Category: Internet of Things (IoT)

Digital Supply Chain and Digital Logistics – a chat with Till Dengel

The logistics aspect of supply chains is increasingly being digitised, and is now often referred to as Digital Logistics.

To find out more about this I invited Till Dengel to come on the show. Till is the Global Head of Digital Logistics Solution Management at SAP, so if anyone could fill me in on Digital Logistics, what it is, and where it is going it would be Till.

We had a great discussion and right at the end Till mentioned that his team had created a digital logistics compendium. This is a very comprehensive ebook with a lot of videos and interactive material for anyone interested in trends and customer stories in this field.

Below is a full transcript of our conversation:

TR: Hi everyone. Welcome to the digital supply chain podcast. My name is Tom Raftery and with me on the show today, I have our special guest Till. Till, would you like to introduce yourself?

TD: Yes. Good morning Tom. I’m very happy to be here. So Till Dengel is my name I globally cover our solution management for digital logistics, which includes our solutions for fulfillment, for warehousemanagement, for transportation, and the Logistics, Business Network.

TR: Okay, cool. Interesting. Just for anyone who isn’t completely aware with logistics, can you give us kind of a logistics 101. What, what is logistics? What does it do?

TD: Well, the logistics I think per definition is the know how goods move through a system and managing that system as goods flows through a supply chain and through different processes in a supply chain. And as we talk about the digitization of logistics processing, it’s basically how to automate and how to process things through warehousing, through a transportation, like scheduling, routing of logistics, or move in a supply chain and then eventually tracking those moves, with solutions for track and trace. But also with visibility tools to provide transparency as the goods move through the supply chain. So it’s really that end to end management and transparency that you’re trying to gain by using technology, as goods flow through a supply chain, or anetwork.

TR: Okay. And obviously the digitization of logistics has given huge advantages and is disrupting the markets;I imagine significantly for our customers. Can you give me some examples of the kinds of things that arechanging, and ways in which our customers are benefiting?

TD: Yeah, so for absolutely, I mean on one thing, technology has changed the game, but on the other side also the way we perceive logistics in our private life. And I think that has a very big impact also on the, on how companies deal with each other. I mean by now we are used to when we order something online that had arrives next day or sometime even same day, and there isn’t, are the same expectation of course, in a business to business environment. And in order to achieve that, you can only do this if you can automate your business processes to a very large extent. And these are the business processes that you have in the warehouse for picking, packing and shipping, but also the business processes around scheduling and routing a truck. So there has to be a lot of automation and that’s obviously, you know, what SAP, where we, where we come from of driving those business processes and trends.

But then there’s of course other technologies which are really changing the playing field in logistics. So one I think is very significant is around internet of things and sensor technology. Um, you can stick a sensor on almost anything today because the sensor technology is so cheap, um, that that you can just put it on some thing and you can track that item as it moves throughout the supply chain. Um, so that’s one big trend that’s changing the game here. Um, the other big one is the blockchain trend of course. It’s still a trend that I would say is I’m moving from its infancy, getting more and more mature. Almost every customer I talked to has at least a proof of concept in the blockchain environment. But that obviously speaks to the supply chain integrity and how goods move through supply chain, tracking on who touched the goods, where did they originate from and and what happens to the goods as they move throughout the supply chain. So that’s another technology that’s very big.

And then the last one I want to mention or the second to last is machine learning and data science. And obviously data science is not new to solutions like, transportation management with automated routing and scheduling. But with machine learning and the advent of machine learning and so many universities, working in this field, there’s just a lot more skills and a lot more knowledge around the topic and the market, which is really useful for the logistics industry, which has a lot of data from all these movements and can make use of that.

And then the last one I would like to mention is the cloud. And why is the cloud important? Well, because you have, different deployment models and you can much more quickly spin up and spin down for example, awarehouse. And we see those quite often with our customers. They are for example looking for that they run a campaign and they’re looking for a, they need a warehouse for six weeks, eight weeks as they ran a campaign in a city. So with the cloud you can spin up warehouse really quickly, run your warehouse processes to your pick pack ship and then spin it down again. So this was not possible many years ago and that’s, I think the big trends that are driving on the logistics industry.

TR: Okay. That’s interesting. That’s four huge trends that are happening and they’re obviously happening at kind of different paces as well. I mean you mentioned that uh, blockchain is very much in its infancy, whereas I imagine cloud is probably further along the line and machine learning is probably somewhere in the middle. How are we doing with, you know, the likes of a customer adoption? You mentioned some and blockchain are doing proofs of concepts, where are we with adoption rates in some of these technologies?

TD: Yeah, I would say the sense that technology and the IOT is probably most adopted just because there has been a lot of investment in those areas in the past few years. And it’s, I mean, building out interfaces and integrating these sensor technologies. Um, blockchain I mentioned, I think it’s, um, there are first few really good use cases. Um, customers are making the business case to invest broader and they are experimentingwith it, which I think is a really good sign that something is moving here. And obviously in blockchain what’s also interesting, it started with a few industries like for example, pharma, which obviously has that need for end to end visibility and enter and tracking of products and batches and everything. But it now moves across into other industries that is also a good sign. So, for example, we’ve talked to a lot of customers from the luxury goods industry, which of course also wants to know the whereabouts of these high value items as they move them through the supply chain and they want to know who touches with them. So thatsthe blockchain in terms of maturity.

Data science I think is a very mature in this industry. Like I said, machine learning is now coming to it, but working with algorithms and more sophisticated methods to determine scheduling  and routing and things like that, that’s been around for 10 years, maybe even more. So I think that’s probably the most mature I would say.

TR: Okay. And then, the adoption of these things depends on many factors. I mean, part of it is skilled resources availability, but part of it as well is potential for outcomes. If something is only going to give me a 1% increase or a 10% increase, does this big difference between the two. In in terms of outcomes, where do you see the the best potential for people with digital logistics?

TD: It’s an interesting point. You mentioned as obviously outcomes is always the end of every business case that, that our customers are driving when adopting those technologies. So when we talk about this data science part and a machine learning part, the outcome of that of course is increased efficiency and increased automation. And if you look at logistics, I mean logistics is reoccurring patterns. There’s only, you know, a certain amount of possibilities and variations that you can move a container through a network, let’s say from Asia to Rotterdam, for example, there’s only a certain amount of vessels, only a certain amount of routes you can take, and a main leg and, and some sequence they can pre leg and things like that. So there’s only a certain amount of variation. So why shouldn’t a system  automatically plan this and support the dispatcher sothe dispatcher doesn’t have to do this manually. So it’s clearly the outcome here is using these technologies like the data science part of it to automatically drive this and by that increase efficiency.

The other outcome of course in the same area is in the warehouse management space. I mean many warehouses these days run completely in the dark. Nobody, humans only touch in a very few touch points the product, but there’s a lot of automation already in the warehouse since many, many years. I mean, that of course speaks very much to the outcome and efficiencies and that’s where our customers make the case that they say, I want to come from a manual warehouse into more of an automated warehouse using software and using for example, packaging algorithms and algorithms that run, pick wave and things like that and thereby increase efficiency on automation. So that’s the efficiency side of the outcome.

What’s also very interesting and that’s a change that you’ve seen lately, is that if you look at more of the top line and the revenue portion of it and the customer centricity part of it, many customers we talk to these days look at logistics as a differentiator. In the past that was looked a lot like it’s a cost driver and we need to, you know, drive cost out of the system. Now it’s looked at more and more like if my logistics experience or if my delivery experience is not good, if my parts, my container arrived late, the experience reflects on the product. So the more I invest in product experience, customers tend to also invest in that delivery experience part of it, which is another outcome, but which is obviously not on the cost side and the bottom line, but rather more on the top line.

TR: All right. Very good. Very good. So lots to think on there. Where, where is all this going? You know, we’re seeing trends towards digitization, but you know, where is all this going to go in the next five to 10 years do you think?

TD: Well, there’s obviously a lot of movement in automation in terms of drone technology and self driving vehicles and things like that. I mean, all of that is obviously in the beginning, but I think in the next few years we see a lot of that becoming more and more mainstream. Obviously not everywhere in the world but incertain parts for example. We get already today, um, we connect to, for example robots and, and different parts in the warehouse so robotic technology in the warehouse is becoming mainstream as we speak. And I think this will expand into the yards and it’s been expand more and more onto the roads or maybe on, you know, some closed roads or from specific lanes where you see automatic driving and, and things like that. So, I think that’s one big trend that’s happening.

And then the other big thing is the rise of the networks, which we haven’t talked much about. So logisticsnetworks basically, meaning that you can manage a business process with your stakeholders, with your partners, or a shipper can manage that with the 3PLs and the carriers. They can all get together online in one single system in the cloud and manage a business process end to end. So that obviously contributes a lot to the business process execution capabilities and the efficiencies of that end to end processing, but also to the transparency that you can provide as if everybody that participates in that supply chain is on one single system. So I think here we will see a lot of that.

And if you look into where investment money is going these days on VC capital is going is exactly in that area of business networks across the different modes and across the different regions of the world.

TR: Interesting. Great. One final question Till. This is a question I often ask people at the end of the show, just in case I’ve missed something. Is there any question that I haven’t asked that you think I should have?

TD: Usually that is the question is, you know, around we talked a lot about automation and efficiency and those things. So usually there is always the question of what does that mean in terms of will there people be in the, I mean the logistics is a huge industry. Will the people be put out of jobs and things like that. And I think the interesting part around that is, I think, you know, the manual labor parts in the warehouse and transportation and things like that and I think they will definitely be challenged in my perspective because there is a robot, there’s more and more automation coming in, similar to what we’ve been seeing in the manufacturing industry a few years back. But on the other side there is a lot of skills and a lot of new employment opportunities around the topic of data science, machine learning, and digitizing these end to end supply chains,which is obviously a different kind of job. But here we definitely, and that’s what we hear from our industry councils and from customers we speak. There’s still a huge skill gap. And for example here in central Europe, it was identified that skilled people, in the logistics industry that know the process, that knowthe industry and that know technology, a huge gap and actually imposing a risk on the digitization of global supply chains.

TR: Interesting. Right, so if people want to know more Till, about Till or about digital logistics, our supply chains or any of the topics we’ve discussed today, where would you have them go? What, what kind of links would you like me to put in the show notes?

TD: So you’ll find myself on LinkedIn. I’d be very happy. There’s a lively community going on. Very happy to connect to anyone that wants to be connected and talk more about the logistics industry, which I’m very passionate about. That’s LinkedIn. Otherwise, sap.com of course there is a, a very large area around logistics and supply chain. And the last topic Tom I’ll provides you with a link to what we have created which is ourdigital logistics compendium, which is a very comprehensive ebook with a lot of videos and interactive material for anyone that’s interested in what’s going on in terms of trends and what are customers doing, obviously using our software in this field.

TR: Oh very good superb. That’ll be very useful, I’m sure for lots of people. I’ll definitely put a link to that in the show notes. Thanks a million for that.

Till that’s been great. That’s been really interesting. I’ve learned a lot. I hope all our listeners have as well. Thanks a million for coming on the show today.

TD: Thank you so much.

If you want to know more about any of SAP’s Digital Supply Chain solutions, head on over to www.sap.com/digitalsupplychain and if you liked this show, please don’t forget to rate and/or review it. It makes a big difference to help new people discover it. Thanks.

This podcast was initially published on the DigitalSupplyChainPodcast.com website

The advantages of Digital Supply Chains – a podcast with Johannes Drooghaag (aka @DRJDrooghaag)

I started a podcast series called The Digital Supply Chain podcast over on DigitalSupplyChainPodcast.com (because I have no imagination and that can’t hurt the search engine rankings!).

For the most recent episode I used Lately‘s transcription service to output the text of the podcast so I could add it into the post but Buzzsprout, my podcast host doesn’t allow posts with a lot of text, so I decided to post the podcast, and the full text of the conversation here. I hope you like it – do let me know in the comments how I could make it better.

This is episode 17 of the Digital Supply Chain podcast. In this episode I interviewed Dr Johannes Drooghaag (also known simply as JD, and @DRJDrooghaag on Twitter).

We had a wide-ranging conversation on Digital Supply Chains covering many aspects including Manufacturing, Industry 4.0, and cybersecurity.

Check out the podcast above, and the transcript below:

TR: Good morning, good afternoon or good evening, wherever you are in the world. This is the digital supply chain podcast and I am your host Tom Raftery.

TR: Hey everyone. Welcome to the digital supply chain podcast. My name is Tom Raftery with SAP and my special guest on the show today is JD. JD would you like to introduce yourself?

JD: Well, thank you Tom. First, first of all, thank you for having me on your, on your podcast. I’m really appreciate this opportunity. Um, my name is Johannes Drooghaag but it’s shortened to JD because that’s much easier and it doesn’t hurt so much to pronounce. Um, I started my career in industrial automation, the classical way, putting a lot of robots and a lot of sensors and a lot of PLCs in a factory. And through time I learned that there are other options and that we can do a lot more with the, with the data we are collecting and turn it into information or what I prefer actionable information. After some 25 years career in corporate roles, I decided to start my own consulting company and I’m focusing on those two fields on the, on the one hand and the organizational side, do human being that is working with the information. And on the other side, the technology that is creating the data out of which we can create that actionable information. I’m 30 years on the, on um, on the road now and I keep learning every day. And that’s one of the reasons why I’m with you today, Tom, to keep learning from you as well.

TR: Oh dear. No, no pressure on me. So no. Okay. So I, I typically start the show asking the guests on the show to give me their personal definition of what a digital supply chain is. Because you know, everyone has a kind of a slightly different approach to it. It’s a broad topic. So how do you define digital supply chain JD?

JD: Well, for me, the digital supply chain is basically the digital twin, so to speak, of the classical supply chain, which as we all know it with, with all the parts moving and the orders. And the digital supply chain is, is the digital twin in which we can do two things. We can constantly respond to what is happening because we need to respond much faster than we used to do in the past. In the past we had mass production, we had large batches, we had orders which were sent out months before we start producing. Nowadays we have to, we have much more dynamics. Orders are changed, we have smaller volumes, we have smaller production batches. We even want to avoid production batches. We want to create, um, single piece flows in our factories. And the second thing we can do is we can start simulating in our digital supply chain. We can do real what scenarios without actually having to touch the process. So we can start looking for opportunities and for optimization, uh, items. We can also look back to the past and see what failed, what didn’t do, what we were expecting that it would be doing and how can we prevent it and what can we learn from that. And that for me is the digital supply chain. The information that we on the one hand get from the existing supply chains, which are much more complicated than they were in the past. And on the other end, the learnings, the organizational handling of that digital supply chain.

TR: Excellent. Excellent. Very good. Very good. You, um, you started off saying that there were kind of two aspects to, uh, your, looking at digital supply chain. One was the human side and the other was the actionable items. Uh, you know, I’ve, I’ve often said that, in these kind of scenarios that the technology is generally very straightforward. It’s getting people to change because the hard part is, is that, is that your, inkling as well that, you know, technology is generally straightforward. People are hard?

JD: Well, we can make the technology as complicated as we want, but that doesn’t lead to anything, right? So if we put, if we start with a straightforward concept and then make sure that the people who we expect to work with it also actually understand what we are expecting from them, which, which kind of responses we want, then we see that there is a, um, an enormous gap because most people are already pretty much loaded with their actual work. Um, and, and we need them to first of all have the mindset then what that when the system is telling them something, they should take it serious. And now on the other hand, they need to understand what the difference is between some kind of general status update and an urgent item that they actually need to respond to. Now having three decades of experience, I have learned a couple of things. First of all, people do not really trust the system because there’s always something which is not right. If we take a closer look, that means we can learn and we can say, okay, we found something in the system, which is not correct. Let’s improve it. Yeah. But the human behavior is to use that as an excuse almost to also ignore all the other things that they see in the system. And the second thing that I’ve learned is when you’re busy going from A to B and somebody is telling you there’s a smarter way you could go through C and then to B, okay. You were focused on going to B, so you’re not paying attention to that additional information. And that’s an enormous challenge on top of the normal change management and organizational challenges we already have.

TR: Yeah,indeed. And how do you overcome that?

JD: Well, the first thing that I always do with my clients is start with the people and look at what their routines are and look at what kind of information they would need instead of the information that they have. Because what I see in my experience is that most service providers make the mistake of just sending more information to the already available information. And production manager or a scheduler or a planner doesn’t need a new report on top of all the reports they need to report or an information overview that tells them what to do and where they should respond to. So I start by filtering. I start by asking them, if you have 20 reports and I take 10 away, which one would that be? Yeah. And the interesting thing is that in most of the time when I ask for 10, they give me 18 because they’re going to use me.

TR: Yeah. There’s a professor of journalism New York whose name is Clay Shirky and he’s got this great quote that I love. He says, there’s no such thing as information overload. There’s only filter failure.

JD: Exactly. I love that.Yeah, yeah, yeah, yeah. No, that’s great. That’s great.

TR: You, you talked as well, uh, not just about the, the people aspect, but of the actionable items. What do you mean by that?

JD: Well, an actionable item. I always take the example of the, of the scada world where I’ve, I’ve spent five years, um, all over the world. If you look at the scada system, you will always have a state to screen where where the operator can see entire refinery or the entire pipeline or any other utilization of that scada. But as soon as the operator is expected to take action, that is automatically put in focus. So at the moment that the operator is expected to take action, the operator sees that action item and that can be a small decision. That can be a big decision, but the system automatically, um, focuses the attention of that operator on that particular item where an action is needed. Okay. Providers of SCADA systems have learned over over the years and they have learned that if you keep that action item in the entire status screen of the refinery, operator won’t notice it because it’s just one little thing in sometimes they have up to a thousand different aggregated devices in the overview and an actionable, actionable item. And an actionable, actionable piece of information means that first of all, the person who shoots take action is informed in the proper way without any kind of distractions. And secondly, the person has a couple of options or has supporting information to make that decision. Now, if I then compare it to what I see, especially in production facilities, that there’s an operator is overloaded with a lot of status written information, which that person should not respond to. And hidden in that stream is that one item where the person should respond to, well then I cannot blame him for not seeing it or ignoring it or pressing the standard button. So the, the popup goes away. Actionable information means to me, I see it when I need it. I get the information I need to take a decision or that actionable information informs me that something is not the way we wanted it to be and I need to do some, some optimizing or it means I need to get some additional resources.

TR: Right. A lot of that sounds like it’s, um, it’s design led issues potentially are maybe not maybe issues with the wrong word, but uh, properly designed screens and user interfaces should do away with a lot of these issues.

JD: Exactly. And then it’s also a system thing because if you look at a supply chain, then it’s not just a screen on a, on a machine. It is a whole stream of information. And if I have somewhere in my supply chain, the change, which was not part of the current, um, planned activities, I cannot wait until that arrives at my facility. I need to respond to that with the appropriate lead time. And if that means a change over in the production planning and that means that I need to schedule some additional machine change over, I need to know that in the proper appropriate time. So we also need to add some intelligence to it. We need to add, um, which timeframes we need. We need to add which kind of materials we need. And if we start figuring that out at the moment that it has already happened, well we are too late, especially when our supply chain is a bit more complicated then the local grocery shop.

TR: Okay. And so you, we have some customers with some very, very complex supply chains. So yeah, like tying all those disparate pieces of data together can prove challenging.

JD: Exactly. I always use this, this lovely example from my own automotive experience. If we look at at the classical, at a car, we have up to 40,000 components. If we look at an electrical vehicle, your favorite topic, we still have about 10,000 components for just one car. Yeah. Now if make one change, just one change, we might have to reschedule, um, a couple of, of those components in the assembly. Now the further we go down the line in that supply chain and we make that significant change, well the more others will have to respond to that. So supply chains are complicated and supply chains are no longer, um, single or dual parties. The same car with, with 40,000 components has up to 1,500 suppliers of those components. And that needs to be managed and it needs to be managed very actively.

TR: Yeah. Yeah. If I needed them or delayed and getting parts to you. Maybe there’s a Coronavirus outbreak and they can’t get their workers to their factories and they have to hold production. It throws everything out.

We are managing the past. With a digital supply chain we are capable of learning how to manage the future

JD: Exactly and if you do that in a in a smart way, and this is what I really enjoy about the digital supply chain because the Corona virus is an example. We have a crisis that might impact our supply chain. Now if we have a properly built and properly designed digital edition of our actual supply chain, that’s the moment where we are capable to say, okay, what happens if we, for example, slow down this line of supply and what does that mean for the other parts? Can we make changes in the capacity or can we increase some full human from another supplier and decrease some folio with this supplier and navigate around that crisis and that crisis never establishes the way we thought. So we can then the next day updated again and we can really start looking forward instead of what most people in the supply chain business always tell me. We are managing the past. With a digital supply chain we are capable of learning how to manage the future.

TR: It’s a, it’s an amazing change isn’t it? In in going from older, more analog technologies where as you write these, say people ran a lays in the past to the digital where we’re analytes in the future. It’s, it’s, it’s, um, I don’t know how to, how to phrase that exactly, but it, it’s, it’s, it’s a huge, huge change in the way people are now able to do business.

JD: It’s, it’s an amazing change and it’s, there’s the simple, in English, we have a wonderful, in German it’s, it’s, it’s almost as wonderful in English we can say, it makes the difference between reacting and acting in the classical analog supply chain management, UI reacting. You’re always reacting to things that have already happened in a digital supply tent. You can act based on the things that you know that will happen because that’s the information you receive. And that’s how you can build your scenarios.

TR: Yeah, that’s it. Exactly. Um, JD. Looking forward the next five, 10 years, where do you see the, the, the biggest, we’ll say potential for change. Um, where do you see the biggest changes that are going to happen? How will they impact?

JD: Well, the biggest changes that I will see, there’s one thing that we are not yet aware of the up to 80% of the production facilities we currently have are built in the previous century classical, uh, built for big batch batches built to, to produce a lot of the same. And companies are starting to learn that you can still use those industry 4.0 and the IOT and the smart supply chain solutions. You just have to be a bit more creative about how to implement them for those, those classical old things. So one of the things that I am already seeing and it’s developing, fortunately that companies are moving forward with their infrastructure, which is in some cases they still plan to use it for the next 20 years. So people stop. I’m believing that all those, all those, those technologies are only available when they build something new or Greenfield facility or to purchase a new machinery. We see that rolling out into the existing infrastructure and that I believe is a wonderful change.

TR: Yeah, yeah, yeah. We, we had an example, I mean, we have, you know, a bunch of examples with different customers, but there was one that, uh, really kind of blew my mind and it was with Harley Davidson. It used to take them 21 days to create a custom motorbike and when they shifted over to digital manufacturing, they brought the time of manufacture from 21 days down to six hours. Just incredible.

JD: That’s incredible. But, but that’s possible.Yeah. Yeah. it’s going back to what you were mentioning, uh, going from facilities which are built to just build lots of, one type of thing. And then when you try and do custom, in this case, motorbikes, it takes a lot more work and takes 21 days. When you switch to a facility which is built to be completely customizable and your lines could be completely fluid, uh, then you can do mass customization and then kind of lot sizes of one and you can drop the time to manufacturer again, in this case of bikes down to as six hours for a custom Harley.

TR: It’s, it’s, it’s really impressive.

…that’s also what industry 4.0 is about. And that is what, what a smart supply chain is about. It’s not just about more data and more technology, it’s especially about becoming more flexible so you can respond to what happens on the market

JD: That’s, that’s, that is really impressive. But it also demonstrates what is possible if you move away from the classical, from the classical patterns. In some cases, that will mean that you actually need to invest in your existing machinery in some cases will mean that you, uh, that you must must reduce some capacity for the mass production, which you don’t need any way, uh, anymore. And in some cases it means that you actually discover that your equipment is doing, is capable of doing much more than you thought it could. You just have to sit down and, and with, with concepts like design thinking, most of it is logical thinking. You need to be able to investigate, to explore, um, to do some, some testing and discover how flexible you can become. Because that’s also what industry 4.0 is about. And that is what, what a smart supply chain is about. It’s not just about more data and more technology, it’s especially about becoming more flexible so you can respond to what happens on the market. Right?

TR: Yeah, that’s true. That’s true. And in the case of Harley, it wasn’t that they did it in the same facility, so they kind of, I won’t say they cheated, but it took a kind of a hybrid approach. Uh, they built a second facility beside their existing facility and then they transferred all of their staff and all their machinery into the new facility. But it was two thirds the size of their existing facility. And yet, and yet, because it was completely digitized, they were able to then, as I say, bring the, the lot times down from days to hours.

JD: Yeah. But, but this is, this will happen in, in many cases and sometimes you have the luxury to say, okay, I’ve got a second production facility and I can basically redesign my existing process with a single piece flow concept in mind instead of batches and long production. In other cases you will have to do that. And we did it at one major automotive supplier, which unfortunately I cannot mention by name. We did it. We did the same thing we did in the existing facility. We started with machine number one and, and eliminated all the batch containers and, and uh, the batch flow, um, and created a single piece flow structure around that and then took it to the next level. And it was very fortunate that we have a very good tie in of the ERP system from, from SAP at that moment. So we could get all the production data, we could get, um, all the, all the settings, uh, the proper product identifications from the system. And we were capable of building a single piece flow throughout the production facility. It took two years because we had to do it step by step and we could not, um, go from, from, um, from the old school to the new school, uh, by just closing down the factory. But one of the results is, is that we decreased the capital on hand to time, which was around 18 days. Um, we’ve decreased that to two days. So from purchasing the material to shipping it to the next facility was reduced by, by more than 80%. That is serious money.

TR: That’s a lot, yeah. That’s impressive. That’s really impressive. Yeah. That’s amazing. Okay. Look JD. We’re coming towards the end of the podcast and uh, typically at this time of the podcast I’ll ask people, uh, is there any question that I haven’t asked you that you wish I had?

JD: Um, one question Tom, and that’s my favorite second topic. Cybersecurity. Um, so if you ask me, um, JD, what would be your top priority in digital supply chain? Besides all the technical opportunities we have and the organizational opportunities we have? I would say cybersecurity has to be the top priority because the more digitized we get, the more risk we have that something bad happens to the digitized world. So cybersecurity, big picture approach, make sure that it is by design and not by coincidence.

TR: Very good, very good. Very good. Yeah, no, hugely important. As we are, uh, opening up our manufacturing facilities and our logistics and everything as we’re opening them up to the internet, we are massively increasing the threat landscape. So yeah, absolutely. Very, very important to consider cybersecurity from, as you say, from the design phase, right through not, you can’t be something that you kind of cobble on afterwards dead right?

TR: So JD, if people want to know more about yourself, what’s the best place they can go to find information about JD?

JD: Well, they can visit me always on my LinkedIn profile or on my website under your JohannesDrooghaag. My website is JohannesDrooghaag.com. Unfortunately, jd.com was already taken, so I kind of,okay. Um, I am on Twitter. I am on, on Facebook, Instagram. Twitter is my main social media exposure. They can find me there under JohannesDrooghaag as well. Um, and otherwise, uh, drop me a note at my website and I will, uh, reply as soon as possible.

TR: Superp, super JD. I will put those links in the description of podcast when I publish it so everyone can have access to them. Thanks a million for taking time and joining me on the show today.

JD: Well, thank you for having me, Tom. It was a great discussion.

TR: Okay, we’ve come to the end to show thanks everyone for listening. If you’d like to know more about digital supply chains, head on over to sap.com/digitalsupplychain, or simply drop me an email to Tom dot raftery@sap.com.

And if you liked this show, please don’t forget to rate and/or review it. It makes a big difference to help new people discover it. Thanks.

This episode was originally published on the Digital Supply Chain podcast.

Seven reasons why the Internal Combustion Engine is a dead man walking

The age of the Internal Combustion Engine (ICE) is over. Electric cars are the future. The transition has just begun, but the move from ICE vehicles to Electric will happen sooner and more quickly than most people suspect.

What are the factors that lead me to say this with such confidence?

  1. China says so! China is now the world’s largest car market (of the 86m cars sold in 2017, 30% (25.8m) were sold in China, compared to 20% (17.2m) in the US, and 18% (15.6m) in the EU). Unsurprisingly, car manufacturers want to have access to this market. However, China has passed a law which requires any vehicle maker to obtain a new energy vehicle score of at least 10% by 2019, which rises to 12% by 2020, and on up to 20% of sales by 2025. As a result of this announcement, all the major OEM’s have suddenly found EV religion. A slew of announcements has followed about the 10’s of billions of dollars or Euros they are investing in their EV development programs and the partnerships or huge investments they are creating to secure their battery supply chain. The CEO of Porsche has even gone on record as saying that after 2030 all Porsche cars will be 100% electric. So, China has spoken, and the car manufacturers have listened. In the next 18 months, expect the number of electric vehicle models available to purchase, to increase significantly.
  2. The main cost of an electric vehicle is the cost of the battery. These price of these batteries is falling significantly. Lithium-Ion batteries cost $1,000 per kWh in 2010. By 2017 that cost had fallen to $200 per kWh, and it won’t stop there. At the Tesla shareholder meeting on June 5th of this year, Elon Musk stated that Tesla would be at $100 per kWh within 2 years. $100 per kWh is widely agreed to be the figure where EVs and ICE vehicles will have a comparable upfront purchase price.
    LithiumIonBatteryTrends
    So, by 2020 the cost of batteries will have fallen 90% in 10 years, and the price will continue to drop.
  3. Lithium-Ion batteries are increasing in energy density at a rate of 5-8% per annum. Mercedes has said that their EQC, which will come to market in 2019, will have an expected range of 500km. While the Tesla Roadster, which launches in 2020, has a stated range of 1,000km. When Electric Vehicles have a range of 1,000km, it is the ICE vehicles which start to have a range problem.
    Moreover, other battery technologies like solid-state batteries will come on stream giving us batteries that are cheaper, faster charging, and with even greater range still.
  4. Contrary to what many believe, the batteries in electric vehicles don’t degrade over time or over miles/kilometers driven either.
    TeslaBatteryDegradation
    This is a graph of the battery capacity of Tesla Model S/X vehicles, and it shows that after driving 270,000km (roughly 168,000 miles), the batteries still had 91% of their original capacity. There are more details in this article, but the bottom line is that the batteries lose about 1% of capacity every 30,000km (18,750 miles). This means that the upfront cost of an electric vehicle can be depreciated over a far longer time – EVs will just keep on working. Having said that, this data is specific to Tesla batteries which may be down to the good thermal management system Tesla has for its battery packs.
  5. Another factor in favour of electric vehicles is that they are far more reliable. The drivetrain in an ICE vehicle contains 2,000+ moving parts typically, whereas the drivetrain in an EV contains around 20. A quick scan of the top 10 cars repairs of 2015 is telling. Not one of these faults can happen to an electric vehicle.
    CarRepairs
  6. Electric vehicles are typically significantly cheaper to fuel as well (unless you happen to live somewhere that has particularly cheap petrol and extremely expensive electricity). And with the price of oil going up 50% in the last 12 months, finding somewhere with cheap petrol will become increasingly difficult.
    12MonthCrudeOilPrice
  7. Lastly, as outlined above, the number of models of electric vehicles available for sale is about to increase enormously; the purchase price of electric vehicles is falling significantly; the range of electric vehicles about to match or even surpass ICE vehicles; EVs have essentially zero maintenance issues apart from the need to replace brakes and tyres; the batteries in EVs last hundreds of thousands of miles/kilometers with absolutely minimal degradation; and EVs are cheaper to fuel, so why would anyone consider buying a car with an Internal Combustion Engine? Most people won’t.
    And consequently, the resale value of ICE vehicles will collapse. And if the resale value of ICE automobiles is going to collapse in 3-4 years, why would you buy one today? Think about that for a second. Why would you buy an ICE vehicle today, if its resale value in 3-4 years will have collapsed? You wouldn’t. And when people start to realise that, the market will flip. And it will happen quickly. Sooner than most people think. Will your next car be an EV?

And if none of that convinces you, maybe check out the rest of the specs for the Tesla Roadster – 0-100kmh (0-60mph) in 1.9 seconds, top speed of 400kmh (250mph), and range of 1,000km (620 miles). Or maybe watch a Tesla Model S race a Boeing 737, or even more incredibly, watch a Tesla Model X set a Guinness world record by towing a Boeing 787 Dreamliner  

And I haven’t even mentioned the growing list of cities that are passing legislation to ban diesel engined vehicles from entering!

UPDATE: I loved this response to this post on Twitter:

https://twitter.com/Banshee2030/status/1012147186639908864

Update 2 – post updated with 2017 car sales figures Jun 29 at 10:22 CET

8 predictions for the Internet of Things (#IoT) in 2018

As 2017 comes to a close, it is customary to look forward to the year ahead and think about what will come. Some of us in SAP put our heads together to come up with a list of likely trends in the Internet of Things space for the next 12 months.

In no particular order:

  1. The IoT hype is over – but the trough of disillusionment typically precedes mainstream adoption. Customers have by now generally accepted IoT as a main driver of digital transformation, however, in 2018, they will be looking for business value and outcomes in every project. There is no doubt that all newly released products and installed assets will be connected with an increasing amount of sensors and intelligence embedded
    IoTvsCloudTrendshttps://trends.google.com/trends/explore?date=all&q=%2Fm%2F02vnd10,cloud%20computing&hl=en-US
  1. The IoT cloud platform market will consolidate quickly
    Microsoft Azure and Amazon AWS will probably take the largest shares. IBM Cloud, Google Cloud Platform, SAP Cloud Platform, and Oracle Cloud will be runners up. Most other IoT vendors will move (or have ported) their IoT offering onto a leading cloud platform-as-a-service stack (e.g. GE, Siemens)Here’s Why GE Shelved Plans to Build its Own Amazon-Like Cloud: http://fortune.com/2017/09/06/general-electric-cloud-pivot/
    Mindsphere debuts on Amazon Web Services http://news.usa.siemens.biz/blog/digital-factory/mindsphere-debuts-amazon-web-services
  1. IoT vendors will refocus and lead with IoT solutions delivering value to their installed base. GE Predix is now focussing on selected verticals and asset-intensive industries; while Microsoft is looking to manufacturing (with new focus on OPC-UA)GE https://www.ge.com/investor-relations/sites/default/files/GE%20Investor%20Update_Presentation_11132017.pdf (page 18)
    Microsoft IoT Central broadens reach with simplicity of SaaS for enterprise-grade IoT https://blogs.microsoft.com/iot/2017/12/05/microsoft-iot-central-broadens-reach-simplicity-saas-enterprise-grade-iot/
  1. IoT architecture will evolve from data ingestion and analytics to an intelligent event-driven solution for end users
    Data science, machine learning, and physics-based models will extract meaningful events from IoT data for users to take prescriptive actionGartner https://www.gartner.com/newsroom/id/3758164
    Blog referencing Gartner https://realtimeapi.io/2020-50-percent-managed-apis-projected-event-driven/
  1. The edge will move from connectivity to distributed intelligence
    Edge solutions are becoming increasingly intelligent and autonomous, adding analytics and machine learning, while distributed edge-cloud programming paradigms emergeGartner https://www.gartner.com/smarterwithgartner/what-edge-computing-means-for-infrastructure-and-operations-leaders/
    Amazon Greengrass https://www.forbes.com/sites/janakirammsv/2017/06/07/amazon-makes-foray-into-edge-computing-with-aws-greengrass/#47b0bc0b3298
    Microsoft IoT Edge https://azure.microsoft.com/en-us/blog/azure-iot-edge-open-for-developers-to-build-for-the-intelligent-edge/
  1. Digital twins will evolve from concepts to blueprint and implementation for data sharing within and across companies
    While many early IoT projects focus on efficiency and cost reduction, the long term business value of IoT is in the network of business partners and digital twins. Marketplaces start to emerge to monetise IoT data while blockchain technologies ensure data provenance and device traceability (and payment)Digital Twins https://www.i-scoop.eu/digital-twin-technology-benefits-usage-predictions/
    IDC Predictions https://www.idc.com/url.do?url=/getfile.dyn?containerId=US43193617&attachmentId=47282916&elementId=54584641&term=&position=4&page=1&perPage=25&id=89172f0a-fdd7-48a1-871b-3bb213638507
    IOTA Data Marketplace https://blog.iota.org/iota-data-marketplace-cb6be463ac7f
    IBM IoT on Blockchain https://www.ibm.com/us-en/marketplace/iot-blockchain/details
    SAP IoT Blockchain initiative https://news.sap.com/sap-announces-first-co-innovation-customers-partners-in-blockchain-initiative-for-internet-of-things/
  1. Integration will remain challenging despite advances in open standards and architecturesIndustry standards will slowly emerge to address semantic integration (e.g. OPC-UA, RAMI), but take long to get fully adoptedhttp://opcconnect.opcfoundation.org/2017/06/there-is-no-industrie-4-0-without-opc-ua/
    IIC and RAMI / Industrie 4.0 align https://www.automationworld.com/industrial-internet-consortium-and-plattform-industrie-40-align-architectures
    Edge  http://www.iiconsortium.org/press-room/08-02-17.htm , https://globenewswire.com/news-release/2017/09/25/1131891/0/en/ETSI-and-OpenFog-Consortium-collaborate-on-fog-and-edge-applications.html
  1. Security and privacy will remain key concerns IoT security
    The standalone IoT security market is dead, but IoT security will be embedded into hardware, network, and systems with IoT security becoming a dedicated threat domain; data privacy legislation and concerns (specifically in Europe and China) will impact IoT architectureIoT security outlook Blogs http://www.ioti.com/security/8-iot-security-trends-look-out-2018 & https://www.i-scoop.eu/internet-of-things-guide/iot-security-forecasts/

Hopefully these predictions will give you some food for thought over the holiday season. In any case, enjoy your time off, and see you in 2018 🙂

 

Photo credit Frank Monnerjahn

Predictive Maintenance for People – the endgame for the Internet of Things (#IoT) and healthcare

Predictive maintenance is one of the oldest and most tested uses cases for the Internet of Things (IoT).  For years now, we’ve been able to analyze incoming data from sensors embedded in machines and make decisions about whether or not maintenance activities should be executed.

Typical scenarios have historically focused on things like wind farms, oil rigs, and fleets of trains. And while there’s plenty of excitement and new developments in these areas, what’s grabbing a lot of attention today is how predictive maintenance can be applied to new scenarios.

For example, in an earlier blog, I talked about predictive maintenance for autonomous vehicles – how sensors can send out data on the status of parts and components, allowing manufacturers to analyse this data to predict part failure and, thus, avoid breakdowns.

Yet, even this scenario keeps us in the realm of machines – because, sophisticated as it may be, an autonomous vehicle is still a machine. But what if we could now take the same general idea of predictive maintenance for machines and apply it to our bodies? Call it preventative maintenance for people – or just predictive healthcare. The reality is that in many ways, we’re already there.

Understanding in context

One of the advantages to predictive maintenance for machines is that incoming data about what’s going on in the moment can be analyzed in the context of historical data about the same machine. Let’s say an HVAC machine on the top of a hotel in Seville – where I live – sends out a high-temperature alert.

In and of itself, yes, this may be cause for concern. But when you realize that the machine sends out the same alert every month at the same time – well, maybe it’s not so concerning. Maybe the HVAC unit runs continuously for 8 hours on the first Monday of every month to help cool a large conference room on the used for the packed monthly meeting of the Seville Dog Walker’s Association.

Or maybe there’s another reason. The point is that in such a scenario, the high temperature alert is understandable and predictable in context – and thus of little concern. It would be nice if we had something similar for healthcare.

More than a snapshot

Here’s the problem: On a typical trip to the doctor you wait in the waiting room for 10-15 minutes, with other people, some of whom are likely sick. When you finally see the doctor, you’re thinking of the next appointment you have across town in 30 minutes so your anxiety levels go up.

My sister Mary was recently diagnosed with high blood pressure because when she was in the doctor’s clinic her blood pressure measured 150/89. The doctor advised her to get a connected blood pressure cuff, and to take regular measurements. When she did, it turned out her blood pressure was 108/75 – completely normal. She was suffering from what doctors call White Coat Syndrome.

IMG_4359

But as with the HVAC machine, the high blood pressure reading was understandable in the context of her being in a doctor’s office. Wouldn’t it be great if the doctor evaluating your blood pressure had more than a snapshot of (often misleading) data to work from? Wouldn’t a whole bunch of relevant historical data be better?

With the smartwatch on my wrist, I can now share 3 years of data with my doctor. Now s/he can see things in context and treat me more effectively. I think it’s only a matter time before their office can take my sensor data in automatically – over the cloud. This will make my yearly check-up more productive. Instead of figuring out what the problem is (if there is one, hopefully not) we’ll be able to focus on what to do about it.

A business network for health  

As with so many things IoT, this is only the beginning. But let’s step back for a moment.

One of our offerings here at SAP is the SAP Asset Intelligence Network (SAP AIN). Think of it as a business network application. With SAP AIN, all of the data (metadata, specifications, bills of materials, whatever) that goes into the creation of a device (a compressor, coffee machine, car, whatever) can be stored in a central location.

When connected to the asset intelligence network, the device can push out real-time data that describes its state at any given moment. When the device owner allows access to this data, the manufacturer can then analyse it in conjunction with other data from other devices – making product improvements that can then be pushed out by way of the same asset intelligence network.

In fact, nothing is stopping device owners from sharing their data with whoever they wish – like maybe a service vendor, or insurance company. If a device goes out of tolerance for some reason, the service vendor could receive a notification and schedule an appointment to service the device automatically. Or in the case of an insurance company – they could then set rates according to actual device usage data.

Returning to the theme of health – what if we took this idea of an asset intelligence network and applied it to our own bodies? What if we had a “people’s intelligence network” – where a device like my smartwatch publishes my health data into a trusted cloud application?  When my device senses high blood sugar, for example, this data gets analyzed not only in the context of the unique moment mixed with my own personal health history – but also in the context of similar data from potentially millions of people.

Based on this much larger dataset, the network could then contact my service vendor – in this case, my doctor – and make an appointment if necessary. Yes, this would be convenient. But more importantly, it would move us away from making medical decisions based on poor data and the intuition of physicians, toward something often heralded but seldom achieved – real evidence based medicine.

Photo credit Chelsea Stirlen

Artificial Intelligence and the Future of Jobs

My role here at SAP is IoT Evangelist. It’s my job to go around and speak about how the Internet of Things is changing the way we live, work, and run our businesses. IoT Evangelist is a job title that didn’t exist 5 or 10 years ago – mainly because the Internet of Things wasn’t a “thing” 5 or 10 years ago. Today it is, so here I am.

The fact is, technological change has a tremendous impact on the way we spend our working lives. Many of today’s jobs didn’t exist in the past. Of course, the reverse is true as well: a lot of jobs – mostly tedious/manual labor of some variety, think miners, lift operators, or similar – have gone away.

Robots and much more

Much of the discussion today about the relationship between technology and jobs is a discussion about the impact of artificial intelligence (AI). Robots in manufacturing is the most obvious example. A lot of AI has to do with big data analysis and identifying patterns. Thus, AI is used in data security, financial trading, fraud detection, and those recommendations you get from Google, Netflix and Amazon.

Screen Shot 2017-11-28 at 14.01.55

But it’s also used in healthcare for everything from identifying better subjects for clinical trials to speeding drug discovery to creating personalized treatment plans. It’s used in autonomous vehicles as well – to adjust, say, to new local conditions on the road. Some say it’s also coming for professional jobs. Think about successfully appealing parking fines (currently home turf for lawyers), automated contract creation, or automated natural language processing (which someday could be used to write this blog itself – gulp!).

The spinning jenny

Will AI continue to take jobs away? Probably. But how many new jobs will it create? Think back to the spinning jenny – the multi-spindle spinning frame that, back in the mid-18th century, started to reduce the amount of work required to make cloth.

By the early 19th century, a movement known as the Luddites emerged where groups of weavers would go around smashing these machines as a form of protest against what we’d now call job displacement. But these machines helped launch the industrial revolution.

As a result of the spinning jenny’s increased efficiency, more people could buy more cloth – of higher quality, at a fraction of the cost. This led to a massive uptick in demand for yarn – which required the creation of distribution networks, and ultimately the need for shipping, an industry that took off in the industrial revolution.

As the spinning jenny came into use, it was continuously improved – eventually enabling a single operator to manage up to 50 spindles of yarn at a time. Other machines appeared on the scene as well. This greater productivity, and the evolution of distribution networks also meant there was a need for increasingly comprehensive supply chains to feed this productivity boom.

Muscle vs caring

Economists at Deloitte looked at this issue of technological job displacement – diving into UK census data for a 140-year period stretching from 1871 to 2011. What they found, not surprisingly perhaps, is that over the years technology has steadily taken over many of the jobs that require human muscle power.

Agriculture has felt the impact most acutely. With the introduction of seed drills, reapers, harvesters and tractors, the number of people employed as agricultural laborers has declined by 95% since 1871.

But agriculture is not alone. The jobs of washer women and laundry workers, for example, have gone away as well. Since 1901, the number of people in England and Wales employed for washing clothes has decreased 83% even though the population has increased by 73%.

Many of today’s jobs, on the other hand, have moved to what are known as the caring professions, as the chart below shows. The light blue bars represent muscle-powered jobs such as cleaners, domestics, miners, and laborers of all sorts; the dark blue, caring professions such as nurses, teachers, and social workers. As you can see, these have flipped.

Screen Shot 2017-11-28 at 13.53.19

The Deloitte study also points out that as wealth has increased over the years, so have jobs in the professional services sector. According to the census records analyzed, in England and Wales accountants have increased from 9,832 in 1871 to 215,678 in 2015. That’s a 2,094% increase.

And because people have more money in general, they eat out more often – leading to a fourfold increase in pub staff. They can also afford to care more about how they look. This has led to an increase in the ratio of hairdressers/barbers to citizens of 1:1,793 in 1871 to 1:287 today. Similar trends can be seen in other industries such as leisure, entertainment, and sports.

Where are we headed now?

Will broader application of AI and other technologies continue the trend of generating new jobs in unexpected ways? Most assuredly. Already we’re seeing an increased need for jobs such as AI ethicists – another role that didn’t exist 5-10 years ago.

The fact of the matter is that technology in general, and AI in particular will contribute enormously to a hugely changing labour landscape. I mentioned at the start of this post that my role in SAP is IoT Evangelist – this is a role I fully expect to no longer exist in 5 years time, because by then everything will be connected, and so the term Internet of Things will be redundant, in the same way terms like “Internet connected phone”, or “interactive website” are redundant today.

The rise of new technologies will create new jobs, not just for people working directly with the new technologies, but also there will be an increasing requirement for training, re-training, and educational content development to bring people up-to-speed.

Will there be enough of those jobs to go around – and will they pay enough to support a middle-class existence for those who hold them? That’s another question – but it’s one that’s stimulating a lot of creative, innovative ideas of its own as people think seriously about where technology is taking us.

 

Photo credit Jessie Hodge

Here come the Jetsons: Flying cars and the Internet of Things (IoT)

Part 3 of 3 on the Future of Transportation and the Internet of Things

If you ever watched the cartoon series The Jetsons – or almost any other show set in the space age – you’ll notice that people often get around in personal spacecraft that they themselves drive. Well, the space age is almost here – at least in the form of flying cars. But we won’t be driving them. Instead, like cars they will be controlled autonomously.

In my last blog, I talked about autonomous vehicles and how much safer they are than self-driven vehicles. To ensure safety in the air, flying cars depend on the same network-connected IoT technology pioneered first in autonomous vehicles on the road.

Is the space age really here?  

Let’s first take a quick look at some of the leading organisations out there doing serious work with flying cars.

  • Lilium: A German start-up, Lilium tested a full-sized prototype of its flying car in April 2017. The Lilium prototype is entirely electric. It can also take off and land vertically like a helicopter – but then change to forward flight for speeds of up to 300km/h, which is much faster than a helicopter. And it’s quieter than a motorcycle. Lilium has raised $100m in two rounds of funding from Tencent, Ev William’s Obvious Ventures, Niklas Zennstrom’s Atomico amongst others.
  • EHang: A Chinese company with deep experience building drones, EHang is perhaps the furthest along. The company produces the EHang 184 – a one-passenger flying car that has already undergone 100 successful manned test flights. Reportedly, the city of Dubai is this year launching a pilot program for an autonomous aerial taxi (AAT) service using the EHang 184.
  • Airbus: The aircraft giant, Airbus, has developed CityAirbus, an electric vehicle capable of vertical take-off and landing for up to four passengers. Airbus Vahana aims in the same direction but for is for individual travelers. And let’s not forget the hybrid Airbus Pop.Up concept, this modular air and ground system involves a passenger capsule that can be connected to a propeller system on top for flying or to a wheeled conveyance system for driving on the roads.
  • And Uber – who recently signed an agreement teaming up with NASA around NASA’s Uncrewed Traffic Management (UTM) project developing air traffic control systems for uncrewed aerial systems (flying cars/drones).
  • Even Boeing is making investments in this space.

This is starting to look real.

No network, no flying cars

What all of these ventures have in common is connectedness. Using IoT technology, they’re all controlled remotely – with the vehicle in constant connection to home base along the lines of what is now a reality for autonomous road vehicles like those made by Tesla.

Of course, the networked nature of vehicles (flying or not) has relevance beyond safety. No surprise, then, that Uber is moving forward aggressively with plans to test an on-demand flying cars network by 2020 in the cities of LA, Dubai, and Dallas, and 2023 in Sydney. Here the network provides convenience – coordinating a ride-sharing service in the sky that allows passengers to hook up with flying cars on the fly.

Drones for passengers

Essentially, what we’re moving toward is a future of passenger drones. One obstacle to this reality is the need for keeping batteries charged. Because of battery life issues, for example, the EHang 184 can only travel 23 minutes. The Lilium vehicle, it is claimed, can travel up to an hour – enough to make it from London to Paris. This, and advances in battery power storage capacity will iron out most issues around range.

When we solve this problem – and get over some regulatory hurdles – flying cars will become a lived reality for people in cities everywhere. The benefits will be tremendous, too. Count among these benefits such as less pollution (both air and noise pollution) and less traffic congestion (with flying cars taking another route entirely). And when it comes to emergencies, first responders can be deployed faster and more efficiently than ever before – helping to save lives. And let’s face it, flying cars would just be fun.

Next time I get to Dubai I’ll have to try one out.

Photo credit Airbus

Connected Cars, Autonomous Vehicles, and the Internet of Things (IoT)

Part 2 of 3 on the Future of Transportation and the Internet of Things

In my last blog, I talked about the simplicity of the electric engine compared to the internal combustion engine – and how this changes everything. From climate to the structure of the auto industry to the way we store, manage, and distribute energy – electric cars are having tremendous impact.

But what I left out of that discussion was the Internet of Things.

Predictive

The fact is, most electric cars are connected cars – connected through the Internet of Things. This means that sensors in the car constantly communicate with mission control (the manufacturer), sending data on the status of components in real time.

By analysing this data, especially in context of historical data, mission control can predict component failure before it happens. For electric vehicles – with engines that already need far less repair than traditional internal combustion engines – this only increases reliability further.

But what’s more, IoT-connected cars also increase convenience. For example, after realising component failure is imminent, your car could also trigger a work order at the dealership to resolve the issue – while ensuring the needed replacement part is in stock when you roll in. And if the car is autonomous, it could drive itself to be repaired while you are at work, and return ready to drive you home once the repair is completed. Speaking of autonomous…. 

Autonomous and safe

Connectedness is also what makes autonomous vehicles possible. And while some people may distrust driverless cars; the data shows that they’re safer than the self-driven sort – at least according to a report of the U.S. National Highway Traffic Safety Administration (NHTSA).

Back in May 2016, a Tesla Model S sedan in Autopilot collided with a semi-truck in Florida, killing the driver (or passenger in this case?) – 40-year-old Joshua Brown. The car, apparently, crashed into the truck, passed under the trailer, and kept driving for some distance – only coming to a stop after crashing through two fences and into a pole.

As a result of this incident, the NHTSA conducted an investigation resulting in a report that largely exonerated Tesla. In fact, the report says that after the introduction of Autosteer – a component of the Autopilot system – Tesla’s crash rate dropped by 40%.

Self-learning

The accident in question happened when the semi-truck took a left-hand turn into oncoming traffic. The reason the Tesla did not detect such a large object in its path is because it could not distinguish the white color of the trailer from the bright white Florida sky in background.

Reportedly, Tesla has since analyzed the crash data from this accident, identified the problem, and made fixes to the operating system on which its fleet operates. Perhaps it’s premature to declare the problem solved – but the idea at play here is an interesting one indeed when considering the potential for connected cars and the IoT.

What this scenario shows is a learning platform in action. Because all of its cars are connected on a single platform, Tesla has access to a tremendous amount of driver data that it can analyze to continuously improve product safety. I don’t know exactly how the analysis proceeded in this particular case, but one can certainly envision the use of machine learning technology to continuously analyze patterns and introduce safety improvements on the fly – making the self-learning driving platform a reality.

Disruptive

A future in which autonomous vehicles are not only viable but safer than self-driven cars will result in disruptions beyond those I’ve indicated for electric engines.

Take the insurance industry, for example. With fewer accidents comes lower risk – leading to lower insurance premiums. And in a future where most cars on the road are autonomous – connected and controlled via IoT – the insurable entity itself will likely shift from the driver (who is now a passenger) to the operator of the network (presumably the manufacturer). Certainly, if you decide you wish to drive your car yourself, your insurance will be significantly more expensive than the insurance for an autonomous vehicle.

Of course, if autonomous cars can get where they’re going without a driver, why even bother owning a car? Why not just call up the ride when you need it – Uber style?

One result would be optimal asset utilization – where cars that are far less likely to breakdown can be used on an almost 24×7 basis by spreading usage across individuals. This would mean we’d need far less cars on the road – which would alleviate congestion. It would also hit the auto industry with dramatically lower sales volume.

And with fewer cars on the road – cars that are in use almost all the time – we’d have less use for parking. This would have tremendous impact on the global parking industry. An industry which generates approximately $20 billion annually.

Beyond industry disruption, less need for parking would open up tremendous urban space in the form of unused lots and garages. Maybe this would mean more populous cities with room to build for more people to live more comfortably without traffic congestion or pollution. Or how about using some of the space for indoor vertical farming using hydroponics technology and LED lights to grow more food and feed more people? Of course, this is already happening. But that’s a blog for another time.

 

Photo credit Nicole Galpern

3 Ways Electric Cars Are Changing More Than the Way We Drive

Part 1 of 3 on the Future of Transportation and the Internet of Things

The world is moving away from cars based on the internal combustion engine (ICEs). The future is electric. With Tesla leading the way on what’s possible with electric vehicles, more traditional auto manufacturers are following suit.

Volvo has announced that all of its cars will have electric motors by 2019. Aston Martin is planning the same by 2025. General Motors plans to have at least 20 electric vehicles (EVs) by 2023. The list goes on.

Much of the pressure is coming from countries banning ICE sales in the not-too-distant future (The Netherlands by 2025; China, India and Germany by 2030; France and the UK by 2040). Industry and consumers, however, want electric as well.

When everybody wants something, it tends to happen. The question is, what will be the ramifications? One safe bet is that the market for your ICE -based car will be drying up quickly – so think about selling now. But beyond concerns for personal finance, we can also expect EVs to have a dramatic impact in a number of areas including climate conditions in cities, the automotive industry in general, and energy distribution worldwide.

Lower emissions

The obvious benefit of electric cars – the reason countries, industries, and individuals everywhere are pushing for them – is lower emissions. One of the cities most concerned about emissions is Beijing. Back in 2015, the notoriously thick smog of the city disappeared quickly when authorities banned driving  for two weeks in preparation for a World War II commemoration parade. The day after driving resumed, the smog returned.

Today, Beijing is planning to replace the city’s nearly 70,000 taxis with EVs. Doubtless, this is a step in the right direction. Yet, while Beijing tends to get the lion’s share of press coverage when it comes to smog, other cities face similar challenges. From Paris to Mexico City and all around the world, lower emissions from electric vehicles will help to improve health for citizens locally and fight climate change globally.

Industry change

The automotive industry is not just General Motors, Volkswagen, Toyota and the rest. It’s also made up of countless suppliers of parts and components. But when you move from a traditional ICE to the electric engine, you lose about 90% of the parts. Electric engines are just simpler.

This means that for companies in the automotive supplier ecosystem, much of the market is going away soon. The simplicity of electric engines will also be felt further down the value chain. Service centers, for example, will feel the hit.  Many of these centers – particularly the large chains – use the inexpensive 3,000-mile oil change as a loss-leader to upsell customers on needed maintenance. But without oil in the electric engine – and without as much need for maintenance – many of these chains will have to rethink their business models to survive.

New energy horizons

One of the most significant impacts of EVs will be on the way energy is distributed – because in addition to being modes of transportation, EVs will also act as energy sources that can plug directly into the grid.

This will help address the challenge of “demand response.” The problem to solve here is one of grid stability in the era of renewable energy. Traditionally, large centrally located energy generation plants –  coal, gas, and nuclear – have churned out a steady supply of energy that results in a fairly stable grid.

However, the renewable energy paradigm – based mostly on solar and wind – is neither centralized nor steady. Rather it is distributed across rooftops, solar farms, and mountain tops. And it is variable according to weather conditions.

With renewables, in other words, utilities have less control over the supply side of the equation – meaning how and when energy is generated. This has the potential to lead to instability on the electricity grid. If you can’t manage the supply, then you have to use demand side management, also known as demand response. This can be done using through incentives, and the technology is advancing such that increasingly the process is becoming automated.

By providing a storage mechanism that can both take energy in and send it out, car batteries on EVs can act as frequency regulators for the grid. This is a big deal that has the potential to change energy distribution forever.

At night, say, when the wind is blowing, a car battery can store energy generated by wind turbines. Or, in the middle of the afternoon when everybody wants air conditioning on a hot day, the same batteries can distribute some of their energy. This leads to improved grid stability.

Industry convergence

Let’s just note, however, that the entities with the closest relationships to the owners of the batteries so critical to grid stability would not be the utilities but EV manufacturers. What’s stopping Elon Musk from enticing Tesla customers from sharing their batteries? Tesla could enable its customers provide energy from their batteries – and then sell it on the grid for a profit. Customers make money. Tesla makes money. Utility companies make money. Everybody is happy.

This transforms the automobile industry into an energy industry. At SAP we talk a lot about digital transformation as a response to digital disruption. This is disruption at its most dramatic.

Elon Musk has stated aims to make 500,000 Tesla’s in 2018. Let’s say he falls disastrously short and only hits half his target. Let’s also assume an average 80 kilowatt hour (kWh) battery size in the EVs – (Tesla cars today have battery sizes ranging from 60 -110 kWh). 250,000 cars x 80 kWh – and you’ll see that this fleet would have the capacity of 20 gigawatt hours of storage. For comparison, a gigawatt is roughly the output of a nuclear power plant. So, Tesla will be producing the equivalent of 20 nuclear power plants worth of storage, at least, per year.

Electric vehicle manufacturers will be able to aggregate the energy on their networks, and sell access to their “virtual power plants”. It is a whole new world.

Stay tuned for more on how the transportation industry is changing forever.

 

Photo credit Tesla

Dear Internet of Things startups,…

Dear Internet of Things startups,

As you may already know, SAP is one of the world’s largest software companies. We produce the software that most companies use to produce their goods. But what you may not know is that we don’t stop there.

On the contrary, SAP also has

On top of all that, according to our 2016 Interactive Annual Report SAP is now employing over 84,100 people globally, who create software for over 345,000 customer organisations spread across 180 countries. In fact, it has reached the point where 76% of business transactions globally now touch an SAP system.

And SAP is deeply committed to the Internet of Things. SAP pledged last September to investing €2bn (US$2.2bn) in the Internet of Things during the next four years, while also announcing the acquisition of two significant IoT companies Fedem and Plat.One.

And SAP’s desire to lead in the IoT space comes from the very top of the organisation as you can see in this tweet from our CEO Bill McDermott:

Cool, right?

Even better, you and your startup can be part of the SAP ecosystem, gaining access to those 345,000 enterprise customers, and their deep, deep pockets. How?

Become involved in SAP’s IoT Accelerator program.

What’s that?

The SAP IoT Startup Accelerator is a globally accessible co-innovation program for B2B startups, innovating in the world of IoT. The Accelerator helps startups grow and scale their business alongside SAP, our vast partner ecosystem and global customer base. We work with Accelerators, Incubators, Venture Firms, Academia and innovative technology providers to expand the IoT solutions ecosystem for our customers.

The SAP IoT Startup Accelerator seeks to find and enable the most promising IoT Startups to bring their solutions to market with SAP, and better yet because of that, SAP is not looking for fees or equity, we are looking for solutions that promote our shared customers success.

Curious to know more? Check out the SAP IoT Accelerator page on F6S.