Jess Barton, Head of Data and Analytics at Ecosurety, discusses the urgent need for enhanced data on packaging and waste, amid increasing regulatory demands and sustainability goals. Emphasising the challenges and importance of accurate data, she shares why a data revolution is essential in tackling rising compliance costs and environmental impacts of packaging.
Packaging and waste data for many organisations can be elusive. From my experience of data in other sectors, packaging and waste data is at the “slipperier” end of the scale – it is difficult to gather and is often passed between owners.
Product specifications, sales records and information on product content or ingredients have historically been the focus, and, when requested, are generally readily accessible for analysis.
In comparison, packaging data typically lags behind. Data is scattered, sometimes across international supply chains, and often the crucial metric of packaging weight (on which packaging compliance is based) is only an estimate at best, or missing at worst.
It can also be difficult to source information that helps us understand the recoverability of packaging, which requires information on elements such as material composition, size, format, inks, adhesives, etc. This is a problem.
Firstly, there are growing compliance requirements that require data on packaging to comply with regulations, whether it is the Extended Producer Responsibility (EPR), Plastic Packaging Tax, or other international regulations such as the European Packaging and Packaging Waste Regulation (PPWR).
Beyond regulation, lack of data also makes it challenging for organisations to understand their packaging footprint and make decisions on what to do about it.
A revolution in data in the packaging and waste industries is necessary if we are going to attempt to address the challenges we are facing, such as rising compliance costs and the environmental impact of packaging.
Organisations need good data to operate within EPR
Over the last year at Ecosurety, we have worked with clients as they have prepared their data for the first year of EPR. From this, we have observed two elements of EPR where good packaging data is crucial:
- Introduction of waste management fees for household waste: EPR will see the introduction of a new set of fees for producers where packaging ends up in household or publicly binned waste streams. This new “double bill” for packaging compliance, on top of existing PRN costs, will make it much more expensive to have overweight or overpackaged consumer goods. Having inaccurate data will no longer be an option for organisations that need to reduce these costs.
- Modulated fees and recyclability assessment: While there continue to be delays to the release of the structures that will drive modulated fees, there are already data points that producers would be wise to start gathering. This is so that these modulated fees are accurately applied to their packaging. Elements such as dimensions of packaging, laminations, and information on closures will likely be required to determine recyclability and determine modulated fees. Not being able to explain the recyclability of packaging through data will be a growing risk to producers.
Broader demands for quality data
If the first stages of EPR aren’t enough, there are greater challenges ahead which will mean that organisations need to get ahead with sorting out their packaging data.
The list of additional demands on packaging and associated data is long – there is upcoming EPR nation data reporting, plastic packaging tax, internal company sustainability targets and forthcoming new EU regulations (Packaging and Packaging Waste Regulations) to name but a few that organisations will need to consider.
The packaging data revolution – some first steps
Regulatory pressures and sustainability reporting make better packaging data essential. While it can feel like organisations are being pulled in multiple directions, there are some practical steps packaging producers can take to move forward.
Here are three that I would recommend organisations focus on to improve data on packaging:
- Treat packaging data as an asset
Organisations are too often surprised to find that packaging data is ownerless in their organisation, so it remains out-of-date, patchy and difficult to use. The data adage “rubbish in, rubbish out” feels particularly appropriate here. Where organisations treat their packaging data as an asset, with responsible guardians to ensure it is maintained, updated, and fit for purpose, you get far less “rubbish in” and can start to realise cost and environmental benefits from making decisions based on accurate data.
- Adopt common standards and open-source definitions
Packaging data can be complicated. A common mistake is to try to puzzle it out from scratch. There are growing resources to help structure packaging data in a common format, making sure the key data points are captured. The Open 3P standard is a good example of this. At Ecosurety, we share our data structures with our members to help minimise the work required here.
However, I believe there is more we can do. For example, open-source packaging specifications from manufacturers could help to plug gaps and create valuable benchmarks and standards for organisations to compare themselves against.
- Use data science, artificial intelligence (AI) & new technology
While it shouldn’t be a substitute for gathering quality data, data science and AI can be harnessed to reduce the burden of packaging data collection and to inform decisions on improving packaging.
Suggested input for packaging types based on product information could help suppliers input data on packaging, while data science can help us to identify better packaging solutions based on characteristics of products and available solutions, to help speed up decision making.
Data will be essential to tackle the challenges we face in packaging and to move towards circularity. By shining a light on these issues, championing effective data solutions for packaging and collaborating to share learnings, I believe that we can start to address these issues and move forward using data to improve packaging.
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