Datengetriebene Optimierung von OKRs: Verbesserung der abteilungsübergreifenden Zusammenarbeit durch KPIs und Data Governance

Abstract

In an increasingly volatile business world, organisations are faced with the challenge of ensuring orientation, collaboration and alignment within their structures. As a result, Objectives and Key Results (OKRs) have established themselves as a modern management tool to strengthen focus, accountability and transparency and to translate strategies into operational terms. Despite this positive potential, it is clear that the mere introduction of OKRs does not automatically lead to improved collaboration or increased coordination between departments. This paper addresses the question of whether a targeted addition to the OKR methodology - for example through Key Performance Indicators (KPIs) and a clear definition of responsibilities - can contribute to improved communication and cross-departmental collaboration in line with corporate objectives. The influence of data-driven frameworks on OKR success and cross-departmental collaboration is measured with the help of a pilot study in a corporate context and the addition of quantitative and qualitative elements through surveys and expert interviews. The results of the thesis provide insight into the possible positive effects and potential for the improvement of cross-departmental collaboration through KPIs and data-driven work. They show that structured data management and clearly defined responsibilities in data delivery can make a considerable contribution to making cross-departmental dependencies in the OKR process more transparent. It can also be concluded that the integration of existing KPIs into the OKR process can specifically support cross-team collaboration.

Date of Award	2025
Original language	German (Austria)
Supervisor	Christina Feilmayr (Supervisor)