Disruptive logistics and strategic resilience 2

Welcome to Part 2 about logistics and strategic resilience. I'm Antonio Pesqueira, and I'm a partner at the Dynamic Capabilities Operational Institute and a professor at Universidade Europeia in Portugal, Lisbon. I have spent the last 15 years helping companies in healthcare and life sciences.

This second part is going to discuss a couple of very important items connected with global logistics. The first one is going to be around carbon-aware pricing, the other one regarding green partnerships, then hybrid decision frameworks, and then we are going to be focusing our attention in terms of ESG KPIs. ESG stands for Environmental, Social, and Governance, and KPI stands for Key Performance Indicators in logistics, and then we are going to review a case study in the energy industry.

Let's start with a very interesting concept that is carbon-aware pricing. That is mainly a strategy that embeds the cost of pollution directly into the logistics decisions. By putting a price on the carbon emissions, and automatically as well driving some of the decision efficiency around sustainability from an abstraction level into a tangible financial incentive perspective, where the main outcome is to make green choices, to the smartest financial choices. And the concept is very simple. We need to factor the cost of carbon emissions into shipping and transportation prices, and being guided by regulatory frameworks like European Emission Trading Systems or what we call ETS, when the pollution has a price tag and the companies are financially motivated to choose lower emissions in order to transport different products, but also to save money in order to allow shipping firms that are already using these models also to optimize routes that can significantly cut both their costs and their environmental impact as well. There are a couple of different metrics that we can put in terms of these key principles, but where we are really already testing some of the models is bringing these AI agents to carbon-efficient operations where responding to carbon pricing also requires to find new efficiencies, and here, AI is the perfect tool that can really help us in some of the processes, because it can help us to not only reduce the costs but also to optimize the logistics and the routes as well in order to, for example, analyze real-time data to find the most efficient full delivery routes and directly reducing the shipping costs and emissions. But also in terms of improving the warehouse efficiency, where, through AI, we can optimize the warehouse layouts, and we can manage inventory with greater precision, preventing over-ordering or reducing waste and lowering the energy to run the different processes at a maximum efficiency from also an emissions and cost perspective. We can also automatically go more upstream in terms of streamlining the procurement processes. The AI platforms can also help us identify the cost-saving opportunities and automatically improve our negotiations with the suppliers and help the companies find the partners that can be more cost-effective, but also more environmentally responsible as well. Here, automatically, it's a win-win for not only the suppliers but as well for the production companies, but also for the distributors, warehouse companies, the end consumer, because this combination of carbon pricing and the AI efficiencies and the AI models can really bring three major benefits. One is the optimization because it can help our logistics networks to become more optimized, not only in terms of the speed or the costs, but in terms of the sustainability of the processes. But also in terms of the efficiency on the resources, but also allowing us to make better decisions. The sustainability starts to become a core factor in all the operational choices that we make as well. By integrating carbon-aware pricing, the companies can make sustainable operations decisions and part of their core business strategy, where being powered by AI, this approach can really be efficient and good for the planet but also good for the profit models.