Benchmarking collaborative asset lifecycle management : strategic insights toward a win-win-win model
Rafati, Azin (2025)
Diplomityö
2025
School of Engineering Science, Tuotantotalous
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Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi-fe20251202113469
https://urn.fi/URN:NBN:fi-fe20251202113469
Tiivistelmä
This thesis explores how collaborative, data-driven practices in industrial ecosystems can enable fair and sustainable management of asset lifecycle data. The research was conducted within the CoLife project, which develops national-level models for the fair-data economy in Finland. The study aims to identify how lifecycle data can be governed and utilised collectively to create value for companies, regulators, and society.
The research applies a qualitative benchmarking approach, analysing 36 European and Finnish initiatives that represent advanced use of data in industrial lifecycle management. The cases were examined through three analytical dimensions: (1) Asset Lifecycle Management and data continuity (A-claims), (2) Collaborative Governance and trust architectures (C-claims), and (3) Value Co-Creation and fair-data business models (V-claims).
The results show that lifecycle data continuity is emerging as a strategic infrastructure that enables predictive and circular decision-making across design, operation, and end-of-life phases. Collaborative governance practices are moving from relational coordination toward policy-as-code mechanisms that institutionalise trust and transparency. Value co-creation increasingly depends on fair and programmable data architectures that link technical datasets with contractual and quality metadata, turning data into a renewable and tradeable asset.
Building on these findings, the thesis proposes the CoLife Win-Win-Win Collaboration Model, which integrates lifecycle data infrastructure, hybrid governance, and layered value architecture into a single system. This model defines CoLife as a collaborative infrastructure which is connecting technical efficiency, institutional reliability, and societal benefit. The study concludes that institutionalising lifecycle data governance can strengthen Finland’s position as a forerunner in fair-data industrial collaboration and provides actionable guidance for implementing the CoLife Playbook.
The research applies a qualitative benchmarking approach, analysing 36 European and Finnish initiatives that represent advanced use of data in industrial lifecycle management. The cases were examined through three analytical dimensions: (1) Asset Lifecycle Management and data continuity (A-claims), (2) Collaborative Governance and trust architectures (C-claims), and (3) Value Co-Creation and fair-data business models (V-claims).
The results show that lifecycle data continuity is emerging as a strategic infrastructure that enables predictive and circular decision-making across design, operation, and end-of-life phases. Collaborative governance practices are moving from relational coordination toward policy-as-code mechanisms that institutionalise trust and transparency. Value co-creation increasingly depends on fair and programmable data architectures that link technical datasets with contractual and quality metadata, turning data into a renewable and tradeable asset.
Building on these findings, the thesis proposes the CoLife Win-Win-Win Collaboration Model, which integrates lifecycle data infrastructure, hybrid governance, and layered value architecture into a single system. This model defines CoLife as a collaborative infrastructure which is connecting technical efficiency, institutional reliability, and societal benefit. The study concludes that institutionalising lifecycle data governance can strengthen Finland’s position as a forerunner in fair-data industrial collaboration and provides actionable guidance for implementing the CoLife Playbook.