2026-09-29T05:35:14Zhttps://odr.chalmers.se/server/oai/request

oai:odr.chalmers.se:20.500.12380/3084362026-02-27T10:04:58ZTechnologycom_20.500.12380_21com_20.500.12380_1col_20.500.12380_57

Bakkenes, Tim Gustavsson, Axel Nilsson, Jakob Bild, Melker Junkers, Erik Trogen, Arvid Chalmers tekniska högskola / Institutionen för teknikens ekonomi och organisation Chalmers University of Technology / Department of Technology Management and Economics Löwstedt, Martin Andersson, Dan 2024-08-20T08:34:27Z 2024-08-20T08:34:27Z 2024 https://hdl.handle.net/20.500.12380/308436 TEKX18 Data governance is an increasingly relevant topic considering the growing global datasphere. Mishandling data can have risks in the form of leaking sensitive data and missed benefits from high data quality. Companies are struggling to implement successful data governance since it is hard to convey the value of data governance to chief executives, there is insufficient cooperation between business functions and IT functions, and there is a lack of data literacy. The purpose of this study is to analyse how organisations can provide conditions for data governance initiatives to succeed. A qualitative approach was used because of the complex nature of data governance. The data collected were both from a literature study, which resulted in a frame of reference, and an interview study with different experts. A majority of the interviewees were done at GKN Aerospace, also the idea-provider for this study. GKN Aerospace is currently looking for ways to improve their data governance. The frame of reference includes scientific articles about data governance and its success factors, frameworks and taxonomies, change management, communication within organisations and portrayal of value, cross-functional collaboration as well as theory about Generative AI and external factors. Besides scientific articles, business reviews and consulting reports have been used to get the latest insights about the subject and also a more practical perspective from people working in the field. The study has found that conveying the value of data governance to decision makers, increasing data literacy, encouraging change, and collaborating for data governance strategy formulation are all central for data governance initiatives to succeed. Conveying value should be done using KPIs, highlighting concrete use cases of data governance, and finally, employing a translator e.g. a Chief Data Officer. To increase data literacy and encourage change it is central to create a common vocabulary and understanding of data governance. Collaboration for data governance strategy formulation is enabled by decentralised data asset ownership for increased responsibility, a unified view of what data is strategically important, and a flexible data strategy that is business oriented. eng TEKX18-VT24-24 Technology Data Governance Data Literacy Cross-functional collaboration Business Oriented Data Governance Artificial Intelligence Data Governance to Support Business Needs A Study with GKN Aerospace Engines Examensarbete på kandidatnivå Bachelor Thesis M2 open.access