Scope 3 emissions represent one of the most complex challenges organizations face in their sustainability journey, accounting for up to 80% of a company's total carbon footprint. The intricate web of indirect emissions from value chains creates significant hurdles in data collection, standardization, and supplier engagement. As a pioneer in sustainable software engineering, Think-it has developed an innovative approach that leverages data spaces and sovereign data exchange to tackle these challenges head-on.

Understanding the Core Challenges

Before diving into solutions, it's critical to understand the key challenges organizations face with Scope 3 emissions:

Data Complexity and Quality

• Collecting accurate data across complex global value chains is extremely difficult
• Organizations often rely heavily on estimations and third-party data
• Suppliers may be reluctant to share sensitive operational data
• Manual data collection processes lead to errors and inconsistencies

Main Challenges with Data Complexity and Quality in Tracking Scope 3 Emissions

Tracking Scope 3 emissions presents deep challenges for most companies—not due to a lack of intent, but because the data is complex, fragmented, and often outside the company’s direct control. Scope 3 refers to emissions that occur across the entire value chain—from suppliers to product use and end-of-life—and these are notoriously hard to quantify.

Data Availability and Access

One of the biggest barriers is access to reliable, granular emissions data from supply chain partners. Many companies are at varying stages of digital maturity, and few have the systems in place to provide real-time or standardized emissions data. Early attempts at Scope 3 tracking typically rely on emissions factors, proxy data, and industry averages due to the lack of direct measurements. As noted in the Smart Freight Centre PoC Evaluation Report (2023):

“Lack of data availability and consistency remains a key challenge in tracking emissions, especially when relying on value chain partners who may not yet be capable or incentivized to provide standardized primary data.”

Lack of Standardization

• Significant variance in measurement methodologies across companies
• Absence of unified frameworks for reporting emissions
• Inconsistent metrics and calculation approaches
• Limited transparency in data collection methods

Impact of Lack of Standardization on Scope 3 Emissions Reporting

A major roadblock to accurate Scope 3 emissions tracking is the absence of global standardization. Without consistent frameworks, companies face difficulties in collecting, processing, and reporting emissions data across increasingly complex supply chains.

Inconsistent Reporting

Organizations struggle to adhere to global frameworks like the GHG Protocol due to a lack of specific, enforceable guidelines at the industry level. This leads to inconsistent approaches, where reporting varies not just by company—but also by sector, geography, and maturity. The EU Data Strategy underscores this challenge, stating:

“A key element in this strategy is the establishment of interoperability, based on open standards and technical specifications, as well as data quality requirements and data documentation.”

Without this foundation, comparability across companies and sectors is nearly impossible.

Data Quality Issues

Most companies rely on secondary data or industry averages, particularly when supplier engagement is low. The Smart Freight Centre PoC Evaluation Report (2023) reinforces this point, noting that the lack of standardized data exchange formats limits supply chain transparency and weakens decision-making. Poor-quality data leads to flawed procurement choices and undermines emissions reduction targets.

Regulatory Uncertainty

Ongoing debates about mandatory Scope 3 disclosures—particularly in jurisdictions like the EU, UK, and U.S.—make it difficult for firms to prepare adequately. Many delay implementation until clearer regulatory direction emerges, leading to further inconsistency and missed opportunities to reduce emissions.

Regional and Size Disparities

There is a clear imbalance in reporting practices. European firms and large corporations are more likely to engage in Scope 3 disclosures, while small and medium-sized enterprises (SMEs) and firms in North America or East Asia often lag behind. This disparity creates data gaps that ripple through global supply chains, skewing carbon accounting and slowing down global decarbonization.

Ultimately, these challenges hinder effective climate action, reduce investor confidence in ESG metrics, and delay progress toward international commitments such as the Paris Agreement.

Resource Constraints

• Substantial personnel and expertise requirements
• Time-intensive data collection and verification processes
• High costs associated with implementing measurement systems
• Limited supplier capabilities, especially among smaller organizations

Think-it's Innovative Solution Framework

Working together with the Smart Freight Centre, Think-it addressed these challenges through a comprehensive approach that combines technology innovation with collaborative frameworks:

1. Data Space Architecture

To take on scope 3 emissions data, Think-it implemented a sovereign data exchange architecture built on three core pillars:

• Decentralized Control: Data remains with its owners, eliminating the need for central storage while maintaining security
• Standardized Semantics: Unified data models based on frameworks like GLEC ensure consistency and comparability
• Automated Exchange: Smart contracts and policies govern data sharing, reducing manual intervention

Decentralized Control and Standardized Semantics in Data Architecture

Think-it's approach to improving Scope 3 emissions tracking and security involves the use of a decentralized control system and standardized semantics within their data architecture. This strategy addresses the complexities of data collection and sharing across global value chains

Decentralized Control & Standardized Semantics in Scope 3 Emissions Tracking Achieving scalable and trustworthy data exchange for emissions tracking requires both decentralized infrastructure and common semantic models. These two pillars support data sovereignty, enhance data quality, and facilitate cross-company automation.

Decentralized Control

Rather than centralizing data in a single platform, decentralized control allows each organization to retain ownership and control over their data. Through the use of dataspace connectors, participants manage access policies, enforce contracts, and share data without relinquishing custody. This minimizes the risks associated with centralized storage—including data breaches, misuse, or loss of sovereignty.

As outlined in the Eclipse Dataspace Protocol:

“The protocol ensures that data remains under the control of the data owner at all times… enforcing policies through connectors without the need to move or centralize the data.”

This approach is aligned with the EU Data Governance Act, which promotes trusted data intermediaries and decentralized technical solutions to ensure legal compliance and individual control.

Standardized Semantics

To enable meaningful collaboration, the data exchanged must be semantically aligned. This is where frameworks like the Global Logistics Emissions Council (GLEC) model come into play. By using shared data models for carbon accounting, companies ensure that emissions data is comparable and consistent across entities, regions, and sectors.

From the Smart Freight Centre PoC Evaluation Report (2023):

“The adoption of the GLEC Framework provides a harmonized foundation for emissions data, enabling consistency across industry actors and automating exchange.”

Standardized semantics also unlock automation. With machine-readable formats and smart contracts, companies can implement policy-based exchanges without manual processing, reducing administrative burden and human error.

Benefits:

• Improved Data Security: Decentralized architectures prevent the single points of failure common in centralized systems.
• Enhanced Data Consistency: Common standards like GLEC ensure reliable, auditable reporting across the supply chain.
• Automated Exchange: Smart contracts and EDC connectors enable policy-driven automation, reducing overhead and increasing reliability.

2. Technology Implementation

The solution leveraged cutting-edge technologies:

• Cloud Infrastructure: Built on AWS for scalability and security
• Eclipse Dataspace Components (EDC): Enables sovereign data exchange between participants
• Microservices Architecture: Ensures modularity and maintainability
• API-First Design: Facilitates seamless integration with existing systems

3. Collaborative Framework

Think-it's approach emphasizes collaboration through:

• Stakeholder Engagement: Regular workshops and feedback sessions
• Industry Partnerships: Collaboration with key players like Smart Freight Centre
• Open Source Contributions: Active participation in EDC development
• Knowledge Sharing: Documentation and training resources

Step-by-Step Implementation Process

Phase 1: Discovery and Foundation

• Assess current data collection processes and gaps
• Define key stakeholders and their requirements
• Establish data governance framework
• Design initial architecture and integration points

Phase 2: Technical Implementation

• Deploy cloud infrastructure and security controls
• Implement EDC connectors for data exchange
• Develop standardized APIs for integration
• Set up monitoring and logging systems

Phase 3: Supplier Onboarding

• Provide documentation and training materials
• Assist with technical integration
• Validate data quality and formats
• Enable secure authentication and access

Phase 4: Optimization and Scale

• Monitor system performance and usage
• Gather feedback from participants
• Implement improvements based on learnings
• Expand to additional suppliers and use cases

Measuring Success

Think-it's approach included clear metrics for success:

Operational Metrics

• Data quality improvements
• Processing time reduction
• System availability and performance
• Number of successful data exchanges

Business Impact

• Increased supplier participation
• Improved emissions visibility
• Cost savings from automation
• Enhanced reporting accuracy

Real-World Impact

Think-it's solution has demonstrated significant improvements in:

• A 93% improvement in operational efficiency through automated data exchange.
• Data quality and consistency through standardized data models.
• Supplier engagement through improved onboarding processes.
• Real-time visibility of emissions data across the supply chain.

Future Vision

Think-it is proud to be able to showcase the possibilities of supply chain visibility and continues to innovate in this space through:

• Advanced Analytics: AI/ML capabilities for improved insights
• Expanded Integration: Support for additional data sources and formats
• Enhanced Automation: Reduced manual intervention requirements
• Industry Standards: Active participation in standards development

Conclusion

Solving for Scope 3 emissions requires a comprehensive approach that addresses both technical and organizational challenges. Think-it's innovative data space solution provided organizations with the tools and frameworks needed to achieve accurate emissions tracking while maintaining data sovereignty and security. Through continued innovation and collaboration, Think-it is helping organizations move closer to their sustainability goals while setting new standards for emissions reporting and management.

For more information on Think-it's approach to solving Scope 3 emissions and data sharing, visit our data sharing webpage.

Frequently Asked Questions

What are the main challenges with data complexity in tracking Scope 3 emissions?

Companies face challenges due to the nature of Scope 3 emissions, which occur outside organizational boundaries and cannot be measured directly. This leads to reliance on estimates and proxy data.

How does lack of standardization affect Scope 3 emissions reporting?

The absence of uniform guidelines leads to inconsistent reporting, data quality issues, and regulatory uncertainty, affecting global supply chain decarbonization efforts.

Why is supplier engagement important in Scope 3 emissions data collection?

Engaging suppliers ensures data accuracy and completeness, fosters collaboration, and aligns sustainability goals, which is crucial for effective emissions data collection.