Lara Schilling: 0:00

The question is also visibility to whom and who is taking decisions. It's very important that digitalisation is not per se a phenomena that will resolve all our problems. We gonna get to digital democracy and all is fine. No, it inherently has the same challenges that we have in supply chain governance in an analogue and in a digital world.

Tom Raftery: 0:31

More supply chain data doesn't automatically mean better decisions and more digitalisation certainly doesn't guarantee greater resilience. Good morning, good afternoon, or good evening, wherever you are in the world. Welcome to episode 140 of Resilient Supply Chain Stories and Strategies that Keep Business moving. I'm your host, Tom Raftery. My guests today are Lara Schilling, Assistant Professor of Supply Chain Management at the Technical University of Denmark, and Professor Stefan Seuring, who has spent more than 25 years researching sustainable supply chains. And here's the odd bit. Their latest research paper used 52 conversations from this podcast as its dataset. And what they found raises some uncomfortable questions about visibility, failure, sustainability, and what happens after the dashboard tells you there's a problem. If you are investing in AI, IoT, or digital supply chain capability, this one is worth your attention. Let's get into it. Lara and Stefan, welcome to the podcast. Would you like to introduce yourselves with maybe Lara going first?

Lara Schilling: 1:44

Yeah, sure. Thanks for having us, Tom. I'm Lara. I'm assistant professor in supply chain Management at the Technical University of Denmark. And yeah I think we've gonna dive deeper into the research part throughout the podcast. Looking forward to that.

Stefan Seuring: 1:59

Yeah, I'm Stefan. I'm working at the University of Kessel. Kessel is a mid-sized city in the middle of nowhere in Germany, but if you roughly point to the centre of Germany, then you are about right. I have been doing research on, supply chains and particularly also sustainable supply chains by now for more than 25 years. And, uh, it's still an interesting topic, which always provides new opportunities for looking at new questions.

Tom Raftery: 2:27

And the reason I invited you both on the podcast is because you published a paper earlier this year based weirdly, and thank you, based on the transcriptions of some of the podcast episodes of this podcast. So let's talk a little bit about that, because it's an unusual way to source data for a peer reviewed research paper. Could you maybe start off Stefan telling me why, what, what made you wake up one morning and say, I know, I'll mine Tom's archive of transcripts and produce a paper.

Stefan Seuring: 3:14

I listened to a number of your podcasts over the time, and, eventually I thought it's a really interesting data source. And let me combine this with at least another side issue. We have typical data sources, which we always use. We always do interviews, we always run surveys, we do certain models and these kind of things. But sometimes you have to think out of the box and try to look at is there something different? And, of course also what are the pros and cons of looking at some different points and some different content. And the podcasts had the advantage we don't have to hunt for people being interviewed. You did this already, great. Even better that the podcasts are fully transcribed, so we can just download the transcripts, making data collection comparatively easy. What we basically developed is a set of keywords, more on digital technologies and on sustainability, because we wanted to look at particular this intersection and then render keyword analysis over all the podcasts available at its time, and then selected out, the 52, which, which we then basically took as the final sample. So so your data provided an untapped opportunity, I would call it, in looking at, related data and doing analysis, in then a more scientific manner, which is an emerging thing to do. So the last years we have also used, Twitter data. We have, once tried to work with, TED Talks, but they did not fully work. But it's not too far away from, from a podcast or something like this. And once more the opportunity of getting a different perspective. That is basically the great point about it.

Tom Raftery: 4:55

And Lara, you chose 52 of the episodes out of several hundred that were there. Why those 52 in particular? And was there anything that became visible from those 52 conversations that we wouldn't see going episode by episode?

Lara Schilling: 5:16

Yeah, that's a, a very important aspect to consider when using secondary data that is available, which, the podcast database kind of is, is to be very critical on, okay, how do I actually select a relevant podcast? In the very same way as we select kind of interviewees or if you design surveys, you have to have a good justification for the sample that you're putting together, right? So obviously we had to look for those podcast series that were relevant to the topic we are looking in. So we want to look at the interplay of different digital technology and aspects of sustainability in supply chain management. So obviously we had to look for podcasts that also cover that topic, because context matters as it, it does in any kind of interview. So we also have to make sure that we are also looking at episodes that are relevant to what we are looking at. So that, that was the reason why why, we had to do that. And at the same point of time, it's, very important also to be very transparent about that in order to make also the data source that we are using and the methods you're applying, very transparent to the audience. And that also means to be aware of its limitations. Because for example, other than primary data in interview settings where we oftentimes have done confidentiality, we anonymize and everything like that, one has to be aware that these are podcasts that are publicly available. That also limits what people say. So this also important aspects we did consider when selecting the source itself, but also selecting then the individual podcast series. Yeah.

Tom Raftery: 6:56

Okay. And Stefan, did you discover anything from going through these 52 episodes?

Stefan Seuring: 7:03

So we had to have an idea on what to look at. Now, we mentioned already that we tried to target the intersection of digital technologies on the one hand side and sustainability on the other hand side. So we basically at the front end put certain digital technologies, artificial intelligence, cloud computing, cloud services, IoT, internet of things and, and blockchain as the core ones. And on the other hand side, we look, try to look at, sustainability outcomes. So the, the typical logic of, economic, environmentally and social outcomes. And in between we basically put some processes like they should link the one side to the other hand side so that we get, an idea on what is there.

Tom Raftery: 7:45

Okay, and the findings?

Stefan Seuring: 7:47

Well, the findings are quite interesting because, as the, core picture basically shows AI, let me just pick on one point. AI should definitely help us in managing supply chain risk. Supply chain risk is an abundant topic. We only need to look at this constant, hassle about the Strait of Hormuz at the moment, but also many other issues. Yeah. And, it should basically then drive all three, outcomes. That's what, we basically aggregated, we see. So environmental, economic, and social outcomes. How this then would appear, how this would basically be really transformed into companies. That's what is typical limit in our analysis, what we cannot fully see yet. But there is some first, first points, but we cannot also go into the others, to talk a bit more about how deep we can go, but also where the, the limits of this are.

Tom Raftery: 8:41

And Lara, sustainable risk management appeared in 45 of the 52 episodes. Why did that dominate?

Lara Schilling: 8:51

It's probably coming very much also if we reflect about who was actually in the sample. It's a lot of industry corporations. I think that reflects very much the, public debate. And particularly if we look into recent EU legislation, of course there's an increasing demand for companies of a certain size to kind of provide infrastructure of evidence, right? That holds on the one hand side for the, the environmental, particularly when we look a little bit more in terms of the EU Deforestation Regulation, but also on, on the social side. When we look into the EU Forced Labour Regulation and other things that are increasingly coming up. And the point is there that organisations seek to find a tool on how they can show compliance to this kind of legislative developments and demands, right? The interesting thing is that in the end that also puts into perspective what we can actually achieve with that. Because in the end as you also reflected upon in, your writing of, of the paper is in the end, these technologies do not make our supply chains more sustainable. Also if we think about it actually the technologies themselves probably make them even less sustainable in the purchasing decision, right? It just depends on how does it actually unfold. And then what we see very clear, the first chain of argumentation is quite clear in the paper where we see, okay, in the end we create visibility by combining certain emerging technologies that have different capabilities and characteristics, but they kind of give us the opportunity to talk deeper into, into the supply chain. However what we don't really know, what do we do with this knowledge gain? It's very much a managerial question on what actually happens. So we see there's a lot of okay with this information certain conclusions can be drawn, certain risks can be anticipated but there's not really a very clear story on how actually this can be done. And I think that's a very much something we have to look deeper into also in future research. Whereas also I think it's important, and maybe we can get back to that also later, is to think about, okay, what is actually behind all these indicators? Because in the end, indicators indicate. So I think why we see a very interesting and positive picture of that. I think actually looking deep into it, it gets also very evident how critical one has to see this relation between digitalisation and sustainability.

Tom Raftery: 11:39

And Stefan, take us inside the the middle layer. How, how do risk management, collaboration, and proactive action turn data into a better decision?

Stefan Seuring: 11:56

Well, well risk management that I, I guess we can just stay with some of the examples that we see at the moment where, where we see have certain disruptions of supply chains, which at the moment surprisingly come a lot really from rather economic or political activities. Which is outlined in the, supply chain, which literature many years ago already. And, you first of all have to follow a classical risk management process, and look at monitor the risks and, be aware that they can also be on the environmental social side, an NGO blaming you for certain misconduct. But by now they already mentioned due diligence, regulation, really putting material demands on, you have to document what's going on actually in your supply chain, which on the environmental side is sometimes a bit easier, I would say, because on the environmental side, you can still measure certain things in a product. Like, like this is a cotton shirt but whether this is organic cotton or not, organic cotton, you can basically measure years later. While child labour you cannot measure many years later. So you have to have, a more precise, I would even say, risk management process in place where you monitor and audit suppliers and, and where you have to be still careful, on, also, let me say positively letting the supplier survive. Yeah. So, so not demand more environmentally and social issues on the other hand side and squeeze them on the economic side. Always wanting more cost reductions and these kind of things, which is not easy. So I'm, I'm still arguing for, we still need to have an economically viable supply chain. and that's a typical debate that you have on Zu with companies that this might be costly on the other hand side by now, overlooking all of these risks and, and ignoring the risk management process. And that's what I see in quite some of the companies. Let me just say with the Strait of Hormuz we saw that the tensions build up. And you could at least have looked at, what is actually transported through the Strait of Hormuz. So if there would be a kind of a clash of the powers, which products are actually affected. And, now I'm not in the fertiliser business, but interestingly, quite some fertilisers going through there. That it would disrupt oil and gas. Well, I guess almost everybody would have had in mind, but fertiliser hardly. And other, some other basic chemicals. Many other people would have not had in mind. Well, if you are a supply chain manager dealing with these products, then you should have an idea on where this actually coming from. And then this is, let me point to this one, because we see this also in the wider body of literature as well as in our own research. Looking beyond your first tier, this is a typical demand that you have by now. So your immediate suppliers, companies typically know quite well, but quite often already the second tier and, and issues that can emerge there not to talk of the, the third or fourth tier or something like this, then, then you have to have this in mind. And, but if you look at electronics where you are, the, the supply chain for a smartphone typically is something like eight to 10 tiers until you really reach, the extraction of, of cobalt in Congo or something like this. Yeah. And, and that's very hard to manage. That's, I, I would admit, but at least having an idea on where, where's this coming from? Where's the manufacturing taking place? If I need certain, rare earth minerals or something like this for, producing my electronics, then I have to have a feeling for how important is China in the production? What other sources are available? What, what can other countries do? and where do we from really from the source through all the processes? And my feeling is that a lot of companies still take this too easy. And that's then very, really at the end to end up in economic risk. And we have seen this multiple times, that the economic risk can be so big that you risk the bankruptcy of your company.

Tom Raftery: 15:46

Mm. Yeah. And I mean, that's where you're hoping that your digital supply chain investments are going to create value when they alert you to the possibility of this or when it happens, help you get out of it, right?

Stefan Seuring: 16:32

Yes, absolutely. I think this is now back again, back nicely to the podcasts because we did not analyse, look at just one, two, or three. We looked at 52. We got a much broader picture and, in a very positive manner, we got a broader picture, which was unbiased. We, we listened to people just talking without having to answer to a one particular question, but really telling a story from their businesses because that's what they typically nicely do in your podcast giving us insights into what's going on. And I initially started listening just to get a bit closer to, to say to practitioners without having actually to go there. So that's a nice, opportunity also on my side in, in doing this. And it once more provided us a much wider perspective than just a single person could ever give. Lara can most likely elaborate a bit more on the blockchain side. but, um, a blockchain where now is for me, partly an unfulfilled promise. I'm, I'm getting increasingly sceptical, but, uh,

Lara Schilling: 17:34

Yeah, maybe, two points to add to that discussion. So on the one hand side when you, when you were elaborating on, bias, Stefan, I would maybe like to add there that I think the nice thing about the podcast is that it gives a different bias than you would have in interviews, right? Because a bias is always there. The bias given by the way it's courted, the people are invited with which perspectives do they come, and also on, but it's typically different biases than you would normally have, for example, in the interview where you as a researcher come in with a certain idea, and then there is this problem that sometimes questions are asked in a way that you kind of shape the answer already the way you ask it. So I think that's, probably also one, one thought to that. And maybe then to the, blockchain as, mentioned that already. I think what for me is a lot about that puzzle in a way is that on the one hand side it's a platform or it's a idea that goes a lot about data sharing and coordinating in inter organisational ecosystems. That was the idea at the, beginning, right? But I think the problem, this decentralised architecture conflicts a lot with idea of focal firms of centralised control. And I think that is a big part of why particularly from a supply chain governance side maybe the, the hopes were high. I mean, there are also many other concerns more on the operational side. But I think from a, infrastructure and governance perspective, that's one of the big struggles of blockchain. Yeah.

Tom Raftery: 19:16

And what about some of the other technologies that were in there? I mean, you mentioned IoT, AI, et cetera. Are they proving their worth?

Stefan Seuring: 19:30

Yeah, I, I have not done too much more research on, on IoT, but internet of things I think is really taking on now. So we also see some overlap among these categories, but particularly in industrial environments, by now, you, can monitor, data that even 10 years ago was basically not available. And, it's changing production and, once more, maybe particular this, this intersection of IoT and AI, will now drive also the next generation of, of robots to a level which many of us most likely find hard to envision. And I, see this as, very interesting. And we might see robots moving into areas where we have not seen them yet. That should really be also one of these points because in the internet of things, we had a strong link to productivity, like companies really driving the things forward, really driving things forward, both for, environmental issues, reducing energy consumption, reducing other resource consumption, better data, more precise data. Any kind of material that I'm not wasting in the process is basically an environment where then as an economic gain, at the same time, I don't need to buy it. If I'm not wasting it. I don't need to pay for having it, put into waste garbage dumps or something like this. So it's, it's a, typical positive win-win situation that we can have in such cases. And IoT is definitely enabled these things that we see this in the wider body of, academic literature also reflected, that such positive levels can be achieved.

Tom Raftery: 21:03

And switching topics for a second. Technology providers made up 64% of the sample and failure scarcely appeared obviously, I guess. So how should leaders separate credible signals from hypotheses worth testing?

Lara Schilling: 21:24

Yeah. I think generally, of course, that comes also in the story of the biases, right? and in general that relates also to a wider societal phenomena. Discourses are created around technologies hypes, come up, language dialogue picked up on each other and they create a certain expectation perception, right? So I think it is actually very difficult also from a, a scientific perspective, not only for you and podcast to find out about failures because it's very easy to talk about success stories also in research projects. But people are less inclined to really talk about failures and to really dive deep into that. However, I think we, can learn of course from both the cases this are kind of good examples, but also those that just didn't work out right. And I think particularly as we talked about it earlier on the blockchain side, there have been now a quite of high hopes that turned out to be not really working out. And I think that kind of indicated us towards, okay, there seems to be a paradox in the way we envision the technology to be set up in the ecosystem and how it actually is realised in the way we organise supply chains, the way corporations take their decisions and, and these kind of things. So I think there we can learn a lot and, and we see that from previous technologies where it didn't succeed, but that's very hard to sometimes find.

Tom Raftery: 22:54

Having gone over it myself, one of the things that I've taken on board is that because precisely of that, I need to start modifying the questions I ask to try and pull out from the interviewees, you know, some failure stories. So I'm going to start asking things like having gotten to where you are now, what would you have done differently? So with that in mind, Stefan, having produced this paper now, if you were to do it again, what would you do differently?

Stefan Seuring: 23:31

Let me partly make a loop first because, I had been involved in another, more editorial task with, Andrea Patrucco one of the co-authors, and we edited for the same journal, also on the same thing, digital technologies and sustainability and supply chains. And out of about 50 papers we got submitted, there was not one single critical one. They were all the same positive stories. So we see the same bias actually in the research community. Partly the explanation is what Lara mentioned already. Typically people working in companies wanna sell positive stories outside and not failures. This is a huge problem for business administration, for management and all the research and knowledge generation, if we hardly can ever look at the failures. And this is so far that even bankrupt companies you cannot interview anymore. Fake people that failed in society, in psychology and sociology, they typically have access to it. A fake product is at least partly in marketing. Yeah, you can be, but, but, for us it's typically more the supply chain and the company level that is interesting. And that's a, that's a huge challenge in itself. So taking it from there, now I, I can be a bit, simple and say mmm at least the construct somehow worked and we got some results and it was not complete nonsense. Yeah, no, no, really positively taken. We, we got insights beyond what, I expected to get. We will definitely do something along the much larger sample of, data that is now available from your side, most likely really look more into the AI topic, which, which is the hot topic definitely at the moment and these kind of things. Typically it's also a bit of uh, and, and I think that's justified, particular from a research side of trial and error. So we typically, analyse with some more framings, with some more concepts, with some more ideas. And, and then we basically see sometimes the one thing works and sometimes the other thing works, but the, the coding is, so, the barriers that coding a few more categories is comparatively cheap to realising we have used the wrong categories and need to start it all over again. So that's why we typically, and to compare this into a bit of a picture, you need to choose, so to say, the right bullet for your target.

Tom Raftery: 25:47

Sure, sure. the implication there is that the archive is rich in success stories, but weak on failed implementations. And Stefan says, academic research faces the same problem. If we mostly study what worked, it becomes dangerously easy to mistake survivorship for a repeatable playbook. Lara, over the next three years, what do you think will distinguish firms that turn digital capability into resilience?

Lara Schilling: 26:17

Yeah, I think one very important thing is, and that came already into the picture when we talked earlier about how this digital infrastructure, the way we have set it up now, helps to very much give us a good idea of what is happening on the environmental side in the supply chain. I think the problem is that looking into the social side of supply chains remain very difficult. Because in the end at the moment, these things are measured, by surveys. They indicate something, right. And I myself have spent a couple of weeks a month in, in Ghana in the cocoa sector and try to see how actually is the European deforestation regulation implemented there. And to just give one example one can, for example, see that an indicator for child labour is whether there are schools around. And whether the kids of families can go to school. However, if the problem is coming from child trafficking, it doesn't mean that when your own kid can go to school, that there is no one else working no kids working on the farm. That's now a long tour to get to my point. I think what is really, really crucial is to contextualise and to understand what is really going on on the ground. And that is a super, super difficult task. However, I think our supply chains, the power and the resilience of our supply chain lies in the viability of social and ecological systems. And if the labour conditions, if communities if they collapse no one has anything. And on the more downstream side of the supply chain left. So I think for, many, many, many years, we, we have always thought about how can we, from a consumer side, maximise the, the value being delivered while we have overlooked really to sense the system. And I think in terms of resilience, this will make a, a huge difference on who actually can sense what is going on in the communities on the upstream side of supply chains.

Tom Raftery: 28:36

And Stefan, what did you expect the archive to answer, that couldn't?

Stefan Seuring: 28:47

one interesting point where we at least did not find anything that was, particular on continuity, which should relate very closely to resilience. And, and in this perspective, the data basically showed just nothing. That was one of the things which I found surprising. because, implementing a technology on at, one point in time, whatever you do, is definitely costly for companies. They have to make all of the investments and these kind of things. And then not looking at how to continue the story, but maybe that's also something for you to take a, along to, to talk to some of the, people in the, in the future on how do we actually make it a long term success, because that's definitely in, any kind of technology including digital technologies investment that companies do. That's what you definitely wanna see is that this makes sense in the mid to long run that it basically pays off, over time and it's nothing that you do shortly. You, would not invest into. Now I can just say all of what we've covered, internet of things, cloud, a blockchain, AI, you would not invest into this just for months. Even a company might eventually have to experiment a little and some things will work better and others will not work perfectly. But, the investment needed for, irrespective of the size of your company is, is definitely of a kind that you have to make informed decisions and that you have to, to look at how does this continue over the long run. And that was one of the surprising things where I expected more.

Tom Raftery: 30:16

Two blind spots have emerged whether the data reflects what's actually happening and whether the value lasts. So Lara, if a leader wants to move from visibility to resilience, where should they start on Monday morning?

Lara Schilling: 30:34

Well, that's a super, super difficult task because we are sitting so much away from this daily, okay, what shall we start doing tomorrow? But no, honestly, so I think, what particularly if you look into companies with multi-tiered supply chains maybe that have some subsidiaries in different countries and parts of the world, I think for me, one of the important things in terms of digitalisation and sustainability is that sustainability in the end is a concept. And we miss a lot of opportunities if we expect it to be conceptualised in the same way everywhere in the world. For a manager, it could be a good way to start on Monday to understand better what can it actually mean from where we source from to establish sustainability there. That probably may be very different than how people here, when I look out of the window in Copenhagen understand sustainability, and that's okay. That's, I mean, that's not only okay, we, we need to give different societies in the world, the space to make their own vision of these concepts, right? That could be something one can start with, even though that's a long-term thing, right? It's, not gonna be something that, will unfold in something measurable tomorrow, but in the end it will still go at some point in these indicators, right? It's just, the question of how you approach that.

Stefan Seuring: 32:00

I would just return to some of the beginning of our talk. First of all, check all of your risk management processes. In the business news, whenever something unexpected happens, and this was even the same for the, the river Rhine, not carrying water anymore this summer in Germany, a lot of people were surprised that, a lot of, fossil fuels are actually transported down south in Germany via the Rhine. And that's well known. And, and it's not what I do professionally, but even I was aware of it. And, and then companies being in related businesses, all over was surprised being looking at, how do we do it now? And then the, the, the idea came up. We can just go to lorries. No, we, the estimate is that we miss a hundred thousand lorry drivers in Germany. Even if you would physically have the lorry, you might not have the driver. We might come back to digital technologies immediately, because if the lorry could be just driven by a pod remotely, and the driver might not be in the car anymore, it would actually increase capacity dramatically. So we expect to see more changes coming up in the supply chains, uh, in recent years. And, one to autonomous vehicles, both for private passengers as well as for goods. But definitely also against. Um, and I would say for me, this is not a belief anymore. This is really relying on science, the move to electromobility. Yeah. The lorries, even the electrical lorries work by now.

Tom Raftery: 33:30

That brings us back to the central issue. Resilience begins before the disruption with a clear view of dependencies, alternatives, and the decisions a digital system is supposed to improve. So I asked Lara and Stefan to reduce the whole discussion to one test. Before approving the next digital supply chain investment, what should leadership be asking?

Lara Schilling: 33:55

For me one very important one is that oftentimes the, the digital infrastructure just mimics the way supply chains and power dynamics in supply chains are shaped, right? And therefore I think it's very important for me to look into these past dependencies. How are the dynamics in the supply chain and how do we envision to set up actually the, communication pathway? Because in the end, the question is also a lot in the paper we were talking about today, it's about visibility, but the question is also visibility to whom and who is taking decisions. So I think it's very important that digitalisation is not per se a phenomena that will resolve all our problems. We gonna get to digital democracy and all is fine. No, it inherently has the same challenges that we have in supply chain governance in an analogue and in a digital world. So therefore, I think it's very important to be very deliberate about that and decide on, okay, whom do we wanna enable? Which communication path? How do we want to share that? Who should be in decision making power? And maybe how can we distribute power? Particularly particularly if it's about also sensing risks in communities. Therefore, communities need power and visibility, right? But visibility for their own sake, not for anyone else to see them in that sense. So I think that are important question for me to consider, because I think that the past dependencies are very strong. Once the infrastructure is set up. It is very, very difficult to kind of redesign it. And of course most companies don't start with zero, they already have the digital infrastructure set up. So it's now much more of a revisiting, but in future decisions, anticipating always that the digital infrastructure set certain, past dependencies on how a certain organisation and the supply chain is covered and what can be seen and what not. Because that is also a risk. Everyone that is not part of this digital infrastructure is kind of left out, also left out of the risk sensing in that sense. So I think that would be my take on that.

Tom Raftery: 36:06

Okay, Stefan?

Stefan Seuring: 36:07

I, I can basically continue and I would, also emphasise the interplay of the different digital technologies. Because that's partly what our paper shows, but what you also learn from other points. AI can do certain things. IotT can do certain things. Cloud services can do certain things, but at the end you need to, organise this all into one, let's, let me say digital ecosystem in a company. First of all, it needs to work for the company itself, but as Lara just nicely explained, you also have to have in mind for whom does it work outside my company and for whom does it not work outside my, company. If I want to source, from certain people particular agricultural produce, then you might have to be aware that some of the farmers might not have access to such technologies. And so the, total, let me stay with the term ecosystem of the different things working together. I think this is one of the issues where, both managers as well as researchers still have, and a lot of open questions.

Tom Raftery: 37:02

Lara Stefan, that's been fascinating. If people would like to know more about yourselves, the paper, or any of the things we discussed on the podcast this morning, where would you have me direct them? Maybe Lara, you wanna go first?

Lara Schilling: 37:17

Yeah. of course these days in academia, but also in industry, I think of course LinkedIn is a place to find where we usually try to share our newest research updates also more smaller bits and pieces. So I think that's of course, a nice platform where people are ha happy to connect and follow. And then I mean, if it's more looking for academic articles, also the article we spoken about today, then typically Google Scholar is a good source to go to and look for the researchers' profiles there. Of course, you can also find us at our university websites. But I think the other twos are probably more recently updated in that sense in terms of content. Yeah.

Tom Raftery: 38:00

Sure, And Stefan.

Stefan Seuring: 38:02

I, I, I think this is perfect coverage. Yeah, that's, basically it. And, LinkedIn is particular a nice professional platform where you do so, also where I update myself on certain things, both on the practical side, companies writing something as well as, as Lara mentioned, also on the academic side. I'm not using other tools just to admit.

Tom Raftery: 38:24

Okay. Okay. Super brilliant, Lara Stefan, thanks a million for coming on the podcast today.

Stefan Seuring: 38:30

Many things. That was very great.

Lara Schilling: 38:33

Thanks a lot Tom.