Like a Formula 1 race car, supply chain trends move at breakneck speed. Every week, it seems like there are new regulations, geopolitical crises, climate events, or sanctions zooming by that keep you on the edge of your seat. If you blink, you’ll miss it and be left in the dust. Which is why it pays to keep up with supply chain and global trade events and understand how they can impact your business.
Earlier this year, we hosted a webinar about industry trends with two of our partners at Dun & Bradstreet. During the discussion, our hosts investigated five supply chain trends they felt were having the most impact on companies. In Part 1 of our blog series on trends, we covered how escalating tensions, uncontrollable constraints, supplier risk, and market diversification can impact your business. In this post, we will discuss the last two of our five noted trends: the demands of sustainability and the role of artificial intelligence (AI) in supply chains. We’ll discuss their impact on sourcing, trade, and logistics, and explore the tools and resources that are available for companies to respond to them.
Sustainable supply chain practices and traceability
In the past, sustainability and social responsibility initiatives were only discussed when a company was caught doing something wrong. At first, watchdog groups and non-governmental organizations (NGOs) were the only ones demanding accountability, but now, government organizations and international investors have moved sustainable supply chain practices to center stage. With every new ESG regulation targeted at supply chains, the more important it becomes for companies to have visibility into and control over, where materials are sourced from, where a specific part was assembled, and understand where and how much CO2 emissions are emitted along the supply chain. That’s where traceability comes in.
Traceability is the ability to see deep into your value chain, from raw goods to finished products, and the need for traceability ties back to the connectedness of the entire modern supply chain. As companies diversify their supplier base, the challenge has become how to trace suppliers all the way down to tier 5, where risks often lurk. Many professionals are confident in their ability to trace down to tier 2, but very few can be distinct and trace further down into their sub-tiers. The recent discovery of counterfeit parts across major airlines reminded supply chain professionals that even large, international companies sometimes lack in-depth visibility into the complex network of suppliers and partners.
Sustainable supply chain practices aren’t just about parts or the environment — they also include labor. Going back to our conversation in Part 1 about Ukraine being the breadbasket of the world, traceability involves more than just sourcing a specific component or ingredient of a product. You must also look at who is providing the labor, the fertilizer, and the agricultural equipment to harvest the wheat. And are the humans behind these tasks and functions behaving in a way that would appease an investor or consumer who is demanding more adherence to environmental, social, and governance (ESG) standards?
The footprint of modern products has grown so much that supply chain traceability includes every input into the product, which leads to the concept of convergence: when a critical supplier is hidden within one of the multiple layers of the supply chain because oversight of that layer is inconvenient. For a company with a multi-enterprise, multi-tier supply chain, it can be nearly impossible for human-only resources to keep up with all the regulations, sanctions, and restricted party lists imposed on its goods. However, there are technology platforms that can automate the due diligence process and provide deep, multi-tier insight into your suppliers and your suppliers’ suppliers. With the right amount of insight and a little help from automation, companies can improve their ability to identify, respond to, or avoid compliance risks.
Artificial intelligence solutions for supply chains
The media narrative around artificial intelligence (AI) is that it will eliminate jobs, which is not necessarily true. AI’s purpose in the supply chain is to eliminate some of the workload from human workers who simply cannot process the sheer amount of information with the speed and scope that AI can. For instance, a major airline that manages cargo and freight may have a tremendous need for enhanced AI and machine learning to optimize their screening capabilities. However, a manual component is still required to complete the job. AI can put as many red flags in the cargo shipment as it sees fit, but then a human needs to step in and evaluate them.
Do artificial intelligence solutions replace all our labor positions? No. Do we realize more positive outcomes by partnering computers and humans in a better loop? Absolutely. According to the World Economic Forum, by 2025, AI may create about 97 million new roles. Like any other transformational change, AI will replace some roles but create new ones we haven’t seen before.
While much of the talk around AI is about jobs, it’s important that any discussion about AI also includes a mention about data. The quality of decision-making based on AI is directly correlated to the quality of the data input: without the right data, AI is almost worthless. In other words – garbage in, garbage out. However, manually cleansing tons of supply chain data poses an enormous challenge for an information technology (IT) team that manages multiple internal systems. The complexity of this task increases greatly when combined with external processes that rely on data from hundreds or thousands of partners or supplier systems.
AI, combined with machine learning (ML), can automate data cleansing and normalization. For example, AI and ML can search for company names in multiple formats, use multi-attribute matching to identify company name-location combinations, enrich inconsistent data with missing information (such as filling in zip codes based on city and state locations), and then harmonize it all. In fact, the use of supervised AI can significantly reduce manual effort by up to 98%, freeing up team members to focus their energy on strategic thinking instead. But this is just one of four types of AI in use in supply chains today. In addition to supervised AI (trained pattern recognition), there’s also unsupervised (discovers hidden patterns on its own), reinforcement (trial and error to define the best outcome), and generative (chat-like interactions). You can read more about AI in supply chains, here.
The most important role artificial intelligence solutions will play in supply chains is in scenario planning. With the right AI fed by the right data, supply chain leaders can gain insights and critical information that will help them build more resilient supply chains and respond more effectively to scenarios such as hurricanes, labor strikes, new regulations, or sudden geopolitical developments. While AI cannot solve a labor crisis, it can empower companies and their partners to make the best decisions about how to navigate these disruptive events.
Smarter decision-making is the key to surviving supply chain volatility
In an era where there’s an abundance of risks and demands surrounding global supply chains, agility is of the utmost importance. If the driver of our Formula 1 race car spots wreckage on the track ahead, they take evasive action. However, it’s important to note that the success of that action is just as dependent on the vehicle as it is on the human behind the wheel. The driver has a pit crew that likely maintains the car and ensures that each working part is in the best shape possible to execute this kind of split-second response.
Supply chains are no different. Like a finely tuned race car, a modernized supply chain with the right technology is capable of taking evasive action at speed while reducing the overall impact on performance. At e2open, we’re creating a more connected supply chain to help our customers react with agility and control. Whether you need to ensure the traceability of each component, automate compliance and due diligence for global trade, or reduce the risks that hide deep within your sub-tier ecosystems, the connected supply chain from e2open provides greater control and visibility over the entire supply chain. Our collaborative platform enables companies to use real-time data with artificial intelligence and machine learning to drive smarter decisions across sourcing, trade, and logistics operations.
It’s tough to predict trends, and you may not notice them until they are already affecting your business. That’s why keeping up with the latest developments can be a crucial part of managing a global supply chain. If you’d like to stay apprised of what’s happening in the world of supply chain, the e2open blog is a great way to check in on a wide variety of current and topical events.
If you’d like to learn more about how e2open can help your company manage the uncertainty and complexity that comes with emerging trends, connect with us today.
