature on AI.The empirical results identified seven factors influencing the adoption and usageof employee SSTs. The factors identified at Mölnlycke can, to varying degrees, belinked to those found in the literature, suggesting that they are not unique to thiscontext. Moreover, the findings underscore the need to build a robust organisa-tional foundation to ensure harnessing the full potential of the technology, whileemphasising a user-centric approach. Effective implementation and maintenancerequire dedicated resources for developing clear strategies and fostering continuousimprovement efforts. Additionally, integrating AI technologies such as AI-poweredsearch engines or chatbots offer promising opportunities to enhance performance ofemployee SSTs and ESM.