It’s gratifying to see governments taking action to bolster a sustainable future. The European Commission’s Product Environmental Footprint (PEF) program, for example, will require brands to calculate and disclose how their goods affect the environment, and by measuring supply chain activities from raw materials through production and finally waste management. Activists have long pushed for such legislation, which would impel big brands to operate more sustainably.  

The PEF isn’t alone among global regulations that seek to hold brands accountable for supply chain activity. Two recent examples are California’s Transparency in Supply Chains Act and Germany’s Supply Chain Due Diligence Act. To comply with new regulations or company-led sustainability commitments, brands will need technology tools for supply chain traceability, plus an updated sustainability mindset. 

Traditionally, brands have approached sustainability from the top down, introducing sweeping corporate initiatives first, and worrying about how to implement their strategies later. But this way of thinking is already dated and ineffective. What’s now required —whether through regulation or an increasingly eco-conscious consumer base  — is moving toward sustainability from the product on up. 

Producing truly sustainable goods requires knowledge about every product and material that goes into them. The key to gathering this knowledge is data — millions of data points, in fact, and a traceability system that can house all of it in one place. 

The capacity to trace products and materials throughout the supply chain can help address many challenges. Greater supply chain visibility allows brands to anticipate disruptions before they happen. Such visibility also enables brands to make product claims and prove their authenticity. For example, a brand can claim to sell a 100% organic wool sweater, but must provide the data to back it up. 

Supply chains in various industries — including fashion, retail and food — are massive, but with little supplier visibility. These companies face the daunting task of trying to track every product as it moves through hundreds of suppliers across the globe. This reality represents a massive technology challenge that only artificial intelligence (AI) and machine learning can remedy. 

Without a traceability system, brands store much of their supply chain data in documents, either paper or electronic, often in different formats and languages. They include chain of custody invoices, social audit reports detailing workplace and pay conditions, chemical test reports for material batches and more. In short, the primary issue is data acquisition.

That’s where AI comes in, with its ability to streamline both physical and digital paper trails, thereby enabling wholescale product traceability. This process encompasses three steps: categorizing, object extraction and identification, and data validation and linking.

The categorizing process starts when the supplier submits a document into a supply chain traceability platform. The underlying AI then automatically classifies the information as, for instance, a production order, facility check or certification. 

Based on the document’s categorization, AI then identifies the key information through metadata. For example, when processing invoices, the traceability system will automatically extract and identify information like buyer, seller, product, quantity and date of delivery. Depending on the traceability system, it might also involve capturing parameters related to working conditions, fair wages, diversity, and more.

After extracting the corresponding objects, AI validates the data and connects it to other existing data within a brand’s enterprise systems. This allows it to use the data for multiple purposes, whether for forecasting, analytics, regulatory reporting or other requirements.

Supply chains are often so intricate, and the available data so broad, that it’s virtually impossible to manage without AI backing. Once enabled with full supply chain visibility, the sustainability of one or more partners in a brand’s supply chain will inevitably come into question. In that case, the supply chain must reconfigure itself through other suppliers to remain in compliance. AI allows for such rapid adjustment. 

As demonstrated by the EC’s PEF program, it eventually won’t be enough to just claim sustainability. It won’t even be enough to disclose evidence. A sustainable future is one in which brands can provide detailed calculations on product sustainability in near real-time.

Many brands are committing to sustainability and social responsibility, even before legislation begins to ramp up. Corporate commitments must now start at the product level. It won’t be easy, but traceability, backed with AI and data, can make it possible. 

Madhava Venkatesh is chief technology officer of TrusTrace.