How to make digital technologies for the circular economy work for your business

How to make digital technologies for the circular economy work for your businessIlan Gleiser – Principal Machine Learning Specialist, Global Impact Computing, AWS

Digital technology for circular economy is an innovative approach that has the potential to revolutionize how businesses operate. It combines technology, data, and creativity to create a more efficient and sustainable way of doing business. By integrating digital technologies into their operations, businesses can benefit from improved resource management, increased efficiency, and reduced waste.

In this blog post, we will discuss the benefits of digital technology for the circular economy, as well as how businesses can implement these technologies to get the most out of them.

What is a circular economy?

A circular economy (CE) gradually decouples growth from resource consumption. Keeping products and materials in use, reducing waste, and regenerating natural systems are the principles of CE. The World Economic Forum’s (WEF) CE definition is “an industrial system that is restorative or regenerative by intention and design”. Resources and products are re-used, recycled, and then remanufactured by the use of a closed loop (circular) process. The advantages of such an approach are substantial. As evidence of this, the Ellen McArthur Foundation did a study that estimates that, by 2030, the circular economy in Europe can produce net benefits of €1.8 trillion while addressing various resource-related challenges, creating jobs, and sparking innovation. Over the next 20 years, the current linear economic model will present huge challenges and negative impacts that are cumulative and set to grow.

Thankfully, the advances of digital technologies have enabled more innovative methods that make the best use of a CE’s potential. They include IoT sensors that track assets and guide decisions; blockchains to increase traceability and validate provenance for secondary markets of recycled rare metals; artificial intelligence (AI) and machine learning (ML) models to enable predictive maintenance; high performance computing (HPC) capabilities to design new materials; additive manufacturing (AM) techniques to enable quick prototyping; and big data analytics to measure circularity performance metrics.

In short, digital technologies have the potential to revolutionize how we think about production and energy usage, bringing us one step closer to realizing business benefits but also living in harmony with our planet.

What are the benefits of implementing circular economy in business?

First, it prolongs the life of the product and its components. Circular economy principles want design innovation to keep products, components, and materials at their best use at any time. Technical materials, such as those from airplanes or cars, can empower recycling cycles through repairing, refurbishing, reusing, and, when no other option is available, recycling the part or object.

Second, to make a system of reuse and recycle successful, companies need to identify obstacles like fluctuating supply and demand and the condition of the returned goods. For a company to decide the next use of a product they have taken back, they would have to consider the various aspects of the product, as well as the current state of the market. This is where artificial intelligence (AI), driven by machine-learning (ML) and high-performance computing (HPC) come in. We can use AI/ML to predict customer needs based on trends, while HPC enables quick crunching of the large amounts of data needed in decisions related to supply-chain efficiency.

Finally, a common challenge to generate value from used material streams (from kitchen waste to used computers) is that these streams are mixed and heterogenous in materials, products and by-products, both biological and technical. The recovery of valuable materials requires homogeneous, pure flows. This often necessitates sorting, cleaning and grading steps within an industrial process before the resources can be put back into circulation. To reduce this sorting time and cost, computer vision algorithms can be combined with robotic automation solutions to enable a more efficient selection and classification of materials and help automate the sorting processes, therefore enabling rapid assessment of resources for reuse for end-of-life sorting intelligence. With digital technologies driving the circular economy forward, businesses will be able to efficiently turn what was once considered “waste” into an evergreen resource.

Which digital technologies can help in achieving a circular economy?

With that scenario in mind, let’s look at some real-life examples of how customers are using AWS services and technologies to accelerate the path towards a circular economy.

Artificial intelligence (AI), machine-learning (ML) algorithms, high-performance computing (HPC), internet of things (IOT), big data analytics (BDA), Blockchain (BC) and additive manufacturing (3D printing) can be combined with robotic automation to create an efficient, automated process that uses resources more efficiently. The combination of these emerging digital technologies enables organizations to identify opportunities, reduce waste and improve operations on multiple levels, allowing companies to track materials used through their value chain, and helping them move towards a circular economy.

By implementing AI/ML algorithms with IoT sensors, companies can identify opportunities for reuse or recycling materials, optimize resource use and help build a zero-waste supply chain. HPC provides the compute power needed to run ML models quickly, and 3D printing provides customized parts on-demand while reducing material waste. In short, these digital technologies allow companies to shift away from linear production systems to achieve the sustainability benefits associated with a circular economy.


High-performance computing is a critical technology for simulation and one of the main accelerators for the circular economy transition. It enables processing of massive amounts of data, quickly and accurately and helps organizations solve complex problems faster than ever before.

Companies can also use HPC to develop new products or services based on the analysis of the data they have collected. HPC makes it easier to identify opportunities for cost savings or potential risks. Ultimately, this allows businesses to become more efficient and competitive in a dynamic and ever-evolving market.

HPC systems are composed of large clusters of computers, specialized software, and high-speed networks. They are used in a variety of fields, like engineering, finance, medicine, and science, to solve complex problems that would otherwise be impossible to solve. Companies use HPC systems to develop new products and services – and to improve existing ones. As the world becomes increasingly complex, HPC is increasingly necessary. The circular economy is one of the most exciting ways that HPC can help make the world more sustainable.

At AWS, we partnered with Good Chemistry, an AWS cloud-native computational chemistry company based in Vancouver, to use the power of HPC to eliminate PFAS from the environment by simulating the exact compound that destroys the “forever plastic” molecule. By designing and building the largest ever Kubernetes cluster on the AWS cloud, the company not only accelerated the path towards a more sustainable future but also did it in a sustainable way.

The PFAS family comprises around 4,700 man-made compounds which are primarily used for waterproofing, creating non-stick surfaces, packaging food, or making firefighting foam and paint. It has been found in water systems and the human body, leading to various health problems.

The paths PFAS take to be broken down can be simulated on the Good Chemistry platform on AWS. This platform (“QMIST Cloud”) uses a combination of ML and HPC to run computational chemistry simulations on AWS. This method is increasingly popular among businesses for a number of benefits that extend to various industries, including drug design and food innovation, to new battery material discovery and carbon capture. In a previous post, we described the benefits of computational chemistry for a circular economy.

In addition, Accenture, the World Economic Forum, and AWS, working together via The Circulars Accelerator, have been pushing digital technologies for a circular economy forward. Our aim is that start-up companies with circularity enabling businesses should have access to supercomputers on the cloud to develop sustainable solutions like these. By doing so, we all hope to contribute towards a cleaner future with fewer environmental impacts.

By supporting leading startups and fostering innovative partnerships through The Circulars Accelerator, we hope to help companies move from insights and commitments to actions, outcomes, and results that can be measured and commercially successful.

Wes Spindler – Accenture, Managing Director, Sustainability,
Co-Author The circular economy Handbook

Big data analytics

Data is essential to answering questions and accelerating action on the transition to a circular economy. Evidence for the impact of circular strategies is steadily increasing, but much work remains to be done in order to build a comprehensive understanding of the effects of this transition. We need data to establish a reasonable baseline, assess interventions, and measure outcomes. But data capture can be challenging as data for employment, emissions, and material consumption can be spotty and siloed. To bridge this gap, surveys and projects that collect specific data related to the circular economy can help to better understand how it affects different systems and help inform decision making. Digital solutions and data arising from artificial intelligence can also unlock circular economy opportunities.

As an example, AI can process large amounts of data to identify patterns, fill in data gaps and uncover trends which we can use for measuring impact. Additionally, we can apply predictive analytics and agent-based simulations to forecast future economic changes and consumer behavior. Going further still, data analysis tools can provide insights into customer sentiment regarding certain initiatives, like those relating to waste minimization or energy efficiency.

Big data provides powerful insights into the economic benefits associated with certain initiatives. Companies use big data analytics to measure the impact of their sustainability initiatives by tracking both direct costs and savings resulting from various measures. This provides them with a detailed view into the cost effectiveness of their efforts and give valuable insights into areas for potential improvement.

Finally, big data – when harmonized into a circular economy data lake and properly cleaned and prepared – enables organizations to track metrics such as the most common key performance indicators (KPIs) to measure circularity.

Some examples we use to measure circularity are:

  • Resource efficiency: This metric measure how efficiently resources are used throughout the product life cycle. This includes raw materials, water, energy, etc.
  • Recyclability: This metric looks at how easy it is to recycle a product or reuse it at the end of its lifecycle.
  • Waste reduction: This metric looks at the amount of waste generated throughout the product life cycle. Companies can use this metric to evaluate their waste management efforts.
  • Renewable energy use: This metric looks at the percentage of energy sourced from renewable sources used by a company. This helps companies reduce their carbon footprint and become more sustainable.
  • Product design: This evaluates the design of a product to assess how well designed it is for longevity and reuse. This can include looking at the parts used in the product and how easily we can replace or repair them.

Measuring these KPIs can help companies understand where they are in their journey towards becoming more circular and identify areas where they need to improve. With big data, companies can gain insights into their performance and optimize their operations to achieve better results.

Fig 1: The infographic above exemplifies some common use cases of digital technologies for circular economy with a Circular Data Lake at the Center enabling the calculation of metrics and KPIs

Fig 1: The infographic above exemplifies some common use cases of digital technologies for circular economy with a Circular Data Lake at the Center enabling the calculation of metrics and KPIs


AI and ML algorithms can monitor and optimize energy use in real-time, identify inefficient processes ,and recommend changes to reduce waste. Machine learning is being implemented across several parts of the economy in order to improve circularity. Data analysis, especially for innovation, forecasting, and optimization, is the most significant application of artificial intelligence in the circular economy according to UNEP (United Nations Environmental Programme).

In the energy sector, an example is the Distributed Energy Resource Management Systems (DERMs), which employs reinforcement learning algorithms to optimize energy usage across horizontal micro-grids of prosumers, and across shared renewable energy platforms. EDF Energy, UK’s largest producer of low-carbon electricity, aims to transform UK’s energy supply by decarbonizing, digitizing, and democratizing it. The company, which uses AWS to scale Powershift, an energy flexibility platform, enables customers to manage and monetize their assets in an intelligent, innovative way.

In retail, more specifically in the consumer-packaged goods (CPG) industry, companies can use generative AI to design packaging with a lower carbon footprint. Customers will be delighted with minimal packaging, fewer damaged goods, faster deliveries and by contributing to a more sustainable world …“saving over a million tons of packaging material in the process” – Bill McGrath, Amazon, describing the benefits of Amazon’s Ship in its Own Container (SIOC) and Frustration-Free programs.

In the auto sector, AWS customer Reezocar, one of the largest buyers and sellers of used vehicles in France, uses AWS Batch and NVIDIA GPUs on Amazon Elastic Compute Cloud (Amazon EC2) instances to render synthetic data of simulated dents in cars to train a machine learning model to automatically identify dents in images of real cars. The output of the ML model informs the price the company pays for used cars, before they refurbish and resell them in the market. By doing so, the company extends the useful life of the vehicles by 5 years, reducing the amount of waste that goes to landfills or gets incinerated.


IOT or Internet of Things, is the extension of the digital world into the physical world. Essentially, IoT is a network of physical objects linked by software, sensors, and the Internet for the purpose of exchanging data. Sensors can collect data about the behavior of processes, conditions, or materials, like temperature and moisture, production and machine conditions, or customer usage performance. We can guide circular economy strategies using IoT data that describes and monitors the type, quantity, and timing of current material flows in real time.

The biggest gains from IoT are likely to be in the B2B sector, with machine-to-machine communications from IOT devices being responsible for generating more data than human to human communications. We can use machine learning to analyze trends and detect patterns that lead to better decision making. IOT, combined with AI, allows for better monitoring and management of resources. It is now considered a crucial element of a circular system, giving organizations and smart cities better visibility of supply chains, CO2 emission or traffic patterns, enabling the creation and processing of data, coming from humans or machine to machine communications. IoT can accelerate the transition to a circular economy by helping to track the movement of materials, goods, and services in real-time.

Fig 2: This architecture demonstrates how information flows and is analyzed as goods move through the supply chain from supplier to manufacturer to consumer. It is an event-driven architecture that comprises physical and business events managed in a secure, role-based access-controlled multi-tenant AWS event processing framework. The AWS event processing framework leverages key AWS services for data exchange with the Edge, Data Storage (Event Lake), Analytics, and AI/ML in the cloud. Events are in the form of messages that are exchanged between the AWS cloud and authorized entities and sub-entities in the supply chain (Supplier, Transporter, Manufacturer (receiving, plant floor, shipping), Fulfillment). The AWS cloud serves as the broker that the entities use to publish and subscribe to events.

Fig 2: This architecture demonstrates how information flows and is analyzed as goods move through the supply chain from supplier to manufacturer to consumer. It is an event-driven architecture that comprises physical and business events managed in a secure, role-based access-controlled multi-tenant AWS event processing framework. The AWS event processing framework leverages key AWS services for data exchange with the Edge, Data Storage (Event Lake), Analytics, and AI/ML in the cloud. Events are in the form of messages that are exchanged between the AWS cloud and authorized entities and sub-entities in the supply chain (Supplier, Transporter, Manufacturer (receiving, plant floor, shipping), Fulfillment). The AWS cloud serves as the broker that the entities use to publish and subscribe to events.


One of the latest technological developments that can help to create a more sustainable world is blockchain. We can apply the digital ledger in several industries.

Blockchain can enhance circular economy practices by enabling transparent and traceable supply chains. This technology creates an immutable and secure record of every transaction or process within a supply chain. By creating transparency, blockchain can reduce waste, fraud, and inefficiencies while increasing trust and accountability.

Blockchain can also enable a closed-loop system by tracking the movement of goods, materials, and resources, from raw material sourcing to final disposal. This ensures that waste materials are recycled and reused rather than being sent to landfills or incinerators. It can also ensure that we can trace the origin of recycled materials, promoting a more sustainable and responsible value chain.

Furthermore, blockchain technology can also incentivize consumers to participate in circular economy by rewarding them for making environmentally conscious decisions. For instance, consumers could earn tokens for returning used products to companies that they can use to purchase new products, thereby reducing waste. Companies can also sell used parts of machines, like cars, trucks, airplanes or hard drives on a secondary market that runs on an Amazon Managed Blockchain. Some potential examples of this type of marketplace include the resale of used clothing, furniture, and electronics. As consumers become more environmentally conscious, the demand for sustainable options is likely to increase. With blockchain technology, it is possible to create a secure and trustworthy marketplace for these used products.

Overall, the use of blockchain technology for creating secondary markets for used products is a promising development for sustainability and social impact. By facilitating the reuse and resale of goods, blockchain can help reduce waste and promote a circular economy.

Additive manufacturing

Additive manufacturing is playing an important role in the circular economy, reducing the use of resources by eliminating wasteful manufacturing practices. The Ellen McArthur Foundation has identified additive manufacturing as a key technology in their Circular Design Toolkit, designed to help companies reduce their environmental impact and increase sustainability.

By using 3D printing, companies can manufacture complex parts with little waste, resulting in cost savings. 3D printing has the potential to significantly reduce resource use and minimize environmental impacts. In addition, with additive manufacturing, components can be tailored to the end user’s specific needs, making mass customization possible. This means we can make products on-demand without stockpiling inventory, and this further helps to minimize waste. It lets companies quickly and cost-effectively create products without the need for traditional production processes like injection molding.

By using additive manufacturing, businesses can gain significant savings in resources while meeting customer demands.


Digital technologies are revolutionizing the way businesses operate and achieve their goals. Leveraging these technologies, businesses can now create an effective and sustainable circular economy that reduces waste, maximizes resource utilization, and minimizes environmental impacts.

With these tools, companies can create closed-loop systems designed to reuse and recycle resources, resulting in a more sustainable business model. To make the most of these digital technologies, businesses should focus on creating flexible systems that can be tailored to meet the changing needs of their customers.

Using AWS technologies such as artificial intelligence, machine-learning, high-performance computing, IOT and Blockchain, the AWS Global Impact Computing Team is actively involved in driving this transformation. If you are interested in learning more how we can support your business, please reach out to us at With the right digital transformation strategy and AWS support, companies can successfully implement a circular economy business model that brings long-term economic, social, and environmental benefits.