David Stephenson: [00:00:03] I think it illustrates a profound aspect of the IIoT, which is that when you open up the data to multiple users and multiple multiple perspectives and multiple individuals get insights that even the most brilliant data scientist working in isolation just isn't going to come up with. [00:00:03][0.0]

Tom Raftery: [00:00:31] Good morning. Good afternoon or good evening wherever you are in the world. This is the Digital Supply-Chain podcast. The number one podcast focussing on the digitisation of supply chain. And I'm your host, global vice president of SAP, Tom Raftery. Hi, everyone. Welcome to the Digital Supply-Chain podcast. My name is Tom Raftery with SAP and with me on the show today, I have David. David, would you like to introduce yourself? [00:00:55][24.5]

David Stephenson: [00:00:56] Sure. I'm David Stevenson. And I head Stephensen Strategies in Massachusetts. And I have been an IoT consultant for about eight years at this point. And I got into the field based on work that I had done for the District of Columbia, opening up all sorts of Real-Time databases and then inviting the public to come in and write apps based on that. And so I was very much involved in the beginnings of the whole open data movement. And I see that as a real commonality here, that one of the critical things about the IoT tea is sharing data, not hoarding it. And that was what really has always shaped my my perspective on this. And I wrote a book, I think it's still the only book on IoT tea strategy two years ago for HarperCollins called The Future is Smart. And I particularly work in two areas, one of which is very relevant to what we're doing talking about today, which is the impact of the IoT tea on reducing environmental impacts and global warming. And the US is sort of a defensive measure. Frankly, I'd given my age. It's so what I answer to the topic of the next book I'm writing called Smart Ageing, that is supplying the IoT T- to improving the ageing process. Interested I and and so particularly Tom common thing that that I know you had a guest on several weeks ago about talking about using the IoT and artificial intelligence to improve predictability of arrival times and things like that for ocean shipping. And I did. I write a regular column for Industry Week on IoT and I did one several months ago about this. And I was frankly flabbergasted that there is this one area that is a huge segment of global commerce and is still largely insulated from the IoT. Now and that is is ocean shipping. And it reminds me of the old maps, you know, from the fifteen hundreds of of the the serpent in the there'd be Monsters. Yes, exactly. Both of the oceans and ironically, from a data standpoint, were not all that far from that now. And and that really has very, very practical implications. It means that the ships are unable to optimise their course based on real time weather data and emerging data patterns and weather patterns and things of that sort. It means that there are they're more vulnerable to deep sea sinkings and a variety of other issues on that, fortunately. That's something that's going down now as a pattern, but still a big issue. And then you've got the whole issue of terrorism and piracy. So know, it's like we have all of this advanced industry everywhere else. All the other components of the supply chain are really advanced. And if there's one thing that I think that CoBots has pointed out to us is how critical the supply chain is in a way that the vast majority of people, you know, people like us understood it, but it is best guarded. People didn't. And now suddenly that's that is front and centre. And yet we've got this big, big area that is still terra incognita. [00:05:04][248.3]

Tom Raftery: [00:05:06] It's bizarre. I had that conversation with that company that you mentioned, port cast there called Port Custódio, where they do they use machine learning and all kinds of data sources to predict the arrival or departure times of ships and containers. But what was amazing was that to me, what was amazing was that they had to use all these disparate data sources to try and do a best guess because the containers and the ships themselves typically don't give off that data. So they're using all kinds of other feeds like, you know, political news feeds on conditions in and around the ports so they know if and when the ship is. Leave rather than actually, you know, getting the data and being able to see all of the ship is departing now, you know, something that you could do it most other forms of transport. You know, like your U.P.S. truck, for example. [00:05:55][49.3]

David Stephenson: [00:05:55] Right. Right. And, you know, interesting, you mentioned U.P.S. truck. I would draw an analogy to one of their competitors to FedEx, and that was that in 2009, long before we were talking in general about the IoT team. FedEx came up with a very clever premium service called Sense of Where. Right. And, you know, those were containers that were very sensor laden and were used for cargo that had very sensitive contents where, for example, light heat, a variety of other things could affect that, including parts for transplants. You know, there isn't anything that is more sensitive than that kind of thing. And they've been able to charge a premium for that kind of thing now for over 10 years. And it's just starting to happen in the ocean shipping area. Maersk, the big Danish firm that really is the kingpin of that whole industry. I some funny there's on the Web site, there's a headline that talks about the the smartest metal containers you can buy. And what they are doing now is they are taking the concept of sense aware. And it's now writ large with entire multimodal yosh ocean shipping containers. And they are they have state of the art refrigeration. They have sensors again for exposure to light. If the container is opened on the ocean and things of that sort. And they're now able they've got a great I believe the the app is called Captain Pete that you subscribe to Captain Pete, you know, for a price. Then you have access to. We old time data about your cargo and its location. And that's something that, you know, again, we've been implementing to a great extent in all sorts of things, in other aspects of business. But comes as like a great revelation when it's applied to ocean shipping. [00:08:24][148.9]

Tom Raftery: [00:08:26] Weird, isn't it? I mean, I guess I can understand it to an extent. These ships are, you know, out of range of land. You know, it's particularly if they're going across the Pacific or something like that. So access to centre communications technologies is gone. So you're relying on satellite communications, which, you know, typically is a lot more expensive than cellular. So it would only be a high ticket items that would be able to do that. And, you know, ships would probably communicate with satellites a couple of times a day just to download weather patterns or whatever. [00:08:55][29.9]

David Stephenson: [00:08:56] Well, and actually one of the options that even though they are required by the National Maritime Organisation to have the communications data, the communications tools on board, they can also turn them off. [00:09:14][17.7]

Tom Raftery: [00:09:15] Yeah. [00:09:15][0.0]

David Stephenson: [00:09:15] Which I find incredible in this day and age. I don't think that's optional anymore. You keep that thing on. Yeah. And it's there. There are get this. There are literally some Ocean-Going shipping containers and ships where they are in the paper and pencil age. Still, it is astounding that that could be the case. But it's it is. And and I think one of the things that were happening we're seeing now is that with all of the refinements in other aspects of the supply chain, that it's intolerable to have this this void right in the middle of the thing. And there is an astounding percentage. The vast majority of all commerce still at one point or another uses ocean shipping. So it it really is intolerable that we have that void. And thank goodness they're there addressing it. Actually, one of my favourite examples of this that goes back at least five or six years ago is is from SAP with the port of onboard. Oh, and then and there and it's got itself a macro system, but with a really interesting micro application as part of it. They are doing everything possible to monitor every aspect of traffic in the port. And it has led to all sorts of great increases in productivity and waste reduction at the same time. My favourite aspect of this is I think it's probably still around because the data is shared amongst all those who need it, because you know what? A port is just an incredibly complex facility with, amongst other things, a lot of really important safety issues. Right. And so one of the things that they do in Homburg is if a drawbridge is going to be up for a certain period of time, they let the drivers of the containers know that. And they they get from the coffee shop that is near them in the port. They get a discount coupon, too. They know that they can run in there, get a cup of coffee because they know that that drawbridge isn't going to open for a certain amount of time. And it seems silly, but I think it illustrates a profound aspect of the IoT tea, which is that when you open up the data to multiple users and multiple, multiple perspectives and multiple individuals, you get insights that even the most brilliant data scientist working in isolation just isn't going to come up with. And the other thing that's interesting about that is once somebody does come up with something like that, it spawns others to think. Well, that's interesting. They can do that. Then they could do this or whatever. And you get this virtuous cycle that is created. Actually, the last chapter, my book, I talked about what I called the circular corporation, which was getting away from silos. And again, we see that so much in ports and with shipping and everything. And instead, by this real time sharing of real time data to go break down the the information silos and bring about collaboration between different functions. And I am convinced that is going to lead to unprecedented precision and also unlimited ingenuity and innovation as well. [00:13:35][259.6]

Tom Raftery: [00:13:37] One of my favourite stories in that kind of scenario of information sharing comes from Continental. Continental are one of our big customers, the German company, you probably know them as a tyre company, but it was only 40 percent of their revenue comes from their rubber products. The other 60 percent comes from the kind of smarts and connectivity that they sell directly to the automobile manufacturers. If you have a car that does a high likelihood that part of the components of your car were manufactured by Continental and then sold directly to the manufacturer. So Continental decided to build this thing called the Remote Vehicle Data Network. And the idea was it was going to be a predictive maintenance or it is going to be because they're still doing it. It's a predictive maintenance play. The idea being that is that they would sell it to fleet managers and also to service centre managers so that the service centre would become sticky for the customers because, you know, typically you don't care which service centre you bring your car to. But if you're if you're going to a service centre where the manager says you listen. Sign up for the service and we'll tell you ahead of time. If a component your car is going to fail, we'd have it ordered in ahead of time. So it's in stock and we'll swap it out before it has failed. And we'll do it in 15, 20 minutes. You know, if you had that kind of service, you'd be more likely to go back to that service centre. So that was the the logic and obviously for fleet managers, very important to predictive maintenance for the fleets of vehicles as well. So that was that was what they were building. They were building this remote vehicle data platform. And as they were building as they were approached by a weather company and the weather company said to them, this New York collecting all this data from cars and vehicles. Right. Time of day, G.P.S. external air temperature, windscreen wiper status, fog, late starters, et cetera. The weather company realised that these cars were little mini weather stations, constantly broadcasting real time geo located weather data and that that would be hugely valuable information to the weather company. And so the two organisations, Continental and the weather company. Worked together, and the last time I spoke to the Christian Bessler who told me this story, they were going ahead with it. They have to dot the I's and cross the T's and all the privacy and security, et cetera, et cetera. But it's now a completely different left field source of revenue from a predictive maintenance project that it hadn't occurred to them at all. [00:16:06][149.8]

David Stephenson: [00:16:07] Exactly. You know, predictive maintenance is such a huge aspect of the IoT it. I liken a diet in my book. I had a chapter that I referred to as a collective blindness. Turns out there was this condition that affected the entire human race. Every single person. Nobody was exempt from collective blindness and weight. Collective blindness manifested itself. Was that once a product left the factory door? We didn't have a clue how it was actually being used or misused. And so three example, the whole thing of scheduled maintenance was largely based on guestimates. And now we're again with with predictive maintenance. And I think the best example that not to get a little far afield do with another aspect of transportation is jet turbines, where basically the sales of jet turbine blinds have plummeted in recent years. And the companies other than right now during Kovik when nobody's buying them. But before that, nobody was worried. And the reason was that the the product was being replaced with a service. And you now that Rolls Royce was really the pioneer on that. Now you're only paying for it. It's called power by the hour. And you're only paying when that turbine is in the air and generating generating thrust. If it's sitting, being repaired, it's not going to bring in any money. And you know another thing, Tom, that's really neat. And I suspect on these ocean going containers, we're going to see more and more of this in the near future. I haven't actually seen any mention of it so far, but I'm going out on a limb and predicting it that you're going to see 3D printers on those ships because with predictive maintenance, they and here they are, the middle of nowhere. They're not going to be able to and just drop a part in there. They will actually manufacture that. Spare part that has been predicted to be needed and they'll have it right there without having to depend on any outside supplier. Incredible. [00:18:50][162.7]

Tom Raftery: [00:18:52] You said as well at the start, David, that you were into using IoT you for environmental reasons. Can you tell me a little bit about that? [00:19:00][7.6]

David Stephenson: [00:19:00] Oh, yes, I, I. This goes back to a passion of mine for many, many years, which is that I always thought that we a lot of the resistance on the part of corporations, particularly in the 90s to environmental things, was largely a communications and lifestyle kind of thing, that they thought this was something that was being imposed on them. And would they associate it with a lot of regulatory compliance, stuff like that, rather than as a way to reduce inefficiency and waste? And that's the way I've always come at environmental issues. And I think that's really the case with the IoT, that being able to say, for example, with shipping, whether it's on terrestrial transportation or on the oceans, that you're able to bring him back because of that integration of the real time weather data and all these things that they were never able to do before. You can get you can really reduce the impacts right now in 2020. There are new requirements going into effect this year on reducing the emissions from the the the fuel that these ships are using. Right. And you're just not going to be able to do that without real time data. And then also, one of the things that's neat with this concept of replacing goods services is that going back to my example of the jet turbines, people are not going to be companies are not going to be replacing their turbines as much what they're going to be doing. And this will lead to much greater loyalty on the part of customers, because as long as your needs are being met, you are going to tend to stay with with your supplier that they will do incremental upgrades. And sometimes that's really just a software upgrade. And they will meet the needs that way. And that is going to continually increase efficiency without requiring scrapping of the product and replacing it with an all new one. So I think we're gonna see a lot of that kind of of innovation with services replacing sales. [00:21:45][164.9]

Tom Raftery: [00:21:46] Yeah. And I mean, I had a conversation with a guy called Tom Kurtz, which I published last Friday on this podcast about that kind of thing. But the shift to product is a service. And it was it was interesting because one of the other key things, as you as you alluded to there, is that previously companies only had a guess of how their product was used in the wild. But now they get real time data back and they can see how it's actually being used. And so you can feed that data into the development organisation and go see, this is how it's actually being used. So in future, you need to optimise for this kind of operating environment, for it, for your for our device. So, you know, versions three and four and five and six are far better because they're based on actual usage data rather than previous estimates. [00:22:33][47.2]

David Stephenson: [00:22:34] Couldn't agree more. And, you know, in the past, product design and maintenance didn't talk to each other. There was really no reason. And now this again, going back to this concept of the circular company, circular management, that operating data that the product design people didn't have access to either. They were pretty good, particularly doing upgrades. They were doing it in a void and guesstimating what customers really might like. And the other thing is, what are the things that data shows that customers are having problems with and where they can then they can remove some of those obstacles to, again, improve operating efficiency. And that was totally impossible. And now we can have the product design people talking to the maintenance people and sharing insights. And that's where you're going to get that kind of creative. I was talking about. [00:23:40][66.1]

Tom Raftery: [00:23:41] It's amazing. I mean, from your example of sending out the coffee vouchers to the truckers in Hamburg to the Continental, using predictive maintenance for weather prediction to, you know, the changing the design of devices based on actual operating data. It all talks to the importance of data. And you never knowing what the data you're collecting might be used for, there are always the possibility of left field use that hadn't occurred to. So data and data collection are usually usually important. [00:24:14][32.7]

David Stephenson: [00:24:14] Exactly. Exactly. And you know, and. Oh. And actually, let me just mention one other thing in that regard that I'm very excited about is that let's go back to the ships. One of there's the whole concept now of low code, no code apps that are particularly designed for users. And I'm thinking in this case, ships cruise where you're not going to send a software designer out on the ship on there. But they are running into issues all the time where being able to apply that real time data will be very important for them. And so there are a number of Start-Up companies now that are creating these some apps that allow basically drag and drop for people on the front lines who have a need to take that data. And they're not doing the macro, you know, big sky kind of stuff. They they need to plan for what they're going to do in the next eight hour shift. And they're able to actually do that now. And it empowers those workers. You know, it's obviously there is a real push to get through efficiency, reduce workforces and all that. You're still going to have a lot of human beings involved in all of these things and particularly on ships. And you need to use that and give them the tools that they would need to take that data that we are going to be gathering, thank God, and apply it to their specific needs. So we've got this whole continuum from on one end, the big macro design of the ships and design of the intermodal shipping containers and things like that. And then on the other hand, you've got these guys who are responsible for what are they going to do that day when there's a storm predicted? [00:26:35][140.8]

David Stephenson: [00:26:36] And the IIoT really can span that whole thing and bring about unprecedented degree of efficiency and removing that big void from from ocean shipping. [00:26:53][16.1]

Tom Raftery: [00:26:53] I got to imagine that Starlink would make a huge difference to ocean shipping companies. [00:26:59][5.3]

David Stephenson: [00:27:00] Exactly. Couldn't agree more. [00:27:01][1.3]

Tom Raftery: [00:27:02] So we're gone over 20 minutes at this point. David and I normally like to keep it to between 20 to 30 minutes. Is there is any question I have not asked that you think I should have any points that we've not brought up that you think it's important for people to be aware of? [00:27:15][13.4]

David Stephenson: [00:27:16] Well, you know, I would bring it to a close by one of my favourite things. I used to do corporate crisis management. And when I would meet a client for the first time, they never were happy to see me because when I walked in the door, they knew they were in trouble. And I would just hand them a very nice card with Wei Ji, the Chinese ideogram for crisis. That combines the ones for danger and opportunity. Now, I know that there is some controversy about whether that's really accurate or not. Let's pretend for the purchaser's discussion that it is. And so right now, we are in an absolutely unprecedented situation. You know, it's not just Covid. It it's the whole issue of systemic racism in everything. And global warming. You see what is happening in California right now. It is just absolutely horrific. And then in the Gulf Coast right now with the hurricane that's heading that way and we don't have the luxury of ducking on these things. And I am convinced that the IoT keep it big by virtue of this ability to collect and share real. Time data is going to be one of the real secrets allowing us to get around these problems. And, you know, yes, right now the danger is abundantly obvious. But I maintain that there is also real opportunity hidden there, too, that we simply would not have been presented with in normal times. And it's really hard. You know, I. I know personally, I'm I'm still having trouble grasping the whole thing. My wife spent two months turning obese men who were dying on a CoBots floor at a hospital. God, at that spilt over to me because I that put me at huge risk. And so I know how hard it is to just cope now. But I think we need to not just cope day to day, but take this as the opportunity that really is to do some incredibly creative thinking and capitalise on this data that we're being presented with for the first time. And I'm convinced that that's going to lead to progress in every aspect of business and our personal lives. [00:30:02][166.2]

Tom Raftery: [00:30:03] I agree. I agree 100 percent. David, if people want to know more about you, yourself or any of the things we talked about, where would you have me direct them? [00:30:13][9.9]

David Stephenson: [00:30:14] Sure. My Web site is Stephensen with a P-H Strategies dot com. And then also I do a continuing column for Industry Week on the IoT T and those would be. And then also my my books. The Future is Smart is for sale. And I think it's still, you know, even though it's two years old now, it's still really relevant, particularly with these attitudinal shifts that we're going to need to make to really capitalise on the IOC. [00:30:47][33.4]

Tom Raftery: [00:30:48] David, that's been fantastic. Thanks for coming on the show today. [00:30:50][2.2]

David Stephenson: [00:30:51] Tom, I really appreciate is fantastic. You know, you're a legend in the futurist world. So it's it's a real honour to be able to to be on this show. Really appreciate it. Thank you so much. [00:31:03][12.1]

Tom Raftery: [00:31:04] OK. We've come to the end of the show. Thanks, everyone, for listening. If you'd like to know more about digital supply chains, head on over to SAP dot com slash digital supply chain or or simply drop me an email to Tom Dot Raftery at SAP dot com. If you'd like to show. Please don't forget to subscribe to it. And your podcast application of choice to get new episodes as soon as they're published. Also, please don't forget to rate and review the podcast. It really does help new people. To find the show. Thanks. Catch you all next time. [00:31:04][0.0]

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