September 16, 2021 / Joanna Matthew

Predicting Global Regulatory Futures: Proactive Product Stewardship


For Product Stewards, control and management of data are essential to managing risk and sustainability initiatives. Companies must learn to adopt a proactive approach that helps them anticipate updates/changes related to the regulation and monitoring of chemical use. However, the rapidly changing regulatory landscape, improving (eco)tox data, and the current proliferation of NGO ‘red lists’, means there is a lot of data to make sense of.

In this blog, we share five ways you can be proactive in your product stewardship. We draw upon our long experience across diverse industries, observation of trends in product stewardship, and our latest research.

Democratize and Collaborate

Product stewardship achieves the most when it is democratized across a company and an industry. Regulatory management tools allow companies to manage regulatory data across the business structure from R&D to Sustainability (life cycles) and Supply Chain management. Increasingly, various industry associations and other NGOs are developing monitoring tools tailored specifically for their industry that defy old competitive rivalries and promote collaboration.

We can find many industry-specific examples - with one of the most advanced examples coming from the automotive industry where manufacturers and suppliers have been working together on various governance projects since the late 1990s.

Example 1: The IMDS (International Material Data System) - launched in 2000, was designed to track all materials used across the supply chain and has become an industry standard because it enables a level of transparency in the industry that is rare. It is this transparency and collaboration that has allowed the automotive industry to work on many other projects.

Example 2: GRMS2 is a regulatory software tool hosted by the European Automotive Manufacturers’ Association (ACEA), where automotive industry users can:

  • track regulations from the draft stage
  • provide feedback on the content or layout of fact sheets
  • ask questions relating to a particular regulation

These examples show that environmental and social agendas are driven forward faster and more comprehensively when democratized and collaborative.

Agile Pathways

Automation, horizon scanning, predictive modeling, and natural language processing are all key developments. With historical regulatory data, one can use time series analysis to predict when to expect updates from particular regulations.

Time series analysis of the CFR regulation, showing when the regulation was updated

Time series analysis of EU CLP versus Australia GHS, showing the difference in pattern over time.

Natural Language Processing (NLP) is a powerful tool used for modelling the information in legal and regulatory documents, enabling the automatic capturing of insights from large and complex data collections. The Hartree National Centre for Digital Innovation (part of the UK’s Science and Technology Facilities Council) has been using NLP to develop an intelligent search engine for regulatory documents, which transfers across languages and regulatory frameworks, using machine learning, machine translation, and knowledge engineering.

Plan for the Unknown

Companies increasingly need an early warning system to reduce regulatory risk. Using AI, for example, can enhance regulatory searches, ranking and analysis, allowing for a balance of breadth and content while reducing errors (a machine won’t miss keywords). New developments include software that can compare the old version of a document to the new, so that the changes can be easily identified, reducing human error from doing these tasks manually.


‘Scale’ in this sense refers to a way of thinking about a place or issue that takes into account both the particular and the universal. For us, scaling within the context of PS means understanding local regulatory particularities, but also the changing global context. Issues such as climate and social justice protests, the histories of local regulatory contexts (are they typically conservative or permissive?), as well as the way regulatory change in one region can affect other regions, all feed into a matrix of understanding and reflect the broadening remit of PS. Media monitoring (at local, national, and international levels), as well as NGO and responsible investor lists, are some of the ways that regulatory monitoring is scaling. A data solution that is modular, customizable, and interactive is suitable to scale your PS proactively.

The Human Element

Software can provide information, but can’t interpret it. Behind the data must lie people who not only understand the science but have a broader sense of the trends. Software tools can be very efficient in finding and analyzing regulatory information; however, it is essential that all the data is checked for accuracy and meaning by a regulatory expert. For example, with regards to the EU Chemical Strategy for Sustainability, product stewards can provide insight since they know which areas are higher priorities than others.

About Yordas Group

Yordas is an environmental consultancy firm that helps clients manage chemical regulatory compliance and the sustainability issues surrounding chemical manufacture, use, hazard communication and life cycle. Learn how you can leverage the power of data to make your Product Stewardship programs a success by scheduling a short discovery call with our Hive team to discuss your regulatory monitoring needs here: Calendly

Joanna Matthew
Senior Regulatory Consultant (UK) at Yordas Group.

With extensive experience of the automotive, aerospace and advanced manufacturing industries, Jo is responsible for coordinating custom projects relating to horizon scanning and emerging regulations, regulatory fact sheets and summaries, global monitoring services, custom software development. Jo has delivered webinars and training workshops on topics such as horizon scanning and emerging regulations and works closely with industry bodies such as ACEA and IAEG. Jo can be reached at


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