How can AI make supply chain more sustainable?

In today’s evolving world, highly informed consumers are more aware about their purchases than ever before. Among their expectations, they want organisations to meet a certain set of ethical standards as far as the

supply chain is concerned. Companies have no choice than to enact significant changes that ensure environment protection, decreased damage, and sustainable sourcing, manufacturing and product distribution.

There is no doubt that the way in which companies organize logistics today is not sustainable. Unfortunately, supply chains are not usually the most environmentally friendly and it is impossible for organisations to maintain a balancing act of the best possible speed, flexibility, cost and carbon footprint when it comes to the shipping and delivering of their goods.

According to a McKinsey report about sustainability, supply chain operations have a direct impact on the environment as they try to compete with a growing consumer base. There is an alarming rate of more than 90 percent of the damage caused to the environment by consumer-packaged goods (CPG) producers. In addition, 80 percent of greenhouse gas emissions comes from the supply chain.

The number of global consumers keeps on increasing and is expected to reach nearly 2 billion people by 2025, a 75-percent increase over 2010. In order to meet climate change agreements, CPG companies will need to cut greenhouse gas emissions by more than 90 percent by 2050. The bad news is that less than 20 percent of supply chain managers say they have the necessary visibility into sustainability practices in the supply chain to make this happen.

Implementing new technologies such as Big Data analytics and AI can help organisations make a positive change, ensuring their supply chains run as efficiently and sustainably as possible. The use of AI can have a drastic effect on supply chains. AI can help organisations achieve the fastest, cheapest and most sustainable routes for shipping, and combining these seamlessly.

So the question is – how can firms implement this? Based on a Supply Chain digital article, there are three very specific areas in which these technologies can applied to create a smart, efficient logistics chain. It all focuses around organisations shifting to a sharing economy when it comes to their supply chains. The new technologies such as AI in supply chain, data and innovative algorithms can significantly improve the sustainability and efficiency of in it by allowing organisations to work together.

Collaborative shipping is also known as sharing shipping. It refers to the shared use of shipping and transport methods between organisations. This can be done by developing an algorithm to help organisations better identify opportunities to share their shipping data and collaborate with other transporting firms.

With the help of GPS data, this algorithm logs the collection and drop-off points of shipping organisations. In this way, the system is constantly aware of the state of the environment at all times, concerning shipping, stocks, transport methods and the costs. By integrating the sharing economy aspect into this, organisations are able to share details of their AI supply chain companies with other firms.

Normally, not all packages are equally as critical to hand out. Many have intentionally long delivery times and some packages can actually change in urgency after they have originally been shipped. With the help of physical internet, organisations can adapt a synchromodality system, which involves combining a variety of transport methods in a sustainable way and taking into account the urgency of these deliveries, without comprising on the flexibility of the shipping.

With a real-time data system, the transportation method of a delivery can be adapted whilst a shipment is en route, meaning that throughout its transportation the algorithm can select the most cost-effective and environmentally friendly supply chain in real-time, continuously shifting to the most efficient and sustainable delivery method possible.

Basically, deep reinforcement learning is a specific element of machine learning and involves training an algorithm to make the best possible decisions. This is usually done through a trial and error process, where the robot is guided to the correct decision through positive feedback on its actions. How does it work? – By positively rewarding the robot, it will learn to narrow down its random actions, and only repeat those that have a good outcome for the organisation.

Companies using this deep reinforcement learning are able to train AI to make complex and positive supply chain decisions, which involve a number of variables. With such practice, AI can determine the exact number of products to ship, when to ship it these and which mode of transport is best to use.

Incorporating AI and new technologies to supply chains benefit the organisation in a number of ways, but from an environmental perspective, using these technologies can reduce pollution and the organisation’s carbon footprint, creating a much more sustainable supply chain and enabling a company to make a positive impact on many of the world’s alarming environmental issues.

Learn more about supply chain data analytics.