Synergy of AI and Businesses to Achieve Shared Sustainability Goals Through Circular Economy Practices

The circular economy model asks firms to review their strategy, reassess their waste stream, and reintroduce previously discarded materials back into the production process, unlike the traditional linear factory model or method. In addition to the circular economy, the value here would also involve incorporating practices that increase usage through solutions that extend product end-of-life and closed-loop, resource methods. Through technology and digitalization, we can transition into circular economy practices, including and concerning product end-of-lifecycle management that includes the entire supply chain.

The circular economy is not simply about minimizing waste - it is about rethinking how we create value! Artificial Intelligence can help enable scalable circular business models, including:

 

1. Product-as-a-Service (PaaS)

The Product-as-a-Service (PaaS) model is a business model where a company provides access to a product through a rental or subscription model. This model, while it does have history as a concept, treats the outcome or function from a product as the service, not ownership, thus giving customers flexibility, cost reduction, and operational efficiency.

 

Some examples to consider:

- Rolls-Royce "Power by the Hour"

Description: Rolls-Royce provides aircraft engines as a service; thus, airlines pay based on the operational hours the engines provide. This business model - from core management, logistical planning, service processes to economic modelling is based on #AI, was better managed on cloud computing - was redesigned for low-level waste and value leaves potential.

 

- Philips Lighting "Light as a Service"

Description: Philips offers lighting solutions, where lighting is billed by lumens consumed rather than purchased as physical equipment. Philips installs, maintains, and upgrades the lighting systems. Circular practices will reward companies that focus on energy efficiency.

 

- E.g. Caterpillar Equipment Rental

Description: Caterpillar provides construction equipment for rental, allowing organizations to rent heavy equipment for a specific project, without having to purchase the equipment.  This provided ongoing service includes maintenance, repairs, and customer service, makes utilization of an asset more cost effective compared to owning an asset when required only occasionally.

 

2. Sharing Platforms

AI is being developed to optimize the use of resources do to networking between users. Algorithms can match people to available resources (e.g. machinery, vehicles, spaces) and balance supply and demand in real time. Uber Peerby etc.

The new models are data-operated and AI provides the intelligence required for optimized asset utilization, keeping circular models profitable and scalable (even for SMEs).

AI and IoT are assisting companies better manage their supply chains in six different ways:

• Better demand forecasting - AI can analyse past sales, market trends, and other outside factors (like weather) to get better estimates of how much product you will need.
• Keeping track of materials - IoT (internet of things) devices can track products through the supply chain and can be very useful to avoid overstock,
• Less overproducing - By matching your production with demand, a company can help minimize waste.

 

SMEs are an important piece of achieving the goals of net zero and economic growth with larger corporation playing an important role in helping their growth through green transition, skills development, and sustainability training. Dubey et al. (2020) notes ‘strategic, operational, and tactical decisions in our organizations impact the ongoing competitiveness’, but RBV (Resource Based View) theory suggests that ‘managing’ resources to build capabilities in order to sustain a competitive advantage over time is the prerequisite for sustainability. However, SMEs also must have the ability to adopt AI through circular business models. These capabilities can involve data collection, analysis, and interpretation, AI-model development and deployment, and continuous measuring and improvement. SMEs can innovate continuously to improve current resources and capabilities to outpace competitors and distinguish itself from other established competition.

 

AI-based platforms provide a reliable way for large companies to safely exchange data with SMEs, thereby building trust and collaboration. Blockchain-enabled AI systems can verify the reliability of transferred data, enhancing transparency in the supply chain. AI-based analytical tools and the Internet of Things can make supply chains more efficient, minimizing waste and resource use. These tools can also assist with smart product design, lifecycle management, dynamic pricing, and eco-friendly products. They can analyse consumer patterns and insights, enabling the co-creation of eco-friendly products. AI tools can also map a supply chain network to identify possible partners.

 

Real-World Example

IKEA is a strong example of a large company working with suppliers, many of which are SMEs, to drive sustainability progress in a circular economy context. IKEA is leveraging AI and machine learning to monitor how products are utilised, maintained, and ultimately thrown away. The information that gets shared with suppliers enables collaborative product design with easy disassembly, recyclability, and reusability at the core of their circular economy commitments. Moreover, IKEA is able to use AI-powered traceability tools to track materials from their origins to sale. SMEs, as suppliers, enter data into digital platforms powered by AI that relate to sourcing, energy, emissions, etc. This data is useful to IKEA to measure environmental impacts continuously and conjointly with SMEs, steering improvements that benefit them both. Furthermore, IKEA uses AI to monitor and predict raw material usage rates based on individual customer use, therefore reducing overproduction driven waste. As an example, aligning their production with actual demand allows an SME supplier to lower their operational cost and environmental burden. IKEA leverages AI powered logistics to reclaim, reprocess and remanufacture products by managing returns, initiating repairs, and managing logistics of returned products. SMEs focused on logistics, repairs, and recycling benefit from AI based learnings that enable them to scale their circular offerings.

                                                                                  

 

Written by,

Dr. Nandini Malini Barua

Assistant Professor, PSOC