Digital commerce has expanded faster than the systems used to verify product compliance and supply chain relationships. Supchara is intended to support a more structured, reliable, and scalable approach to exchanging product safety and compliance signals among trusted participants.
The purpose of the PBC structure would be to balance commercial sustainability with the broader public good associated with product safety and compliance visibility, helping to assure by corporate charter a minimal-cost approach that maximizes adoption and thus maximizes positive consumer impact.
A working group of stakeholders across the product safety ecosystem, including brands, retailers, ecommerce platforms, testing laboratories, consumer safety advocates, and regulatory policy experts has been formed.
The working group is exploring the viability of a scalable supply chain mapping solution.
The Consumer Product Safety Commission (CPSC) has implemented a new requirement for electronically filing product safety data when regulated imported products arrive at U.S. ports. This data set involves independent laboratory testing to CPSC regulatory requirements and confirmation of the existence of the data set at the point of retail, whether brick and mortar stores or ecommerce platforms, can substantially reduce consumer risk.
While all forms of supply chain compliance could ultimately be supported by a Public Benefit Corporation, the early Supchara focus is leveraging CPSC electronic product safety data filing.
At the core of the challenge is establishing trust in the commercial relationships among brands, distributors, sellers, platforms, carriers, and other stakeholders. Once a product leaves the direct control of the brand, the complexity of supply chains blurs traceability to the point of retail. Traceability is essential to creating trust in product compliance.
The working group is exploring methods to enhance traceability but with scalable methods that allow immediate adoption by supply chain members, with the recognition that trust will scale over time as members build their base of connections within Supchara.
Trust would also be enhanced with third party laboratory testing, in-factory product inspection, and factory audit reports analyzed by Supchara.
Supchara would leverage the broad adoption of GS1 standards in place today.
The Global Trade Item Number (GTIN) is a globally unique product identifier. It forms the basis of retail UPC and EAN barcodes.
The Global Location Number (GLN) is a globally unique physical location identifier that can be applied to all supply chain members.
The Serial Shipping Container Code (SSCC) is identifier assigned to logistics units such as pallets or cartons and acts like a "license plate" to track shipping units through the supply chain.
Members of Supchara would be required to provide their GLN for traceability purposes.
While GS1 standard identifiers can be used to help brand protection, they are not consistently used and can also be mis-used by bad actors. Counterfeiters will often use the brand's GTIN on their own products, posing a significant risk to brand reputation as well as revenue. By establishing methods to increase Chain of Custody trust within Supchara, brands and consumers can be better protected.
Using an invitation model, Facebook achieved over 1 million users in less than 1 year. Often referred to as the "Facebook Effect", the invitation model can be applied to Supchara membership to achieve rapid scale as members invite their upstream and downstream business partners to join.
The success of a broadly adopted supply chain traceability solution will depend upon rapid scalability with members actively bringing new members on board.
AI would play a key role in establishing trust levels.
Analysis of the data in Supchara would be performed on a continual basis, determining membership weight based upon the number of connections, the accuracy of GLN data, and the accuracy of GTIN claims. AI would also analyze publicly available recall data and information provided to Supchara by consumer advocates and consumer protection organizations.
Additionally, reports uploaded directly by laboratory testing, product inspections, and factory audits would be analyzed by AI to validate member integrity. Bad actors would not likely have third party reports that support trustworthiness.
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