Category: Internet of Things (IoT)

Kuka manufacturing robot
Internet of Things (IoT)

How the Internet of Things Can Make Your Manufacturing Business More Sustainable

The Internet of Things, often abbreviated as IoT, refers to the network of physical devices, vehicles, home appliances, and other items that are embedded with electronics, software, sensors, actuators, and connectivity which enable these objects to connect and exchange data.

The Industrial Internet of Things, or IIoT, is a specific application of the Internet of Things that pertains to the manufacturing sector. In recent years, sustainability has become an important issue for manufacturers as consumers increasingly seek out products that have been made sustainably and with minimal impact on the environment.

Fortunately, the IIoT can help manufacturers reduce their environmental impact and become more sustainable. Here’s how:

  1. Collecting Data to Increase Visibility and Transparency Across the Value Chain
    The first step to becoming more sustainable is to have visibility and transparency across the entire value chain. This means understanding where your raw materials come from, how they are sourced, how they are used in your manufacturing process, what happens to your finished products after they are sold, etc. In order to gain this visibility and transparency, manufacturers must collect data at every stage of the value chain. This data can be collected manually or automatically through sensors and other digital technologies. Once this data is collected, it can be analyzed to identify areas where your company can become more efficient and reduce waste.
  1. Connecting Machines to Improve Efficiency
    One way that manufacturers can use the IIoT to become more sustainable is by connecting their machines together in order to improve efficiency. For example, if one machine is idling while another machine is overloaded, this presents an opportunity to optimize production by redistributing work among the machines. By connecting machines together and using data analytics to optimize production in this way, manufacturers can avoid wasting energy and resources.
  2. Using Renewable Energy Sources
    Another way that manufacturers can use the IIoT to become more sustainable is by using renewable energy sources such as solar or wind power instead of traditional sources such as coal or natural gas. While renewable energy sources may have been more expensive in the past, advances in technology have led to a decrease in cost while simultaneously increasing efficiency. As a result, many manufacturers are making the switch to renewable energy sources in order to reduce their environmental impact.
  3. Implementing Predictive Maintenance Schedules
    Predictive maintenance is a type of maintenance that is performed before problems occur. This is in contrast to traditional preventive maintenance which is performed on a regular schedule whether or not problems exist. By using predictive maintenance schedules based on data collected by sensors, manufacturers can avoid unexpected downtime due to equipment failures. In addition, predictive maintenance can help extend the lifespan of equipment which leads to fewer replacement cycles and less waste over time.

The IIoT offers many opportunities for manufacturers to become more sustainable businesses. By collecting data across the value chain, connecting machines together for improved efficiency, using renewable energy sources wherever possible, and implementing predictive maintenance schedules; manufacturers can reduce their environmental impact while simultaneously improving their bottom line. As consumers increasingly seek out sustainable products, there has never been a better time for manufacturers to take advantage of these opportunities presented by the IIoT .

Reflection of a wind turbine in an office window
Internet of Things (IoT)

How IoT Helps Fight Climate Change


The internet of things, or “IoT,” is a system of connected devices that share data and work together to achieve a common goal. By 2025, it’s estimated that there will be 75 billion IoT devices in use worldwide. That represents a major opportunity to reduce carbon emissions and make our economy more sustainable. Here’s how IoT is already reducing carbon emissions, and how it can do even more in the future.

Monitoring and reducing energy usage: One of the most direct ways IoT is reducing carbon emissions is by monitoring and reducing energy usage. Connected devices can track everything from how much electricity a building is using to how much water a factory is consuming. This data can be used to make real-time adjustments that result in significant reductions in energy usage. In some cases, these reductions can be as much as 30%.

Improving transportation: Another way IoT is reducing carbon emissions is by improving transportation. Connected devices can be used to optimize shipping routes and traffic patterns. This results in fewer vehicles on the road and less congestion. Additionally, IoT can be used to develop new alternative fuel sources like electric vehicles.

Increasing green energy use: In addition to reducing energy consumption, IoT can also be used to increase the use of renewable energy sources. For example, wind turbines and solar panels can be outfitted with sensors that allow them to adjust their output based on real-time conditions. This ensures that they’re always operating at maximum efficiency, which reduces the need for traditional (and emitting) forms of energy generation.

IoT presents a major opportunity to reduce carbon emissions and make our economy more sustainable. By monitoring energy usage, improving transportation, and increasing green energy use, IoT is already having a positive impact on the environment. As the number of connected devices continues to grow, so too will the potential for even greater reductions in carbon emissions.

If you’d like to know more about successful climate emissions reduction strategies, don’t forget to check out my weekly Climate 21 podcast. With roughly 100 episodes published, you’ll be sure to find lots of learnings there.

Martin Barkman profile pic
Digital Supply Chain, Industry 4.0, Internet of Things (IoT), Podcast

Digital Supply Chain, Industry 4.0, and the Covid-19 Coronavirus – a chat with Martin Barkman

We are in a very strange times! On this third Digital Supply Chain podcast on the theme of Industry 4.0, I had chat with Martin Barkman. Martin is an SVP and the Global Head of Solution Management for Digital Supply Chain at SAP, so I was keen to have a conversation with him about that, but the conversation went a bit off track!

With all that is going on in the world right now it is difficult to avoid talking about the current Covid-19 coronavirus pandemic which has turned all of our lives upside down. So, despite not intending to, our conversation quickly veered into a discussion of the implications of the coronavirus contagion, and its effects on supply chains, manufacturing, and ourselves.

This is an extremely topical podcast, which ends on a positive note. I hope you find it useful.

Listen to the podcast using the player above, and/or see the full transcript below:

Martin Barkman [00:00:00]   The first thing that I think in in times like this organizations have to understand this is what is my what is my supply? Where do I have products? Can I get the product? Am I relying upon regions that are even more hard hit by the particular crisis and whether it’s this viral situation or just in general I think companies are rethinking making sure that they have alternative sources.
Tom Raftery [00:00:29] 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.

 

Tom Raftery [00:00:39] Welcome to the Digital Supply Chain podcast. We are in the series themed around Industry 4.0 and my special guest on the show today is Martin. Martin, would you like to introduce yourself?

 

Martin Barkman [00:00:52] Absolutely, Tom. And thank you for having me. I am Martin Barkman and I head up solution management for SAPs digital supply chain area based in the United States and super excited to be here talking to you today.

 

Tom Raftery [00:01:08] Thank you. Thank you, Martin. so, digital supply chain and industry 4.0. How are they connected?

 

Martin Barkman [00:01:16] It’s a great it’s a great question. I mean, there’s a lot going on with supply chain today. Obviously, the topic at the moment is everything the world is doing to mitigate the effect of this virus. But even before the virus, supply chains were becoming more prominent and more central to the conversations in company boardrooms and frankly, even amongst consumers. Geopolitically, we saw things like trade tariffs, and regulations coupled with uncertainties around the exit of Britain from the United, from the European zone. All of these put pressure on companies supply chains. And then at the same time, you also have consumers that are pickier and have more desires than ever before.

 

Martin Barkman [00:02:15] Whether it’s the personalization of products or even the speed…

 

Tom Raftery [00:02:21] They’ve been spoiled, consumers have been spoiled by the likes of Amazon who are now giving them deliveries same day and even, you know, sub-hour times and things like that. so, that’s gotta put huge pressure on supply chains as well.

 

Martin Barkman [00:02:32] Yeah, it’s interesting. So, you have governments, you have individual consumer. And then there’s this underlying thread around topics of sustainability. You know, consumers are starting to figure out that having the delivery truck come to their house many, many times every day maybe isn’t the most sustainable option. So, we’re seeing a convergence of a lot of these global trends, consumer trends, and it’s converging around the supply chain. And so, how do you set up a supply chain that can really accomplish all of this in a fundamentally different way? You asked about Industry 4.0, and it’s an interesting term. It actually originated in in Europe many, many years ago. And it was primarily focused around the automation of the factory or the plants. Now we’re seeing the concepts actually extend to the entire supply chain, to the assets that are deployed throughout the supply chain, all the way to the way distribution and logistics is handled. And it’s all about using technology and data to fundamentally change and take a step change in productivity. Other times it’s called industrial Internet of Things, so, I just wanted to throw that out there, that that’s also a term that’s often used.

 

Tom Raftery [00:03:52] Sure, sure. And I mean, we’re not going to harp on the whole Coronavirus thing because, you know, there’s lots of other people talking about that. And, you know, people better, better informed than us. But things like that are going to be putting huge pressure now, you gonna think on supply chains. I mean, particularly there’s going to be a huge increase in the requirement for logistics as more people, you know, stay at home and have a requirement to have things delivered to their home. so, that that’s going to that’s going to change the logistics industry. It’s going to grow the logistics industry, and it’s going to completely you got to think change how a lot of supply chains are organised.

 

Martin Barkman [00:04:31] Yeah. No, no, no doubt. And it is it is absolutely the topic of the day and what companies are focusing on. I mean, you know, the first thing that I think in in times like this organizations have to understand is what is my what is my supply? Where do I have product? Can I get the product? Am I relying upon regions that are even more hard hit by the particular crisis and whether it’s this virus situation or just in general, I think companies are rethinking, making sure that they have alternative sources identified. They understand the implications of those sources.  They have the ability to switch and shift order volumes from one, one to the other. You know, so. That that I think is kind of step one in a time like this, of course, with that comes also an understanding of where you have inventory in the supply chain and how can you use that inventory to ultimately create new finished goods and move those finished goods to the point where they are most, most desperately needed. I think at the same time, demand is is really, really changing. We’re seeing spikes in demand for products that are absolute critical.

 

Tom Raftery [00:06:01] Toilet Rolls?

 

Martin Barkman [00:06:01] Whether it’s. But it’s not just I mean, it’s paper products in general. Right. Diapers and such. Certainly, in personal hygiene products. I mean, right now, Amazon is prioritising the delivery of those to consumers at the expense of maybe some products that are not deemed to be quite as urgent. I think for companies, what’s critical is understanding, you know, just by how much and where and to what degree demand has changed, because ultimately that picture has to be you have to form the unified picture of demand and supply and ultimately how you how you solve for that. so, you want to get your arms around. So, I yeah. This is a you get your arms around that. That demand certainly part of the supply picture is also the capacity. And you mentioned people are now working from home, certainly in some professions that’s a possibility. In professions like running a manufacturing operation, that’s not always the case. The customers we have that I’ve talked to are trying to keep these critical plants up and running plants that are involved in producing products that are more needed now than ever before. But the method in which you do that right, the way you run your shifts, the way you inform and encourage people to work when they are on the shop floor is different. Right. We can’t stand shoulder to shoulder anymore. We have to maintain the social distancing even in the workplace. so, I think its capacity, its inventory, its supplier and supply and its demand and forming that picture and understanding also what is it saying I need to do today? But what are the what ifs and the scenarios? We live in an extremely dynamic environment. so, this week is fundamentally different than last week. so, whatever I thought was my plan last week, it’s very likely that that plan now needs to change. so, I need an environment and an ability to rerun those scenarios very, very effectively. Once I choose a scenario and I say, OK, this is the one I’m going to operate, that, how do I put it into action all the way down to planning the transportation and understanding how to get it ultimately to the end consumer?

 

Tom Raftery [00:08:29] And demands have got to be swinging wildly as well at the moment. I mean, we talk about people working from home. That’s going to mean a huge drop in demand for, you know, petrol, diesel those kinds of fuels to get people to and from work. And on the other hand, there’s going to be a huge uptick you got to think and demand for things like webcams so, people can more effectively work from home.

 

Martin Barkman [00:09:00] Yeah. so, it’s interesting right now, I think we’re all trying to come to grips with what is the the new…the drop in, you know, what is the the drastic change in demand, and as I mentioned earlier, how do companies get their arms around that? But soon we will have to start to plan for the recovery. Is the recovery going to be like the letter V, where it’s a sharp drop and then a sharp rise, is it going to be like the letter U where it’s a drop and then it’s a period of really, really low band in general, but then an uptick. Or frankly, it’s almost gonna be like the letter L you know, the classic where we’re gonna be at a low point of demand for quite some time and then maybe we see a gradual, slow recovery. And the answer is, of course, we don’t know, and it may actually differ for different products. I also think we have to think about the possibility that when we emerge from this, yes, things will be fine, but they will be different. Right. so, if you think back to the 9/11 crisis, we started to fly again, but airport security was fundamentally changed. Will our way of working be fundamentally different when we emerge from this crisis? so, we have to understand how we will emerge and what the scenarios are so, that we can plan accordingly. But then let’s not assume that everything returns to the way it was. It may not be for certain parts of the economy or for certain industries or for certain types of products.

 

Tom Raftery [00:10:57] And how do companies plan for that?

 

Martin Barkman [00:11:02] Yeah, I think…

 

Tom Raftery [00:11:07] The 64-million-dollar question?

 

Martin Barkman [00:11:08] Yeah, look, I mean, you hear it said every day. Right. These are unprecedented times. Companies that have a good handling of their data, of their information and they’re able to bring it into one environment where they can run these scenarios. Not to pretending that they know exactly what’s going to happen, but they can say, you know what, if this happens, what if we have a quick recovery? What if we have a prolonged recovery? What if they make some more of our products coming out of the recovery maybe is a little bit different? What if a part of the world relapses later this year and the epidemic comes back in a limited form? so, I think companies that have that kind of digital environment are going to be able to plan these different scenarios. They may not know, but they can certainly weigh the different options. But I also think it’s interesting. Right? so, Industry 4.0 if we over time, are able to automate and run more critical parts of the supply chain in an autonomous or perhaps in a remotely controlled way. And this is already happening. I mean, I’ve been to see many production operations. You know, the people there are operating them behind a glass wall or in the case of milling and mining, significant parts of the operation might be controlled in a control centre that’s located hundreds of miles away and then using cameras and digital infrastructure they’re able to control the equipment. The interesting thing about that is when the next pandemic, and I hate to even say it comes, supply chains might be able to operate more autonomously, because people are not necessarily working and standing right next to each other. It’s not that we have eliminated the need for people completely, but we’ve eliminated the need for people to stand closely together performing the tasks and potentially risking their safety as a result.

 

Tom Raftery [00:13:38] so, Martin, I think one of the most important things at this kind of time is transparency in supply chains. Can you talk a little bit about that for us?

 

Martin Barkman [00:13:48] Absolutely. And it’s really interesting because supply chains almost by nature, right? You think everything happens in sequence from one step to the other it’s very linear oriented, and in many cases, it is, right? You start with a but raw material and you convert it into something that you ultimately distribute and sell. However, that’s a very simplified view. And what has been happening already is supply chains are becoming more networks. Right? so, you source raw materials more through a network, in many cases. Your manufacturing setup is a network. You have your own manufacturing sites and you have the ability to go out and work with contractors in a network type of capacity. Transportation. Same thing. You source transportation through a network and you work with a network of providers. And as a result, the supply chains are actually becoming less linear and sequential and more networked. Now, more than ever, visibility of what’s happening in your supply chain is very important. And because it’s more networked, you need the visibility through your network. so, you need to understand. Not just what’s happening within the four walls of your supply chain, but within your supply chain network. so, this is a topic that was already becoming important. I think now more than ever, it’s of upmost importance. Companies are setting up, you know, war rooms and crisis management centres to understand how to maximize their ability to serve their customers. And of course, information and visibility are very, very key to that. Now, beyond this pandemic, there are other cases where having visibility is very important. What if there’s a product recall? How do I ensure that I can trace the source of the recall or the cause of the recall through my supply chain and remove the product that is subject to the recall without overdoing it, without removing a product that does not have to be subject to the recall. so, there there’s just a lot of ways in which this connecting everything and then having that be rendered simultaneously more closer, if not real time. It’s becoming very, very important.

 

Tom Raftery [00:16:23] And for organizations who are in the throes of this right now, I mean, what would you advise them to do if they haven’t got the kind of transparency that they need or if they are starting on that project or if they’re even if they’re in that in that project and they’re looking to increase their  visibility into their supply chain where we’re should. What should they do? What kind of steps should they take?

 

Martin Barkman [00:16:51] Yeah, it’s hard to think of a one size fits all, but. There’s a good chance that there are some pockets of places in their supply chain where the information resides digitally. Sometimes that could be very large pockets, large repositories. I would say an initial key step is assess what is the digital environment you have? What are the existing tools you have in place and look for ways to activate elements of those tools that maybe you haven’t otherwise activated. So, for example, we have customers that are running the SAP integrated business planning application to do the scenario analysis that I talked about earlier. It has inherent capabilities for things like visibility. We call it the control tower. Ensure that you’re leveraging those capabilities to the fullest, which in some cases, if you aren’t, isn’t a big undertaking to go do.

 

Tom Raftery [00:17:53] Okay.

 

Martin Barkman [00:17:55] And certainly that’s something that that companies can consider.

 

Tom Raftery [00:18:00] All these things are kind of on a curve so, they can move kind of further to the right on the curve to increase their visibility, you’re saying?

 

Martin Barkman [00:18:07] Yeah. I mean, it’s a matter of time too, right? And, you know, are there quick wins that can be attained right now? At some point, companies may look to say, you know, how do we how do we take a step change in our in our digital environment, in our infrastructure, so, that we can do this on an ongoing basis, not just when a pandemic comes across, but frankly, sometimes you see a spike in demand that you hadn’t forecasted. You would like nothing more than to meet that demand. But you don’t know if you can or what it would take to meet that demand. so, you need to be able to run these plans and rerun the plans more often. You know, that’s the kind of capability that I think companies at some point are going to start to say, you know what, it makes sense to pursue that.

 

Tom Raftery [00:18:53] Excellent. Martin, we’re coming towards the end of the podcast now. We’re at about 18 minutes, 19 minutes into the into the podcast. Before we end up before we finish up, is there is there any question that I have not asked you that you think I should have?

 

Martin Barkman [00:19:14] I perhaps one thing we should conclude with is, you know what what is, pandemics aside, if we allow ourselves the luxury and the pleasure of removing that that new lens just for a second, maybe what is on the other side? And what do we think is is of utmost importance to companies? And I’d just like to talk about that, because I think we have to allow ourselves the ability to think in those terms, right? For the future and to us and what we see from our customers is supply chain is moving increasingly, from a pure back office function to something that’s at the at the boardroom level, very much part of the discussion. And the reason is we are moving into an era where it’s all about the experience economy, meaning what is it that customers want to experience when they do business with you? What is it that your employees want to experience when they go to work? What is it that your shareholders are looking for you to accomplish right in your community? Same thing with the environment. And we think that’s very exciting for those of us that are passionate about supply chain, because how can you accomplish something on all those axes and on all those vectors without a really, really comprehensive approach to supply chain management, right? What is the point of selling a product that’s marketed well, if in the end the product doesn’t meet customer needs from a quality and functionality standpoint? What is the point of having the most perfectly manufactured product with all the bells and whistles if in the end it’s delivered late to customers? so, the supply chain is what brings that ultimate experience very much together. And we see companies making investments in supply chains in ways that traditionally wouldn’t have been wouldn’t have been thought of. And it’s so, that the supply chain can help the company be successful in the experience economy. And we think that’s exciting and we think that’s very much on top of minds of companies right now, maybe a little bit further back of their mind, given the urgency, but nevertheless, something that absolutely has to be continued to be addressed.

 

Tom Raftery [00:21:57] Excellent, excellent, excellent. Martin, if people want to know more about Martin or about supply chains or about business planning or any of the above, where would you have me direct them? I’ll put some links in the show, notes in the description, this podcast so, you just tell me what to put in there.

 

Martin Barkman [00:22:17] Sure. Let’s assume they want to know about supply chain more so, than they know about me. Certainly, I’m on LinkedIn. But for for supply chain and what we’re doing at SAP, I would invite everyone actually to go to SAP.com, and in there we have sections for supply chain management. We have a lot of interesting content of what we’re seeing are the big trends and what companies are doing. And we have a lot of testimonials from companies with whom we work. And I think that’s an exciting place for people to start to learn more.

 

Tom Raftery [00:22:55] Super, super. Martin, thanks again for joining us on the show today.

Martin Barkman [00:23:01] Thank you so, much. It’s a pleasure.

 

Tom Raftery [00:23:04] 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.com/digitalsupplychain or simply drop me an email to Tom.Raftery at sap.com. If you like to show, please don’t forget to subscribe to it in your podcast application to get new episodes right away as soon as they’re published. And 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.

Profile pic of Elvira Wallis
Cloud Computing, Digital Supply Chain, Edge Computing, Internet of Things (IoT), Podcast

Digital Supply Chain, Industry 4.0, and IoT/Edge Computing – a chat with Elvira Wallis (aka @ElviraWallis)

On this second Digital Supply Chain podcast on the theme of Industry 4.0, I had a great chat with Elvira Wallis (@ElviraWallis on Twitter and Elvira Wallis on LinkedIn). Elvira is the Global Head of IoT at SAP, so obviously I was keen to find out her take on how Digital Supply Chain, IoT and Industry 4.0 intersect.

We had a great conversation covering Supply Chain, Internet of Things, Edge Computing, Cloud – their use cases, challenges and opportunities.

Read the full transcript of our conversation below, or listen to it using the player above.

Elvira Wallis [00:00:00] The Internet of Things is a key enabler for industry 4.0, and it is required to make industrial IoT, to make industry 4.0 possible because you need to connect to sensors, you need to connect to autonomous systems. You need to connect to CoBots. You need to connect to big data lakes and so forth.

 

Tom Raftery [00:00:21] Good morning, good afternoon or good evening. Wherever you are in the world, this is the digital supply chain podcast. And I’m your host, Tom Raftery. Hi, everyone, welcome to the supply chain podcast. This is another of the industry four-point all themed podcasts of the digital supply chain podcast. And my very special guest on the show today is Elvira Wallis. Elvira would you like to introduce yourself.

 

Elvira Wallis [00:00:48] Sure Tom. Thanks for having me on the podcast. So hello, everyone. My name is Elvira Wallace and I am running Internet of Things here at SAP.

 

Tom Raftery [00:00:58] Super. Well, that’s a great role. Can you tell me Elvira, we’re on the obviously Industry 4.0 themed podcast today, so how are we connecting Industry 4.0 and Internet of Things? Cause, you know, for a lot of people who think about Industry 4.0, they might think about maybe, you know, improvements in manufacturing and things like that. But it is just that? Is it more than that? How do you how do you see Industry 4.0 and the connection to IoT?

 

Elvira Wallis [00:01:27] Yeah. So, let me maybe start with some, you know, regional flavour here. In Europe we often like to call things industry 4.0. If you look into North America the same phenomenon, namely the phenomena of an industrial transformation using new digital technologies such as Internet of Things or Edge and cloud computing, big data lakes and so forth, is termed industrial IoT, so dependent on the region of the world, the terms industry 4.0 and industrial IoT are used interchangeably and referring to an industrial transformation using new digital technologies. And if you didn’t go to Asia, it’s called ABC Country 2025 or D E F Country 2030. In other words, we’re all talking about a phenomenon of industrial transformation which we often call Industry 4.0 in Europe. And it requires new digital technology such as the Internet of Things, edge and cloud computing, big data lakes. So, in other words, the Internet of Things is a key enabler for Industry 4.0. And it is required to make industrial IoT to make industry 4.0 possible, because you need to connect to sensors, you need to connect to autonomous systems, you need to connect to Cobots, you need to connect to big data lakes and so forth. So, you need an enabler. And the key here is, all of that data in and by itself is relatively uninteresting. Where SAP comes in… And that has to do with our rich history and also our hopefully very rich future is bringing this type of data with our technologies in the context of business processes.

 

Tom Raftery [00:03:21] OK, OK. Now, for people who may be unfamiliar… We’re obviously not a hardware company. We’re a software company. And IoT is very much a mix of hardware and software. So, where do we fall into that kind of ecosystem?

 

Elvira Wallis [00:03:37] It’s a very, very good notion that you bring up. Clearly, Industry 4.0 as well as Internet of Things is not a one person’s island. Whoever sets out with the idea of it’s me, myself, and I shall fail miserably. It is an ecosystem play that requires the OT players, it requires the hardware players. It requires some clearly various software companies and even into software realm, it’s not SAP alone, it’s us and our esteemed ecosystem. Where SAP is playing is clearly solely in the realm of software, right? Not hardware. Of course, we have a lot of hardware partners that we work very closely with so we can recommend to our customers in specific situations, specific types of hardware.

 

Elvira Wallis [00:04:23] So we’re not ignorant, we’re just not owning that space. Yet to your question, where we’re playing, we’re playing in two places if we cut it very broadly. One is the cloud where we have, of course, the applications that run in the cloud as well as the underlying technology for Internet of Things that works in conjunction with the applications and the second realm where we’re playing is edge computing. The world is moving more and more towards distributed computing. And when SAP says edge computing, we’re of course again referring to software and our software runs on various types of hardware, very close to the source of data. And as to the hardware we run on we’re agnostic, we play with many of the key industry leaders here.

 

Tom Raftery [00:05:17] OK. OK. So, for anyone who is unfamiliar with the concept of edge computing, could you just give us a 101 on that?

 

Elvira Wallis [00:05:25] Oh, definitely. And it’s one of my favourite topics. So, let’s not start with, you know, with SAP. Let’s start with the trends in the market. Right. Great. And. If we put it very, very generically, then edge computing is a new form of distributed computing, meaning not all data will be processed in the cloud. Some data will be processed at the edge. So, what is the edge? It’s basically edge computing means running data applications and business processes near the source of that generated data. So, the source of the generated data could be a factory, a plant, a mine. And it refers to the concept of running the data running the application, the business process near to the source of the data, and if people now say, oh, isn’t it very far away and do we need to deal with that today?

 

Elvira Wallis [00:06:19] Maybe some data points, Tom. If we’re if we’re looking at edge computing, it has been growing steadily in the past and if you if you listen to the analysts, Gartner, for example, predicts that by 2025, 50% of enterprise generated data would be created and processed outside a traditional centralized cloud data centre. Now, 50%, is that a lot or not? Well, that would be up from 10% in 2019. So that’s quite a big growth in the ability to, you know, extend and run business processes at the edge, meaning in the plant, in the factory close to the source of data that enables customers to automate and run their operations independently, and that’s what a lot of people want in the world of industry 4.0, in the world of industrial I.T. in order to endorse the digital transformation. They say, hey, my plant, my factory needs to run independently of the cloud. So, in order to endorse the cloud, we see a new form of distributed computing, namely the edge. And the edge addresses customer concerns with running and low latency. Right. Very often we hear that I need to run low latency, low bandwidth. And then let’s not forget in many places of the world there, specific security and regulatory requirements which says, hey, the data must be processed locally instead of in a centralized cloud. So, it can also be regulatory reasons why edge computing starts to prevail. And if you listen to some more data points and then IDC, for example, predicts that by 2023, 70 percent of IoT deployment will include edge-based decision making, right. So, the decisions will be made decentral supporting the organization’s agenda. So, meaning we can do industrial IoT. We can do industry 4.0 without it, meaning some central cloud-based system taking over. Local autonomy can happen if edge computing is involved. And if we look at the IDC saying they’re saying, OK, 70 percent of all enterprises will run varying levels of data processing at the edge. And that also means organizations will have to spend a lot on IoT edge infrastructure in that timeframe.

 

Elvira Wallis [00:08:53] So I think edge is here to increase in prominence and in relevance for our customers, and it’s a good idea to get prepared. I mean, we at SAP we’re very well positioned to run data driven business processes at the edge. We can run manufacturing processes at the edge orchestrated from the cloud, and we provide our customers the option to run applications in a hybrid approach meaning, at the edge and clouds and this hybrid cloud edge offering helps customers accelerate the transition to the cloud by addressing their need around data privacy, around security, around latency and regulatory requirements.

 

Elvira Wallis [00:09:37] Now, going back to no person is alone. It’s, of course, clear that we also in the realm of edge computing, we’re in need to be committed to a strong ecosystem. No one can do it alone. You need the hardware providers, and we have announced strategic partnerships with the hyper scalars and also in some cases regional industry specific players in IoT and edge where we leverage the strength of all the players in the ecosystem to help our customers be successful. It’s a joint digital transformation where SAP participates together with our customers and our partners.

 

Tom Raftery [00:10:14] OK, super, super for any of our customers, potential customers or just anyone who’s listening, who is interested on embarking on some kind of industry 4.0 project. How do you start something like that? Where do you kick off?

 

Elvira Wallis [00:10:35] And so it’s a very good point to raise. My first perspective would be. There is no one size fits all right? Customers are. By and large, all increasingly challenged to adapt to ever changing conditions. Now, mind you which of these conditions is the most prevalent and in which line of business is it the trade wars? Is it managing the global supply chain? Is it skills shortages? Successful customers need to embrace the digital transformation right to discover new ways to solve their business problems and to keep their customers engaged. Because this is also to do with customer experience and customer loyalty. Now, customers might start in different areas. They all centre on their customers. But whether they start with reinventing production to centre on their customers or whether it is connecting various departments in their company to overcome their own segregation of duties in a way that is hindering success. That is something that customers really will vary. In other words, SAP can help make industry 4.0 an everyday reality. Now where customers start, whether it’s with the intelligent asset and managing the overall equipment effectiveness or whether it’s the intelligent product where customers want to understand the business impact of design and engineering changes in products, or whether it’s the intelligent factory where IoT helps enterprises to be agile and deal with varying production volumes and new manufacturing technologies, or whether it is with empowering people so that people can fulfil complex tasks with a fast work-around that is really dependent on the customer need. We need to understand that it’s important to centre on the customers and connect the entire company, but it doesn’t mean you need to start everywhere at the same time with the same urgency. Our clear perspective is customers have a choice where they start and we recommend to start somewhere, where of course there is an immediate need and it can be time boxed because nothing is more convincing than initial positive results and then you can widen the exercise.

 

Tom Raftery [00:13:02] Okay, very good. What kind of challenges are companies likely to face on a journey like this? I mean, you mentioned, you know, having skilled staff there. Is it is the staffing or is it technology or is it a combination or is it something else entirely and you know, having then identified a couple of the challenges, what would be ways of overcoming them?

 

Elvira Wallis [00:13:28] It’s a very good question. And there are some interesting studies out there in the market that I enjoyed. One is by McKinsey and that study showed clearly that the success rate of these digital transformation projects are not necessarily tied to the area within which they are started. So, you couldn’t say, oh, let’s start it in production or let’s start around the asset and as it is more successful than production or, vice versa right? What they showed is it is other factors that correlate with success. In other words, the more initiatives a customer ran. So, in other words, if they addressed digital transformation in more lines of business, they were likely to be more successful than if they were just doing what I would call island exercise in one area. So, spreading wide helps clearly with the RoI. The other thing that some of the studies showed is time boxing is key, having a line of business sponsor is key. So, in other words, it doesn’t work if you have just some little IT exercise or if it’s just some innovation centre not connected to the line of business. So, sponsorship, time boxing, clear KPIs as to what do we want to achieve, and which problem do we want to solve. In other words, all that is more successful than what I would call analysis paralysis and looking for the perfect case. Or the what I would call research approach where let’s take some sensors and collect them and produce a dashboard. So, you need to have a clear proof business problem to solve, a business sponsor, time boxing, clear KPIs and ideally more than one initiative. Spreading it and seeing what are the successful front runners and building on those. Those are clearly some of the what I would call non-technology challenges in a way they are common sense that we learned from various studies, but also from working with our customers.

 

Tom Raftery [00:15:30] OK. OK. Very good. We’re coming up towards the end of the show, now Elvira. Is there any question that I haven’t asked you that you think I should have?

 

Elvira Wallis [00:15:44] It’s a very good question. I would say when we look at the type of use cases, what kind of typical use cases do we see is one question that I very often get asked and I mentioned before, yes, we have the area of intelligent asset, intelligent product, intelligent factory and empower people. Now, another dimension to look at it would be what type of goals are people pursuing? Is it about new business models? Is it about efficiency? Is it about customer experience? In other words, what type of goal do people look at? And one thing I’d point out is we see increasingly people looking at some product as a service offerings. Now, that doesn’t work for all types of offerings, but that is something that we see a shift to product as a service in the construction, transportation, hospitality, realm and insurance industries. Where we see a shift and I believe we look at new customer experience, in other words, does my digital transformation help me create a better, better customer experience is clearly something that we see where people look at their customers, but also their customers customers. And I would encourage people to take that line of sight to look in addition to the productivity gains and the overall production. Really the focus on the customers and to put that at the forefront and the centre of a digital transformation.

 

Tom Raftery [00:17:17] Superb. Elvira if people want to know more about Elvira, or IoT, or Industry 4.0, or any and all of the above where would you have me direct them and feel free to give multiple links? I’ll put them into the description of the show notes when I publish this.

 

Elvira Wallis [00:17:35] Oh definitely join me on Twitter. Join me on LinkedIn. And of course, we have our flabbergastingly great web site SAP.com/IoT. And not to forget, we’re going to run an openSAP IoT course in the near future. And I would really appreciate you joining us in that openSAP course.

 

Tom Raftery [00:17:56] Fantastic. I’ll have links to all of those in the show notes. OK, that’s been great. Elvira. Thanks a million for joining us on the show today.

Elvira Wallis [00:18:01] Thank you, Tom. It’s always great to be one of your interviewees.

And 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.

Hans Thalbauer profile pic
Digital Supply Chain, Industry 4.0, Internet of Things (IoT), manufacturing, sustainability

Industry 4.0, Digital Supply Chain, and Sustainability – a chat with Hans Thalbauer

The buzz around Industry 4.0 is starting to grow so I decided it might be interesting to have a series of interviews themed around Industry 4.0 here on the Digital Supply Chain podcast. 

To kick off this series I asked my friend, and colleague Hans Thalbauer to come on the show to talk about where he sees the relationship between Digital Supply Chains, Industry 4.0, and how they can help organisations become more sustainable.

We had a fun, wide-ranging conversation covering manufacturing, connected assets, and the importance of using data for decision making in supply chains.

Check out the audio of our conversation using the player above, and/or the transcript below:

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: Hi everyone. Welcome to the digital supply chain podcast. This episode is one of the series that are themed around Industry 4.0 and my guest on the show today is Hans Thalbauer. Hans, welcome to the show.

 

HT: Thank you very much.

 

TR: Hans, could you, for anyone who doesn’t know, could you introduce yourself to our audience?

 

HT: Yeah, absolutely. I’m if you will, a supply chain veteran. I was working in the supply chain space all my life. I’m with SAP 20 years. All these 20 years I was in supply chain, manufacturing, product life cycle management, operations areas. I’m working with customers around the world and having fun doing that.

 

TR: Good stuff, good stuff. And we’re, we’re on the digital supply chain podcast on the series that is themed around industry 4.0 for anyone who’s unfamiliar Hans, could you tell us what you think Industry 4.0 means, what actually is industry 4.0? Cos it’s kind of a buzz term that’s out there and everyone’s kinda got their own definition. What, what do you think industry 4.0 is?

 

HT: Yeah, you’re totally right. There are many, many definitions about industry 4.0. And if you will, there are also different nuances to industry 4.0 dependent on which region or which country we are. And so, if you just take it from, I think their original definition we are talking about the fourth industrial revolution. We are talking really about a step change in productivity. We are talking about really something significant happening to industries, manufacturing industries. And the digital transformation for manufacturing industries. Industry 4.0very often actually is narrowed down to manufacturing and operations, which is true, right? So there’s a lot happening in these two spaces in these two areas, but it goes beyond, it’s really about the digital transformation of manufacturing industries which is of course much broader than only the manufacturing and operations part. This would be my high-level positioning or, or definition of industry 4.0. So it’s really about the digital transformation of manufacturing industries.

 

TR: Okay. And again, we have a lot of terms here. This is the digital supply chain podcast and we talk about digital supply chain quite a lot, but we also have industrial internet of things and industry 4.0. Is there a, a kind of a natural segregation between those terms or are they kind of the same thing, just you know, different ways of looking at things or how do you see that?

 

HT: They’re the same and they are not. I mean, industry 4.0 obviously started in Germany  with the government initiative about, I want to say even seven to 10 years ago. And really started with the idea of there will be a big change. How can we prepare the industry for this change? The idea is that data are valuable and can be leveraged much different than ever before. Technology like machine learning, artificial intelligence can be leveraged in a very, very different way and really make a big change in how companies run manufacturing. How can actually companies be successful going forward. That was kind of the basic idea and leveraging data in order to do that.

 

In the US industrial internet of things has been created.  Very similar approach going in the same direction. It is broader and narrower at the same time. It has not a strong manufacturing focus. It has much more of a consumer focus and much more these IOT solutions related to consumer products, consumer usage and there are many, many examples of which  everyone is aware around the world from yeah all the products which have been introduced and really have the connectivity and really are consumer oriented. And I think everyone is using them every single day. And so this is kind of where the US discussion has gone much more IOT centric than industrial centric.   

 

If you go to China, there is of course a plan which is called China 2025 which is really also looking into productivity gains in manufacturing. Right? And there it’s really very, very much on manufacturing focus. If you go to Japan, it’s a robotics focus. If you go to India, it’s about Make in India, right? So the big slogan, how to introduce actually a much more efficient and manufacturing industry in India. And so there’s a common thread to all of this. All of it has to do with we get data from machines, from assets, from things, and we want to leverage this data in order to be more efficient, in order to be more precise, to predict outcomes, you know in the future, and really do things differently.

 

By the way, I also would say that industry 4.0 and sustainability go hand. The efficiency in manufacturing. The reduction of energy consumption in manufacturing, the reduction of water consumption during the production processes, all of this actually goes hand in hand. And so both topics for me are connected.

 

TR: Right? No, it is interesting you bring that up because sustainability is obviously a topic that a lot of people are interested in at the moment. It’s, it’s quite a hot topic, but a lot of people may not be aware that obviously sustainability is about doing away with waste. It’s about maximizing use of resources for the, you know, maximizing the, the outcome or the output using the minimal inputs. So it’s getting rid of waste. So to your point, yeah industry 4.0 is all about that, it’s all about getting the best outcome for the minimum inputs or the least waste.

 

HT: Yeah. It’s, it’s really perfectly defined rates are, and what you discussed is perfectly correct. Because when you think about it in the context of sustainability, we are talking about the circular economy. What does it mean? I need to be connected. I need to be connected to the business partners I need to be connected to the things, the more connectivity I have, the better I can manage actually their efficiency. And efficiency in transportation where I really make sure that the truck is never empty. That the truck really has actually the  shortest route to between point A and point B. So it’s all about reducing waste. It’s about water consumption, right? So water consumption, a big, big topic actually during production processes. If you can reduce that also in the product itself, if you can reduce the water in the products, big topic. If you think about energy, it’s biggest topic by itself, right? So with using the energy and then you see actually what companies are doing around the world and especially in the manufacturing industries how they go about  sustainability. It’s really taking the  idea of how can I reduce the carbon dioxide impact? How can I reduce the energy by itself or their consumption by itself. So all of this actually plays hand-in-hand with if I’m more efficient and I can be more efficient with industry 4.0 concepts, then I’m better off not only in my productivity but actually also in my sustainability efforts.

 

TR: Yeah, absolutely. And so  you mentioned different regions like Japan and India and America and Germany. Everyone has kinda got a different focus on it. Are they all industry 4.0? I mean what I’m saying is we’ve, we’ve titled it in some kind of way, IIOT in the U S Industry 4.0 in Germany, but is it all really the same thing? Is it all about maximizing our outputs and minimizing our inputs to get the best results for everyone?

 

HT: I think there is, there is something common around this, right? And then the common things around this is really connecting the assets, connecting the machines, getting the data. So now we have the data, now it’s about getting insights, right? So, okay, good. Now we can see actually much more. It’s a big step forward. I built these data lakes andand, and. The next step needs to be that I really learn from this data. And so there’s a massive amount of data. If you just think about every using the machine, every single assets delivers every milliseconds, hundreds of data. And so you get really this big, big data lakes. So we need machine learning, we need actually algorithms which are able to deal with this data. And I think technology made huge progress there.

 

So we do have technology in place in order to really understand the data and have machines telling us what it really means. So machine learning and artificial intelligence plays a huge role in this context. Why? Because what this leads to is that I really change the way how I run my business. At the moment every single supply chain in the world is an alert driven, reactive supply chain, which means something happens and I need to correct it, right? I’m always actually running after the fact something happened and I always tried to correct it. This is the thing. Exception-based management, exception-based management, alert driven, supply chain, whatever you want to call it. And this is really what, how everything is built up. But what if I can turn this around? What if I can use this data now in order to predict an outcome? Right? So, and this is a big thing and I think it’s not yet well understood in the market that this means all the supply chain around this world become predictive supply chains. So I predict not only the maintenance, I predict the quality of a product while I am producing the product, right? So reduce waste dramatically. It doesn’t go through the entire production line anymore and at the end I find out in quality control that well, it doesn’t meet my criteria. I can do that while I’m producing. I do the same on, on transportation. Right? So I don’t waste the time of, of waiting for a delivery. I can predict actually it might come exactly at this time. Right. And I predict that something might be in the way which doesn’t allow me to deliver at this time. And I can inform all the people who are involved before things happen. Right? And it’s always about, I really am enabling people and companies to look into the future and predicting outcome. And with that, reducing  inefficiencies on a very, very dramatic way.

 

TR: Interesting. I’m intrigued that you’re talking not just about manufacturing, but also about the logistics and deliveries because traditionally I think a lot of people would associate industry 4.0 with manufacturing, but not necessarily with the logistics, with the deliveries, with all that kind of stuff.  How, how does that fit in? Well,where, where does, let me ask an even broader question – where does the scope of industry 4.0 start and end?

 

HT: Like I mentioned before, right? So it’s really for me, the transformation of a manufacturing industry and not of manufacturing only, right? So the manufacturing processes, yes, of course. The operation processes. Yes, of course. But it’s really about the end to end processes in manufacturing. Right? We are talking about here, it’s really the digital transformation for the manufacturing industries, which would be, would be, I think, my description of it. And so where does it end? Where does it stop? I don’t know.  It’s really the whole design to operate process.  If I’m more efficient in designing a product if I have feedback and input at the, at the very beginning, if I introduced this idea of… I reduce whatever plastic consumption while I’m packaging my goods and all these kinds of things all go in design direction, right? It’s, it’s actually really about building an environment where I’m allowing companies to really look into the future. Like I described it before to start predicting an outcome before things happen. And with that running actually in a very, very, very different way than before.  So, yeah, that’s how we would describe it.

 

TR: Okay. Okay, cool.  So we’re getting to, I got to say, this is a journey, you know it’s, for any company it’s gotto be a series of projects to kind of roll out industry 4.0 technologies, it’s not going to be one individual project. It’s going to be a series of projects and it’s going to be an ongoing journey to get there. But where does it end? I mean, for many people, they’re still very analog, so they have a long way to go. For others, they’re further along the journey, but you know, will it ever end?

 

HT: It is an ongoing journey. It is a transformation. I wouldn’t put an end point on it. It’s really because we get smarter and smarter by the day by learning more and more and using data in a very different way. I would maybe an idea to describe it is we are still living very much in a transactional world, right? If you run the business processes in manufacturing, operations and logistics, it’s very much a transaction. I have a delivery and I transact the delivery, I execute on it and so on. And we changed it around and create a data-driven world  where I analyze I simulate and I just make my decisions based on this information. Right? I’m not just blindly executing a transaction anymore, I start simulating. And now if you, if you start doing that, it’s not necessary to do it for everything at the same time.  Of course, you start in certain areas and then you grow from there, right? And then you find out all of a sudden that, well, if I connect these data, I can be smarter. Right? So I give you an example.   If I’m, let’s say starting in predictive maintenance and I find out in this product, yeah, if I predict maintenance, if I reduce here, the maintenance schedule ends on, I really can save a ton of money by doing that, right? So I’m predicting I’m not just doing blindly scheduling, my maintenance for the asset, I’m really predicting when I need to do it and then I do it. So that saves a ton of money. But then the, the thing is if you really go to this data and then you find out what if we would design this asset differently, if the product would have been designed in the first place in a different way, the product would be more stable, more robust. And so therefore I wouldn’t even need to maintain this, this part which always breaks, right? So now you could start to connecting from maintenance you start now connecting the engineering world, right? So it becomes a maintenance driven engineering process, which doesn’t really happen at the moment. Right? So and now you can build these connections also to manufacturing and to logistics, right? If I understand from these other departments what they need, what would be the impact? What is the influence? If all of this would be much more harmonized, then actually I am better off in total. And so my recommendation is always, okay, start in the area where, where you, you think actually there is the biggest value for you, right? In many cases it’s in the maintenance or in the manufacturing area, but then really think about the possibilities you have. Learn from this data and now start to connect to the other areas, connect to engineering, connect to assets, connect to logistics. And by doing so you become much, much more efficient overall.

 

TR: Sounds like it’s a lot about breaking down silos and making organizations more horizontal.

 

HT: It is right without necessarily an organizational change. Right. So I think, I think actually what is always in the way is if systems or processes would require, we introduce that and this means also do I need to change my organizational set up of the company? Not necessarily. Here what we are doing is we connect these organizations with data. What we need to have is really the data needs to flow. We need to have a data model which allows that. We need to have a data lake where we not have only a data lake for operations and one for manufacturing and one for logistics. No, we need to have the possibility to correlate the data and connect this data and with that actually make every single organization unit in the company much smarter.

 

TR: Okay. Yep. Makes sense. One challenge I guess I see for for organizations is a lot of organizations are still not thinking data first and obviously to go down the route that you’re describing, that’s a mindset then that they need to switch to. And I guess that’s more people than technology thing, but how do we convince organizations to to make that change?

 

HT:  I think actually people would be and are willing very much so to switch to a much more data driven approach. They would be happy to get   the information they need in order to make a decision immediately in real time. They don’t have it right now. It takes a day in order to get a report. By then they have already made decisions hundred times during the day and transformed and executed on a transaction. So what do we need to get to is we need to get the information to the people so that they can make these decisions and I’mabsolutely convinced, I haven’t seen it once where people would be hesitating adopting this type of approach. They really like this approach. There is of course, one aspect, which is very important when you talk about this whole aspect of automation, the whole aspect of everything runs by robots and so on. There is the fear that it takes jobs away, right? And it’s not just a fear, it’s a fact, right? So in manufacturing on the shop floor in their houses what do you see right now is a lot of robotics are in there  and less and less people work in this environment. But you also where it’s very interesting if you look into statistics, the last 10 years, many new jobs have been created. There are new job titles which were not existing before. A chief digital officer, something 10 years ago, if you would’ve said, where’s your chief digital officer? Everybody would have said, what? What, what is that? Now every company has a chief digital office and not just the chief digital officer, but the whole organization around it. Right? Which, which really tells me this digital transformation really opens up completely new jobs and job titles we haven’t seen before, which tells me also that there’s a huge opportunity actually for people. Of course it means education, it means training, it means different skills, but in the services part of it, so operations, maintenance part of it, this is a big job area. And also in this whole data part, it’s a big, big job area with like I said, many new job titles, which we haven’t even seen before.

 

TR: Indeed, indeed. Hans, we’re coming towards the end of the show. We’re up on around 20 minutes now. Is there anything that I have not asked you that you think I should have?

 

HT: No. I don’t think so. I think  the discussion is very, very important. The discussion also needs to be that we need to understand how we really can leverage data, make this transition from transaction to a data driven approach that we go into this  predictive way of running a supply chain. So looking into the future instead of looking always into the past  this will have big impact in how companies run their businesses. Also, I think what is very, very important, it’s not just a hot topic to talk about sustainability. I think actually it’s essential to talk about sustainability and we need to have that as another dimension in this industry 4.0 discussion because this really enabled, Industry 4.0 enables us to be more sustainable and we need to measure it, we need to control it in a much better way and we need to leverage all the concepts which are being created from sustainability, circular economy, the whole waste reduction concepts and so on as part of the Industry 4.0. So it really goes hand in hand in my mind.

 

TR: Super. That’s great. Lastly, Hans, if people want to know more about yourself or about  Industry 4.0 or any of these things, where should I direct them to go? Where should they go?

 

HT: Well, go to sap.com. There you’ll find actually Industry 4.0 on the top where it’s a big theme and where you find a lot of additional material about Industry 4.0 and the approach SAP is taking. Yup.

 

TR: Okay. Super. Hans that’s been fantastic. Thanks a million for coming on the show.

 

HT: Thank you.

 

 

And 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.

 

Digital Supply Chain, 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

cybersecurity, Digital Supply Chain, Industry 4.0, Internet of Things (IoT), manufacturing, Podcast

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.

Internet of Things (IoT)

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

Internet of Things (IoT)

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

Internet of Things (IoT)

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