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Thesis Lisa Janssen

Abstract: Both digital transformation and ESG (Environmental, Social, Governance) objectives are mainstream, yet critical to today’s economy. Multiple studies argue that there is a connection between digital transformation and ESG within the business context, but what that connection precisely entails remains a black box. The insurance industry is lagging in both digital transformation and ESG, so it could be assumed that insurance firms also lag in the possible connection. Several important factors were discovered by conducting an extensive literature review, several semi-structured interviews with experts in the field of insurance, and a validating document analysis.

There seems to be no direct influence between digital transformation and ESG if this is not included in the organization’s business strategy. To have the most significant possible impact on ESG objectives after a digital transformation, a practical roadmap has been designed as a support for insurance firms, where the first step is to include ESG objectives into the business strategy, then to change the organizational structure and company culture, to lastly be able to make more sustainable decisions and to invest in a greener IT infrastructure.

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Thesis Guillaume Manoukian

Abstract: This thesis examines the crucial issue of AI governance in companies and addresses the lack of clear governance frameworks that facilitate adopting and maximizing AI benefits.

Through a qualitative approach involving ten participants from the Bosch environment
(Belgium, Netherlands, Germany, and Portugal), this study investigates the implementation of AI-driven tools and proposes insights for effective governance. Companies should prioritize implementing Intelligent Process Automation by leveraging precise analyses and establishing clear internal guidelines. Moreover, creating dedicated teams, such as a data team, can significantly contribute to automating processes across different departments.

This research is built upon existing literature and knowledge in the field while providing unique insights by incorporating an internal perspective within Bosch. In practice, the recommendations from this study can be applied by creating specific teams within the company and emphasizing comprehensive documentation of AI processes and guidelines.

Further research could explore developing tailored approaches to suit specific company requirements. It is essential to acknowledge that a limitation of this study is the perpetual evolution of IPA.

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Thesis Victor Lhuilier

Abstract: In recent years, the predominant focus of organisations lied on automating business processes and augmenting productivity using ERP, SCM and CRM solutions. Nonetheless, to maintain competitiveness in the future, organisations must now surpass process automation by embedding them with greater intelligence through the integration of analytics into their processes and business application. Cutting-edge technologies like HTAP have facilitated the convergence of operational and informational environment leading to the creation of a new technology: embedded analytics.

Embedded analytics offers relevant and timely insights directly within the context of an application, reducing the need for users to switch between multiple tools or interfaces. Despite its rising popularity, research embedded analytics adoption is still inexistant. The thesis extended the UTAUT to explore factors influencing embedded analytics adoption in organisational contexts. The results indicated that performance expectancy, social influence and facilitating conditions are the primary drivers of embedded analytics adoption. It suggests that organisations and researchers should focus on enhancing performance expectancy by emphasising the usefulness and benefits of embedded analytics, leveraging social influence to promote adoption through influential figures and social norms, and providing facilitating conditions such as resources and support to remove barriers to adoption. Moreover, the findings show that company resources such as UX design, data quality and company mandate strengthen the aforementioned relationships.

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Thesis Camille Jennepin

Abstract: Organizational Sensemaking is still a hot topic for IS research field. This approach enables IS researchers to highlight the undergoing social and cognitive processes which an IS project goes through, and the way construction of meanings from these complex situations are achieved.

Mergers and acquisitions became progressively prevalent in today’s dynamic environment as organizations seek strategic growth and competitive advantage. Consequently, these events often trigger significant changes in the structure and functioning of the IS, leading to the need for restructuration projects.

To reach the research goals, a qualitative methodology approach utilizing a case study methodology and interviews will be employed. The selected case study organization will have undergone an M&A event followed by an IS restructuration project. In-depth interviews will be conducted with key stakeholders involved in both the M&A event and the later IS restructuration project. These interviews will provide rich insights into the experiences, perceptions, and interpretations of organizational members during the sensemaking process. The qualitative analysis of the interview data will involve thematic analysis to find patterns, themes, and categories related to sensemaking and its relationship to the M&A and IS restructuration.

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Thesis Loys Guglielmi

Abstract: This research study explores the nuanced impact of the Generative Artificial Intelligence’s emergence (GenAI) on employee stress levels, expectations, and challenges within the consulting and audit sector. The study was inspired by realizing the unregulated and under-acknowledged usage of GenAI tools, particularly ChatGPT, within Deloitte, a phenomenon termed ‘shadow use.’

The study strives to discern whether employees view this trend as a boon or a bane for
their professional roles and to identify the measures they consider necessary to ensure this
disruptive technology does not adversely impact their careers and work-life balance.
An interpretive exploratory research approach was employed to attain a comprehensive
and in-depth understanding of the issue at hand. This method involved conducting extensive interviews with Deloitte France employees across different hierarchical levels and an AI expert to gather diverse viewpoints. This qualitative research strategy gave an enriched perspective on how GenAI is perceived, used, and regarded within a well-established consulting firm among the market leaders.

The findings from the study reveal a spectrum of opinions and apprehensions among
employees about the advent of this technological innovation. While many consultants
acknowledge the significant potential of GenAI to automate tedious tasks, there is a general unease related to job security as the capabilities of AI continue to escalate. Various GenAI adoption challenges were identified during the research, with paramount emphasis on data confidentiality and the veracity of information. These concerns are especially significant in light of Deloitte’s responsibility to safeguard sensitive client data.

The study offers a set of pragmatic recommendations for Deloitte and analogous consulting firms. Those aim to help them facilitate an efficient, ethically compliant, and secure transition towards a generalization of GenAI in the workplace to minimize adverse impacts on employees’ well-being while optimizing productivity.

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Thesis Justine Gauchon

Abstract:

This master’s thesis presents a comprehensive framework for identifying and managing Critical Success Factors (CSFs) in Change Management within Digital Transformation (DT) initiatives.

The significance of DT, particularly in the public sector, is emphasized due to its potential to revolutionize operations, enhance service delivery, and improve citizen engagement. Yet 70% of the DT initiatives fail, mainly due to resistance coming from people.

Change management is explored as a crucial process that facilitates the successful implementation of DT, ensuring that organizational members embrace and adapt to the changes effectively.

Drawing from an extensive literature review, five key CSFs are identified: Organizational Effectiveness, Change Commitment, Project Management, IT/Technology, and External Environment. These factors are considered essential for enabling a smooth and successful transition in DT initiatives. To validate the framework, three case studies and seven interviews are conducted, providing empirical evidence and insights into the practical application of the CSFs.

Overall, this thesis offers a valuable contribution to the field of Change Management in DT, providing a structured approach for organizations, especially in the public sector, to navigate the complexities and challenges associated with these transformative projects.

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Thesis Clara Noudogbelli

Abstract: This master thesis presents a comprehensive analysis of the multifaceted impacts of outsourcing on different phases of Business Process Automation (BPA) implementation.

Through interviews with specialists involved in BPA outsourcing, valuable insights were
obtained regarding the experiences, perspectives, and challenges faced by organizations
during various stages of BPA implementation. The study identified key findings in each
phase, highlighting the importance of involving external vendors from the start, establishing effective communication channels, and addressing regulatory hurdles. Additionally, concerns related to knowledge loss and dependency on external vendors were explored, emphasizing the significance of documentation and knowledge transfer practices.

The findings align with existing literature on outsourcing and BPA, while also providing unique contributions by emphasizing the establishment of a specific vocabulary, linking outsourcing to regulatory challenges, and offering practical insights for managing outsourcing risks. The implications for theory suggest the need for careful management and coordination throughout the outsourcing process, as well as the significance of early vendor engagement.

Practically, the study offers recommendations for organizations, including the involvement of external vendors from the beginning, proactive planning for potential challenges, and the adoption of specific strategies to enhance vendor relationships and project monitoring. The study acknowledges limitations and suggests future research directions, such as exploring different industries and regions, incorporating quantitative data, examining decision-making processes, and investigating the long-term sustainability of outsourcing arrangements.

Overall, this master thesis provides a nuanced understanding of the impacts of outsourcing on BPA implementation, offering practical recommendations for organizations seeking successful outcomes in their automation journey.

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Thesis Albert Bonnin

Abstract: This thesis provides an empirical examination of the impact of the Covid-19 pandemic on business continuity planning and disaster recovery planning among businesses in Luxembourg. Guided by an initial set of six hypotheses derived from literature, this research employed a qualitative method, conducting interviews with 11 Deloitte employees and 4 professionals from different sectors in Luxembourg.

The findings revealed that the Covid-19 pandemic has underscored the importance of continuous adaptation, improvement, and integration of BCPs and DRPs. Businesses have reevaluated the criticality of different aspects of their operations and updated their response strategies accordingly. The pandemic has also led to an increased scrutiny from auditors and regulators, prompting businesses to engage in more rigorous testing of their BCPs and DRPs and to involve external expertise for plan development and certification.
Moreover, the research highlighted the need for improved communication strategies, greater cooperation with local government officials, and more proactive collaboration among stakeholders.

The interviews also suggested that digital transformation and shifts to remote work were integral components of these strategic shifts. However, further research is needed to explicitly investigate these areas, as well as the broader socio-economic impacts of crises and the specifics of supply chain resilience.

Overall, this research contributes to the understanding of BCPs and DRPs in the context of the Covid-19 pandemic, providing valuable insights for businesses, regulators, and policymakers. It underscores the importance of empirical evidence in grounding and enhancing theoretical hypotheses, highlighting the need for businesses to remain adaptable and resilient in the face of evolving threats.

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Thesis Thomas Kruger

Abstract: Artificial intelligence in the financial industry is a rapidly growing trend, and the alternative asset management industry is no exception. This paper studied the key success factors for AI adoption in alternative investment firms. The author, who recently joined
the alternative investment industry, was able to gather insights from his network. This paper seeks to explore the opportunities and risks associated with employing AI in alternative asset management as well as the challenges related to automating manual tasks across front, middle, and back offices, considering the impact of automation implementation on employee roles and responsibilities. A literature review on the application of AI in finance, specifically in hedge funds, as well as the barriers of AI adoption in organizations is presented. A research survey resulted in 103 responses from individuals working in the industry, enabling us to draw conclusions on formulated hypotheses, supported by statistical analysis.

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Thesis Bran van Wingerden

Abstract:

The advancement of Artificial Intelligence (AI) technologies increased significantly in the last few years. Moreover, the application of AI models expanded to a broader range. Hence, auditors are progressively encountering AI like systems, models and algorithms during audit and assurance projects. The growing scientific domains of eXplainable AI (XAI) and Responsible AI raise concerns around the transparency, explainability, and other ethicalities. These concerns, in combination with upcoming legislation, demand audit statements on reliability, integrity, and other aspects of AI models. Where auditing is a formal well-established practice, AI auditing is a novel practice. This research includes literature research, exploration of AI audit cases, and interviews with AI experts in order to discover relevant methods and specificalities of AI audits. Through the methodology of design science, a first formalised AI Audit Process is developed and proposed in order to provide AI auditors with a flexible reference frame to conduct customised AI audits. This research is a step towards the advancement of an AI auditing method and offers valuable insights for science and practice.