Blogs

Leveraging AI and human intelligence for supply chain sustainability

There’s no doubt that Artificial Intelligence is a powerful tool, especially when applied to data-rich and intensive analytical processes such as supply chain management. AI does more than just collate a multitude of data. It helps customers identify hidden relationships and anomalies within their data, unveiling insights that allow a deeper understanding of their supply ecosystem. Imagine having a tool that not only processes data from various sources to present a comprehensive summary of risks and suggested mitigation actions but also does this in a fraction of the time it would take a human. AI achieves this while constantly processing real-time data and considering historical data. It’s not merely a gimmick—it’s the solution supply chain managers have been eagerly anticipating. 

AI is great at identifying patterns and helping supply chain managers spot potential gaps. In the ever-present quest to create supply chains that are not only efficient but sustainable, the ability to continuously improve supply chain management is priceless. Of course, supply chain managers will want to monitor emerging and inherent risks, ranging from climate change to geopolitical events. However, using AI to work towards a greener supply chain will not only help maximize efficiencies, but will also minimize the risk of non-compliance to Environmental, Societal, and Governance (ESG)-focused legislations around the world. Plus, it may even help your reputation with consumers as well!   

Sustainability in supply chains  

There’s been a big push for sustainability in supply chains, spurred by public interest and by legislative means. But regulation and reputation alone aren’t the only reasons why you should be reforming your supply chain to be as sustainable as possible. 

sustainable product metricFigure 1 – Sustainable products are more important following the COVID-19 pandemic than prior 

Sustainability refers to a broad range of issues within supply chains, from environmental to societal concerns, such as fair pay, to fair and transparent governance. Each of these elements represents a risk within every global supply chain. Unexpected or unusual climate events, for example, can delay shipments of materials or products. Or, if your company is unknowingly found to have modern slavery practices within your value network, you could be facing severe fines and blocks to trading. Finally, poor governance can lead to a loss in trust, which is key in conducting business.  

Of course, prioritizing sustainability within your supply chain isn’t all about avoiding the negative consequences. In fact, prioritizing sustainability can help you maximize efficiency throughout your supply chain. For example, you may decide to fully map your value network, down to your n-th tier supplier, to ensure that you’re aware of any instances of modern slavery, perhaps to ensure compliance to a global regulation. Having this full understanding of your supply chain will also keep you aware of any hiccups within your supply chain that could cause downstream effects. 

Explore real-world use cases of AI in supply chain risk management.

DOWNLOAD REPORT

You can leverage sustainability concerns for your own competitive advantage. But make sure you’re doing so in a way that is sustainable for your company – and your supply chain management team, in particular – to maintain.  

Combining AI and human intelligence  

Introducing AI into your supply chain management practices relies on two premises: one, that AI is a powerful and advanced tool that should be used to ease the previously manual burden of data collection and analysis. And, two, that AI, within a supply chain context, must be used in connection with human oversight and decision-making. AI-powered data collection and analysis is the tool that will allow your supply chain management team to focus on making the right decisions around sustainability, monitoring and adjusting as necessary.  

Alerts could range from meteorological indicators signifying a major weather event to news articles from a different region revealing labor malpractices or factory shutdowns. This is the kind of data collection that a human simply cannot keep up with, even if they did know every language in the world and were experts in just about everything. However, human oversight is still key in this process, ensuring that any false or misunderstood information is noted as such, so the AI can avoid the same mistakes in the future.  

For example, an AI-powered solution, such as Everstream Reveal, receives data from a variety of streams, including publicly-available and proprietary sources. Reveal then collates the data, highlighting any emerging risks that the team should be aware of. The supply chain management team is then responsible for reviewing the data, confirming its accuracy, and making educated decisions accordingly.  

ai patternsFigure 2: Everstream Analytics engine of AI and ML to generate actionable intelligence

Next Steps

If you’re looking to up your sustainability game within your supply chain – and you should be – AI is the tool that’s going to help you get there. And, if you’re not already using AI within your supply chain management generally, it’s time to jump on the bandwagon.  

Start by finding the right AI-powered tool that will help you understand your end-to-end supply chain, alert you to potential or emerging risks, and provide a baseline of up-to-date information for your team of supply chain experts to use for effective decision-making. Once implemented, your supply chain management team should work to train the AI to look out for the risks specific to your business and products, on top of any supply chain risks that the AI will find. Remember, AI is a tool that can be flexible to your company’s needs, and can reflect your company’s risk scoring priorities and methodology, and be modified and trained differently if needed.  

Then, use your AI tool to identify sustainability risks and leverage them to your advantage. Making supply chain decisions based on ESG criteria can help you weed out unreliable or risky suppliers, find methods of transportation that are unaffected by major weather events, and find other new efficiencies throughout your supply chain. Armed with the right information, your supply chain management team can lead your company to all kinds of operational advantages.

Don’t worry – the robots aren’t putting supply chain managers out of business. They’re just making their jobs less manual, leaving the human experts to do what they do best – making informed and effective decisions, and adjusting the AI where necessary. Using AI in supply chain management may seem like a big step into an uncertain future, but in today’s business context, it’ll give your company the best chance at creating a sustainable and efficient supply chain.  

Explore real-world use cases of AI in supply chain risk management.

DOWNLOAD REPORT

Share this post