 Expert Connect series leading the digital supply chain. My name is Ira Sager and I am Vice President of Global Learning Initiatives for the Center for Global Enterprise. This is the second in a series of six Expert Connects we will present on the digital supply chain. Next week, June 19th at this time, our Expert Connect will look at technology enablers, blockchain and its application in the supply chain. Before we get to this week's Expert Connects, we will have a few housekeeping notes. This session and all the sessions that follow in this series will be recorded and posted on the CGE YouTube channel. The end of this presentation, we will have a slide with the upcoming schedule for additional Expert Connects, as well as a link to the digital supply chain Institute website for more information. We will leave approximately 20 minutes at the end of this session for audience questions. If you have a question for our presenter, you will see at the bottom of your screen a feature that says Q&A. Please submit your questions using the Q&A feature. We'll try to get all the questions time-permitting. Today's Expert Connect is about demand management. Our presenter, George Bailey, is the Managing Director of the Digital Supply Chain Institute. George is going to discuss why the digital supply chain is a prime driver of demand. He'll explore why it is important to generate real-time data to improve demand forecasting to make better decisions and create new opportunities that stimulate demand and growth. We'll look at supply chain and digital supply chain strategies rather that help some companies better sense, match, and ultimately drive new demand. All right, I'll turn it over to George now. Here you go. Hey, thank you, Ira, and welcome, everybody. Glad that you could join us for this discussion today. And we're going to talk about something very interesting to me, and I hope to all of you, and that is, how can you use your supply chain to actually manage demand, to actually grow revenue? So it's not about cost reduction, it's about growing revenue, and that's a new theme for supply chains and one that we think is part of the future of supply chains. And I'll explain why as we go through this and you'll get a chance to really understand what we're talking about and how you can help your company make the same kind of changes. So as Ira said, please give me as many questions and let's have a good discussion about this as we go forward. And I want to make a point about who helped us put this work together. We're a not-for-profit. We were founded by Sam Pomozano, who is the ex-CEO and chairman of IBM, and he's told us that what he wants us to do is create insights and ideas that help companies compete. In other words, practical measures that help us complete. And the issue in front of you now is a set of logos. And these are the companies that we've been working with. It's a community of companies that we'd like to invite you to join. Many of you already have joined. And this is about 1.8 trillion US dollars in revenue, over 6 million employees. So it's a powerful group of companies that have contributed their ideas that you're about to hear. Now, as I go forward, I'm going to talk about this idea of the front-side flip. And some of you have seen this before, and I'll just take another second to explain what we mean by this, because it's an analogy that gives you a good way to understand what we're talking about. My son happens to be a very competitive snowboarder. He's the second best amateur big mountain snowboarder in the US. And he does a trick called the front-side flip. And essentially, he rockets down the slope. He launches into the air. He flips up in space, turns over, and lands on the front side of his board and rockets down the hill. And it's a trick that helps win competitions, and it's a great way to talk about supply chain, because in the past, supply chains have always focused on the back end of the business, minimizing costs, on keeping the supplier base, the whole tier one, tier two, tier three, and played an extremely important role in all companies. But now that role is even more important, because now the role is gonna take a front-side flip, and the front side is the customer. So the way you run your supply chain will not only be about keeping costs low and delivery high, it's also gonna be about creating revenue and revenue opportunities, a new new approach that actually many companies are taking already. So here are the objectives we have for today's session, and there's four of them. Number one, I wanna just take a quick moment to review how the digital supply chain exists in the future and the demand that it manages, both now and in the future. Second, I wanna describe some ways that the digital supply chain will influence demand, and already there's examples around the world of this happening. Third, I wanna be able to provide some guidance on what it takes to be successful here, what are the prerequisites, and finally, and most importantly, I wanna get you ready to make change. As I mentioned, our not-for-profit is all about helping companies make change, and if you don't do anything with the information I give you today, it's not a success. I'm hoping that what you learn and what you find out about will cause you to make some changes in your operation as you go forward. Okay, so here's the first point about revenue that I wanna really emphasize. It's all about the demand stack. So we talk about it as a stack because there are several kinds of demand that you can manage, and here are the four types that we outline. I'll just start at the bottom-left corner, demand matching. Demand matching is something that your supply chain already does, and in fact, supply chains have always done, which is match what you've got to what the market wants. And typically that happens through some stimulation in the market, the sales force tells you, hey, we need 10,000 of these, you get your suppliers up to speed, they provide goods to your manufacturing, manufacturing creates something, and you then go ahead and sell it. Demand matching is still an important part of the demand stack, but now there's some new types of things that you can do. If you go up to the top left, you can see demand stimulation. This is a really powerful approach that says, we can do things with our supply chain that will stimulate demand, that will grow revenue. I'll give you some examples of that as we go through. Demand management, the one next to the right, is all about how can we manage our demand to make sure that it occurs in times that are optimal for our customer and also optimal for us. So for example, I was the chief transformation officer for Sony in Tokyo for four years. And when I did that role, we had a really big issue. And the issue was that almost the entire electronics revenue came in in one quarter, the quarter around Christmas and the New Year season. That is really difficult from a supply chain perspective because you have to build all year in order to ship at that time. It's difficult from a revenue management perspective because it means all your revenue comes in one quarter. And if you don't make that quarter, the year is gone. So we did things to try and create new demand in the summer season, for example. So demand management means can we shape the demand that happened when we need it and in a way that will help the customer. And the next thing that's really important is the bottom right, demand sensing. Demand sensing says, how can we get a really keen understanding of the demand signals in the environment? And I'll show you some examples of what companies are doing now that are really quite powerful. Now all of this is wrapped up in a thing called the platform business model. It means that you want your suppliers and customers to see you as a platform that they can do business upon. And also in some cases, you'll be doing business in other people's platforms, but there's a platform model here. And really importantly is the outer ring called security and compliance. It's absolutely essential that as you create this digital supply chain, as you work on the demand side of the business, you really have high levels of security and compliance across all types of information with your demand stack. And you've seen what's happened with cybersecurity and cyber risk lately and the increasing risk we all have of cyber attacks. Well, I'm telling you right now that as we move into digital supply chain era, there'll be attacks on supply chains and things will go missing. Shipments will not arrive, assets will disappear, intellectual property will be stolen. There'll be a lot of things that happen unless we've really built our security system quite strongly in our digital supply chain. So it's about the demand stack. It's about managing revenue. And on average, if you talk to those companies that we've been working with, there's about 30 that are next group we call the global experts group. They believe that on average revenue growth will be 10% from a digital supply chain. Digital native companies will get much more. And if you think about Amazon, they're probably the most visible example of how you use a supply chain to create advantage. People go to Amazon because the supply chain is so extraordinarily good. You can have one site. You'll see everything that you need to buy. You'll know what competitor products are. You'll see ratings and ideas about each thing that you're looking at. Before you check out, you'll be told people who buy this also tend to look for these 10 things. And all this grows demand. And in fact, what happens with an Amazon user, and I'm one of them, is you become loyal to that supply chain. You like the process. You know you're gonna get it delivered in two days. You know the prices are reasonable. And you're willing to have customer loyalty. So Amazon Prime is a great program that many people have. And it's because their supply chain is just so strong. Another example that everybody knows is Uber. And the Uber Play is about putting a supply chain in your hands. It's about revenue growth. It's not about cost reduction. So if you look at that Uber app and probably all of you use Uber all the time, who takes taxis anymore, you can see right on that screen where those cars are, where the assets are. So you know where the assets are. You can understand exactly how long it'll take for them to get to you. You'll know the price that it will happen. And you also know that it'll be billed directly and you won't have to mess with paying the driver as you would in a taxi cab. A really, really powerful idea of putting a supply chain right in the palm of your hand. And oh by the way, it's interesting to watch traditional business cope with this. The traditional taxi companies have done approximately nothing. Even though Uber has demonstrated that this supply chain information is so powerful and so useful, traditional companies have not been able to respond to it. And I mentioned that only because many of you are not at Amazon. You're not at Uber. You're from traditional companies. But you know what? It's really important for you to understand how to do this work, because there will be an Uber or an Amazon in your future if you don't figure this out. And some of your competitors, I'm sure are working on this as well. So think about this as we go through it. I'll give you some examples from traditional companies as well, but Uber is certainly a really good example of a supply chain that wins revenue. Now, when I talk about supply chain, the digital supply chain, I'm talking about an end-to-end focus. That means it starts with pre-production, pre-product, all the way to post-delivery. And it's also true that this process is not only about product. It could be about service. It could be about financial services. It could be about almost any industry in the world today. So when you saw that set of logos, you'll see some of them are financial services, like Idle Vice is the leading investment management firm in India. It's also about services companies. And then you'll have an example about Aracent in a few minutes here. It's a company that does engineering and design work. And it's also about product companies like Colgate Pomalov. So it's every kind of company across the world in almost all industries. And it's really from pre-product where supply chain information is going into making products better because the supply chain touches customers. It knows what they want and it knows what customers' customers want. So it goes into pre-production and it goes to post-delivery. When I was at Sony, we had a really interesting set of power cords. In fact, every single product at Sony had a different power cord. We had something like 179 different power cords. So we had a program that supply chain people said, you know what, from now on, we need to minimize power cords because it doesn't help anybody get a Sony experience if you have to have so many different power cords. And so you'll notice now that there are many, many fewer power cords if you're buying Sony products. And that's a supply chain move. Also, engineering and design to manufacturing and customer service is all part of supply chain. So of course, manufacturing is, but so is sales and customer service and delivery afterwards. And finally, deep and comprehensive data has to be gathered from each stage in this process. And you'll find out that this new data model that a digital supply chain needs is probably quite different than what you're doing today. For most companies, it is anyway. And it includes new data from sensors and IoT devices. And I thought I'd bring you a few examples today about that as we talk about this topic. And oh, by the way, as I'm going through this, if there's anything that I'm saying that you disagree with, please go ahead and do a Q&A. If there's anything you really agree with, please mention that and the Q&A. And if you have an example from your company or a question, please use the Q&A. It's really helpful for everybody, if all of us interact on this call and have a good discussion about what's possible and what could happen. All right, next slide is a Colgate-Pamala slide. They're a really, really ambitious company that's done some great work in their supply chain area. And I wanted to highlight one thing they did. I think you might find very interesting. I don't know how many of you know about this. Maybe all of you know, but there is actually a Colgate-Pamala smart toothbrush. And I have a photo of it here on the slide. And this smart toothbrush gathers data from you as you use it. It tells you about the duration of how long you brush your teeth for. It tells you about frequency, how often you do it. It tells you about how much surface you're covering. It identifies where you have areas with plaque. It gives you a whole set of data points that are really critical for dental health. And oh, by the way, when you want to buy this, you can buy it at the Apple store. So the data that's gathered is extremely valuable. In fact, in a lot of these companies we're working with today, the data they gather actually becomes another product line. So Colgate-Pamala is not selling this data to anyone right now, but you can imagine it in the future as customer data is collected that it can be of value to other companies to provide things to their customers as well. And it really boosts sales because guess what? If you know about your customer's toothbrushing habits, you can probably pretty much tell when they need more toothbrush. And it opens up a possibility, which is not done right now, as far as I know, of a direct channel. So increasingly as you have a digital supply chain in the future, as you're creating close link with your customer through your supply chain, you're able to in fact sometimes cut out the middleman and go direct to your customer and more and more companies have a direct channel in addition to their normal wholesale or resale our channel as well. So Colgate-Pamala is a great example of a company that's doing exciting things in your supply chain and harnessing new data as they do it through this kind of an example. Okay, now one of the things we found out as we went through this with companies is that growing revenue through your supply chain requires a new focus. In your supply chain organization and in fact across your company. So one of the things we do is we have executive leadership forums. Last year we had one in Hong Kong, one in Zurich and one in Baltimore. And oh, by the way, they're just selected because we have companies that sponsor us to do this as part of our discussion series. And the last one we have was actually in Santiago, Chile. And in Santiago, we invited people from across the organization. So we had supply chain people plus CIO, plus chief operating officer, plus CEO, plus sales and marketing because it turns out that the growing revenue through your supply chain is in fact a cross silo, cross organization effort. So here are the four things you need to take care of. One is demand which I've mentioned which is all about real time, continuous engagement with the customer. The second is about people because it turns out to have a demand focus. In your supply chain requires a really a big shift in people and people skills. You'll need a lot more people who understand numbers, who understand analytics, who understand data science than you probably have today. You'll also need more people who understand sales and marketing and have the customer contact point as part of their history. So a big, big change in people. In fact, there's one of our companies that we're working with every day is a company called Lee & Fung. They're probably the world's leading wholesaler across the world. And they bring all the goods and services from China to companies around the world. And they do a great job. So if you go to Walmart, almost everything you see there, I'm exaggerating a little bit, has come through Lee & Fung's sources. And they have to do a thing, they talk about nerds and snipers. And the way they talk about it is based on this movie called American Sniper, which I thought was a really social movie, but they liked it. And they thought the key point was, there was a sniper who pulled the trigger, who knew how to shoot and get things done. But there was a nerd who directed that activity, somebody who had the radiate, who knew what the coordinates were, who understood the importance of targets. And they thought this is a great example of supply chain, that right now, traditionally supply chains have a lot of snipers, people who shoot, especially things like procurement or deal making or manufacturing. But they have very few nerds, people who know how to do the analytics, understand what the market wants, how to get it to the market in the right way. So getting that right combination of people turns out to be really, really critical. So demand and people, then technology. You'll hear a lot about technology in digital supply chains, enterprise-wide technology. It's platform technology. It's about agility and customer visibility. It's about AI and ML. And it's about making sure you can get the data and use it. And finally, risk, as I mentioned before, really enhance risk management capability. So you're gonna have to run that demand stack. You're gonna have to handle both the sales side as well as nerds. You're gonna have to collect and analyze data. And you're gonna have to handle the risk factors that occur as you go through this. Okay. Now, I'm probably not surprising you about this because people know this will happen. This is a survey that we did this year and 51% of the respondents agree or strongly agree that their supply chain can help grow revenues as well as match demand currently right now. So over half believe that their supply chain is a, it can grow revenue and is growing revenue and matching to demand currently. So that says it's happening today. And I'm curious to know about your companies. So if you just take a second now to think about your organization and use your Q and A button and to click on it and just say a few things about, do you believe that your supply chain can increase revenue in the future? Or you might say, how much are you doing right now around managing sales or revenue through a supply chain? And finally, how do you see the future around this topic? So please contribute your thoughts as we go through this discussion. Okay, I'll give you another example of a company that was part of our group. It's Goodyear and they are creating sort of the fit bit of tires. I don't know if you've heard about this, but that is a photo of a sensor in a tire. It turns out that for Goodyear, the supply chain is massively important because producing the right tires for the right wheel size, for the right use, for the right combination of width and so forth is really critical. And having those available to a customer when they need them is absolutely essential. Well, what if you had a sensor on a tire that would monitor the use of the tire? What if you could tell not only how the tire is being used but you could tell the wear on the tire. You would have an incredible opportunity to help that customer because you would know when they need a new tire. You would know it before they know it. You would know how they drive, so you'd know what kind of tire they probably need. You could recommend a tire that has all season capability or one that's lower profile. Well, that's exactly where Goodyear is heading. They're creating the fit bit of tires. And oh, by the way, when they do this, there's an opportunity to have people on a subscription model and have, you know, you have a certain kind of tire, you get Goodyear to hook up with you through this sensor-based system and you're able to actually create growth in your market share, growth in your revenue because instead of going to Big O Tire and seeing, you know, 300 different tires on the wall, they actually can go direct to you and you'll just get Goodyear again because they're working fine and actually Goodyear's helping you. So that's a good example of another company using this kind of approach. Now, one of the things that's really, really key about this, and I wanna make sure this, I don't miss this point, is that algorithms are, it's an important part of winning this battle. Algorithms means formulas, means ways to sense customer demand, shape your production delivery and yield a winning customer service experience. Really, really critical. There's public algorithms that are common across and industry, there's also private formula that are not. And companies that have a strong library of both are winning in the marketplace. And to make this work, to make algorithms work, you need several things. One of the things you need is AI and ML. In other words, collecting data that helps you do a better job and as you collect it and as you do more transactions and more sales. Not only are you doing a better job but you're also getting better every day because the machine learning captures the transactions, captures the knowledge and allows you to improve the work that you're doing. So it's an important part of this digital supply chain topic that we're discussing today. So winning algorithms. Now, a good example of this is Google's AlphaZero. Google's AlphaZero AI became the chess master in exactly four hours. This is a photo, not from Google's AlphaZero. This is a photo that I captured from when IBM beat Gary Kasparov, the world's leading chess master. And IBM created a server that played chess. And at first when it played chess, I could beat it and I'm not a good chess player but it learned and got better and learned and got better. And then it beat Gary Kasparov and it could beat any chess master in the world. Well, Google has an AI system now, AlphaZero. And the story is that after four hours of learning about chess, exactly four hours, it was able to beat any chess master in the world. That's pretty impressive. It shows you the power of AI, the power of continuous learning, the power to take data and turn it into a winning play by creating algorithms that allow you to win a chess match or win a market. So in most companies, there are people who do product planning and they're doing their very best to forecast demand and to give demand signals to the organization. And they do this and some of them are good and some of them are not so good. Some of them are great. Some of them are very bad. And there are a lot of companies that end up with way too much inventory or go out of stock or have other kind of problems. Well, imagine you could take the world's very, very best product planners and make them better. That's what AI will allow you to do. In fact, one of the things that happens and as you go through this process is some of this becomes automated to the point that there's no human interaction needed. So some of the main forecasting become totally automated and so forth. One of our companies that we work with is company called Adelweiss. They're a leading financial services company in India and they have a great approach to automating many, many of their financial transactions that they do for their clients. And they have a measure that I think is very interesting which is they measure the percentage of transactions that are made without human intervention. Quite interesting, quite interesting. That frees up people to do other things which are more valuable around innovation and creativity. Okay, so just a good example of how you can use AI and algorithms to win every game, not just a business game. But to do this, you need a new data model and this is far, far different I guess than the data model of most of the companies on the call today. So this says, okay, we've got to start with some macro factors that drive a customer's behavior. Things like the overall health of the economy. Things like weather, by the way, weather is a huge determinant of customer behavior across almost all industries. Regulatory issues like GDPR, risk environment and so forth. All that influences a customer and the customer's customer. Increasingly, companies have to look at not only their customer, but also their customer's customer to drive demand. So the customer and customer's customers in the center of this and those groups of customers generate a huge amount of data. There's buying behavior data which you can capture at the store site. There's IoT data where sensors are in devices and are transmitting usage patterns to you. There's, I mentioned a toothbrush, there's rice cookers, there's automobiles. I mean, everything now is IoT. There's smart sensors. There's already nearly one trillion sensors in the world today. I showed you one on a tire. They're gonna be everywhere and they already are everywhere, but growing like crazy. Social media, of course, is prevalent and used around the world. Text data, image data, more and more video data, unstructured data of all different types. All of this data indicates a customer's intention. Now, most companies have trouble dealing with the data they currently collect. They find they're overwhelmed even with the current amount of data. And the idea of going out and collecting and making sense out of all these new data sources is quite intimidating. But these companies are smart and they are doing more and more things to get more and more competent. So for example, they're using AI and machine learning to collect that data, clean it, which is super important, and then analyze it and make decisions. And they get better and better at that every single day because experience helps you that way. Now, it turns out that it's not just about customer data and it's not just about algorithms, it's about making decisions. And to do this well, you actually need to create something called an algorithm council. And I'll describe what that looks like right now. But the basic idea is you can't do this within one silo. Now, once the algorithm council makes a decision about demand or capacity or future needs, that gets generated into a demand plan, technology plan, manufacturing plan, and the whole organization lines up and executes. So it's quite a powerful process. All right, now, we did some work about this and the survey said, okay, look, if you wanna find out what are the areas that are most challenging for you to do the supply chain as you do this transformation, the number one thing that everyone said was people. The people challenges are the hardest thing that people are working on in order to create this kind of success. And as I mentioned before, it's about data scientists, it's about more quote unquote nerds, it's about people of IS experience, it's about people who are used to making decisions based on data. It's a whole cultural shift that's required across the organization, not just within supply chain, but also in sales and marketing, for example, and within finance. When we asked how much revenue is driven by your supply chain right now, 32% of the people said essentially zero. But on the other hand, if you look at 20% or more or 10 to 19%, you're gonna find that there was a big bulk of people who also felt that right now, their supply chain is already creating revenue. Now they said, okay, what about in five years? How much revenue will be driven by your supply chain within five years? This is a far, far different answer. 20% or more by 50% of the companies. Only 1% said essentially zero. So there's a consensus around this as being the way of the future. Now, if you ask the question, which we did, do you collect new data, use AI and ML and have new ways to analyze and drive decisions? Very, very, very, very few companies said they collect most of the data and they're making those decisions right now. These are tend to be digital native companies that we talked with. And most people, 62% said, you know what, we have trouble managing the data that we currently collect, cleaning it, analyzing it and using it. And in fact, we don't deploy AI and ML in a substantial way. So this is another area where much, much change is required and hopefully you're on this path right now as you work on your supply chains. So this algorithm council I mentioned, let me describe it a little bit more. It's a cross-functional leadership team. It identifies and defines specific market opportunities that your digital supply chain could exploit, given of course the right algorithms and the right data. And oh, by the way, thinking through what data you need is not a small task, but companies that do this well and then get the data and analyze it are way ahead. The second thing is the algorithm council actually sets the organization's priorities for data collection, analysis, identifies the algorithms that will bring market success. Third, council members will typically include sales and marketing, HR, finance and supply chain because the data and perspective needed really cut across traditional organizational silos. I'm guessing that many of your companies are like this where sales and marketing collects their own data, maybe not broadly shared. Supply chain has their own data sources, probably not included in some of the discussions. And there's generally a sense that each silo is protecting and owning their data. Well, this algorithm council that we're talking about collects data across. So what does this mean? The algorithm council needs support from data scientists, mathematicians, information systems experts. You need to use AI and ML and you need to monitor the performance of your business just execution and decide where more algorithms are needed and how to get them going. So it's a very important role that companies do not have right now for the most part and will need to have over the next year or so. In fact, we're working with a company right now, very famous company, a sporting goods company and they are developing an algorithm council that's just fantastic and their performance is getting better. Okay, so here are some ways to generate improvements. Number one, collect new data, even it's almost impossible to get. Number two, develop a taxonomy of variables. When you get that data, you've got to decide how it impacts the decisions you're making. So we call it taxonomy, but a way to actually take the data and use it. The third thing is create or deploy algorithms that have a customer focus. So these algorithms are talking about are not finance algorithms. They're algorithms that include what your customer needs and what you can focus on in your supply chain. And the big idea is to use your supply chain customer experience as a competitive advantage just like Amazon does today. Super, super good example. All right, so let me keep going here. Here's what we suggest as your next steps. And I hope you're thinking of questions to ask because we're gonna be going into Q and A fairly soon here. Next steps, really important for you to decide how your supply chain can generate revenue growth. How your actions in the supply chain can actually make a difference improvement in your sales. Second, you find your data supply chain strategy with a focus on revenue. So if you're talking about building a digital supply chain, please include revenue growth as a key item that's part of your goal. Okay, get the team aligned, right people, right communication. Next, decide investment returns in metrics. Really, really critical that you have the right metrics as you make this transition happen. So we've done a lot of work in this area and it turns out that metrics for the digital supply chain are quite different. Metrics around revenue growth belong in the supply chain's scorecard. And then, of course, after you decide your investment, you've got metrics to manage it, then execute. Make sure you get it done. And that's a lot of what we were about in this institute, we're about helping companies get things done. And we hope that as you hear about what we're describing today, you take the initiative, get it done within your own companies. Next, we also like to invite you to join our institute. It's a great organization. You can collaborate with your peers in other industries. We have a limit of one company per competitive set. So we have Colgate Pomalov in our group. We would not let a competitor organization join to Colgate Pomalov. So that's how we work it. So we can have great and open discussions with our peers. Deploy the digital supply chain institute tools. We have a set of tools that you can use. You can see them on our website, but we have in-depth ones for members only. For example, we have a transformation maturity assessment, which allows you to know where you are right now with respect to digital supply chain in the future, understand what the gap is. We have a tool for setting performance metrics that are required for the new digital supply chain to be fully implemented and operational. We have a variety of things around algorithms and algorithm counsel and supply chain strategy. So these are tools you can use that will hopefully accelerate your progress towards change and shape the future. Because this is leading edge work. This is where supply chains are going, and you'll have a chance to really shape the future. So Ira, I'm gonna stop for a minute here and just pause and see if you have any questions or if there's questions from the group of people who are on the Zoom call here. Thank you, George, very good. And we do have some questions from the audience, but before we get to the question audience, because they tend to be a little more focused, let's say, and in depth, I wanted to ask you a few general questions based on this presentation. You talk about front side flip and the notion of customer facing, which is really what the front side flip is about. Customer facing is a concept or notion in business that's been around for quite some time. So why is it now that we're seeing it heavily applied to the digital supply chain? Yeah, that's a good question. I think a lot of things have come together at the right time. One thing is that the data, the data about customer needs, customer wants is more prevalent than ever and more collectible than ever. So we're now able to collect information from sensors, from smart devices, like even from smart toothbrushes. Or for example, you know, Under Armour is a company that's part of our group and I have my shoes tell me every day what my running pattern has been, how much exercise I've gotten, my pulse rate, all kinds of information. So my point is that now more than ever we have data available that tells us what customers want and need and would want and need it in the future. So that's important. The second thing is the science of AI and machine learning have really, really increased to the point that they're usable in business on an everyday basis. So in addition to more data being required, we also now have tools that allow us to go in and make sense out of it. And third, the whole idea of digitalization, digitalizing your supply chain is happening at the same moment. So those three things all happening now allow us to this front side flip, allow us to have a different focus on the customer. And you know, by the way, if there's a company that doesn't do that, they're at risk of losing their share. The same way the tax industry lost their share when Uber arrived and had a totally different supply chain. Let me pick up a little bit on people and talent, which is part of this equation. And I know we're gonna have, by the way, another session dedicated to people and talent as part of this equation. But if I'm a supply chain executive and I'm listening to you, one of the things I have to be thinking in the back of my mind is this is such a radical change and a great opportunity to take this technology, to take the data, to apply it to generate business. And that's a much more proactive point of view. But in years past, or the way I've run my business has been very reactive supply chain. So if I'm thinking of the people that I have, is this a radical remake that I need to step up as I look at implementing or transforming to a digital supply chain? You know, I think that there is a need to radically change the people equation for the digital supply chain to be effective. And there's sort of three elements of that. So the first element is there's a new reservoir of data scientists who have to be added to the mix. These are data scientists that not only go how to do analytics and understand data, but they also understand the business. And these people are rare. You know, you've gotta find them or build them. People who understand not only analytical tools but also understand the industry you're in and how you compete. So that's one thing you have to do is acquire that kind of talent. The second thing you have to do is you have to do increased focus on database decision making. And this requires a change perhaps to training plans within your organization as people learn about how to do this. It requires a change perhaps to where you promote people to higher roles and based on their analyzed data and make decisions that are increasingly correct because they're database. So that's the second thing is building capability. And the third thing is about sharing. And most organizations today operate in silos with sort of boundaries between sales and marketing and supply chain, for example. And the ability to create a council and collaborate with purpose across boundaries like that is a key way to remake the people side of your equation. So if you have new people, you have people who've been retrained and you have new ways of working together, I think the people side will come together. Great, thank you. All right, let's go to some of the questions. And let me remind our audience members that if you have a question for George, please enter in the Q&A button. You'll see at the bottom of your screen. We have an anonymous attendee who's asking, says that yes, the supply chain can increase revenue. Do you have any thoughts on the major software solutions which can aid in the enterprise to enterprise software supply chain development? Well, I'll tell you something that, I'll mention something here that we're working on that's proven to be quite interesting and valuable. And that is a blockchain. So, we couldn't decide what we believed about blockchain because we read so much hype in the paper about what blockchain was about. And we couldn't decide, is it really as good as they said? So we said, we're gonna do three pilots. So three of our member organizations who are part of this digital supply chain institute said, hey, look, we wanna do a pilot with you. So we got together a leading provider of blockchain services. For example, in this case, I'll mention Bitfury. They're really great company that's pioneered with Bitcoin and now does blockchain services around the world. And we took a company called Arasim, which is one of our member companies in San Francisco. They're an engineering services company. And we said, let's use blockchain for your DevOps process. And let's find a way to take the value of blockchain in your supply chain because DevOps is a supply chain issue because you have all sorts of layers of a vendor who are supplying code to you as you build your solution. And we developed this incredible blockchain solution. In fact, we had three key outcomes. The outcome one was cycle time. So when we use blockchain in this supply chain around DevOps, we found we could reduce cycle time by 32%. That's almost a third. That's ridiculous, ridiculously faster. And that's really super important to companies around the world. If you can have solutions, software solutions faster, it makes a difference. The second thing we found out was we're able to improve quality. So quality means number of defects. Quality improves about 11%. And finally, we improved productivity and productivity improved by about almost 30%. So there was a breakthrough solutions because blockchain had that kind of power and applied in the right way could make a difference. So that's one example of a software tool that makes a difference. Obviously, some of the big ERPs like SAP are making changes to how they configure their enterprise systems. They're even enabling blockchain now as a part of their solutions. And then there's a number of analytical tools that are available to you as people go out and create those solutions for these kind of examples. So I think that's how I would answer that question, Ira. Great. All right. Gregory Millen asks, let's see, how important is the robotic process automation to create value from historical data or old forms of data? RPA is a growing trend. And I think that probably you're gonna see more and more RPA solutions in the marketplace. And I think it is an important thing to do, especially for companies that own their manufacturing base. And you're gonna see a lot of advancements in this field. So I don't have any specific to say about it, but almost all the companies we're working with are using RPA tools and reporting good progress. Okay. All right. Let's see, Prasun Goel asks, with regards to software for supporting digital demand management, does implementation of standard packaged application, many of them claim out of the box machine learning algorithm capability, outweigh developing bespoke software with my own machine language learning library for a company. Please share your views. Okay. This is a really good question. I think there's a couple of things that it makes me think about. One is the difference between public algorithms and private algorithms. You know, there are some algorithms that you can get publicly available for an industry that work and that need to be implemented. Now, how well that works for you is based on the data you collect, how well you collect it. Your A9 ML tools and so forth. But having public algorithms is an important part of the mix. The second part of the mix though is proprietary algorithms. These are formula that you create that better than anyone else tells you how to meet your customer's demands. And this is a big thing that companies are working on right now that I think create a huge advantage. So there's public and private algorithms. Now then the question is, what kind of tools can you use to create these algorithms and use them? Should you program them yourself or should you get new ones? I think my experience has been for the most part, for most companies using a standard package tools works. Works pretty well. Works enough that you can create value and your differentiation is gonna come based on the algorithm you use and the AIML that you've employed not on the software tool. Now in some cases that's not necessary and you should develop your own algorithm and your own tool, your own way of doing it, your own software. But I'd say most companies find that having a package is adequate and spend most of your time on the algorithm itself as opposed to the software package. I hope I answered that question adequately, but that's what I've seen. Very good. All right, I'm gonna ask another question while we remind people that they could submit their questions via the Q&A function at the bottom of your screen. All right, I'm gonna ask my question. A similar one I asked at the last session and that is if I'm listening to this and I'm a supply chain executive and this is all great information but I only have limited resources, if I had to pick one or two leverage points to manage demand or stimulate demand, George, what would you recommend I focus on? Okay, well, I think the question is good because when you decide to make a transformation happen, having a vision for where you're heading is important but being practical about what you can get done in a timely manner is also important. So picking one or two things to go after and get done is a good idea. In fact, we have a tool called the accelerator program where we do exactly that. We take an agile approach to organizational change and we actually carve out one or two things that a company can do and we'd get them done quickly and then with that success we go to the next thing. So if I were to pick one or two things to work on, I'd say number one, it would be forming this algorithm council, getting a cross functional group of people together that can collect data and look at it in new and different way. And I guarantee you that when you bring that team together and you get it working effectively, you will discover new algorithms that make your business better. I don't know what they might be in data gathering, they might be in demand management, they might, I don't understand my simulation, I can't tell you where they'll be but that cross functional team will find things that otherwise are not seen. So that's one of the first things I do. The second thing that I would do is I would think about what kind of skills do I need to bring into my organization that will help me compete better. In other words, do I need more data scientists? Do I need people who understand demand management from the customer side? So the two things that that'd be the second thing I pick, which is really doing an in-depth discussion around people strategy because one of the quickest ways to change organizations, to change people, their focus, their skill set. And that's certainly something that's really important as you move to a truly digital supply chain. Very good. Now I wanna follow up on the algorithm council, George. Is this a concept that is specific to the supply chain or should companies use the algorithm council to embrace all their company-wide algorithms, whether or not it touches the supply chain? Well, I think there's a question of focus here. I think when you first set the algorithm council, the focus should be on the supply chain topics that I'm describing. I think what happens as this council meets and works is they discover new markets. They discover new things that the company can do to create value. So for example, I mentioned maybe they'll discover that you know what, we should give this item away and go to a subscription service based on content or we should go direct. So these, the outcomes may be very different than where you started. May in fact be a new business model, where something that you're selling now is given away, where something that you don't even have in your portfolio becomes a key part of what you offer. So therefore that algorithm council which started with a supply chain focus has a much broader focus. And oh, by the way, I say supply chain focus, but it turns out that sales and marketing input is key in this and a key driver. The financial information from the CFO's team is critical in making the right decisions. So inevitably the algorithms start attacking other areas of the business, which all link back to the supply chain but may go deeper into one area or another. Now, so much of the transforming the supply chain into a digital supply chain obviously is technology based, but is it critical to have the AI, the machine learning skills, in-house to build that up if you're really going to leverage your supply chain in this transformation? Is that a key technology that you must master? I think the IES organization needs to look carefully at what skill sets it needs in-house and what is appropriate to outsource. So for example, some companies, maybe they're middle market companies, maybe they're companies who have no history of work in this area will choose to outsource AI to an expert developer of AI solutions. And that's totally fine. In other cases, companies will say, you know what, the way this data model that we're building, this digital supply chain that we have is so critical and it's so important to make that work based on getting better every time we have a transaction that we have to have some AI and machine learning skills in-house. In fact, I think about the CIO of Colgate-Pomolov, he has a very strong AI capability in-house because he knows that it's important to be able to develop that technology as Colgate-Pomolov gets smarter and smarter and smarter about collecting customer data. So I guess I'm gonna say it's based on the size of the company and based on their history. But so there'll be a mix. There'll be some companies that contract out for it and there are other companies which create a center of excellence that gets used every day. Very good. I have a follow-up question for Prasoon Goel. He wants to know if does the Digital Supply Chain Institute have any reference framework for major public or open source algorithms specific to supply chain demand management? Well, you know, we're working on that right now. What we do as a supply chain institute is each year we take on a different set of things to do deep research on. So when we started out, the very first thing we did was research what is a digital supply chain? What does it take to get that to happen and to get the benefit from it? And what are those benefits? That was our first year. Our second year was all about how do we measure? What are the performance metrics that we need now and in the future to manage ourselves to create this digital supply chain and to manage it after we've got it? And we also looked at transformation management. How does it take to change from where you're going? Now, this year we're looking at several things. One is algorithms, the algorithm council. And what is the right way to approach that? What's available open source versus, you know, should be developed proprietary. And so we're working on that right now. We don't have that available today, but we will have it. So you can stay tuned and, you know, if you join the digital supply chain institute, you can be involved with helping guide us on that. But we're working towards that. But I want to say one more thing about that, you know, we also, I mentioned blockchain earlier today because I think blockchain is part of the answer to the digital supply chain. There's a lot of things that it can address that are important. And I mentioned we had some really bold improvements and cycle time quality and costs and we did the work. But we have a regular blockchain discussion session. Once a month we have a, we call it a Collaboratory. We bring our member companies together, plus we bring a leading thinker on blockchain. In most cases it's a vendor. In some cases an academic. In some cases it's a company that's executing it, but they provide a really in-depth view of what they're doing and how it's working. And it gives the people on the Collaboratory a chance to ask really tough questions and to make sure they understand how these things work and how they don't work. Because like all these technology questions, the answer is not just technology. It's in process change. It's in people change. You know, as I mentioned those four areas, demand people technology risk. All those things have to happen to get the benefit. And, but anyway, this blockchain Collaboratory I, you know, I invite you to join and participate in it. It's once a month and it's a good example of how we gather around different topics and get smarter about them. Great. And on that note, George, I think we're gonna wrap up because that's it for our session today. And I want to thank everyone in the audience for attending and especially George for your time and remind people that next week on June 19th we will have our next session which will be on blockchain. You can find out more about the Digital Supply Chain Institute at our website. And I think there's a slide that will have the URL for the Digital Supply Chain Institute. If we could post that. And there's the schedule for the upcoming Expert Connects. You see the blockchain is one and we're gonna do another session on artificial intelligence and machine learning. And we will, the next to last will be on talent strategies. And then of course we're gonna finish on risk and competitive advantage. All right. Well, thank you all for joining us today. All right. Thank you, everybody.