Towards Co-AM

Introduction

This section establishes practical steps for Collaborative Asset Management (Co-AM):
  • Transition from asset owner-centric AM to ecosystem-level collaboration (Co-AM)
  • Co‑AM stakeholders, roles and relationships across the lifecycle
  • Principal elements of Co-AM

Collaborative asset management (Co-AM): how does it change operations?

While traditional asset management focuses on optimizing assets within a single organization, Co-AM enables ecosystem-level coordination, shared use of asset lifecycle data, and collective value creation across organizational boundaries.

What is changing?

  • Shift asset management from an asset-owner perspective toward an ecosystem-based model.
  • Value is created collectively.
  • Organizations in the ecosystem may operate their own asset management systems; however, collaborative asset management requires these systems to be aligned with the asset owner’s asset management objectives to ensure coherence in planning, execution, and performance evaluation.

Characteristics of Co-AM

  • Multiple organizations and stakeholders.
  • Collaborative operation, maintaining and improving assets throughout the lifecycle.
  • Enabled by shared data, aligned asset management systems, and coordinated responsibilities.

Traditional owner-centric AM vs. Co-AM

While traditional AM focuses on optimizing assets within a single organization, Co-AM emphasizes ecosystem‑level coordination (trust, rules), shared data, and joint value creation throughout the asset lifecycle.

Table 1: Traditional AM vs. Co-AM
Aspect Traditional AM Collaborative AM (Co-AM)
Governance Owner-centric governance Ecosystem-centric, shared governance
Stakeholders Single dominant owner Multi-stakeholder cooperation
Data Siloed data, proprietary Shared data, interoperability
AMS One AMS per owner Multiple aligned AMS across organizations
Lifecycle Owner responsible for lifecycle management Joint lifecycle management with shared responsibilities
Business models Transactional, cost-driven Value-sharing, new service models
Culture Low transparency Trust, collaboration, shared rules, transparent

Asset management in the ISO 55000 context: traditional asset management

Traditional asset management under ISO 55000 is internally focused and owner-centric. Governance is centralized, with planning guided by asset owner-led Strategic Asset Management Plan (SAMP). Data, competencies, and lifecycle operations typically remain within organizational silos. Performance is assessed using internal KPIs. Improvement occurs through internally managed continuous-improvement processes.

Table 2: Traditional asset management in the ISO 55000 context
ISO 55000 Traditional AM
Context Internal, owner-centric
Leadership Centralized governance
Planning One SAMP, owner-led
Support Siloed data, internal competencies
Operation Owner-run lifecycle processes
Evaluation Internal KPIs
Improvement Internal continuous improvement

Collaborative asset management

In contrast to the traditional asset management, the Figure 2 and Table 3 below present a collaborative, ecosystem-wide approach to asset management. It aligns shared plans, objectives, policies, risks, values, and KPIs across organizations. Partners jointly implement asset-management plans through common processes and shared maintenance and analytics capabilities. Supporting elements include interoperable asset-management systems, shared data spaces, and cross-organizational competencies. Performance is evaluated through ecosystem KPIs, collaborative value creation, and shared learning.

Table 3: Collaborative asset management
ISO 55000 Co-AM
Context Network/ecosystem context with multi-party dependencies
Leadership Shared governance, trust frameworks
Planning Multi-AMS alignment; shared risks, values, KPIs
Support Shared data spaces, interoperability, cross-organizational competences
Operation Joint lifecycle processes, shared maintenance and predictive capabilities
Evaluation Ecosystem KPIs, collaborative value realization
Improvement Multi-party improvement cycles, shared learning

Stakeholders description: multi-stakeholder ecosystem

A brief overview of the various actors typically involved in a networked production-asset lifecycle-management environment.

Table 4: Stakeholders in a multi-stakeholder ecosystem
Role type Role Description (role in ecosystem)
Industrial customer Capital intensive industrial company Uses and manages production assets in their production sites.
Production asset manufacturer Production asset manufacturer Produces (and usually also maintains, remanufactures, refurbishes) production assets for industrial customer.
Production asset component provider Produces (and usually also maintains, remanufactures, refurbishes) production asset components for industrial customer.
Lifecycle (maintenance) service provider Maintenance service provider Provides different types of maintenance services for industrial customer.
Supportive service provider Asset management solution provider Provides solutions for ecosystem’s asset management.
Inspection services Provides inspection services for production mills.
Logistics provider Provides delivery (or reverse) logistics for assets / spare parts etc.
Engineering & consulting Provides engineering services.
ERP/MES solution provider Provides ERP/MES solutions for industrial customer.
Data management & analytics Provides data related services.
EOL & recycling partner Materials recycling, component / spare part recycling.
System integration service provider Company providing integration services for IT and industrial systems.
Ecosystem and infrastructure provider Ecosystem coordinator Daily ecosystem activities. Communicates ecosystem and engages new partners.
Infrastructure service providers Provides tools, cloud services and interfaces for ecosystem operation and management.

Colife ecosystem stakeholders

The Colife ecosystem brings together multiple stakeholders that collaborate around asset lifecycle data to improve asset management practices and create value from shared information. At the center of the ecosystem is the industrial customer or asset owner, which owns and operates production assets and is ultimately responsible for their performance, risks, and lifecycle outcomes.

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The asset owner collaborates with several stakeholder groups:

  • Production asset manufacturers
    • Production asset manufacturers design and deliver industrial equipment and production assets. In many cases, they also support the asset throughout its lifecycle through maintenance, upgrades, refurbishment, or remanufacturing activities. Manufacturers contribute valuable product knowledge, design information, and device-level data that can support improved asset management and decision-making.
  • Service providers
    • Service providers deliver maintenance and other lifecycle services for production assets. Their role is evolving from executing individual maintenance tasks toward actively supporting value creation, data-driven decision-making, and organizational learning across the asset lifecycle. Service providers contribute operational experience, maintenance records, and practical knowledge about asset condition and performance.
  • Supportive service providers
    • Supportive service providers supply specialized solutions and expertise that enable effective asset management. These may include asset management software providers, data analytics companies, system integration partners, ERP and MES solution providers, and other organizations that help collect, process, analyse, and utilize asset-related data.
  • Infrastructure providers
    • Infrastructure providers offer the technical foundation that enables ecosystem collaboration. Their services can include cloud platforms, data-sharing environments, communication interfaces, and other digital infrastructure required for managing data and supporting ecosystem operations.
  • Ecosystem coordinator
    • The ecosystem coordinator is responsible for establishing common operating principles and facilitating collaboration between ecosystem participants. The coordinator manages governance processes, stakeholder engagement, ecosystem rules, and day-to-day coordination activities that ensure the ecosystem functions effectively.

Data shared within the ecosystem

The ecosystem facilitates the exchange and utilization of a wide range of asset management data, including:

  • Product and equipment data
  • Sensor and condition monitoring data
  • Operational and production data
  • Maintenance history and service records
  • Inspection and validation information
  • Best practices and operational knowledge
  • Data standards, templates, and governance documents
  • Performance indicators and roadmaps
  • Platform and infrastructure performance data
  • Access management and security information

By combining these different data sources across organizational boundaries, ecosystem participants can improve asset performance, support predictive maintenance, enable better lifecycle decisions, and develop new data-driven services and business opportunities.

Principal elements of Co-AM: business value from shared data

Collaborative Asset Management enables organizations to create business value from shared asset lifecycle data. Achieving this requires more than technology alone. Organizations must ensure that data is available and interoperable, establish governance mechanisms that promote trust and secure data sharing, and transform shared information into operational and business value. Together, these capabilities support more effective lifecycle management, improved collaboration across stakeholders, and the development of new services and business opportunities.

Data quality and interoperability

This capability area focuses on ensuring that asset-related data is accessible, reliable, and can be exchanged seamlessly across systems and organizations.

Table 5: Data quality and interoperability elements, based on Valkokari and Kääriäinen (2025)
Element Description
Data availability and quality Effective asset lifecycle activities depend on reliable and accessible data. High-quality data must be available throughout the ecosystem and usable in decision-making processes.
System interoperability Data often resides in multiple systems and organizations. Interoperability enables the integration of data from different sources to create a comprehensive view of assets and their lifecycle status.

Governance

Governance provides the organizational, technical, and cultural foundations needed for secure and trusted data sharing.

Table 6: Governance elements, based on Valkokari and Kääriäinen (2025)
Element Description
Data Secure data management, clear ownership, privacy protection, and transparent policies are essential for establishing trust between stakeholders and enabling data sharing.
People and culture Successful collaboration requires an organizational culture that supports openness, competence development, and cross-organizational cooperation. People must be willing and able to share and use data effectively.

Business

The ultimate goal of collaborative data sharing is to generate measurable operational improvements and create new business opportunities.

Table 7: Business elements, based on Valkokari and Kääriäinen (2025)
Element Description
Value creation from data Shared data should enable predictive maintenance, reduced downtime, optimized maintenance activities, and better operational decision-making. Analytics and AI can further enhance value generation.
Business renewal Strategic use of asset lifecycle data supports the development of new service models, innovative operational practices, and ecosystem-wide value creation.

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References

References

ISO (2024) “ISO 55000:2024 Asset management — Vocabulary, overview and principles.”
Valkokari, P. and Kääriäinen, J. (2025) “Colife konseptin elementtien tunnistaminen teollisuuden omaisuudenhallinnassa,” Promaint, (4/2025), p. 44. Available at: https://www.promaintlehti.fi/lehtiarkisto/?issue=339.