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Article

Bridging Sustainable Supply Chains with AI

Bridging Sustainable Supply Chains with AI
Sustainable Development
Published on:

When it comes to the renewable energy transition, all actors in the supply chain have different stakes, incentives and barriers. HEC Paris Professor Sam Aflaki aims to help organizations contribute to this renewable energy transition in the fields of supply chain management, sustainability and energy efficiency. In this interview, he discusses his ongoing research, exploring the dynamics of stakeholders' incentives, technological advancements, and the challenges shaping sustainable practices in today's world.

iStock_mutarusan_management research_cover

Photo credits: Mutarusan on iStock

Professor Aflaki, how are you working to make supply chains more sustainable?

I use a multidisciplinary research approach that combines data analytics, operations management, and behavioral science to identify the key leverage points within the supply chain where interventions can have the most significant impact. To do this, I study the incentives and barriers that businesses, policymakers, consumers, and suppliers face when investing in sustainable measures. I also look at how regulatory frameworks can balance sustainability with innovation and growth. Additionally, I examine how consumer behavior can be influenced toward more sustainable choices through information, transparency, and choice architecture redesign.

 

By leveraging data and analytics, companies can better manage their supply chains, identifying where to improve energy efficiency, invest in renewable energies, and reduce waste.

 

Our goal is to explore how technology can illuminate the footprint of supply chain activities. By leveraging data and analytics, companies can better monitor and manage their supply chains, identifying areas where improvements can be made in terms of energy efficiency, investment in renewable energies, and waste reduction.

Energy seems to be a central theme in your research…

Absolutely! My research critically examines energy efficiency and the transition to renewables as fundamental components of a sustainable energy shift. Despite the clear economic and environmental benefits of energy-efficient solutions, their adoption rates lag behind their potential. I'm particularly focused on bridging the energy efficiency gap, exploring how data analytics and strategic contracting can encourage the adoption of energy-efficient technologies, moving us closer to net-zero targets. This research, entitled “Performance-Based Contracts for Energy Efficiency Projects,” is funded by donors of the HEC Foundation’s Research Committee, who I would like to thank.

Your research on renewable energy was just published in the Harvard Business Review, and received a lot of attention. What challenges does this sector face, and how does your research overcome them?

In addition to energy efficiency, a sustainable energy transition requires investment in renewable sources of energy. In this research, we focus on the renewable energy sector, particularly offshore wind energy. We investigate the delicate balance between maximizing energy production and mitigating environmental impacts. While it is essential to move towards renewable energy sources, there is a risk of overlooking the long-term environmental consequences, such as waste management and the lifecycle footprint of renewable technologies. Based on the lessons we've learned from past technological rushes, like the e-waste crisis, our research advocates for a more nuanced approach. Our research advocates for a lifecycle approach to renewable technology development, ensuring we don't overlook long-term environmental costs in the rush toward renewables.

In supply chain management, what specific challenges are you focusing on?

Supply chain management is undergoing significant transformation due to the tightening of due diligence regulations worldwide. These rules demand greater accountability and transparency from companies through all supply chain levels, not just with direct suppliers. We examine how the relative bargaining power between suppliers and buyers influences the design of these legislations.

Navigating this shift is complex, as it involves understanding the dense network of global supply chain relationships, which span diverse legal and compliance landscapes.

Yet, this complexity also opens doors for innovation in supply chain management. Digital technologies, particularly data analytics and blockchain, are pivotal in ushering in a new era of transparency and accountability. Blockchain, for example, enables the creation of secure, immutable records, offering unprecedented traceability and verification capabilities across the supply chain.

This is where data analytics and AI can be useful to navigate these supply chain challenges, right?

Indeed! AI and machine learning are game changers, improving supply chain forecasting, risk evaluation, and compliance. These technologies offer insights that can significantly enhance supply chain sustainability, including improved forecasting of disruptions, better evaluation of supplier risks, and enhanced social and environmental compliance. For instance, AI tools can process large datasets to forecast disruptions and highlight ethical concerns with suppliers, which is crucial for enhancing the resilience and sustainability of the supply chain. This would allow companies to have less exposure toward non-compliance penalties enforced by due diligence legislation.

Can you provide a detailed case study where these technologies have been successfully applied?

The use cases are extremely diverse and effective. A cool example of this application is the initiative by CMA CGM, for which I am honored to hold the HEC Chair on Sustainability and Supply Chain Analytics. I am currently in the process of writing a case about their use of predictive analytics to protect marine life. The company utilizes advanced data analysis to predict the migration paths of whales and adjust their shipping routes accordingly. This initiative demonstrates the potential of predictive analytics in reducing environmental impact.

With the rapid advancement of AI, there is growing concern about its ethical and environmental implications. How do you consider these challenges?

As we harness the power of AI, we must be vigilant about the potential unintended consequences, including the environmental impact of powering AI systems and the ethical considerations around data privacy and algorithmic bias. 

My research on investment in renewables advocates for a comprehensive approach that considers their full lifecycle and implications rather than just the immediate benefits. This same approach can be applied to the development and use of AI. It is crucial to consider ethical, environmental, and social impacts from the outset to ensure that our pursuit of technological advancement does not compromise our commitment to sustainability and ethical integrity.

As part of the Hi! PARIS Center, co-founded by HEC, you're at the forefront of research in AI and sustainability. What opportunities does this affiliation provide?

The Hi! PARIS Center is a vibrant hub where academia, industry, and policy intersect, providing a unique platform for interdisciplinary research on the intersection of AI and sustainability. Our collaborative initiatives, such as the Hi!ckathon - a hackathon and several roundtables - we held last December on the impacts and uses of AI in supply chains, demonstrate our commitment to using AI for positive environmental and social outcomes. The center fosters the exchange of ideas and encourages innovations that are technologically advanced yet grounded in sustainability principles. Ultimately, this contributes to a more resilient and efficient global supply chain.

 

References: Working papers by Sam Aflaki (HEC Paris) and Ali Shanti (Toulouse Business School): “Transparency and Power Dynamics: A Game Theoretic Analysis of the Supply Chain Due Diligence Regulations”, with Sara Rezaee Vessal (ESSEC and HEC alumni); “Performance-Based Contracts for Energy Efficiency Projects”, with Roman Kapuscinski (University of Michigan).

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