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.