Accenture & AWS: Helping Firms With Data-Driven Circularity

Accenture and Amazon Web Services (AWS) are combining their industry muscle and expertise to help numerous companies to utilise data to boost circularity.

The work was detailed in a blog post written by Ilan Gleiser, Principal Specialist, Emerging Technologies at AWS, Joshua Curtis, Circular Intelligence Global Lead and Patrick Ford, Circular Intelligence North America Lead, Accenture Sustainability Services.

They write: “It’s clear that resource use and circularity are critical to the creation of a sustainable, healthy economy.

“But how do we realise this value? How does a business identify where and how circular strategies can create financial and environmental impact?”

Josh Whitney, MD, Sustainable Value Chain and ESG MAP Lead for North America, Accenture, said he is “super proud” of the guidance, adding that “every company has a circular economy data problem”.

A US$4.5tn reward

The blog says it is “well documented that the circular economy is an opportunity for positive impact on business and society”.

In fact, Accenture’s analysis finds that the global economy could benefit to the tune of US$4.5tn if it departs from the current ‘take-make-waste’ economic system.

It pinpoints “actionable data on circular economy performance and impact” and the solutions that lie in emerging technologies as key drivers of transformation.

The move to circularity is not a might-have, it is a must-have. The newly-launched European Sustainability Reporting Standards (ESRS) include a requirement for companies to report on circular economy metrics including:

• The percentage of material used for products and packaging that are renewable, recycled or reused
• The volume of waste by stream that is recovered by destination
• The financial effects of material risks and opportunities arising from resource use.

Achieving data-driven circularity

The blog says that one of the key challenges is how to identify and measure patterns in circular economy data to enable sustainable change.

Solutions include:

• The Internet of Things (IoT), which enables tracking of product movement and health through use phases
• Machine learning algorithms, which can help companies identify patterns in circular economy data
• Blockchain technology, which can be used to create a transparent and secure ledger of circular-related transactions.

The blog says: “As we continue to tackle the circular measurement challenge, it is essential to approach it with a data-driven mindset.

“Digital technologies have the potential to revolutionise how we manage and analyse circular economy data, allowing us to create a more sustainable and efficient economy for the future.”

The challenges to transforming circular data

The authors list three big challenges facing companies as they endeavour to transform their approach.

1. Selecting the right metrics

The European Commission’s regulations ESRS E5 on resource use and the circular economy provide “headline metrics for business disclosure”.

At the same time, the Circular Target-Setting Guidance from the Circular Economy Indicators Coalition (CEIC) provides an overview of leading measurement methodologies and approaches for business implementation.

But the blog adds that these do not account for the “specific value chains or functional priorities of businesses in different sectors.

“For example, the metrics to measure circular economy performance (and therefore the data required) vary significantly for a fashion retailer compared to an oil and gas major.

“Ultimately, selecting the right metrics must be led by each business, drawing on the wealth of supporting materials, best practices and market standards.”

2. Identifying, collecting and transforming the data

While the foundational data itself is “simple enough”, the challenge is collecting that data across product lines, business units and geographies and then transforming it to be usable.

The blog says: “For example, when calculating your percentage of materials that are recycled, renewable or re-used, materials data must be segmented in ways not currently built into enterprise data capture.

“Without technology, this requires line-by-line segmentation based on data that is available e.g. through supplier declarations.

“The bottom line is that collecting data to measure circular performance is an arduous process, requiring time and costs, and is hindered by data gaps.”

The blog adds that such work “depends upon” digital technologies.

3. Transforming the data into actionable insights

The blog says resource use data must be connected with other internal and external data sets like sales data and emissions intensity factors.

It says: “Companies must understand how different material choices impact carbon emissions, as well as procurement costs and business profitability.

“The true story of corporate circularity is of trade-offs and investment requirements to capture long-term value.

“Without a comprehensive approach to circular economy measurement and data transformation, understanding those trade-offs properly and making impact-driven decisions is impossible.”

What do Accenture and AWS bring to the table?

Accenture and AWS are collaborating to bring the best of their combined data, technology and sustainability expertise to transform circular economy data management.

AWS says it “offers the broadest set of capabilities in artificial intelligence, machine learning, Internet of Things, big data analytics and high-performance computing in the market”.

Accenture, meanwhile, is the world’s leading integrator of AWS solutions and technologies – completing over 1,100 projects with AWS over 15 years of partnership.

Accenture says it has developed core assets as part of a suite of circular intelligence solutions, powered by AWS.

These include industry-specific KPI frameworks, a foundational data model and a proof-of-concept dashboard to act as a platform for client co-development and customisation.

A core priority of the collaboration is to enable the automation of circular data ingestion, transformation and analysis to enable ongoing performance measurement and generation of actionable insights for companies across the value chain.

Accenture and AWS are using their co-developed Velocity platform, which adds new cloud innovations at speed to develop the data architecture which pulls resource use and circular economy-related datasets into a central, circular “data lake”.

Call to action

The blog says each company’s journey on circular economy measurement will look different, depending on industry, strategic priorities and technical maturity.

It says there needs to be “a level of customisation and co-development using existing products and repeatable solutions where available”.

The authors urge businesses to define their circular economy blueprint with key metrics across each area, then assess their current functional and technical maturity to measure and manage these metrics.

The blog says: “Identifying where the raw data lives, how it is collected and stored and who is responsible for it is critical to map the journey towards automation.”

It adds that the next step is to “design, build and test”, with cross-functional teams working together to integrate solutions as part of a circular data lake."

Finally, it says deployment must be thought of as a “multi-generational journey.

“Companies should focus on their key requirements for a Minimum Viable Product (MVP) solution that supports their core business priorities.

“The MVP must also include solutions for data pipeline automation and a data governance strategy.”

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