Master Thesis MSTR-2019-34

BibliographyKattige, Ajay: Strategic Portfolio Analysis on the fly – A metric based digital transformation of a foundational decision support framework.
University of Stuttgart, Faculty of Computer Science, Electrical Engineering, and Information Technology, Master Thesis No. 34 (2019).
109 pages, english.

Digital ecosystems are becoming increasingly important in today’s interconnected economy. They are becoming essential to creating new relationships and capabilities, leveraging new technologies, and accelerating innovation. The digital transformation is no longer just an add-on feature to existing channels or products and services. Instead, it is recognized as a disruptive change of the industry with the immense potential to shape the future industries. The horizontal and vertical integration of business and technological processes in and between companies represent the basis for the digital transformation. This leads to fundamental changes in the production and work processes. To keep up with these changes, it is necessary to transfer knowledge and experiences from research & development into practical usage. Thereby, the practicability and profitability of solutions could be focused on. As computing becomes more pervasive within the organization, the increase in complexity to manage the infrastructure for the disparate data sources, distributed data and software becomes proportionately expensive. With the possibility to dynamically scale the resources & enable multi-tenancy based resource sharing, cloud offerings are a promising economical choice. By creating Strategic Portfolio Analysis (SPA) On the Fly platform, which is a digitalized version of the former extemporaneous portfolio analysis technique, the effort for the collection of crucial data points and preparation of the interpreted visuals is undoubtedly reduced. Further, the platform also attempts to improve data security and results’ transparency. Thus, the concept developed in this thesis conquers the challenges – resulting from the ad hoc nature of the data generation and consumption – by presenting a comprehensive approach that involves different aspects of the application development (methodology selection and technical choices). In doing so, it compares several prominent software development methodologies and business intelligence tools based on pertinent KPIs to finally develop the prototype(s) with the optimum choice.

Department(s)University of Stuttgart, Institute of Architecture of Application Systems
Superviser(s)Leymann, Prof. Frank; Falkenthal, Michael; Wurster, Michael; Ince, Cafer
Entry dateAugust 7, 2019
   Publ. Institute   Publ. Computer Science