Smart Supply Chain

Perspectives

Five in 5: A smarter supply chain—AI and collaboration

Managing supply chain complexity in the 21st century

Obstacles abound in the modern supply chain world. From rapidly evolving digital technologies such as artificial intelligence (AI) to historic disruptions such as the COVID-19 pandemic, the complexity within supply chain management grows. In this Five in 5, we’ll explore how technology and collaboration can help overcome supply chain challenges.

1. What are some of the key obstacles to managing the ever-changing complexity of supply chains today?

Benjamin Dollar: While managing costs will always be critical for supply chain, supply chain executives are now focusing more on resilience, agility, and managing complexity. Recent disruptions in supply chain have taught us that the traditional way of managing supply chains won’t work going forward if we want to be able to respond quickly to disruptive events. The things that have historically driven up costs—increased shipping costs, shortages, logistics, contingency planning—are now even more acute because the overall supply chain environment is more complicated. And now, just like end-user consumers, business-to-business (B2B) consumers are increasingly demanding in terms of what they require. If you don't have a clear understanding of their requirements and a clear way to engage them, it can add to both cost and complexity. This is where leveraging digital technologies such as artificial intelligence and machine learning in supply chain management can help companies get ahead of cost increases and potentially help mitigate them.

Aaron Parrott: Almost all supply chains to date have been developed based on cost models: How do I get the lowest price possible to manage the overall cost of building my product? And what we’ve learned as the result of events like the pandemic, global disruptions, and inflation is that supply chains are highly sensitive to disruptions because they weren’t developed and managed with resiliency in mind. Very few supply chains are built based on: How do I manage my risk within my supply chain? Many companies look at it from the perspective of piece-price cost as opposed to total cost, whether it's total cost of ownership or total cost plus risk exposure and the impact to their supply chain.

By changing our frame of reference, we can look at what “cost” really represents, and how to better manage what that real cost is to the client across the supply chain. And then we can understand what specific issues are impacting those costs and how to address them. If you're chasing the next lowest-cost provider for your supply chain, the next disruption is going to just interrupt the supply chain all over again—or you’ll extend your supply chain and your lead times, limiting your ability to respond to marketplace changes because it takes a while to have those changes flow through the supply chain. More and more, because of the global footprint, multi-tier supply chain, and complexity, we’re seeing a lack of vertical integration— where suppliers are very specialized in the type of work they do. What used to be one or two suppliers in the past now takes multiple tiers. We need to look at some of the strategies around changing vertical integration, so that a company’s footprint on a multi-tier supply chain is condensed, the movement of the product less, and the total cost exposure potentially reduced.

We need to think differently about supply chains and how they support manufacturing—strategically focusing on costs to better understand the true cost position and where we can focus to address it with better visibility, risk reduction, and minimization of the overall footprint, to be more localized suppliers. This will help us understand what the cost is being driven by, so we know where to focus our time and effort.

2. How can organizations address these challenges?

Benjamin Dollar: The tools available have become increasingly powerful. These tools allow for digital technology and analytics to take a more proactive and preventative approach in supply chain—technologies such as AI, machine learning, and big data, are able to provide deeper insights than have ever been historically available. The challenge is knowing what questions to ask and how to use data to generate insights—most companies have mountains of data, but they don’t know what to do with that data to prevent and mitigate supply chain disruptions. This could be data from suppliers and supply networks, or external data on customers, geopolitical events, commodity trends, or just about anything. Being able to understand how to use the data you have to ask and answer the right questions is critical.

The ability to use big data, customer data, and supplier data to understand the true multi-tier network and where there may be vulnerabilities in your supply networks will help you understand where risks may be—so you can proactively address them versus waiting for a crisis to occur and then responding to it. Similarly, I think using data to understand customer demands, predict what customers will want, and even to help steer customers to the products best suited for them can enable a more proactive approach to supply chain development and management. Additionally, increasing capabilities, technology, and data is enabling us to improve the way we work with suppliers: Supplier management, collaboration, and development can really help to address supply chain challenges.

Aaron Parrott: When you think about the critical partners in your supply chain, it’s key to move the supplier/manufacturer relationship to a strategic partnership that helps better manage complexity within your supply chain—driving toward a much more efficient way of delivering products. Many manufacturers feel their customer base to be very demanding and wanting of configurations and options. Now, consider simplifying either the configurations or options you offer within the marketplace. Every option and every new part births additional complexity into your supply chain, which not only creates additional costs from a standpoint of parts but also from producing that product and having the right product availability for your customers. It all adds complexity. There’s an opportunity to manage that complexity by rationalizing your options and configurations to meet market demands without trying to be all things to all people across the entire marketplace.

Also, it’s about how you measure people and what it is you're targeting them to do. If you’re still going to manage your organization on piece-price cost or landed delivery cost, you're not going to change the behavior on reducing complexity in your supply chain to drive better outcomes and management of complexity, risk, and cost. The metrics, measurements, and data available and how you support them to execute those things will be critical for long-term success—what gets measured gets done.

3. What role could AI play in managing this supply chain complexity?

Benjamin Dollar: AI can help proactively identify problems, so you can prevent them instead of react to them. With so much data available, the question is: How can we use all this data to prevent disruption? AI and machine learning, by their nature, can take enormous amounts of information, identify patterns, and enable rapid decision-making—much more rapid than natural intelligence would allow—which enables us to take action before a disruptive event in the supply chain occurs. Whether it’s planning, forecasting, or logistics, AI will help us be more effective across the board. AI can enable identification of patterns and events that may be counterintuitive—that one would not be able to detect by manually sifting through enormous amounts of data. AI enables us to proactively see where shortages may occur—such as a combination of geopolitical events and shifting commodity prices—providing us with forward-looking and preventative capabilities in our supply chain management.

Aaron Parrott: One of the real advancements from AI and machine learning is added predictability and seeing patterns and connection points to various external events—being able to predict and connect trends, along with the potential impacts. If X happens, then Y is going to happen as a result—leading to a disruption in your supply chain. I think that's where AI and machine learning really advance our management capabilities in our supply chains. AI and machine learning look for patterns and have the capability to predict things that humans cannot detect.

4. Why is supplier collaboration an important aspect of managing complexity in the supply chain?

Benjamin Dollar: Some companies have a very adversarial relationship with their suppliers, while other companies consider their suppliers to be partners. Increasingly, managing supplier relationships is probably the single most important factor to limit supply chain risk and cost. The better the relationship with the supplier, the more you'll be able to handle forecasting, lead time, costs, and inventory, among other things. Some organizations go so far as to work with their suppliers to help them build their own internal capabilities. So you might have people actually onsite working with the supplier to help them improve the way they deliver product. The more transparency and shared agenda there are, the more connection there is between the suppliers and the manufacturers they're supplying to—this is critical to not just the product cost, but also to the resilience, availability, and agility of your supply chain.

Aaron Parrott: Partner relationships and collaborations are ultimately what help address issues, as opposed to taking a transactional approach. Strategic partnerships help manage risk, boost collaboration to deliver product, and offer support if a short lead time, increase in quantity, or change in schedule is needed—a strategic partner will work with you. The other key factor is typically that the majority of total costs for most manufacturers come from the supply chain. If you want to manage costs, you need to think about working with your suppliers to help identify cost reduction opportunities for building their product (your parts and materials), which benefits both the supplier and you. If the relationship is adversarial, it’s likely there's no vested interest in a supplier to come to you with a shared model on how to save costs or with advice and direction. As strategic partners, companies and their suppliers work together to address the bigger costs and risk issues—collectively identifying new ways to improve overall product and material.

5. How can organizations begin their journey? What should they do to get started?

Benjamin Dollar: Acknowledge the need for change. The long-standing status quo is no longer going to work. The events of the past several years have been a wake-up call to supply chains, and to the industry in general—that we need to do things differently. The key though, is understanding where you are and where you want to go/need to be. And that's a deliberate activity. There has to be a clear vision of what needs to change/where you want to be.

And then the next big hurdle, and I think one of the most important things to address, is data. Most large companies have plenty of data—so many different sources of data in some cases that the data contradicts itself, or people don’t trust it. Data can be organized into a single source of truth—a place where data can be analyzed quickly and turned into insights to drive proactive decisions. Then, the next hurdle is changing the way work is done. If you've set the vision and have a good set of data and systems in place, the next consideration is to examine what needs to change from an organizational perspective. Is there a need to change what gets measured? Is there a need to change the nature of interactions with suppliers? There's a whole host of organizational changes that can be made, but it’s all going to come from that initial vision for change and having your data and technology in order. At that point, you can be very deliberate about rapidly changing the way work gets done.

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