Assess & Define
This chapter includes the following capabilities:
Data sharing vision, ambition & value casing
Data sharing vision, ambition & value casing
“The purpose of circular data sharing is for everyone in the value chain to perform better, make better choices, and optimize the production efficiency – done right, it’s a source of value.”
– Roundtable participant in the Nordic Circular Accelerator
Introduction
“The purpose of circular data sharing is for everyone in the value chain to perform better, make better choices, and optimize the production efficiency – done right, it’s a source of value.”
– Roundtable participant in the Nordic Circular Accelerator
Why a shared vision?
It is essential to define a shared vision and value case at the outset of your collaboration to establish a common focus, a clear scope, and spark continuous engagement throughout the collaboration. The vision and value case must provide value to all participant and be closely linked to your respective corporate strategies as well as the pre-defined data-sharing use case.
Vision & objectives
The vision defines the purpose of the ecosystem work clearly. Questions to consider include: “Why do we share circularity data in this ecosystem?” The reasons may vary from achieving regulatory compliance collectively, answering to new customer demands, or other aspirations. The vision is supported by objectives that guide your collaboration towards its vision.
Where the vision can be set by asking ‘Why’, the objectives are defined by asking ‘how’. “How will we collectively achieve our vision?”. You should aim at setting 2-3 key objectives that will contribute to reaching the vision.
Value case
Ensuring mutual benefits for all ecosystem actors is crucial to maintain engagement and foster trust within the collaboration. The aim should be to create a 'win-win-win' scenario that addresses the interests of all parties involved. Value should be assessed across multiple dimensions, including financial and sustainability considerations.
It is essential to define a shared vision and value case at the outset of your collaboration to establish a common focus, a clear scope, and spark continuous engagement throughout the collaboration. The vision and value case must provide value to all participant and be closely linked to your respective corporate strategies as well as the pre-defined data-sharing use case.
Vision & objectives
The vision defines the purpose of the ecosystem work clearly. Questions to consider include: “Why do we share circularity data in this ecosystem?” The reasons may vary from achieving regulatory compliance collectively, answering to new customer demands, or other aspirations. The vision is supported by objectives that guide your collaboration towards its vision.
Where the vision can be set by asking ‘Why’, the objectives are defined by asking ‘how’. “How will we collectively achieve our vision?”. You should aim at setting 2-3 key objectives that will contribute to reaching the vision.
Value case
Ensuring mutual benefits for all ecosystem actors is crucial to maintain engagement and foster trust within the collaboration. The aim should be to create a 'win-win-win' scenario that addresses the interests of all parties involved. Value should be assessed across multiple dimensions, including financial and sustainability considerations.
Introduction
Why a shared vision?
It is essential to define a shared vision and value case at the outset of your collaboration to establish a common focus, a clear scope, and spark continuous engagement throughout the collaboration. The vision and value case must provide value to all participant and be closely linked to your respective corporate strategies as well as the pre-defined data-sharing use case.
Vision & objectives
The vision defines the purpose of the ecosystem work clearly. Questions to consider include: “Why do we share circularity data in this ecosystem?” The reasons may vary from achieving regulatory compliance collectively, answering to new customer demands, or other aspirations. The vision is supported by objectives that guide your collaboration towards its vision.
Where the vision can be set by asking ‘Why’, the objectives are defined by asking ‘how’. “How will we collectively achieve our vision?”. You should aim at setting 2-3 key objectives that will contribute to reaching the vision.
Value case
Ensuring mutual benefits for all ecosystem actors is crucial to maintain engagement and foster trust within the collaboration. The aim should be to create a 'win-win-win' scenario that addresses the interests of all parties involved. Value should be assessed across multiple dimensions, including financial and sustainability considerations.
It is essential to define a shared vision and value case at the outset of your collaboration to establish a common focus, a clear scope, and spark continuous engagement throughout the collaboration. The vision and value case must provide value to all participant and be closely linked to your respective corporate strategies as well as the pre-defined data-sharing use case.
Vision & objectives
The vision defines the purpose of the ecosystem work clearly. Questions to consider include: “Why do we share circularity data in this ecosystem?” The reasons may vary from achieving regulatory compliance collectively, answering to new customer demands, or other aspirations. The vision is supported by objectives that guide your collaboration towards its vision.
Where the vision can be set by asking ‘Why’, the objectives are defined by asking ‘how’. “How will we collectively achieve our vision?”. You should aim at setting 2-3 key objectives that will contribute to reaching the vision.
Value case
Ensuring mutual benefits for all ecosystem actors is crucial to maintain engagement and foster trust within the collaboration. The aim should be to create a 'win-win-win' scenario that addresses the interests of all parties involved. Value should be assessed across multiple dimensions, including financial and sustainability considerations.
Key learnings
- Define a a shared problem statement and clear objectives at the outset of the collaboration to later the data requirements and technology choices – not the other way around
- Establish a common denominator to motivate everyone - the act of data sharing must deliver tangible benefits to everyone in the collaboration (e.g., reduced inefficiencies, improved market competitiveness) or else you risk losing momentum and engagement
- Quantify and balance the benefits of data sharing (e.g., risk mitigation by regulatory compliance) with the costs of data sharing (e.g., data generation) to understand the net value
- Make sure the value case outweigh the common barriers to share data, e.g., fear of losing ownership of data, security and competition concerns, lack of data sharing capabilities and frameworks
- Be transparent with the needs and incentives of everyone in the collaboration when defining the shared goals to build a strong foundation for continuous collaboration and engagement
- Take an explorative approach when defining the scope: Start with a set scope, open it up for exploration to finally realign the scope with the new findings
Key learnings
- Define a a shared problem statement and clear objectives at the outset of the collaboration to later the data requirements and technology choices – not the other way around
- Establish a common denominator to motivate everyone - the act of data sharing must deliver tangible benefits to everyone in the collaboration (e.g., reduced inefficiencies, improved market competitiveness) or else you risk losing momentum and engagement
- Quantify and balance the benefits of data sharing (e.g., risk mitigation by regulatory compliance) with the costs of data sharing (e.g., data generation) to understand the net value
- Make sure the value case outweigh the common barriers to share data, e.g., fear of losing ownership of data, security and competition concerns, lack of data sharing capabilities and frameworks
- Be transparent with the needs and incentives of everyone in the collaboration when defining the shared goals to build a strong foundation for continuous collaboration and engagement
- Take an explorative approach when defining the scope: Start with a set scope, open it up for exploration to finally realign the scope with the new findings
Get started with your data sharing vision, ambition & value casing
Get started with your data sharing vision, ambition & value casing
Key questions to ask your collaboration in this step: | ||||||
1 | Define the shared vision for the data sharing ecosystem Establish why data sharing is important for your collaboration. Clarify its purpose and intended impact, drawing inspiration from common use cases in the Nordics (Chapter 2). A strong shared vision ensures alignment and commitment from all stakeholders. |
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2 | Agree on the ambition level of the collaboration Determine how bold and transformative you want your collaboration to be. This includes defining the scope, scale, and level of commitment required to achieve your goals. Use the ambition levels outlined in Chapter 1 as a reference to position your collaboration effectively. |
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3 | Outline 2-3 key objectives Identify specific objectives that will guide your collaboration towards achieving its vision. These should be SMART—Specific, Measurable, Achievable, Relevant, and Time-Bound—to ensure clarity and accountability. |
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4 | Build a value framework Define how the collaboration will create value for all stakeholders involved. This includes economic, environmental, and social benefits, ensuring alignment with broader impact measurement frameworks such as The Business Impact Framework. |
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Using the Business Value Framework will help you to outline the value dimensions of your circular data sharing collaboration
To articulate the value of your data-sharing collaboration, drawing up a Business Value Framework can be useful.
A business value framework helps companies identify and communicate the expected value of a potential business initiative by outlining key value levers across pre-defined dimensions.
The example business value framework displayed here categorizes business value by whether it increases positive outcomes or decreases negative ones (y axis) and according to the level of tangibility (x axis). This creates four dimensions (quadrants): New business opportunities, Brand & innovation enhancement, Business & efficiency optimizations, and Risk mitigation & regulatory compliance.
Tip! Take inspiration from the Business Value Framework but tailor it to the specific context of your data-sharing collaboration.
Increase positive | |||||
New business opportunities
| Brand & innovation enhancement
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More tangible | Less tangible | ||||
Business & efficiency optimizations
| Risk mitigation & regulatory compliance
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Decrease negative | |||||
Case in point
Value Case for Digital Product Passport (DPP) Implementation
Case in point
Value Case for Digital Product Passport (DPP) Implementation
“DPPs are not just a compliance tool – they open new revenue opportunities for brands while driving circularity.”
– Stina Behrens, Project Manager Future Materials, Axfoundation
“DPPs are not just a compliance tool – they open new revenue opportunities for brands while driving circularity.”
– Stina Behrens, Project Manager Future Materials, Axfoundation
Axfoundation, Filippa K & GS1
Axfoundation, Filippa K & GS1 Sweden developed a value-driven approach to assess how data sharing through Digital Product Passports (DPPs) can enable profitable and sustainable fashion resale.
At the outset of the collaboration, the actors worked together to define a clear value narrative and have this inform their pilot planning.
They took the following steps:
- Identify key financial, operational, and sustainability value drivers
- Validate value assumptions through data collection and interviews
- Define pilot scope and scaling plan in accordance with value drivers
This approach ensured that the DPPs were positioned as a business enablers for circular fashion, rather than just a regulatory requirement.
Resale process | Seller initiates process and provides garment details | Garment listing is published to marketplace | Buyer finds and purchases garment | Seller packages and ships the garment to the buyer | Payment and claim handling |
↓ | ↓ | ↓ | ↓ | ↓ | |
Business outcome | DPP-driven volume boost | Increased sell-through rate Reduced manual inspection time | Higher average resale price | Reduced shipping costs | Reduced costs due to claims/disputes/returns |
...DPP data enables new resale insights, drives adoption of shared data standards, and unlocks new value drivers… | DPP-enabled value drivers  More marketplaces and brands adopting DPP in resale | …improving the resale experience for key actors such a resale sellers, buyers, and marketplace personnel… | |||
Better DPP data over time | DPP-driven resale growth | ||||
…resulting in higher resale volumes and longer garment lifetime, driving significant fashion industry sustainability impact… | …driving measurable, profitable business outcomes for both fashion brands and marketplaces… | ||||
Exercise
Exercise
Participants
5 - 10
5 - 10
Duration
1.5 hrs
1.5 hrs
Participants
5 - 10
5 - 10
Duration
1.5 hrs
1.5 hrs
Instructions
Individually or in smaller groups, brainstorm potential value drivers related to circular data sharing. Use the provided framework and its axes to guide your thoughts. Add your insights on post-it notes to place on the exercise poster.
Once everyone has contributed, reconvene as a full group and share your post-it notes in turn. Cluster the post-it notes to pinpoint 3-5 primary value drivers for each quadrant.
Next steps
Identify the cost drivers associated with data sharing to create a comprehensive value case for your collaboration.
Instructions
Individually or in smaller groups, brainstorm potential value drivers related to circular data sharing. Use the provided framework and its axes to guide your thoughts. Add your insights on post-it notes to place on the exercise poster.
Once everyone has contributed, reconvene as a full group and share your post-it notes in turn. Cluster the post-it notes to pinpoint 3-5 primary value drivers for each quadrant.
Next steps
Identify the cost drivers associated with data sharing to create a comprehensive value case for your collaboration.
Partner screening & ecosystem setup
“We shared insights that we typically keep internal, and it immediately created a better collaborative environment.”
– Vattenfall, Nordic Circular Accelerator participant
Partner screening & ecosystem setup
“We shared insights that we typically keep internal, and it immediately created a better collaborative environment.”
– Vattenfall, Nordic Circular Accelerator participant
Introduction
Why work together in a data-sharing ecosystem?
In a circular data-sharing ecosystem value chains actors collaborate on data sharing to collectively shift from linear to circular ways of doing business. By combining the resources, expertise, and insights of different actors, you create value chain visibility, advance decision-making, and drive systemic change that individual actors cannot achieve alone.
Partner screening
The first step to a successful data-sharing ecosystem is partner screening. The process involves identifying and engaging appropriate partners to form a primary ecosystem that can later be scaled into a broader network. Consider who are ‘need-to-have’ partners to kick-off the data-sharing project, and who are ‘nice-to-have’ partners to involve later to scale the work.
Choose partners ready for immediate implementation to test the collaboration but who are also aligned with the long-term strategic vision.
Ecosystem setup
A successful data-sharing ecosystem requires multi-stakeholder collaboration and effective leadership to overcome traditional barriers such as lack of cooperation and action. Strong partnerships include by-design mechanisms to enable joint ownership and foster synergetic incentives that make key stakeholders generate greater value from participation and progress. The ecosystem thrives when common practices promote trust and fairness in the digital environment, ensuring all stakeholders benefit from shared resources, knowledge, and capacity.
Introduction
Why work together in a data-sharing ecosystem?
In a circular data-sharing ecosystem value chains actors collaborate on data sharing to collectively shift from linear to circular ways of doing business. By combining the resources, expertise, and insights of different actors, you create value chain visibility, advance decision-making, and drive systemic change that individual actors cannot achieve alone.
Partner screening
The first step to a successful data-sharing ecosystem is partner screening. The process involves identifying and engaging appropriate partners to form a primary ecosystem that can later be scaled into a broader network. Consider who are ‘need-to-have’ partners to kick-off the data-sharing project, and who are ‘nice-to-have’ partners to involve later to scale the work.
Choose partners ready for immediate implementation to test the collaboration but who are also aligned with the long-term strategic vision.
Ecosystem setup
A successful data-sharing ecosystem requires multi-stakeholder collaboration and effective leadership to overcome traditional barriers such as lack of cooperation and action. Strong partnerships include by-design mechanisms to enable joint ownership and foster synergetic incentives that make key stakeholders generate greater value from participation and progress. The ecosystem thrives when common practices promote trust and fairness in the digital environment, ensuring all stakeholders benefit from shared resources, knowledge, and capacity.
Key learnings
- Develop ecosystem partnerships with intention and shared strategic goals at the center – your ecosystem needs to have a clear raison d'être
- Design your collaboration for scale, with priority foundational partners, but flexibility to grow the ecosystem through more value-adding partnerships
- Prioritize partners with a strong track record of collaboration and data transparency – this helps building a trustworthy and efficient ecosystem
- Involve potential partners early on and make sure there is a common understanding of what is important, and why each partner is important to reach joint success – ownership should be anchored early on and across the ecosystem to create a sense of commitment
- Include a good orchestrator when setting up your partner ecosystem – you need a (neutral) champion that will drive the mission relentlessly
- Make sure mutually favorable outcomes are at the forefront of decision-making and focus on progress to motivate continuous partner engagement
Key learnings
- Develop ecosystem partnerships with intention and shared strategic goals at the center – your ecosystem needs to have a clear raison d'être
- Design your collaboration for scale, with priority foundational partners, but flexibility to grow the ecosystem through more value-adding partnerships
- Prioritize partners with a strong track record of collaboration and data transparency – this helps building a trustworthy and efficient ecosystem
- Involve potential partners early on and make sure there is a common understanding of what is important, and why each partner is important to reach joint success – ownership should be anchored early on and across the ecosystem to create a sense of commitment
- Include a good orchestrator when setting up your partner ecosystem – you need a (neutral) champion that will drive the mission relentlessly
- Make sure mutually favorable outcomes are at the forefront of decision-making and focus on progress to motivate continuous partner engagement
Get started with your partner screening & ecosystem setup
Get started with your partner screening & ecosystem setup
Key questions to ask your collaboration in this step: | ||||||
1 | Cluster business stakeholders Consider your full business stakeholder landscape, and cluster the stakeholders into subgroups, such as outlined in the Circular Business Stakeholder framework. Now mark the stakeholders that could be in scope for your circular data sharing ecosystem, pending on your use case. |
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2 | Define partnership criteria Determine your criteria for partnership selection. These may focus on common circularity goals and commitments, technical interoperability, market reach, industry focus, value chain roles etc. |
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3 | Assess potential partners against criteria Conduct an analysis of your existing business partners (outlined in step 1) and potentially a broader market scan to score potential partners against your selection criteria. Base your analysis on publicly available materials and interviews. |
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4 | Set up your data sharing ecosystem Rank your potential partners according to their score against your criteria and do a pre-liminary partner selection. Meet with your partners to validate feasibility, define pilot scope, and align on next steps. |
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Grouping your stakeholder landscape can help you select the right foundational partners for your ecosystem
Identifying the right partners for your collaboration is a crucial first step towards shared success.
Establishing a data-sharing ecosystem with priority partners, while already considering potential partners for future scaling, allows you to start now and remain flexible.
Grouping stakeholders based on their proximity to your core business can help you dissect your stakeholder landscape to identify essential actors for your partner screening. Whether you include multiple stakeholders from the same group or a range of actors across groups depends on your use case and ecosystem ambition.
Tip! Once key stakeholder groups have been identified, try to define key partnership criteria (e.g., data interoperability, market reach, and commitment to circular business principles) to guide your screening.
Actors directly involved in your product or service delivery who also contribute or depend on circularity-related data flows | ||||||||||
(B) Extended Data Network
Efficiency is the key to long-term profitability. By sharing and analyzing supply chain data, businesses can eliminate waste, optimize resource use, and enhance operational performance. Leveraging real-time data improves decision-making, drives agility, and strengthens resilience in a rapidly changing landscape. | ||||||||||
(C) Broader Ecosystem
Actors beyond your immediate value chain that shape the enabling environment for circular data exchange | ||||||||||
Successful partner ecosystems are set up on several foundational pillars which enable progressive advancement and collective impact
For a data-sharing ecosystem to work, all participants need to collaborate and remain engaged.
The collective impact framework summarizes the five conditions that together produce true alignment and lead to powerful results
When setting up the ecosystem, you should first establish a shared vision, value case, and measurement strategy to maintain focus on the objectives and progress (see ‘Data sharing vision, ambition & value casing’).
The data-sharing activities should be designed to complement each other and create synergistic incentives between actors.
Throughout the collaboration, communication and guidance by an impartial party is key.
Tip! Include a neutral party to act as ‘orchestrator’ – this will help you overcome barriers in the collaboration.
Kania & Kramer (2011), Collective Impact | ||||
Common vision | Shared measurment strategy | Mutually reinforcing activities | Continous communication | Backbone support |
Establish a shared vision and value case for all actors to agree on the primary goals of the partnership | Agree on a shared methodology to continuously track progress and measure business impact | Integrate data-sharing activities undertaken by each actor to ensure they support each other and the common vision | Establish communication mechanisms to foster trust and progress among participants | Ensure ongoing support and facilitation from a dedicated (and often neutral) orchestrator |
Case in point
Sogn Biohub
“Ensuring that each partner's capabilities and objectives align with the project's goals is crucial for effective collaboration and success."
– Sogn Biohub, Nordic Circular Accelerator participant
“Ensuring that each partner's capabilities and objectives align with the project's goals is crucial for effective collaboration and success."
– Sogn Biohub, Nordic Circular Accelerator participant
Sogn Næring, ViteMeir, Simas, and other industrial partners are collaborating to develop a pyrolysis plant in Kaupanger, transforming regional biological waste into biochar and renewable energy.
The initiative aims to reduce greenhouse gas emissions and optimize resource efficiency by stabilizing carbon in biochar. The plant generates 22 GWh of renewable energy annually, fostering sustainability and regional economic growth.
A key learning for the project has been to involve partners early in the process and to
anchor the ownership across ecosystem actors for everyone to feel committed to invest time and funding during the entire collaboration.
Sogn Næring, ViteMeir, Simas, and other industrial partners are collaborating to develop a pyrolysis plant in Kaupanger, transforming regional biological waste into biochar and renewable energy.
The initiative aims to reduce greenhouse gas emissions and optimize resource efficiency by stabilizing carbon in biochar. The plant generates 22 GWh of renewable energy annually, fostering sustainability and regional economic growth.
A key learning for the project has been to involve partners early in the process and to
anchor the ownership across ecosystem actors for everyone to feel committed to invest time and funding during the entire collaboration.
Each partner's unique role strengthens the project's capacity to handle technical challenges and ensure sustainability:
- SIMAS and SIRKLA for waste management,
- Are Treindustrier for production infrastructure, Sogneprodukt for workforce inclusion, and
- Sogn Næring facilitates business networking, connecting various stakeholders and promoting collaboration.
Exercise
Exercise
Participants 5 - 10 | Duration 1.0 hrs |
Participants
5 - 10
5 - 10
Duration
1.0 hrs
1.0 hrs
Instructions
Individually or in smaller groups, brainstorm potential value drivers related to circular data sharing. Use the provided framework and its axes to guide your thoughts. Add your insights on post-it notes to place on the exercise poster.
Once everyone has contributed, reconvene as a full group and share your post-it notes in turn. Cluster the post-it notes to pinpoint 3-5 primary value drivers for each quadrant.
Next steps
Identify the cost drivers associated with data sharing to create a comprehensive value case for your collaboration.
Instructions
Individually or in smaller groups, brainstorm potential value drivers related to circular data sharing. Use the provided framework and its axes to guide your thoughts. Add your insights on post-it notes to place on the exercise poster.
Once everyone has contributed, reconvene as a full group and share your post-it notes in turn. Cluster the post-it notes to pinpoint 3-5 primary value drivers for each quadrant.
Next steps
Identify the cost drivers associated with data sharing to create a comprehensive value case for your collaboration.