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An Outsider View: EDI Link to heading

After leaving Amazon, I joined a company that created and sold product primarily through retailers like Walmart, Macy’s, and Kohls. As an Outsider to this industry, I had a lot to learn about the business.

My responsibilities included overseeing the development of our more technical products (smartwatches, ear buds and other connected devices) as well as managing all of the company’s technology needs. In a short amount of time, we experienced 10x growth, expanding our product offerings significantly and achieving hundreds of millions of dollars in annual revenue. This growth and our increasing retail customer base presented considerable operational and logistical challenges, leading us to outgrow our ERP system and implement Infor.

This was my first direct experience with Electronic Data Interchange (EDI). After years of working on complex integrations with Fortune 500 companies, EDI seemed archaic and brittle. We chose a tool to standardize EDI messages into a more “digestible” JSON format, which helped with the new ERP integration, but connecting to partners, accurately mapping partners’ EDI and handling exceptions remained a challenge.

EDI has been around since the mid-1980s, a long-standing solution due to major retailers’ influence and investment. Despite being a “standard,” EDI lacks strict uniformity, allowing for many variations. EDI defines a document format, not specific data structures or communication methods, leading to diverse implementations. As a result, EDI is complex and costly to implement and maintain. While meant to improve communication, the costs of EDI implementation and maintenance create supply chain inefficiencies, increase operating expenses, limit participants, and result in a lack of a single source of truth.

More than a year ago, at an Infor executive summit, I casually proposed using blockchain – often linked to cryptocurrencies and perceived as having high transaction costs – to improve communication and reduce EDI’s overall inefficiencies. Combining reliable, cost-effective blockchain communication with AI integration for inventory, sourcing, planning, and logistics would allow the retail industry to evolve, enhancing customer experiences while lowering costs for all supply chain stakeholders.

The following narrative is a result of months of my on-going conversations with AI platforms (primary Gemini) around how concept this might be implemented.

EDI: The Supply Chain’s Tower of Babel Link to heading

Imagine a world where every business speaks its own unique language. A retailer places an order, but the supplier struggles to decipher it. A shipper receives instructions, but key details are lost in translation. This is the reality of today’s supply chains, still heavily reliant on Electronic Data Interchange (EDI).

Despite decades of standardization efforts, EDI remains a Tower of Babel. Each company implements it differently, leading to a complex web of bespoke mappings, costly errors, and agonizingly slow transactions. I’ve seen firsthand the frustration of teams wrestling with incompatible EDI formats, spending countless hours on data reconciliation instead of focusing on strategic growth. The promise of seamless, efficient communication remains elusive.

But with existing technologies that have evolved over the last decade and growing pressure to improve efficiencies and reduce costs, we have an opportunity and obligation to fundamentally reshape business-to-business (B2B) interactions, moving beyond the limitations of EDI to a future of frictionless data exchange. We have the ability (if not the will) to build a collaborative ecosystem built on distributed ledger technology (DLT), where a dedicated consortium defines and enforces truly standardized data formats. This isn’t just a technical upgrade; it’s a chance to finally achieve the interoperability EDI promised but never fully delivered.

The Limitations of Traditional EDI Link to heading

Electronic Data Interchange (EDI) has been a cornerstone of B2B data exchange for decades. However, its inherent limitations continue to pose significant challenges:

  • Inconsistent Implementations: Despite EDI standards (e.g., ANSI X12, EDIFACT), the actual implementation varies significantly between trading partners. This necessitates complex and bespoke mapping and translation processes.
  • High Costs: The setup, maintenance, and ongoing management of EDI systems, including VAN fees and translation software, are substantial.
  • Lack of Real-Time Visibility: Traditional EDI often operates in batch processing mode, leading to delays in data availability and hindering real-time decision-making.
  • Complexity and Errors: Mapping and translation processes are prone to errors, leading to data inconsistencies and potential disruptions in the supply chain.
  • Onboarding Challenges: Integrating new trading partners into an EDI ecosystem can be time-consuming and complex due to the need for custom configurations.

Solution Objectives (Unless You Can Think Of Better Ones) Link to heading

To address these issues, the industry should establish a next-generation platform for supply chain data exchange with the following objectives:

  • Standardization: Ensure that supply chain communications adhere to a uniform data format across all entities, dramatically reducing integration complexity and promoting seamless interoperability.

  • Interoperability: Enable seamless data exchange between all participants, regardless of their size or specific systems, by adhering to a single, enforced standard.

  • Energy and Resource Efficiency: Minimize environmental impact and operational costs through optimized energy consumption and efficient utilization of computing resources (CPU, RAM, storage). Streamline integration with existing systems, reducing the human capital and resources required for setup and ongoing maintenance.

  • Cost Reduction: Lower the total cost of ownership (TCO) for data exchange by eliminating redundant processes, reducing manual intervention, and streamlining transactions.

  • Auditable, Accountable & Transparent: Provide a real-time, immutable, and verifiable “single source of truth” for all participating parties, enhancing transparency and accountability across the supply chain. Provide all authorized participants with a clear, real-time view of relevant supply chain data and transactions, fostering trust and collaboration. This improves the accuracy, completeness, and consistency of supply chain data, reducing errors and disputes.

  • Evolutionary Compatibility: Support the continuous evolution and improvement of data exchange standards and technologies while maintaining compatibility with older transactions and systems. Enable gradual migration from legacy systems, including EDI, to the new platform.

  • Scalability: Enable the network to easily accommodate new participants and expanding transaction volumes without compromising performance or security.

Solution: DLT-Based Need-to-Know Privacy and Enforced Standardization Link to heading

To address the shortcomings of EDI, this approach leverages Distributed Ledger Technology (DLT). DLT is a way of recording and sharing data across multiple computers in a network, rather than relying on a central database. This provides increased transparency, auditability, and data integrity, as once a transaction is recorded, it becomes very difficult to change or delete.

In a typical blockchain, every transaction is visible to all participants. However, for sensitive business data in a supply chain, a “need-to-know” approach is more appropriate. This means that transaction details are shared only between the parties directly involved (e.g., supplier and retailer), enhancing privacy and minimizing unnecessary data dissemination. To achieve this, each participant operates a node, maintaining a copy of the ledger with only the information that participant is authorized to see.

To ensure that all participants use the same data formats and business rules, “distributed applications” are used. These are standardized software programs that define:

  • States/Data Objects: The structure of the data being exchanged (e.g., purchase order details).
  • Contracts/Rules: The rules that govern transactions (e.g., an invoice can only be issued after goods are delivered).
  • Flows/Workflows: The sequence of steps involved in a business process (e.g., purchase order creation to payment).

The DLT approach also supports versioning of these distributed applications to accommodate evolving business needs and technology. When mistakes occur, the DLT’s immutability ensures that the original, incorrect transaction is recorded along with a new transaction that compensates for the error, providing a clear and auditable history.

Handling Exceptions: While this DLT-based platform enforces standardized data formats and typical workflows, real-world supply chains often involve exceptions. The platform design accomodates these deviations by providing a framework for recording agreed-upon conditions or modifications to standard processes. The detailed decision-making for handling exceptions remains within each participant’s internal systems. However, the DLT serves as the auditable and transparent record of the final agreed-upon terms and the actual execution of events, ensuring all parties have a shared understanding, even when scenarios deviate from the norm.

As of the writing of this narrative, platforms like Corda seem well-suited to implement these concepts, though the creation of a specific blockchain to accomodate these requirements my be necessary.

Technical Design: Architecture, Deployment, and Scalability Link to heading

A robust and widely adopted DLT-based supply chain solution hinges on a well-architected technical framework.

Participant Nodes and Secure Connectivity Link to heading

Each participant (retailer, supplier, etc.) operates a node on suitable hardware within their private network. Nodes communicate securely using strong authentication and encryption. Approaches for secure communication may include:

  • Private Network Infrastructure: The consortium will establish or utilize a dedicated private network infrastructure (e.g., a physically isolated network segment, a managed private network service) that interconnects all participant locations. This ensures network-level isolation from the public internet.

  • Strict Firewall Rules and Access Control Lists (ACLs): Communication between participant nodes will be governed by explicit and tightly controlled firewall rules and ACLs implemented on network devices at each participant’s edge. These rules will specify the exact IP addresses and ports allowed for communication between authorized nodes, effectively limiting network access to only necessary interactions.

  • Transport Layer Security (TLS/SSL) with Mutual Authentication (mTLS): All communication between blockchain nodes will be encrypted using TLS/SSL protocols. Furthermore, we will implement mutual TLS (mTLS), requiring each node to authenticate its identity to other communicating nodes using digital certificates. This ensures that only authorized and verified nodes can establish secure connections and exchange data.

  • Node-Specific Cryptographic Identities: Each participant node will be assigned a unique cryptographic identity (public/private key pair). This identity will be used for authentication at the application level of the blockchain, verifying the origin of transactions and other network communications.

When considering the Solution Objectives the most effective strategy is likely a combination of mTLS and Node-Specific Cryptographic Identities combined with Firewall Rules.

Key Management Link to heading

Each participant is responsible for managing their cryptographic keys. Ideally the service or platform would assist with Key Management, though the methodology should be open enough that a participant can use or implement their own preferred Key Management solution.

Types of Keys Link to heading

  • Identity Keys: Each participant has a unique identity on the network, represented by a cryptographic key. This key is used to sign transactions, proving the participant’s identity.

  • Data Encryption Keys: For sensitive data that needs to be shared on a “need-to-know” basis, participants use encryption keys. These keys can be symmetric (shared between the parties involved) or asymmetric (public/private key pairs).

Participant Responsibilities Link to heading

  • Generating Keys: Participants generate their own identity keys and encryption keys using secure cryptographic algorithms.

  • Storing Keys: Participants must securely store their private keys to prevent unauthorized access. This might involve hardware security modules (HSMs), secure software wallets, or other robust key management solutions.

  • Distributing Keys: Participants share their public keys with their transacting partners. This allows them to verify signatures on transactions and encrypt data for the intended recipient. In the case of symmetric encryption, participants establish a shared secret key through a secure key exchange protocol.

  • Key Rotation: Participants should periodically rotate their keys to enhance security.

  • Key Revocation: Participants need a mechanism to revoke compromised keys and update their transacting partners.

While this DLT solution may result in a new type of blockchain, platforms like Corda can provide the infrastructure for managing identities and signing transactions. Corda also supports secure key exchange protocols. However, the responsibility for generating, storing, and distributing keys still lies with each participant.

Decentralized Data Sharing: The “Need-to-Know” Principle Link to heading

The core of this DLT solution lies in its decentralized data sharing model, built upon the fundamental principle of “need-to-know.” Unlike traditional systems where data is often centralized and accessible to a broad range of users, this approach ensures that each participant node within the private blockchain only stores and has access to the specific data directly relevant to their own business transactions and authorized interactions.

This selective data sharing is achieved through the inherent design of the DLT platform and the implementation of distributed applications. When a transaction occurs between two or more parties (e.g., a purchase order from a retailer to a supplier), the details of that transaction are securely recorded on the ledger and are accessible to the involved parties. However, this information is not automatically broadcast or made visible to all other participants on the network.

Benefits of a “Need-to-Know” Model Link to heading

  • Enhanced Privacy and Security: By limiting data access, the risk of sensitive business information being exposed to unauthorized parties is significantly reduced. Participants can confidently exchange information without unnecessary data dissemination across the entire network.

  • Improved Performance and Scalability: Smaller data footprints on each node translate to lower storage requirements and potentially faster query and processing times. This localized data storage contributes to the overall scalability of the network as the number of participants and transactions grows.

  • Reduced Data Redundancy: Eliminates the need for every participant to store all transaction data, minimizing data redundancy. This leads to more efficient resource utilization and lower storage costs.

  • Compliance with Data Privacy Regulations: The “need-to-know” principle aligns with various data privacy regulations by ensuring that personal or sensitive business data is only shared with those who have a legitimate need to access it.

  • Increased Trust and Collaboration: Participants are more likely to engage actively in the ecosystem when they have confidence that their sensitive data is protected and only shared on a necessary basis. This trust encourages more open collaboration within the supply chain.

This decentralized, “need-to-know” data sharing model is a critical differentiator from traditional EDI. It provides a secure, efficient, and privacy-preserving foundation for building a collaborative and standardized supply chain ecosystem.

Transaction Validation: Ensuring Trust and Accuracy Link to heading

Every data exchange within this private DLT ecosystem – from purchase orders and shipping notifications to invoices – undergoes rigorous validation to establish trust, ensure data accuracy and authenticity, and enforce agreed-upon business logic. This multi-faceted process acts as a gatekeeper, guaranteeing the integrity of the shared ledger.

Key Elements of the Transaction Validation Mechanism:

  • Digital Signatures: Each data exchange initiated by a participant is digitally signed using their private key. This cryptographic signature verifies the sender’s authenticity and guarantees data integrity, as any alteration would invalidate it.

  • Pre-defined Rules and Contracts (Distributed Applications): Distributed applications (smart contracts) embed the consortium’s explicitly defined data formats, business rules, and process workflows. The validation process checks each transaction against these rules. For example:

    • Purchase orders must adhere to standardized data structures with mandatory fields.
    • Shipping notifications must reference valid purchase orders and include tracking information.
    • Invoices must correspond to confirmed deliveries and comply with payment terms. Transactions failing to meet these predefined rules and formats are deemed invalid and rejected.

  • Consensus Mechanism: Ensuring Agreement Through Validation: To guarantee a consistent and accurate record, the platform employs an efficient consensus mechanism like Raft. This involves authorized participants (nodes) validating each proposed data exchange against the established rules and the current state of the supply chain. Only valid exchanges receive the necessary acknowledgements (votes) to be committed to the shared ledger.

  • Ledger Update and Immutability: Once a data exchange is validated and committed through consensus, each participating node updates its local ledger, reflecting the agreed-upon changes. This creates an immutable and chronologically linked record of the event. The cryptographic chaining of transactions ensures that any tampering with past records would be immediately evident.

Preventing Data Integrity Issues and Process Violations Link to heading

The transaction validation process proactively prevents various issues that could compromise data integrity and operational flow:

  • Invalid Data Formats: Strict adherence to standardized formats eliminates errors and delays caused by misinterpretations and manual data translation, fostering true interoperability.

  • Unauthorized Actions: Verifying the authorization of participants to initiate specific actions (e.g., suppliers sending shipping notices for confirmed orders) prevents fraudulent activities and maintains accountability.

  • Process Violations: Enforcing predefined workflows (e.g., requiring a delivery confirmation before validating an invoice) ensures adherence to the correct supply chain sequence, minimizing errors and disputes.

  • Data Tampering: The verification of digital signatures guarantees the data’s origin and ensures it has not been altered since submission, providing a reliable and auditable single source of truth.

This robust and multi-layered transaction validation mechanism, leveraging digital signatures, distributed applications, efficient consensus, and the inherent immutability of the ledger, establishes a trusted and reliable platform for seamless and standardized supply chain communication.

Scalability and Performance: Designed for Growth and Efficiency Link to heading

The DLT platform for this supply chain ecosystem must be architected with scalability and performance as core objectives, ensuring it can seamlessly accommodate the increasing number of participants and the growing volume of transactions inherent in enterprise-level operations. Several key design choices contribute to this scalability:

  • Permissioned Network Architecture: Unlike public blockchains that are open to anyone, this is a private, permissioned network. This controlled membership significantly reduces the overhead associated with verifying unknown participants and managing a potentially vast and anonymous network. Knowing the identity of each participant streamlines authentication and authorization processes, contributing to faster transaction processing.

  • Point-to-Point and Channelized Transactions: While the underlying ledger is distributed, many transactions will occur directly between the involved parties (point-to-point). For interactions involving specific groups of participants (e.g., a retailer and a set of their primary suppliers), dedicated “channels” can be established. These channels act as private sub-ledgers, isolating transaction traffic and consensus processes to only the relevant nodes. This reduces network congestion and allows for parallel processing of different sets of transactions, enhancing throughput.

  • Efficient Consensus Mechanisms (e.g., Raft): As discussed earlier, the platform will leverage an efficient, CPU-based consensus mechanism like Raft. These mechanisms are significantly less resource-intensive than Proof-of-Work used in some public blockchains, allowing for faster agreement on transactions with lower computational costs. Raft’s leader-based approach streamlines the consensus process under normal operation.

  • Optimized Transaction Size through Data Standardization: The enforced data standardization is not just for interoperability; it also directly contributes to performance. By ensuring that all data exchanges adhere to concise and well-defined formats, the size of individual transactions on the ledger is minimized. Smaller transactions require less bandwidth to transmit and less storage space, leading to improved network efficiency and faster processing times.

  • Strategic Use of Off-Ledger Data Storage (Where Appropriate): While transactional data requiring immutability and consensus will reside on the DLT, very large or less critical data elements (like detailed product specifications or large attachments) can be managed through secure off-ledger storage solutions, with only cryptographic hashes or links to this data being recorded on the DLT for verification. This prevents the ledger from becoming bloated and maintains performance.

  • Adequate Hardware Resources and Network Optimization: Best practices, certifications and potentially certified appliance solutions can be created for participant nodes to ensure they meet the necessary hardware specifications for optimal performance. Nodes should be optimized to only retain necessary “hot” data in memory, reducing resource requirements. Network infrastructure should be designed and optimized for low latency and high bandwidth to facilitate rapid communication between nodes. Observer nodes should be used for auditing and offloading necessary data to reporting systems.

Through this combination of a controlled environment, efficient communication strategies, optimized data handling, and a lightweight consensus mechanism, the DLT platform is designed to scale effectively to support a growing ecosystem of thousands of entities and a high volume of business transactions without compromising speed or reliability.

Value Proposition: DLT Over EDI - Scalability, Cost Efficiency, and Beyond Link to heading

The limitations of traditional Electronic Data Interchange (EDI) in today’s dynamic and high-volume supply chains are becoming increasingly apparent. While EDI has served industries for decades, its inherent complexities, inconsistencies, and batch-oriented nature create significant hurdles to achieving true efficiency and responsiveness. For large actors, like Walmart, managing the sheer volume of EDI transactions through point-to-point connections and local ERP processing often leads to resource bottlenecks, high operational costs, and delays that ultimately impact the end consumer.

Moving to a DLT-based platform offers a paradigm shift with a compelling value proposition, directly addressing these limitations and unlocking new levels of scalability and cost efficiency:

Enhanced Scalability for High-Volume Transactions: Unlike EDI’s reliance on cumbersome batch processing of relatively large files, a DLT platform facilitates a more granular, event-driven approach. Transactions reflecting individual supply chain events are recorded and shared in near real-time. This allows actors (shippers, suppliers, retailers, factories, etc.) to process information as it occurs, distributing the workload and avoiding resource spikes associated with processing EDI documents. The DLT platform’s architecture, with features like point-to-point communication and potentially channelized transactions, optimizes network traffic and processing, enabling the system to scale horizontally to accommodate growing transaction volumes without overwhelming individual nodes.

Significant Cost and Resource Optimization: The transition to a standardized DLT platform promises substantial cost and resource savings compared to the complexities of managing diverse EDI implementations:

  • Reduced Integration Costs: The enforced data standardization on the DLT platform eliminates the need for complex and bespoke mapping and translation processes that are a hallmark of EDI integration. This reduces development, maintenance, and CPU resources currently consumed by these tasks within ERP systems.

  • Lower Processing Overhead: Real-time, event-driven processing of smaller, standardized transactions on the DLT network is far more resource-efficient than the batch processing of varied EDI files. This minimizes the strain on participant internal systems (CPU, RAM, I/O).

  • Minimized Data Redundancy: The “need-to-know” principle ensures that each participant node only handle relevant data, reducing storage requirements and processing overhead associated with filtering irrelevant information from large EDI documents.

  • Offloading Complex Logic: Distributed applications (smart contracts) on the DLT platform can handle intricate business rules and validation processes in a decentralized manner, offloading this computational burden from internal ERP systems.

  • Efficient Consensus Mechanisms: Modern consensus algorithms like Raft offer a lightweight approach to ensuring data integrity and agreement, minimizing the energy and resource consumption associated with maintaining a consistent and trustworthy shared ledger.

Beyond Scalability and Cost: Unlocking New Value Link to heading

The benefits of a DLT platform extend beyond just handling volume and reducing expenses:

  • Real-Time Visibility and Responsiveness: The near real-time nature of DLT provides participants with unprecedented visibility into their supply chain, enabling faster decision-making and improved responsiveness to disruptions or changing customer demands.

  • Improved Data Accuracy and Reduced Errors: Enforced standardization and automated transaction validation significantly reduce the data inconsistencies and errors that plague EDI-based systems, leading to fewer disputes and more efficient operations.

  • Enhanced Transparency and Trust: The immutable and auditable nature of the DLT ledger fosters greater transparency and trust among all supply chain participants.

  • Foundation for Innovation: The DLT platform can serve as a foundation for implementing advanced technologies like AI and IoT, leveraging the standardized and trusted data for more intelligent inventory management, predictive analytics, and optimized logistics, further enhancing efficiency and customer experience.

While the operation of DLT nodes does require resources like RAM and CPU, the overall architectural shift away from the complexities of traditional EDI, coupled with strategic design choices in platform selection and data management, offers a clear pathway for all participants to achieve superior scalability, significant cost and resource optimization, and unlock substantial new value across their entire supply chain.

Architecture and Cost Considerations: Aligning with Solution Objectives Link to heading

The design of the DLT platform prioritizes scalability, cost efficiency, and ease of integration for all participants, from large enterprises to smaller suppliers. Rather than mandating specific, potentially expensive hardware configurations for every member, the architecture embraces flexibility and the potential for managed service offerings.

Architectural Flexibility Link to heading

  • Modular Design: The platform’s architecture is designed to be modular, allowing participants to interact at a level appropriate for their technical capabilities and transaction volume. While some participants, like large retailers with existing robust infrastructure, may choose to operate and manage their own full DLT nodes, the platform also envisions support for lighter-weight client integrations and the potential for managed node services provided by a core platform or accredited third parties.

  • Managed Node Options: A core platform can abstract away the complexities of running and maintaining DLT node infrastructure. Participants can subscribe to tiered service levels that align with their transaction volume and performance needs, paying a service fee instead of investing heavily in dedicated hardware and expertise. This lowers the barrier to entry significantly, especially for smaller entities, promoting inclusivity.

  • Strategic Offloading (Future Potential): While core ledger operations require dedicated nodes, the architecture could evolve to strategically offload computationally intensive tasks, such as complex smart contract execution, to specialized and potentially shared compute resources. This could optimize resource utilization across the network and reduce the burden on individual participant nodes.

  • API-Centric Integration: Regardless of how participants choose to interact with the DLT (via their own node or a managed service), the platform will provide well-documented and easy-to-use APIs for seamless integration with their existing IT infrastructure, minimizing the complexity and cost of connecting to the new ecosystem.

Efficiency as a Guiding Principle Link to heading

These architectural choices are directly aligned with creating the most cost, energy and human resource efficient solution possible:

  • Right-Sized Participation: The flexibility in node operation and the potential for managed services allow participants to choose a level of involvement and associated cost that matches their needs and resources, avoiding unnecessary capital expenditure.

  • Energy Efficiency Focus: The selection of an efficient consensus mechanism like Raft, coupled with guidance on optimizing node resource allocation (CPU, RAM, storage) based on actual workload, promotes energy efficiency and lower operational costs for all participants. The platform design will encourage resource monitoring and right-sizing.

  • Standardization Dividend: Enforced data standardization minimizes the need for costly and resource-intensive data mapping and translation processes that are prevalent in EDI systems.

  • Reduced Operational Overhead: Managed services can significantly reduce the human capital and resources required for participants to set up and maintain their connection to the DLT network.

By prioritizing architectural flexibility and cost efficiency, this DLT-based platform aims to create a sustainable and inclusive ecosystem that delivers significant value over traditional EDI for all participants, regardless of their size or technical infrastructure.

Consortium Governance: Establishing and Maintaining Standards Link to heading

A dedicated consortium is necessary for establishing and maintaining this DLT ecosystem. This independent body, inspired by other standards group governance models, will be the authority for creating, evolving, and governing the data standards. It will also define the rules for network participation, dispute resolution, and application change management.

To promote wide adoption, the consortium will release core applications under an open-source license, enabling free implementation of the standards and encouraging the development of open-source tools that facilitate interaction with the DLT network.

To ensure the long-term viability of the consortium and the platform, a sustainable financial model is necessary. Revenue streams may include tiered membership fees, certified appliance solutions, support and training services, custom application development, certification and compliance fees, grants and sponsorships, and revenue from conferences and workshops.

To balance representation and financial sustainability, the consortium could adopt a tiered membership structure:

  • Founding members: Early stakeholders who drive initial development would have significant early influence and voting rights.
  • Voting members: Active participants contributing to standards development would pay membership fees to support consortium operations and hold voting rights on application and governance decisions.
  • Participating members: Entities primarily using the network for transactions, would have lower (or no) fees or transaction-based contributions and input mechanisms (advisory committees, forums) to influence direction.
  • Technical committees/working groups: Technical experts from member organizations or open-source contributors, would be responsible for application development, testing, and maintenance.

To balance financial contributions with inclusivity, the consortium will implement mechanisms to ensure that all members, including smaller entities, can contribute to the direction of the network. These mechanisms could include:

  • Tiered membership with weighted voting: Different membership levels have varying voting power, balancing influence with contribution.
  • “Idea contribution” voting credits: Members earn votes by submitting valuable ideas, empowering participation beyond financial means.
  • Representative voting for small entities: Smaller members collectively elect representatives to amplify their voice in governance.
  • Open forums and advisory committees with voting power: Inclusive working groups focused on specific areas have a direct say in relevant decisions.
  • Innovation challenges with voting rewards: Participation in problem-solving initiatives can earn members increased voting influence.
  • Staggered or reduced fees for early-stage or small entities: Lower financial barriers to encourage broader participation from smaller organizations.
  • “Merit-based” voting rights: Additional votes are awarded for valuable contributions to the ecosystem beyond financial investment.

Conclusion: A Future of Efficiency, Transparency, and Enhanced Customer Experiences Link to heading

By combining the strengths of DLT with a robust consortium governance model, this solution offers a compelling path to replace traditional EDI with a truly interoperable, secure, and efficient platform for supply chain data exchange. The enforced standardization and real-time visibility inherent in this DLT ecosystem will empower participants to move beyond the limitations of EDI, unlocking significant benefits across the supply chain.

For each participant, the transition promises substantial cost reductions through the elimination of complex and error-prone EDI mappings, decreased manual data reconciliation, and streamlined communications and transaction processing. The inherent transparency and auditability of the DLT platform will also minimize disputes and improve overall operational efficiency.

This evolution not only improves processes and operating costs compared to EDI, it can translate into significantly enhanced customer experiences. Real-time data and standardized communication enables greater transparency regarding product origin, journey, and estimated delivery times. More efficient inventory management, driven by AI insights applied to the DLT’s single source of truth, ensures retail sites have the right products at the right time for the right customers, minimizing stockouts and maximizing customer satisfaction. This can all facilitate a retail transformation: enabling retail locations to become agile mini-fulfillment centers, enabling faster and more flexible delivery options, and catering to evolving customer expectations.