Complete And Accurate Product Compliance Supply Chain Data – Too Much To Ask For?

  • Blog
  • Environment, Health & Safety

Complete And Accurate Product Compliance Supply Chain Data – Too Much To Ask For?

Organizations across product value chains submit or collect data – or both – for product compliance, safety and sustainability. Although ERPs and PLMs are typically the source of truth for product BOM data, directly surveying suppliers is the only way to meet extensive product regulatory data demands.

However, manufacturers often struggle to collect reliable, timely, accurate and complete data from their suppliers. There is no single reason why: survey questions are misinterpreted, IP concerns inhibit data entry, suppliers are not properly incentivized to submit data or are over-burdened with data requests. There can be underlying systematic data collection hurdles too; PFAS requests are an emerging example that are extremely challenging to identify.

The supplier-buyer power dynamic is another critical component impacting data collection. For instance, larger buyers often have more influence over smaller suppliers, allowing them to positively influence data submissions. Furthermore, regulatory enforcement combined with potentially catastrophic litigation risk means that taking suppliers’ ‘word for it’ is not good enough. Manufacturers must show appropriate due diligence processes and granular audit trails, often necessitating digital solutions.

Verdantix finds that the combination of litigation pressure, an increasingly complex product regulatory landscape, and product digitization initiatives through digital product passports (DPPs) are driving manufacturers to migrate from in-house systems to commercial tools and services that bring regulatory expertise and de-risk compliance efforts. To support supply chain product data collection, manufacturers should consider a two-pronged technology and operational approach that leverages industry best practices, adopting:

  • Commercial product stewardship software with innovative data collection tools.
    Example suppliers in the market: 3E, Assent, iPoint-Systems, Source Intelligence, UL Solutions, Veeva Systems.
    • Many-to-many data collection models that reduce the volume of supplier responses needed. 
    • Low barrier to entry supplier data collection portals, for example local language, no log-in, intuitive interfaces, help text and chatbots.
    • Digital training solutions to upskill suppliers and improve future submissions.
    • AI-driven data management used to identify submission errors and automate aspects of supplier data entry.
    • IP protection features, such as ‘negative’ declarations and security features.

  • Operational and commercial approaches to improve supplier data collection.
    • Full material disclosures to reduce long-term supplier workloads.
    • Start with smaller, bite-sized data requests before expanding and increasing complexity.
    • Build full material transparency into contractual agreements with suppliers.
    • Attempt to build a relationship with suppliers through training, upskilling and combining software with service-driven data collection methods.

Fortunately, data collection challenges have accelerated innovation and techniques to improve declarations. For more information on best practices and technology solutions to navigate product compliance, chemical compliance, product stewardship, supply chain sustainability and circularity concepts, visit the Verdantix website.

Senior Analyst

Chris is a Senior Analyst in the Verdantix EHS practice. His current research agenda focuses on EHS software, product compliance software and digital mental health and wellbeing solutions. He was also the lead author of the most recent Verdantix EHS Software Green Quadrant benchmarking study. Chris joined Verdantix in 2020 and has previous experience at EY, where he specialized in robotic process automation (RPA). He holds an MEng in Engineering Science from the University of Oxford, with a concentration on machine learning and machine vision.