Improving data analytics to help track materials through their life-cycles is a powerful way to contribute to a circular economy and a world beyond waste – and help the resources sector contribute to net zero. Phil Lattimore speaks to the head of the UK’s first national circular economy ‘data observatory’ about why creating better data around waste and resources is crucial in supporting industry and everyone striving to implement circular principles.

It may not be as headline-grabbing as the latest high-tech, low-carbon gadgetry, electric vehicle innovation or zero carbon energy solutions, but efforts to drive improvements in data analytics in waste and resources could have a far more profound impact on efforts both to achieve net zero and move towards a circular economy.

‘You cannot achieve net zero without a circular economy. And quality data analytics is critical in making the circular economy work in a proper way,’ says Professor Peter Hopkinson, Professor of circular economy at the University of Exeter and co-director of the Exeter Centre for the Circular Economy.

Alongside fellow academic Professor Fiona Charnley at the university’s Business School, Hopkinson leads a circular economy hub (CE-Hub) research project that aims to spearhead efforts to create a sustainable circular economy in the UK as part of the £30m UKRI National Interdisciplinary Circular Economy Research (NICER) initiative.

Bringing together academics, industry practitioners, policy-makers and civic society stakeholders, the CE-Hub coordinates activity across five separate UK circular economy centres tasked with focusing on specialised areas of material flow in the UK economy: chemicals; metals; mineral-based construction materials; technology metals; and textiles.

Quality data analytics is critical in making the circular economy work in a proper way

Each centre is looking at how to reduce waste in these specific areas, increase circularity and minimise the environmental impact of those sectors. The Exeter CE-hub was set-up with £3.5m funding from UKRI and a key component is developing the UK’s first national circular ‘data observatory’ to improve the provision and quality of data, to provide a source of evidence for the UK’s roadmap towards a circular economy.

Hopkinson believes the UK economy needs a complete system redesign of how resources are used. ‘How do you create value from a circular economy? One of the broad principles is generating the highest value for the longest period from the resources that flow through the economy, to protect that value of resources,’ he explains.

‘So how do you do that? It’s a major challenge, and part of the reason is that people have a very poor understanding not just of waste flows, but of resource flows through the economy at different scales – national, value chain, firm, individual product.

“Data coverage for parts of the linear economy is better documented on the inbound – the resources and how they’re transformed at different parts of the value chain, but really poor in terms of what happens to the products and their materials after they leave their first-use cycle or their consumption phase.

“And even then, the steps for the linear economy are not fully joined up in understanding resource flows right back to the source, auditing suppliers, feedstocks, and so on.’

Hopkinson continues: ‘From a circular economy perspective, you have to improve the access to data on the inbound, and then connect the inbound and the outbound flows.

You have to understand where the value potential is and where the value leakage is – where value is being lost. And that’s not only in terms of resources but also everything else that goes into these value chains – all their impacts along the chain, negative and positive (including environmental, social and others).

‘So, if you want to achieve the overarching goal or meet the principle of circulating products, components, materials, resources at their highest value for the longest time, it’s very difficult to do that if you don’t have full oversight and full data. Even then, you have to do many, many other things to ensure you are circulating it at highest value for the longest period. And data analytics is critical to that. That’s one of the solutions and one of the key enablers for a circular economy.’

That’s why the team is developing and setting up a circular economy data observatory. ‘If you want to be able to answer industrial policy and societal questions about resources and circular economy, you need much better data and the analytical tools and methods to translate into meaningful and accessible outputs,’ he says.

Making systems work

Simone Aplin is a technical director UK at global sustainability consultancy Anthesis, one of two companies – along with data analytics specialist Topolytics – commissioned by Defra in 2019 to work separately on a project to develop a prototype end-to-end digital reporting system for Defra’s smart waste tracking project (see panel ‘Defra’s Smart Waste Tracking project’ on page 22). She believes the dearth of useful data in the UK is a fundamental barrier impeding the transition to a circular economy we need.

‘We don’t even know for sure how much waste is produced by commerce, industry, construction, and demolition or what it is,’ Aplin says. ‘Those numbers are estimates generated by a complex methodology that pieces together different snapshots of information we have.

The data we do have is often poor and patchy, and leaving aside local authority collected waste, for which there is a relatively comprehensive end-to-end reporting system, we don’t track waste.

A lot of information is held on paper so is not useable or auditable, and there are lots of “dark corners” in which waste crime can flourish, so recycling rates are difficult to calculate.’

A lot of information is held on paper so is not useable or auditable, and there are lots of “dark corners” in which waste crime can flourish, so recycling rates are difficult to calculate

Aplin says these factors make it difficult to design and deliver policy to drive a circular economy. While some data snapshots in specific areas are generated by policies such as WEEE for electronics and electrical goods, a huge amount of much more granular data will be required for extended producer responsibility (EPR) for packaging and other materials, which ‘we’re miles away from at the moment’.

‘This makes it difficult to invest in new recycling and recovery infrastructure as that detailed information is needed to build a strong investment case. If we know what materials are in the system and where they are, we can make clear decisions about how best to manage them to maximise their utility.’

Aplin says, at a micro level, there is other information needed about the composition of products and materials to ensure they are managed in a way that protects the environment and captures the most valuable resources – substances of concern and substances of interest – which would address fears about the potential to contaminate recyclate and recycled products.

Complexity and transparency

Michael Groves, CEO and founder of Topolytics, concurs that the complexity and lack of useful data in the waste system creates an issue of trust in that data, with limited transparency about what’s happening to materials and resources throughout the value chain.

‘If we want to move to a circular economy at scale, that is something we have to address. And one of the ways to do so is to get a better view of what’s happening, getting a better understanding of the data, better knowledge about the quality of the data, and ensure better quality data is being generated and is available to all the players in the system.

This is essential for better decision-making and for creating the environment where circular business models can work.’ He highlights not only circular activities such as reuse, remanufacturing and recycling but also servitisation models, where quality data is critical to managing and optimising resources.

The complexity within the sector, not only around operational functions and scale but also around regulation and levels of digitisation, has worked against a comprehensive approach to generating useful data, with legacy structural issues, a lack of transparency in supply chains and an absence of a central reprocessing strategy framework creating a disjointed reporting system, often linked to individual regulations rather than an overarching system.

Groves explains how Defra’s smart waste-tracking project is aiming to address some of these issues. ‘You have real supply chain complexity,’ he says. ‘What Defra has set out to do with its smart waste tracking system – and, of course, it’s a mandatory system – is include every licence contractor, all of whom have to report into the system.

You’re talking about tens of thousands of entities across the sector. It’s not so much of a software challenge, it’s a data challenge because what you have to do is be able to accommodate that range of different levels of sophistication, a range of different systems, the range of different ways in which different-sized contractors and other players will manage that data.’

That system has to be transparent and work efficiently. ‘It needs to work from the point of view of the regulators to provide them with the visibility that they require to make regulatory or policy-making decisions. By the same token, it needs to work for the industry, because it can’t stop the industry operating. We have to find that balance.’

Data systems

Both Anthesis and Topolytics developed separate end-to-end waste tracking systems for the Defra project, and have commercial offerings now available informed by this research and development (Anthesis’s Vastum, and Topolytics WasteMap) that can track complex waste across value chains through digitally recorded and verified transactions.

Although their approaches may be different, both systems enable greater digitisation of waste tracking and, therefore, greater transparency, traceability and verification of waste streams, with Anthesis’ solution focusing on legal compliance, transparency and business intelligence and Topolytics claiming its system is ‘making the world’s waste visible, verifiable and valuable’.

Such data analytics platforms reflect the increasing digitisation and availability of technology within the waste sector – from AI, machine learning and the internet of things (IoT) to bin sensors, vehicle sensors, and GPS – which is enabling the development of a more data-driven approach.

Meanwhile, new regulatory requirements around waste such as EPR and the plastics tax, plus the zero carbon agenda, the growing importance of environmental, social and governance reporting and the increasing awareness of the need for resource security, are all factors driving the demand for better quality data.

People are beginning to scale circular economy business models and new ecosystems that are underpinned by data analytics and digital enablers

Hopkinson believes the momentum for this transformation in data analytics is also being driven by progressive, pioneering organisations, companies and individuals that see the value – and the business – opportunity, as well as the impact on achieving net zero targets.

‘People are seeing that, by deploying digital solutions and data analytics, you can start to unpack and spot opportunities for value creation and value capture that wouldn’t have been possible previously. People are beginning to scale circular economy business models and new ecosystems that are underpinned by data analytics and digital enablers,’ he says.

He cites Google and SAP as two examples of giant organisations leading the way around transparency of material flows in their value chain.

He says the issue of resource security was another factor behind the NICER project, with the pandemic providing a wake-up call for government around the issue of supply chain risk and reliance on certain geopolitical markets, such as China, and the realisation within Whitehall ‘about the role of data analytics to visualise and understand where the brittleness is in current supply chains around major resource flows’.

Observation

Explaining the goal of the ‘data observatory’, Hopkinson says: ‘We feel that data and technology is key to not just driving the value proposition, but evidencing it – because, often, there’s a lot of talk but not so much evidence.’

He maintains that, often, we’re not collecting the right data, and through the existing waste systems we’re incentivised to collect data in a certain way, so we need to think about how we measure, report and record and make data accessible. A lot of data isn’t, he says, particularly in the commercial area. ‘And you need access to that because that accounts for a large portion of resource and material flows through the economy.’ Some areas are not collected at all, compounding a situation that generates data multiplicity and fragmentation.

Using data to establish evidence is, therefore, a central mission of the observatory. ‘We’re not short of data – we’re short of insight. And short of practical evidence at different scales, whether it’s product scale, firm scale, value chain scale or national scale.’ Data analytics is crucial to visibility and transparency of the supply chain, he says.

What better data analytics and a robust evidence base should do is allow us to optimise not just resources and waste flows, but also much higher value creation from stocks and flows of resources in the economy

At policy scale, frequently asked questions around the waste and resources sector and the value creation opportunity from systemic circular economy transformations could be addressed with a greater degree of certainty by using data analytics more effectively. ‘Our aim is to create this open-source architecture and infrastructure that enables many stakeholders – with complementary interests and, perhaps, access to data and tools – to come together, so the data ecosystem creates more than the sum of the parts.

‘That’s what we’re trying to do, and answer lots of different stakeholder challenges and questions in a coherent, systematic and comprehensive way. The idea behind the observatory is to create an open-source approach that enables different stakeholders to take part and collaborate.’

Hopkinson adds: ‘Without an evidence base, making the economic or business case for circular economy is that much harder. Nobody has an overview of global, national or even local resource and material systems. What better data analytics and a robust evidence base should do is allow us to optimise not just resources and waste flows, but also much higher value creation from stocks and flows of resources in the economy.’

Defra’s Smart Waste Tracking project 

More than 200 million tonnes of waste are produced in the UK each year but there is currently no single or comprehensive way of tracking it.

Defra wants to join up the existing systems and replace paper-based record keeping by delivering a UK-wide waste-tracking service that makes it easy to track waste and resources throughout the economy.

To ensure waste is turned into a resource wherever possible, Defra says information is needed about what waste is being produced and where it ends up. High-quality data needs to be collected over time to understand changes in how products and materials are used. This data – whether raw or resulting from analysis or analytics – will support policy-making in central and local government and help businesses make better investment decisions.

It is looking at how the waste-tracking project can help support and provide some data required for implementation of major waste reforms, particularly the introduction of EPR.

The waste-tracking project is being delivered in phases:

• Phase 1 developed five proof of concepts. It ran from December 2018 to March 2019
• Phase 2 produced two prototypes. It ran from November 2019 to October 2020
• Phase 3 takes the learning from Phases 1 and 2 into a service that can be developed to Government Digital Service standards. It started in January 2021.

Defra is seeking views on its proposals via a consultation (open until 15 April 2022) here.

This feature first appeared in the Jan/Feb issue of Circular.