Governance of vehicle generated data: A study on the practices of data governance towards a productisation of vehicle generated data
Examensarbete för masterexamen
Product development (MPPDE), MSc
In this globalised world, technological advances require evolution in the way of capturing values when producing a resource. With this mindset, companies seek to find new resources and methods to generate a virtuous economic cycle. Data productisation is proving to be a strong trend in industry, as customers seek companies not solely for the possession of tangible products, but for the usefulness of services they provide. Thus, data governance must follow the best practises to guarantee high quality data to support services. Basic principles for understanding the area of data governance, connected vehicles, and life-cycle management within an academic setting are presented. Theoretical foundation introduces notions about products and services, leading eventually to an understanding of their role in digital transformation. The activities of data governance were studied in an industry setting. Collection of data used to understand the scenario were mainly obtained through interviews, case company documentation studies and surveys. Methods and the sequence implemented are relative to the resources available, to highlight the major points, both for researches and for the studied case company. The study begins by identifying the stakeholders involved in the data lifecycle, from its creation through its final consumption. Exploring the existing barriers through an in depth investigation to grasp the company’s current condition, its organisations, culture, methods, and stages. Within the organisation’s data governance practises, 11 barriers were discovered. The biggest roadblock encountered was data documentation. Thesis attention shifted to tackling this major barrier. As a result, a list of the organisation’s customer needs was created in order to improve or minimise impediments to the data productisation flow. The research establishes a comparative bridge between theoretical knowledge and infor mation gathered from the case company. The comparative analysis identifies theoretical enablers and drivers that the case company can prioritise in order to align current prac tices with theoretical frameworks. The barriers identified in the study centre around data challenges and working in silos. Theoretically these barriers can be addressed by focusing on actions related to data characteristics, data governance, and fostering collaboration across silos. By understanding and addressing these barriers, the company can effectively close the gap between theory and practice, facilitating a future productisation of vehicle generated data. Findings indicate that data documentation is the primary barrier hindering the produc tisation of vehicle generated data. This can be tied to an initial neglect amongst data creators to plan for future uses of data. Instead of developing planned systems, the com pany adopted approaches to address minor issues incrementally, presenting implications of data productisation and associated services. Recommendations raise focus on address ing the root cause to overcome barriers through organisational and team-level actions, by rethinking data flow and processes, leveraging data governance. Implementation of these recommendations will facilitate a successful productisation of vehicle generated data.
: Vehicle Generated Data, Data Governance, Data Management, Product Lifecycle Management, PLM, Closed-loop, Productisation of Dat