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.

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.

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.

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.

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.

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.

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.

Thesis Rens van Eggelen

Abstract:

Business Intelligence (BI) is commonly used to get value from data. It does have several limitations, though: power users serving business users is a severe bottle neck. A new approach has recently emerged to solve this bottleneck and to make business users independent: Self-Service Business Intelligence (SSBI).

Research on SSBI is slowly emerging, but the adoption is still rather slow. There are several challenges to overcome during SSBI implementations, but all research focuses on the perspectives of the organization adopting SSBI and their employees. Consultants often play a large role in these implementations, but their challenges and strategies for overcoming them is yet to be researched.

To research this, a case study design is used with the single case of consultants at Deloitte, a global leader in Data & Analytics service provision, implementing SSBI. Interviews were conducted with consultants from Deloitte Switzerland and Deloitte the Netherlands. These were then analysed using Thematic Analysis. As a result, eight categories containing a total of 23 challenges and four categories containing a total of eight strategies to overcome those challenges were identified. These were discussed with existing literature and classified as to being specific to SSBI implementations, specific to broader information systems (IS) implementations, and general consulting.

The results found that consultants do not only face SSBI-specific challenges, but also IS and consulting challenges. Furthermore, they do not only use SSBI strategies, but also strategies from IS implementations and general consulting. Although based on past observations, knowing about these challenges and strategies can help increase the success rate of SSBI implementations, as well as increase the adoption in the future.

As such, the thesis introduced a new unit of analysis to the literature of SSBI
implementations. As SSBI consultants face similar challenges and use similar strategies as other consultants, this research does not only shine light on the complexity of SSBI implementations, but also possibly enriches BI implementations and more general IS implementations. This does require future research to validate the findings.

Thesis Alina Verneret

Abstract:

This research focuses on assessing the potential benefits related to implementing a text mining tool, inside the processes handling customer feedback analysis. This study will adopt both the perspectives of customers, and business, related to the processes of customer satisfaction reviews and analysis.

The study has confirmed the following artifacts:
1. Text mining can leverage the use of customer unstructured text data.
2. Text mining can help optimizing some internal processes.
3. Co-creation of value can create new sources of knowledge flows across
the organization and enhance the customer experience.

Text mining has the potential to subsequently optimize both the processes, and the customer experience as a whole.