Nordic Data Sharing Playbook, May 2025

How to build the right capabilities and kick-start a circular data sharing journey?

Mastering six core data capabilities will enable you to gain value from your circular data-sharing ecosystem


Data sharing vision, ambition & value casing Developing a shared vision, ambition, and value proposition for data sharing that aligns with the business strategy and is anchored in concrete use cases, ensuring all partners derive clear benefits from the collaboration	Partner screening & ecosystem setup Identifying partners and establishing ecosystems to enable secure and effective data sharing, ensuring alignment with clearly defined use cases that drive impact across the value chain	Data standardization & requirements Setting a strong data foundation with standardized data formats to enable seamless interoperability, accuracy, and consistency across the ecosystem and identifying opportunities and requirements for data sharing


Data management, governance & security Implementing governance frameworks, access controls, and security mechanisms to ensure secure, compliant, and responsible data management and sharing	Data sharing model, technology & platforms Defining a secure and scalable infrastructure that enables seamless data exchange, system interoperability, and integration with existing technologies	Data analytics & insights Using AI and advanced analytics to generate actionable insights from shared data and support data-driven decision making across the ecosystem

These capabilities evolve in complexity and impact as ambition increases from compliance to operational efficiency and business growth


Capabilities		Comply with regulations	Optimize operations	Drive business growth
	Data sharing vision, ambition & value casing	Shared vision for data sharing, focused on regulatory compliance and risk mitigation	Aligned vision of data-sharing initiatives with partner’s operational efficiency goals	Shared vision to use data sharing to enable new business models, foster innovation and differentiation
	Partner screening & ecosystem setup	Minimum viable data-sharing partners to meet compliance requirements	Expanded ecosystem to optimize operations and integrate data flows across supply chains	Fully interoperable and collaborative data-sharing network
	Data standardization & requirements	Basic data-sharing processes and standards to ensure regulatory compliance, and preventing data misuse	Interoperable, automated data-sharing frameworks that enable operational efficiencies	Real-time data standardization and dynamic models to support predictive decision-making and new business models
	Data management, governance & security	Basic IT infrastructure to facilitate essential data exchanges for compliance purposes	Interoperable systems that ensure secure and responsible data exchange at scale	Fully integrated governance frameworks supporting capturing business value from data
	Data sharing model, technology & platforms	Basic IT systems enabling minimal data transfer for compliance reporting	Integration of real-time platforms to support automated and scalable data exchange	Collaborative platforms enabling seamless data integration and innovation across partners
	Data analytics & insights	Limited analytics focused on compliance reporting and audit support	AI-driven analytics to improve operational performance, waste reduction, and efficiency	Predictive and prescriptive analytics to drive innovation, and enable circular business models

Regardless of the ambition level, designing, building, and scaling a circular data-sharing ecosystem can be divided into three steps

Steps	Capabilities
Assess & Define
This phase establishes the foundation for a data-sharing ecosystem by defining the vision, ambition, and value proposition. It also involves identifying and screening key ecosystem partners to ensure alignment and collaboration.		Data sharing vision, ambition & value casing
		Partner screening & ecosystem setup
Setup & Manage
The focus here is on structuring and operationalizing the ecosystem by defining partner roles, standardizing data-sharing frameworks, and ensuring interoperability. Strong data governance, security, and compliance measures are implemented to maintain trust and integrity.		Data standardization & requirements
		Data management, governance & security
Evaluate & Scale
This phase emphasizes monitoring, refining, and expanding the ecosystem through scalable technology and platforms. Data analytics and insights are leveraged to assess impact, optimize processes, and drive continuous improvement.		Data sharing model, technology & platforms
		Data analytics & insights

Discover your data-sharing maturity level with a quick assessment and unlock tailored insights to accelerate your circularity journey

Select a Maturity Level based on the Result of the Assessment

Emerging

Your organization is in the early stages of developing circular data-sharing capabilities. Early steps such as internal discussions, initial partner engagement, or pilot exchanges may already be underway.

This stage is characterized by growing awareness and interest in aligning on shared goals and building the foundations for collaboration.

Continued progress will come from clarifying your collective ambition, identifying mutual value across the ecosystem, and developing structured approaches to support long-term data-sharing efforts.

Establishing

Your organization is actively shaping the foundations needed for effective circular data sharing.

Early work may include defining initial use cases, exploring standardization approaches, or considering governance needs. These steps reflect a growing commitment to structuring how data is shared and managed across the ecosystem.

Focusing on aligning data standards, clarifying sharing requirements, and establishing governance and security frameworks will help unlock greater value and trust in your ecosystem.

Scaling

Your organization is actively scaling its data-sharing capabilities.

Platforms and infrastructure are in place, with growing interoperability and automation. Analytics and insights are increasingly embedded into decision-making processes, supporting more strategic and predictive use of shared data.

Continued focus on integration, automation, and advanced analytics will help maximize value across the ecosystem and position you to lead in circular data sharing at scale.

Go to ‘Assess & define’

Go to ‘Setup & Manage’

Go to ‘Evaluate & Scale’

Emerging

This stage is characterized by growing awareness and interest in aligning on shared goals and building the foundations for collaboration.

Continued progress will come from clarifying your collective ambition, identifying mutual value across the ecosystem, and developing structured approaches to support long-term data-sharing efforts.

Go to ‘Assess & Define’

Establishing

Your organization is actively shaping the foundations needed for effective circular data sharing.

Focusing on aligning data standards, clarifying sharing requirements, and establishing governance and security frameworks will help unlock greater value and trust in your ecosystem.

Go to ‘Setup & Manage’

Scaling

Your organization is actively scaling its data-sharing capabilities.

Continued focus on integration, automation, and advanced analytics will help maximize value across the ecosystem and position you to lead in circular data sharing at scale.

Evaluate & Scale

For each capability, this chapter summarizes real-life learnings, best-practice examples, and tangible approaches on how to get started

Introduction & key learnings
Introduction to the capability and key learnings

Approach & framework
Framework to guide you in how to set up the capability

Best-practice example
Real-life examples from Program participants or other relevant cases

Exercise
Interactive exercise for you to leverage the learnings in practice