Chemicals Go Digital! Smart technologies and the Supply Chain in the digital age - Webcast (English)
Till. We. Start maybe. For those of you that are already online following, us under, two speakers, always, you can't hear us. And. If, you have any questions. To us, just. Use as indicated, here below the. Email, addresses chemicals, that digital @x, account - partners, calm or, the, google or youtube chat for, this you need to log in if, you have an account in Google or YouTube. Another. Minute also. And then we. Will start. I think. We can start. And. Good. Afternoon. Good, evening everyone. Want. To talk, a bit about, supply. Chain and the digital. Transformation. What. Will change. Digital. Transformation, in the, supply chain in chemicals, or what state-of-the-art, collaborative. Technology, that's how I called it. Today. Can do to your supply chain, first. A good round of introductions, my, name is Lorenzo for Maconie I am one of the managing, partners, of, excellent. Partners, boutique, consulting specializing. In the chemical, industry and. Eighteen, years working. As a consultant with, focus, on operations, management supply, chain management, in. Digital transformation, for the chemical companies. My. Name is welcome Karen I'm a chemist, by education, since, about thirty years in the business first. Eight years as found in Germany and Asia in the chemical, industry and, since about 20, years our management consultant, specializing. On, innovation, management and, supply chain management and, these, days I'm conducting a, cross industry survey, on professions. 4.0. Ie, how well are chemists, engineers, work, in the digitized chemical. Industry. In a couple of years. David. And, we can start before, we start and we will go into your. Presentation. Moodle so you will not see us anymore, but we will hear us please. Do unmute, us because otherwise you, don't hear us and, if. You have any questions, or any inputs, just, write. An email to chemical. A, Texican, - gardeners calm. So. We, are now disappearing. And. Switch. Here we are. Presentation. Mode exactly. So yeah. Again our faces, and, names. And. Don't, really thank. You low and slow supply. Chain has been an attractive, subject. Over about 50. To 60 years in the meantime and, over. The last. 50, 60 years there has been somewhat like a height on supply, chain management with. A number of, evolutions. And successes. And new technologies. Adopted, however. Over, the last couple of years we, have seen a bit of a lack of excitement, on, further. Achievements. In supply chain, however. The last, change. In five years, to indicate, that, we can expect a very attractive. Transformation. In supply chain management, when. Digitalization. Is the, ground and. In. The next couple of minutes, we, are going to talk to, you about three. Selected. Areas, supply. Chain digitization, is a huge, area, that we have to focus a bit on a couple of applications, and. Fields, for. Today's session we have decided, to talk about forecasting. And playing for a while Lorenza. Will take you through transactions. And monitoring, in the supply chain in the digitized era and last. Not least we'll, have an outlook, on the. Automation, of, transports. On the road and as well. As within the fences. Of a site let's. Start with forecasting. And planning where. The issue is today, people. Are. Doing, when the best to, provide. A sales cost. Based. On which will I create, a production, plan and so forth however, it's. A bit the rubbish in rubbish out, disaster. If, the forecast. Accuracy, is limited, the. Don't. Chain benefit. Will be somewhat limited but, predictive, analytics, will, be able to do in the future is to.
Accelerate. The. Planning process, while. Increasing. Its accuracy, and it all starts, and they're a very beginning, with increased, focus, accuracy. By, combining, certain. Predictive, analytics, data, which. We're going to discuss, with you right. Now. If. You compare today, and tomorrow you can say you compare, the current, April, and Europeans. Which, give you quite some good overview on historic, data and, neutron, data such. As sales history all. Kind of data from your customer relationship, management database, and current. Point of sales data. Furthermore. McMullen, studies, research, papers, social network pages in support are, not yet automated. Or even digitized, in current systems. Tomorrow. And we do talk about low. Number of years of Lee the. Scope of data capturing, and they were functionality. And their benefit, will, be much broader. The, biggest analytics, will, include, marketing. Studies and macroeconomic. Leaders in, research paper, when. In use of social networks, is able. To do a couple of metre analysis. And others more it will be a much, more comprehensive, much. More timely and much more accurate. Analytics. Than today. After. Have given some positive, outlook, this picture may come. As a little shock to you because. It looks for other complex, and in fact. Which one has predictive, analytics, is a rather complex, subject, the. Human. Slaves of any, analytics, service, providers, hardware providers, integrators. Data. Sources, and so forth the. Key message here is, pick. What's best filling. Your. Company's. Needs, that, you have to define first, be. Very sure on each interest, sources you will have to need and what the limitations for your data quality, would. Have to be and then, you need to go down either, path, one. Is she, relies on our historic. And. Holistic, commercial. Software, solution, on a suite if you like the. Other one is tailor-made, one that, he compels, of the various modules.
And Components and, integrated, with, the help or some, relief. Analytic. Experts. Basically. Two ways of implementation. Before, used to make absolutely sure where, to start from and what you hear with wormans will be. This. One is a bit less, complex, and. Expected. Basically, off-the-shelf. Solutions, that are available and are reused today's, in numerous. Applications. For. Example Microsoft Azure. Or. Amazon, Web Services, or at the latest movie analytics, will ring a bell, among many of you these. Are currently applied. Predictive. Analytics, trillions, and systems, that. Are primarily, known, from. The b2c. Market, the. Basic fundamentally. Implemented. Functionality, is of course, to. Be rushed to the b2b market as well, what. They. Do in principle, is to understand, in, detail, market. Dynamics. Incidence, or market conditions. Were. Able to customize. The, various. The. Combinations, of parameters to provide, you with so called sentiment, analysis. Most. Of that is taking. Place in the cloud already. It's also one of the reasons why we do not focus. A day on cloud as a digitized. Or. Digitalization. Technology. So much because it's more or less standard already, and for. You as the decision-maker, is a supply chain manager, or institution. Manager, or production planner what's, important, for you is to have this data, transformed. Into information. Visualized. For you to, make, timely. And hopefully, the right decisions. That's. All, yes. The second. Chapter. Of this. Webcast, is about transaction, and monitoring. In. The supply. Chain and, the. Supply chain chemicals, is actually, a big. Concatenation. Of many, many transactions, out of wonder. Intake or the processing. Association. To a stock stock reservation. Payment. The. Whole gist exchange, up to the delivery up to the proof of the delivery, come. Complain. Complain, management. Etc and. The. Level, of personal. Intensity. And personal Borak in. The chain, notwithstanding. All the automation, that's already have been made is still very very high not. The same kind of transparency, that we have. Around. The shipments. Around the orders especially. If you compare with me, to see, application. Like Amazon, for example is very low, so. The. Tracking. And tracing especially. In when, you have. Trans-regional. Transportation. Is very very low and. Customers. In other continents usually, don't know when, the goods will be exactly arriving, now. We. Believe that the, digit. The, industry, 4.0. Level. Of digitalization, will. Change this significant, is one of the areas which are actually. More most interesting, in. Terms of in, terms of new, wave of technology, and, we. See here especially true, technologies. They will help. A hell of a lot in overcoming. The shortcomings, as. Of now one is the blockchain and, the. Second is the artificial intelligence, so. Let's. Go. Into each of these a bit a bit more. First. Of all that do not change what is the blockchain the, blockchain is, a method. That, allow. To. Track information and. Transactional, information. About. Exchanges. About buying, and selling about, different. Movements. Of, goods and/or. Of. Our, services, through. A distributed. Ledger technology, to, a system, that allows to track the information. Not. In one proprietary. System, that, belongs to someone and usually is prone. To be to. Be paid and is, requiring, a field in, a distributed way over, many many computers, in this system at the same time allow. A. High. Level of security because. The. Same record, of, a. Transaction. Is being. Recorded on several, computers, and it's impossible, or very very difficult to. Falsify. The. Records. On, all these computers. So. This is the theory the. Most famous gold application. Of the blockchain is, the, coin and, they. Say the the blockchain currencies. There are hell of a lot more. That. Came into, the debate because of a significant. Bubble, financial. Gravity generated in. The. Bubble is a signal, of the fact that the technology is. Still. Very controversial. The. Application, the logistics, are since. Long already, debated, in nowadays. There are some initial, pilots, you see here in, the picture one specific, pilot made by the IBM there, is also supported, by the Watson.
Artificial. Intelligence technology that. Is surely the. Transportation. Of off. Of, goods over. Different different. Different. Points and how, this information is being recorded, so the transport history with, all the relevant information occurs, at the time location, event, etc. So. The. Thing is with, the blockchain is it's very very, promising, technology is. Still very, controversial, to what extent, it can be applied and. There. Are still discussions. To, what extent it can be used also. In in the chemical, industry there. Are at this stage not, yet. Concrete. And broad applications. The. Second, technology, that we expect. Significant, benefits, in the supply chain acquired, in the transactional, part and the monitoring part is artificial, intelligence it. Has been, one. Of. Debated, division. Gradients itself, is not moved is, something that started, being, analyzed, already in the seventies, of the last century but. Has got a significant. Boost basically. Through. Major. Drivers, the, first driver is, the. The. Speed of the of, the, calculator. That increased, significantly. And. The. Second, is the, broad. Mass of available. Data through. The, internet, and especially through social networks, the. The, broadness, of data is important, because this mass of data is the pace through which, several. Artificial. Intelligence, applications. Can. Be taught, through. The so-called machine. Learning and deep learning. Mechanism. Basically, the, machines are being. Fed. With all this data and automatically. Learned, from the data how, to conduct, something more efficiently, and correctly. So. Out of this family, of, of. Technologies. Under the label of artificial intelligence there are a series of concrete, technologies. That have a direct, application, into. Into, the fields that are interesting for us what. Is the speech recognition, every. Of you may. Know the. Personal. Assistant, Siri from from, the iPhone or, Alexa, from Amazon, and. They. Recognize. The. Speech and will, really provide initial. Simple. Answers, to the most common, problems. Similarly. There are so-called chat BOTS the blue roughly, the same thing, even, in Britain way and there. Are already a series of of. Application. Like how to desk and, in. Others you.
Have Already, automatic. Translators. Like, the Google pixel us that. Are headphones that are just plugged in, the years and automatically. Translate in multiple languages, what. They receive, as, a as an audio input. And. We, have more complex, and professional. Technologies. Like expert, assistance. That. Help. Automating. Complex. Repetitive. Activities. Like for example. Editing. Preparation. Of articles, this. Is the case of disellio graph for the Washington Post or pre-processing, of digital. Documents. Like. For example invoicing. And invoice checks up. To, information. Retrieval. Technologies. In deep learning algorithm. For reading. Environmental. Data. All. These technologies, and more. May. Have applications, on the transaction, of our chemical supply chain they, are where we see the biggest, application. Is customer service customer. Service is still extremely. People. Based, and. Extremely. Transactional. Basically. 80%. Of the activities of a customer service are around or the intake, or the processing, in SA P or, the confirmation and and, payment tracking and. Logistics, tracking so, all these things can. Even need to be highly, automated it, to a. Became. Of different technologies. Secondly. The back-office part, invoice. Checking. Payment. Checking, and. All. The financial part can, benefit. Of these technologies, a bit less transportation. Warehousing. They're the real big. Bang will come from other technologies, and we will discuss this a bit later so. The first two parts customer. Service, and make office here, me believe there will be significant. Advantages, in the not so long term. To. Go a bit more in today into the practical. Examples. Here, we, have depicted. Existing. Service, called, ask Alexa it's a it's. A it's a collaboration, between. Amazon. Alexa. Artificial. Intelligence, assistant, and DHL. It helps at the moment, to, follow, some. Shipment tracking some, relatively. Simple activities. But. Has he expected, to. To. Enhance on a bit more complicated activities. Very soon so, it's gonna be lets, say the, logistics, assistant, of DHL. And. As we see here it's, already integrated, through several. Communication. Technologies, like voice but also chat and SMS and phone so. That you can access. This assistant, from different ways. Another. Aspect, of of. Where. Artificial, intelligence can help is, the, customs, brokerage, custom. Brokers for those of you that had exposure, to it is, a, huge. Pain and. For. In a significant. Absorption of, personal and cost resources. Because. It's. A necessary, requirement. For exporting, goods but. Is, extremely, dependent, upon, the. Specificities. Of custom. Clearance and impacts. Aspects. Of each of the countries where you have to export so. In short all. The acting is related. To the shipment. Data, collection, to the harmonization, of document, formats, to, the declaration, of goods the translation, into the different customs, codes for the different customer, for. Different states up, to the validation to the customs. Officer, and the. Retrieval. Of the track statements, etc they're all actually, repetitive, activities, because. Of either of the complexity. Of the, of. The regulations, and rules behind it and the variety, because, of the many many countries existing. In. This world this. Is highly, time-consuming. And this is one of the classical, cases, where. Artificial. Intelligence, and its ability to manage this complexity, once, it. Has learned can, really help, so. They have to imagine that basically, to, address this kind of activities.
There. Is a significant. Initial process, of machine, learning to learn the, requirements of each country regulation, to learn how to deal, with each and specific, case. In. Another aspect of their artificial intelligence, is more related. To the image recognition. Technology. Bit the, technology, side of it. And. Is basically, the, the. Part that is very to the visual inspection of the, logistics, assets logistic, assets meaning, wagons. Carriages. Containers. And, you. Name it that are. Returnable. Reusable, and because. Of this are prone. To wearing. To damage and. Are. Object, of a. Regular. Maintenance, rate, when it is too much of course the price goes up and when is not enough drives, utilization. Down. So. For this reason the. Image. Recognition can, help very much because, it's, basically, a relatively. Economical, approach. Of condition. Based monitoring, there. Is a camera, that can. Take. Regular. Pictures. Of the, assets for example when some. Carriages. Are passing, to a specific, Check Point analyze. The image, identify. Patterns of potential, wearing, then. Triggers. A signal, for, maintenance. Intervention. That, can fix the, wearing before it becomes the. Reason for for. Downtime. This. Kind of applications. Are in fact already. Fairly. In use, especially. In the rail. In. The rail and the big. In the big. Role. Acoustics, company, because. It's fairly. Easy to have fixed. Checkpoints, where. The containers, are our. Going through in. The. In the image. In visual inspection, technology, and the image processing technologies. Are, significantly. Growing up in. Increasing. To the machine, learning the quality, of the. Air. Monitoring, this. Is one of the aspects, that is. Really significantly, improved in the last year's the quality. Through deep learning to identified, what, is a wearing from what is just for example a, bit of dust or or, just. Some. Dirty spots. The. Image recognition is, also used, in. In association, with artificial. Intelligence. Through. For, for inventory management purposes another aspect, of the supply chain management. You. Know we see an example, of this company, copies copy, store, go. To store tracker which. Is basically adopting, image recognition. Technologies. To identify, whether. On shelves, there, are some empty spots in which items, are still. There and are not there and also. To understand, what is their, turnover. Of each item and whether it preserves more or less space on a shelf. You. Can, imagine the power of this relatively simple system in. Comparison. To the transaction, based erp systems, that are based on working in and out of goods. And we, are always somehow. Not. Real time but are. Ported. To, the dealers of any on a manual tracking so. We can very well imagine that this kind of image recognition human, training can be used also, in b2b, environment. And. That, they, can be used also. In the chemical industry. Last. Model least words about e-commerce e-commerce. Has. Been. Let's. Say a, topic. Of discussion in the chemical, industry since the year 2000, the were already initial attempts, to create to. Create platforms, for, for exchanging, and selling. Chemicals. Over the Internet, already in the year 2000, during the first dot-com bubble. Matter. Of fact many, chemical, companies, still don't use, e-commerce. And, they still relied to the classical, sales, force based. Selling, and to the classical, people based customer. Service. Now. Things are changing and you. See you, start seeing an initial, offering. Of chemicals. The. Real first pioneer, is Alibaba. That's. The would, say the Chinese Amazon, where. You see a lot of b2b, offerings, and, and. Formats, also on this platform and you also see chemical, companies, selling products, on their platform, and on. The base of this experience. Also. Western. Based. Companies. And platforms, are trying their luck. Not. Least we, know about the. The, platforms, can, get that. Has been spun off of the. Company. Girlfriend. Germany and also Castro, on a bigger scale is. Developed. It's own platform. For exchanging, and. Selling chemicals, so. We can expect that after so much time of, waiting, the. E-commerce channel, will, pick up relatively, soon thanks to that the. New technologies, and advancement. And the. Experiences. As well of the. B2c. Sector. Often. Thanks. Let's, the product are the goods. Or the. Transportation. Of the automation. Of our, transportation. In the chemical. Industry this. Is nothing here basically. Today. We would say there's, a lot of manually, trading or many. Removed, vehicles. The, forklift as a classic one basically. Transportation. Manually. Controlled. As taking place in the four floors within. The fences of a site. Partially. On Rails partially, on the road. This, is people. Stand up and not very, let's, say attractive, because it's just a given one it's, somewhat limited, though we're. Slowly progress in the future that we can expect I, was. Emphasizing an, annual, operations, go out of it so the logical next step is the automation, of.
Vehicles. That are self. Driving and. If. You look at the discussions. In the US for example with, the accident. That occasionally, happen on the other side of the technology. Or progress, what. Is the essence. In a nutshell a, lot. Of the, chances. If you. Making. Self-driving vehicles. There. Is a lot of additional. Complexity. Because simply the skilled and the rails are. Much more, weak. Than the. Dimensions. Of your site and there, is a certain risk associated to, it if. You manage the complexity, and the risk if, you have a sense of supplied, and are, managing, the transmission, of the signals, then. Self-driving. Vehicles, even, on the road and we're talking about trucks ultimately. Will. Have a huge. Potential. Currently. Self-harming. Vehicles, in the limited. As. I, own factories. Where, a couple of applications for. That are. Evolving. It's. Not a revolution it's more an evolving, to works benefits, such. As increased, safety, if you take out people, from, your warehouses. And, use. Self-driving. Later to start that's, a clear benefit, on the, other side. You'll have a high accuracy and productivity. Speed. And reliability of. These tools is higher, than, the human. Guarantee, human errors and, your. Country should extend eliminate, this a lot of means if you have friends relatives warehouses. You are much more flexible and using, in using, your spaces. And so forth so, the evolution, of current. Existing. Autonomous. Driving vehicles. In warehouses, is on. Its way and. The. Purpose, we are going to see, very soon, is. Autonomous. Trucks on the roads and. I'm referring to soon. I'm, not talking about the mid-20s, I'm talking, about next. You're already there. Are a couple of trucks. Factories, experimenting. Pirating. Self-driving. Trucks, such, as Tesla. And Volvo and, also. Alabama, is on its road definitely speaking. She, launched. The first soft. Driving, trucks. Next. Year or very early in the 20s, or will, need are the benefits, one. Of them is he'll, err is human, fatigue. Will. Be. Risks. Too for. A certain crash and you eliminate to a certain extent. Settings. And tools of, flu. Come. From, the. Platoons. If you, have. Trucks. One, after the other and. A country at a control speed. Via. Slate efficiency, fuel efficiency, is going very. Much up and you save a lot of fuel, cost. And on. The way logistics, is a major cost, in chemicals, main and the commodity chemicals, that, are still these days. Low. Cable chain, with the right senators. And transmission. Technology, that idea was mentioned before to. Track. The. Location and, the condition, of your move, this real-time. Which is another. Nice benefit. So, as I mentioned, we expect, this to be launched early, next year and then, over the next two or three four years of, major rollout with, her at least in the US if not yet already in, the European. Continent. Let's. Talk about warehouse. Autumn. I oughta Meishan in a couple. Of minutes. The. Automation. In, the warehouse, probably. The best example. To, describe that is, system. Called Aviator which is around since average 2010. It's, a three dimensional, transportation. System within the warehouse, it's. Much, more efficient. Than the previous, systems. That, had you been, over on. X-axis. Are, not to avoid exists, and move. Or call, a pellet. In the set direction. In, a three-dimensional, warehouse with, a ways. Or tracks and, that our automated, warehouse using, an aviator system, you're much faster have. Moved more Goods at more, accuracy, to. Shipping standards, even safer, because you eliminate. The, need to have people working there. That's. A given in the day, progress, of optimizing. Warehouses, these days and we expect, this, to further evolve. But, an expected real, revolution. There rather than the, systems getting smarter, over the next couple, of years. If. You put basically, everything, to building a to get as, far as the gist expression, has conserved a pretty complex. Picture as this one shows. In. A nutshell at, DHL. Maintain. Half under, one roof if you like already vision. Based inventory. Management that Lorenzo, was referring to you machine. Learning were self learning, agb's. Another, one in providing the. Machine. Learning and the. Automatic. Driven, vehicles. We. Have a little control over the, circumstances. And. Conditions of. Use. And of assets, in awareness for example, we. Have which, based intelligence, working there we. Have certain about autonomous. Delivery, fleet just on, the last slides. We. Did have other. Features, more and if, you have, all of that in a. Area. In a warehouse. Or, in a plant this. Is looking rather complex. And rather fury stick in fact. It is not future, is the given standard already not. In the chemical, industry yet, suddenly. Impact. On the chemical industry the. Demand. For them or the request to the chemical industry is to. Manage their transition, manage, the transfer, from, another industry, it's, possible, is there only.
Have. To adopt it through the chemical industry and we expect this to, be happening very soon, again. Very. Good. Actually. Almost at the end of our, session, or we are again of what we wanted to share. With you and. Then I said all the topics of, course as, you said one from we. Wanted to focus on these three aspects. Forecasting. Predictive. Analytics, the. Transaction. Part with the blockchain artificial. Intelligence, and the. Transportation. Part with autonomous, vehicles. And the. Way housing automation, now, there are other aspects, these, are the, one that we consider, most. Interesting, and more, specific, to the supply chain, in. This session now. Is the third and last one, of the plan were for this health year. Or 2018. We. Were having. A first, session. Back in end of February March on the. High-level. Perspective. Of, 30k foot view on, digitization. In the chemical industry we, had another. Session in the very pro about manufacturing. And, asset management and. We. Will continue with this webcast, or not and, we'll. Send out our. Indications. And timing. Until the end of the year soon just. For you as our first appetizer, on the topics that we would, like to address and, we haven't scheduled yet we. Want to spend some time on marketing and sales and what, is the impact of digital transformation there. As, well as an innovation in R&D. Also. Circular. Economy and, sustainability are a big topic especially, for the chemical, industry there, we want to spend. One session, and also. We, have two three sessions for, let's. Say the people side of the transformation. One. Big. Topic is the change of the professions, in chemicals, so. How, will. Look. Like the. Professional. For example an engineer a chemical, engineer, or a chemist in, 10 or 20 years time what are the competencies, and. What. Are the activities that, will be necessary, and will not be necessary anymore for example, also. How shall, digital. Projects. Be. Driven we. Know that there are components, that are very different, from a mobile project, and. One, big big topic is how to drive change management, individual, age in, how to make sure that a company. With traditions, with rules with. A background of people that are not only language is able. To move into. The digital age and. Maintaining. The, good detainment. They have. Collected. To the traditions, but also adequate, to the to the times, so. Again, these topics, we, want to touch and in, the next, couple. Of, weeks. We. Will send, out a more precise schedule and invitations, to all of you and. Of course if you have any ideas or inputs, to it just, please do write to us at chemicals go digital at exocomp - partners, calm. And. Now, back. To our. Transmission. In. Fact we wanted to have questions, we, got only one question this time. Address. On. The, topic of supply chain and is about the blockchain technology, is not water, has. Been a big debate around, bitcoins, so.
And The question is is. The blockchain, right. For utilization in the chemical, industry and in logistics. In. The answer is almost. But, not yet. We. Used to say that the, blockchain at the moment is right, for pilots, there are several pilots, around there. Are being now. In utilisation both, ologist, expires, and that chemical suppliers and of course in other, industries. But, there are more, big scale. Applications. That are right for market. That are right for for. Being used more. Than a bunch of suppliers. Customers and, maybe, one or two companies. There. Are several reasons for this one. Is overall, standards. One. Is. Security. Of the system then. One is simply, let's, say. Speed. Of change within relatively. Traditional companies. Nonetheless. We believe that in the next 2-3 years we will see a bottoming, of this of this of. The. Solutions, maybe, also. In in, in connection with a, platforms, ecommerce, platforms. But. One. Story short the. Current. Situation of mob chains is, an, eyelid level if, you want if you are not, iron here but let's say a fast, follower you better wait another six or nine, months right. I. Think we end our session, thank, you very much for all our audience that have followed us and wish. You all a great evening or a great day whatever, times. When you are so thank you okay, take care everybody just, all right.