Transcription
Supply Chain management and artificial intelligence are two of the hottest trends in the transformation space right now. What happens when those two areas converge? That's what we're going to talk about here today. My name is Eric Kimberling. I'm the CEO of Third Stage Consulting. We're an independent consulting firm that helps clients throughout the world reach the third stage of digital transformation success. And much of the work we do with clients is surrounding their supply chain management initiatives, as well as artificial intelligence initiatives. And those are two areas I love to cover on this YouTube channel. I love to talk about it with clients. And what's really fun to think about is what does the future of Supply Chain management look like with the combination of artificial intelligence? And it's still an emerging area. People are still trying to figure out how to use artificial intelligence within their supply chains. So what I want to do today is talk about the 10 things, the 10 use cases, that I think are going to be the most prevalent and the most immediate for those looking to leverage AI within Supply Chain management.
Before we dive too far into today's content, I want to share a little bit of information about Third Stage Consulting and who we are. Third Stage Consulting Group is an independent, technology-agnostic provider of consulting services to help clients through their digital transformations. We help with digital strategy and software selection, as well as implementation planning. And during implementation, we provide services related to program management, organizational change, business process improvement, as well as enterprise architecture. These are just some of the services we provide. We have offices in North America, as well as Europe and Asia Pacific. So if you'd like to learn more, I encourage you to check out our Resource Center, which includes a number of resources that will help you through your digital transformation. And you can access that for free using the QR code here or the links below. You can also reach out to me directly if you'd like to discuss your digital transformation and brainstorm ideas on how to improve where you're headed on your journey.
Now let's jump back into today's content. The first big opportunity that AI has to really help Supply Chain management, help supply chain managers be more effective, is in demand planning. When we look at forecasting and planning demand, this is a big area of opportunity for organizations. First, it helps understand why forecasting and planning is so important. If you think about Supply Chain management, everything we do within Supply Chain management is focused on satisfying customer demand. So we have to anticipate when we think customers are going to need certain things, whether it's raw materials or sub-assemblies or finished goods or some combination of all the above. We have to figure out not only when do those products need to be done on the shop floor or procured in our warehouse, but we also have to figure out how we're going to get it to the customer at the time we've promised. There's a lot that goes into forecasting and planning. You have your internal data, so you have your historic data that you can be looking at. And AI can help you analyze historically how has customer demand evolved and fluctuated, what's the seasonality throughout the year. But you can also look at external factors as well. And this is where it gets really interesting in how AI might be able to help, because a lot of organizations and supply chain managers use tribal knowledge and just their gut instinct on what's happening in the marketplace to try and adjust their forecast and plan for the customer demand. So, for example, if we know that the economy is going to grow at a slower pace next quarter, for example, that may have some sort of material impact on our forecast and plan. And rather than using tribal knowledge, we can be using AI to analyze the historic data we have, as well as external data points such as macroeconomic indicators. We could also be looking at weather patterns or potential supply chain disruptions, other things that might affect how customers demand might be impacted for our finished goods or our end product. So look for AI to really revolutionize how supply chain managers look at customer demand and the forecast and plans that go along with that.
Inventory is one of the biggest costs that a lot of supply chain intensive organizations have. You think about all that inventory you're sitting on in your warehouse and your multiple distribution centers throughout the world, and that's a lot of money. That's money that's on your balance sheet. Those are assets that are sitting there that could be generating cash. If you have too much inventory, then your costs are too high and you're not generating cash flow fast enough. So if we can optimize inventory, that's ideal. We can find that balance between making sure we don't have too much inventory and we're sitting on wasted inventory or potentially obsolete inventory, but we also want to make sure we have enough inventory to where we can satisfy customer demand when they need it. We also want to know that we can plan for stockouts and that sort of thing. So if you look at AI and what AI can do here, AI now can take these mass amounts of data, looking at inventory levels, looking at potentially obsolete or slow-moving inventory, and it can help us understand better what some of those trends and patterns are. And it can help us anticipate where we might need to invest more time and money in our inventory and perhaps liquidate other areas or spend less time and money in other inventory areas. So AI can truly change and transform the way we optimize inventory, and this has been a challenge for decades now, despite the evolutions in technology. And hopefully, AI will be a way that we can start to really manage and optimize inventory levels.
Most supply chains we work with involve multiple systems, multiple data sources, both tribal and centralized data sources, and that makes it very difficult to have real visibility into what's going on throughout the supply chain. With AI, even if you have disparate systems, you're going to be able to look at multiple data sources now and understand and have better visibility across the enterprise. Not only do you have access to this data because of AI, but now you can have a conversation with AI to get to that information easier. You can ask AI questions around things that you want to know about your supply chain. You can find out things like which distribution center has the highest inventory level, or which SKUs are most at risk of experiencing a stock out based on current inventory levels and current demand forecasts. There's a lot of different things you're going to have visibility into that you may not have today. And it's really a great opportunity for us to rethink how we use technology to get better visibility into supply chains. Better data, better visibility, better understanding, better information – that really is the holy grail of effective Supply Chain management. And that's where AI is going to really help revolutionize Supply Chain management as we know it today.
With a better understanding and the better visibility to supply chains that AI affords us, now we can start to take things a little bit further and really look at how we're pricing our products. If there's a way that we could be pricing things to be more competitive, to potentially undercut competitors, or perhaps demand is so high for a certain product or certain SKU that maybe we need to actually raise our prices. AI can be a great way to anticipate some of these potential shifts in the way our pricing should be. And the way most pricing works right now is organizations will look at their cost structure and add some sort of margin on top of that, or they'll go with what they think the market will bear based on human knowledge, which is always imperfect. But now with AI, we can look at things we hadn't considered before. We can anticipate potential spikes in demand which might suggest that we should be raising our price, or we can anticipate potentially hyper-competitive situations where it might make sense to lower our price. And AI could be a great way to help us think through and understand where some of these pricing optimization opportunities are. And that's something we often times don't think about when we think about Supply Chain management. Often times we're focused on cost, inventory optimization, understanding demand, but we're not always focused on what the right price is that we should be charging for any given product. So AI has the opportunity to truly change the way we think about pricing and help us understand and respond to pricing opportunities in a way that we never have been able to in the past.
Suppliers are a key part of any supply chain, and finding the right supplier and managing that supplier is very important, obviously. And there's Supply Chain management systems out there that allow us to track suppliers and their performance and scorecards and things of that nature, but it doesn't always give us the information we need to anticipate where challenges might lie. If we have quality issues with a certain supplier, we want to be alerted as soon as possible. If we have sole dependency on a single supplier for a critical raw material, that would be very disruptive if that supplier wasn't able to satisfy demand. We need to recognize what those situations are. And when there's geopolitical risk that's happening in the world today here in the 2020s, we need to understand what suppliers are at risk as a result of that geopolitical risk, especially in a global supply chain. So AI has a way for us, and it provides us more complete access to information and understanding of what the supplier situation is, which ones we should be selecting, which is going to be the best for any given raw material, and which ones might be at risk. And help us identify where we might need to diversify our use of that particular supplier. So look to AI to really change the way we think about supplier selection and sourcing.
When we look at the procurement aspect of Supply Chain management, that's one of the most important things because there's not only so much money being spent to procure raw materials or finished goods, whatever the case may be for your supply chain, but there's also the opportunity, either through human error or more nefarious behavior, for there to be fraud in the procurement process. If you think about it, for some organizations, I could create a vendor named Eric Kimberling and I could go ahead and pay Eric Kimberling a million dollars for some raw material that we never received. Now, obviously, you want to set up the right security profiles and things of that nature to make sure that you don't enable the same person to create a vendor and pay the same vendor without any sort of oversight or checks and balances. But AI has a way for us to proactively flag potential fraudulent situations. It has a way of understanding what's normal and what's abnormal in different data patterns in terms of how we procure raw materials and other indirect materials as well. So AI can be a very powerful internal audit mechanism to help us identify potential issues when it comes to procurement, in particular fraud. So look to AI to really change the way we think about fraud and risk management as it relates to the procurement process.
For supply chains that are very capital intensive, that involve expensive machinery, expensive trucks and fleets, things of that nature, predictive maintenance is a big deal because you want to make sure you're maintaining those assets and you're getting the most out of those assets for as long as you can. And the key here is you don't want to spend too much money on maintenance, but you don't want to spend so little that things start to break and it creates disruptions in your supply chain. So AI has a way for us to more intelligently anticipate where the needs are, where the potential risks are within predictive maintenance. If you think about, for example, a piece of machinery that is particularly stressed or is experiencing a big spike in usage, a human may not recognize that or may not recognize the increased need for maintenance and repair on that machine. But AI might flag that and say, "Hey, this is an abnormal use of this piece of equipment, so there should be more inspection happening or more maintenance and repair happening." So we look to maintenance and repair, that's a big opportunity for us to really optimize how we're managing our assets to make sure that we're getting the most out of the assets without stressing the asset so much that it breaks and creates a disruption to our supply chain.
Warehouses and distribution centers are really the lifeblood of a lot of supply chains because they're not only bringing in raw materials, but they're also stocking finished goods and they're shipping those finished goods to customers from those distribution centers in many cases. And so there's a lot of opportunity to be more efficient. There's a lot of opportunity to better manage inventory. And there's a lot of opportunity to more quickly turn inventory in those warehouses. And when you combine AI with the use of robotics and Internet of Things and other things that are already happening in warehouses now, that convergence of those types of technologies creates an opportunity for us to create smart warehouses. We can now really optimize the location of inventory, we can optimize the flow of inventory, the flow of goods, we can optimize which inventory levels we need to have, which we talked about earlier in this video. And it's a great way for us to really create the smart warehouse using artificial intelligence combined with robotics, Internet of Things, and other trends in the industry. So look to AI to really fast-track this whole concept of smart warehouses, and it's another opportunity for us to become even more efficient and effective in our warehouse management function.
We talked earlier in this video about supplier management and procurement and how we can better manage those suppliers. And within that, there's also the aspect of contracts. When we think about contracts we have with suppliers, there's different terms and conditions, there's different criteria that need to be met. And if we can use AI to flag potential non-compliance or potential issues with contracts, that's something that is a big pain point for a lot of supply chains today. You think of an organization that has hundreds or maybe even thousands of suppliers with thousands of different contracts and terms and conditions. It can be overwhelming for any supply chain management person or a procurement professional to manage all those different moving parts and details. So AI can be a great way to leverage and understand where there might be contractual issues or potential opportunities to renegotiate with customers and suppliers. So look to procurement and contract management in particular to be totally transformed by AI here in the near future as well.
Organizations that manage their own fleet of trucks and other transportation logistics find that route optimization is very important. Fuel costs are high, the cost of maintaining the assets are high. So anything you can do to optimize the routes and make sure that they're being as efficient as possible in how they get the product out to the market, in that last mile in particular, is going to be extremely important. So if we can optimize the routes of our transportation management, that's going to save us in fuel costs, it's going to save us in maintenance and repair, it's going to save us in capital investment. And there's a lot of upside potential to optimizing routes. Now, to be fair, there's been a lot of technology for decades now that help optimize transportation routes, so this isn't anything new. But AI really allows us to take it to another level and it adds a whole another layer of intelligence and efficiency optimization to that. So look to AI to also improve the way we handle transportation management and route optimization in particular here in the coming years.
So I hope this has given you some guidance and some ideas on how AI might transform your supply chain in the future. There's a lot more here we haven't talked about, but these are 10 that I think are particularly compelling. In some cases, we've already seen organizations start to deploy some of these use cases. In other cases, they're in the early stages of thinking through these things. And in other cases, these are just new capabilities that are just coming out in the marketplace. And this top 10 list is bound to change over time, so it'll be fun to revisit this here in the coming years. But in the meantime, hopefully this is giving you some things to think about. Now, if you'd like to learn more about Supply Chain management, I encourage you to read our guide to effective Supply Chain management. You can learn a lot more about trends and different technology options in the supply chain space. You can download that for free by scanning the QR code right here, or you can go to the links below. So hope you found this information useful and hope you have a great day.