The following master’s thesis explores the optimization of the dashboard prototype of the FHNW abiliCor platform. This platform is a tool and intelligence amplifier, supporting companies in their strategic decision-making processes along the digital transformation journey by leveraging survey data.

The thesis outlines the identification, prioritization, and implementation of optimizations, which were derived through a combination of interviews, literature review, and platform testing. These improvements aim to enhance the prototype's functionality, promote the self-service concept, and positively impact the abiliCor platform’s core strength by providing an autonomous, location- and time-independent strategic analysis.

The thesis documents and visualizes the optimizations implemented within the dashboard evaluate their effectiveness, and offers insights into potential future developments and approaches, enabling multilingualism and more individual but standardized and auto-mated recommendations in a modular fashion. Through a continuous improvement process, the aim is to incrementally enhance the quality of analyses by leveraging emerging technological possibilities. This is intended to empower companies to profitably analyze the impact of digital opportunities on their business processes or overall business models. Consequently, it supports more efficient resource allocation, the identification of gaps, and the strategic achievement of sustainable competitive advantages or the targeted mitigation of competitive disadvantages to ensure long-term economic sustainability.