Cognizant: How Can Technology Support a Circular Economy?
The traditional "take-make-dispose" economic model is increasingly unsustainable.
Enter the circular economy—a transformative approach that reimagines how we produce, consume and manage resources throughout their lifecycle.
Unlike the linear economy that has dominated industrial development for centuries, the circular economy envisions a regenerative system where waste and pollution are designed out, products and materials are kept in use, and natural systems are regenerated.
Manoj Mehta, EVP and President, Cognizant Europe, Middle East and Africa explores technology’s role in a circular economy – and how it can be incentivised.
What is the circular economy, and why is it a positive way of doing business?
The circular economy is an economic model designed to eliminate waste and keep materials, products and resources in use for as long as possible. It moves away from the traditional ‘take-make-dispose’ approach, instead promoting a system where resources are reused, refurbished and recycled to create a continuous value loop.
This model provides a profitable alternative to exploitative business practices that no longer have a place in the modern world. By bending the linear trajectory of business into a regenerative cycle, the circular economy offers global benefits—reducing environmental impact, creating economic opportunities and ensuring long-term profitability.
Why haven’t most businesses achieved a circular economy, and how can this transition be incentivised?
Today, most circular endeavours remain controlled experiments rather than full-scale transformations. And it shows: according to some estimates, the world dumps over two billion tons of waste every year. One measure finds humanity is using resources gleaned from the earth 1.7 times faster than the planet can produce them.
Businesses have spent centuries implementing the linear economy’s practices of resource exploitation. Moving away from these deeply ingrained practices requires a fundamental mindset shift. The key incentive lies in recognising the commercial potential of circular models. Once businesses see the market opportunities that circular practices unlock, they will find the economic justification to make meaningful changes.
However, this will require devising entirely new business models for circular value recovery, which differ significantly from linear economic models. Both short- and long-term value propositions need to be carefully laid out. By defining the market opportunity and mapping the pathways to achieve it, businesses can begin their circular transformation with confidence.
How can businesses deliver circularity at scale?
Establishing a scalable, circular business model requires transforming many operating processes. To deliver circularity at scale, businesses must adopt four systems of change into their operations.
Firstly, they must design for sustainability. The principles of Design for Manufacturability/Reliability (DFM/DFR) are traditionally driven by product economics. Design for Sustainability (DFS) complements many of these established practices but also contradicts some. Serviceability, extensibility and recyclability become important principles to retain and recapture value throughout a product’s lifecycle and beyond. AI-driven models can help simulate and optimise the lifecycle value of a product, making it more valuable to maintain or upgrade, including through software-driven lifecycle extensions.
Next, they must ensure supply chain traceability. Data which enables traceability in the supply chain is critical to re-engineer carbon-intensive, one-way supply chains can create more economic opportunity across communities, including the ones in which the products are used. Rather than exploiting the environment or labour for raw materials, the idea is to extract parts, components and materials and reintroduce them into the supply chain or use them in new applications.
Businesses must also establish strategies for the reintroduction of recovered material. The reduction of single-use and intermediate materials in the manufacturing process, such as packaging, is also important. Data models, such as Digital Product Passports and Lifecycle analysis (LCA) are critical in enabling the design of the extended supply chain, contract manufacturing arrangements and logistics processes.
Finally, circularity requires a rethink of the product itself, the market in which it’s sold, the ecosystem that supports that market, and the value delivered to customers. Manufacturers of large assets, such as turbines and earthmoving equipment, have had to think beyond being a manufacturer to being an owner of a fleet of assets which deliver revenue ‘by the hour’. It is also critical to consider an integrative view of lifecycle costs to maximise value beyond manufacturing. Remote asset management, digital field services and enhanced aftermarket service models become significant levers for reducing Scope III emissions and improving sustainability.
How can AI and other technologies accelerate circular business models?
AI, machine learning and IoT are key enablers of circular business models, helping companies overcome barriers and accelerate their transition. By enhancing collaboration, visibility and operational efficiency, these technologies support businesses in redesigning systems, optimising resource use and unlocking new value streams.
Firstly, businesses must engineer a system of change – this will allow companies to capitalise on near-term value opportunities to prove the concept, then work toward a more fundamentally transformative opportunity. AI-driven system design also helps deliver a flexible enterprise technology framework to support this evolution
Organisations also must integrate downstream visibility. Whether through takeback programs, subscription services or reverse logistics processes, businesses need to track what happens to their products and the materials they contain throughout their entire lifecycle. While much of this information exists within enterprise systems of record, Gen-AI and other technologies can consolidate this data to identify opportunities which lead to circularity.
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