AI can impact Supply Chain Management (SCM) outcomes. But many such attempts by companies lead to disappointing results. What’s missing? Why hasn’t AI delivered in SCM? What’s needed to harness the most value of AI for SCM?

Contributor

• • Rainer Steffl, CIO, Mondi Group

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Transcript

Sanjog Aul [00:00:22]:

Hello, and welcome to this segment on CTN. To learn more, please visit ciotalknetwork.com, and the topic for today is AI And Supply Chain Management, and our guest for today’s show is Rainer Steffl, who’s the CIO with Mondi Group. Hey, Rainer. How are you?

Rainer Steffl [00:00:38]:

Hi. How are you?

Sanjog Aul [00:00:39]:

Good, sir. Good. So 2019, amazing start, a very fast start. How has that started for you? How is your organization doing? How are you doing as a leader?

Rainer Steffl [00:00:51]:

We’re doing pretty good, I would say. So growth in sales is up from last year. January started as busy as December has closed, I would say.

Sanjog Aul [00:01:02]:

Yeah. January just flew by. So we are already in February. So that said, so now the question, that we wanted to ask today with respect to AI and supply chain management, and then let me set the stage. So supply chain management has always, as a function, tried to optimize because it connects itself to the efficiency, and lately, we are also looking at supply chain as a source of innovation. It could also lead to more customers or retained customers, and AI as an infusion of a disruptive technology can be used in that space, but is it just a tool which you want to and have been using in in other ways? Like, you’ve used different tools to get more visibility into supply chain and also reduce risk. So is AI just another tool added to that arsenal or there is something beyond you’re looking at when it when it comes to AI in context of supply chain management?

Rainer Steffl [00:02:11]:

I would say when it comes, is it a tool? It’s basically yes and no, I would say, but what we are doing for years is forecasting visibility of the tracks of shipments we do. What we just see is that the technology is much, much faster now becoming mature, and we are really preparing the next major step forward, I would say. So advanced analytics or pattern recognition is there since a couple of years, but really the big steps we’re making, I would say, since 1.5 years.

Sanjog Aul [00:02:51]:

So if you are looking at that and of course as you said the you said yes and no, so what’s the no part of it? Are you looking at a different way of thinking on how you’ll tackle supply chain?

Rainer Steffl [00:03:06]:

I think the challenge is that we have now the big promise AI and we need to get into the heads of the people that we apply the technology where it’s most beneficial for the optimization. We’ve seen it over the last couple of years, for example, in the sales forecasting, which is pretty normal and state of the art today, but we see that if you do it with the advanced technology, you can really get almost all the manual interventions out, which was like if you compare it 5 years ago, there was no way that you needed a lot of manual intervention. Today, the tools and the technologies are really capable of handling these processes by themselves without any major manual intervention, and the know-how is also

Sanjog Aul [00:03:58]:

Yeah, go ahead.

Rainer Steffl [00:04:00]:

And now we also see that the real, I would say, the real intelligence in artificial intelligence is very premature. So I believe we are pretty far off in having self-learning systems and doing all the decisions by themselves, and then getting back into the process or in the machinery, and we are still talking about concepts which are around since the 1960s or 1970s, I would say.

Sanjog Aul [00:04:30]:

So would you attribute that to the maturity in using technology in different areas for the Mondi Group as your organization alone? Or are you in a way making a statement regarding the industry as a whole where while AI is a cool tool that you could utilize to get the most value, but organizations are not ready yet to capitalize on it?

Rainer Steffl [00:04:52]:

I mean, I can only speak about the Mondi Group as such, but I think we see it from peers that artificial intelligence is here and there, but the progress is to some extent pretty disappointing. On the other hand, we see what’s coming around with Quantum Computing that the next major step is really in front of us.

Sanjog Aul [00:05:15]:

So Quantum Computing, if I understand correctly, is the underlying foundation or infrastructure which will support AI adoption. It’ll make AI doable. So are we coming in,

Rainer Steffl [00:05:28]:

I would say.

Sanjog Aul [00:05:30]:

Yeah. So in a way, can I interpret your statement as, okay, AI is there, but perhaps the provisioning, the kind of, real time availability of that intelligence, that artificial intelligence, you’re not able to provision because the underlying infrastructure is missing? But then there are organizations or services where they say AI as a service, where they can inhale all the data that you could provide them, and they would churn it in the cloud. They really don’t you don’t really need to care whether it’s been done using cloud computing or they put 10,000 servers behind it, but you can get the output. So are we truly waiting for the infrastructure to catch up at our own premises, or are you willing to go out wherever you can get that capability of AI? How are they provisioning it?

Rainer Steffl [00:06:23]:

I think we are ready to get it from wherever we can get it. This is not a topic for us whether it’s on-prem or in the cloud and we are having many cloud services in place already, and many of the, I would say, the things we do today like pattern recognition or sales forecasting is already coming out of the cloud. I just see the next major step around the corner with these new technologies, and I would say they will come definitely out of the cloud. So I’m pretty sure, as a manufacturing company we would not be able to build it on-prem.

Sanjog Aul [00:07:06]:

So let’s take the provisioning, howsoever we make it happen. Assume AI delivers to you. So the executive management not able to see where it can create value or we are beyond that stage of building a business case and they are ready to fund it, but now changing our internal processes and infrastructure to support that shift or adoption of AI in context of supply chain management because that’s the scope we’re talking about on this show today. Is that holding us back? Is it us not—I would not say ready, but it’s more like a work in progress that till the time all different pieces of supply chain are adopting AI, then it is half cooked still. Until the time you don’t have all different pieces adopting AI and AI is embedded in the very DNA of supply chain management, you will not be truly able to see the value. Is that the type of claim you’re making that we have to go all the way or half-baked AI will not cut it?

Rainer Steffl [00:08:18]:

I agree with that certainly. What we see is that we need to get the capabilities or the understanding what AI can do for supply chain into the heads of the supply chain managers. So they need to understand the potential of the technology. They need to understand what is really possible today, what is possible tomorrow, and then they need to embrace this new technology and then come with business cases or let’s say topics where we can add business value by applying AI throughout the supply chain organization. What we

Sanjog Aul [00:08:57]:

have decided. So

Rainer Steffl [00:09:01]:

what we have decided and done in the last couple of months, we have set up a thing which we call the digital boot camp which is also about what are the potentials of these technologies and how can the business leaders in the organization identify potential in their respective processes. We’ve set up this boot camp and now we are running it really full blown in the entire organization to cascade the knowledge of AI down to the business leaders, and I think that will unleash the potential and also drive the application of AI within the organization.

Sanjog Aul [00:09:41]:

When you talk about these supply chain managers, and you and I both know that you will not just put something like AI or any of the cryptic technology-centric output in front of them, which is difficult for them to comprehend. For a supply chain manager to actually get another insight that we provide them. So are they not able to envision what’s even possible? Is that where the limitation is? Or the solutions that we are putting in front of them, are they demanding certain data input which they are not able to provide, which renders it worthless. So where do these supply chain managers need to grow? Or where do they need to be resourced to be able to use AI to the fullest?

Rainer Steffl [00:10:39]:

I think at the moment it’s pretty difficult to identify the potentials within their processes because the picture as such is pretty blurry when it comes to artificial intelligence. In the end in many cases we confuse machine learning with advanced analytics, with pattern recognition, and I think the people need to understand what the technology can do for them, and once you have cracked that nut, I think then it’s starting really to roll. What we have seen through the organization that we also have within the supply chain organization, really different levels of understanding, and if you have people who understand the capabilities, then the project and the tools, they

Sanjog Aul [00:11:25]:

are really applied pretty straightforward.

Rainer Steffl [00:11:29]:

In our case, we’re not talking about when you do sales forecasting, these are not multi-year projects. These are pretty simple projects where you just take all the data, run it through the statistical engines, make projections and then compare it to what you already have and then you see that the engines can deliver extremely high accuracy. The tricky thing with identifying these potentials and harvesting these potentials is that you will only harvest this potential if you have standardized the processes beforehand. So this is work which has happened the last ten years basically, and if you have not your basic processes under control, then it’s pretty hard, pretty difficult to apply artificial intelligence on top, and then you don’t get a big leverage, in our case, between the factories. So what we have seen is that standardization is key and then having a couple of projects with people who understand the potential and then you can really go in a mainstream deployment of artificial intelligence.

Sanjog Aul [00:12:39]:

So you made a statement about the supply chain managers not able to envision what all they can do to exploit AI. So do you need Steve Jobs, the founder of Apple, who brought the iPad before people even thought that they could do computing like that? So do you, Rainer, need to become that Steve Jobs for the company or somebody from outside has to come and help simplify because should they care? Or are they the one responsible for envisioning how to best utilize or someone else could bring that help from within the company or from outside so that we just don’t wait. Somebody is to take ownership. If they are not able to, perhaps they were not trained. Supply chain managers were not trained to envision how AI can help them. So should some help come from outside?

Rainer Steffl [00:13:35]:

Tricky question, to be honest, because if you don’t understand the supply chain processes within the organization in detail it’s pretty difficult to come in from the outside. What we have seen is that it’s pretty effective if we just give them the basic concepts in a very easy and digestible form and then they start to grasp it. We don’t believe in big armies of people from the external world coming in and explaining to them what AI is and not being that tangible for them.

Sanjog Aul [00:14:14]:

So that said, let’s take a quick break. Listeners will be right back, and let’s talk about the specific areas. So while we, of course, understand that supply chain managers are attempting, they have all the intention and are willing to put their heads together to understand how AI can help. At least that effort is going on, but the results also make an impact on how motivated everyone feels. So let’s talk about the accurate forecasting of the demand behavior which would actually help you optimize inventory levels. That’s just one use case of AI, and then there may be other use cases which at least have been identified by supply chain managers and others? Have we been able to adopt them and see value coming out of AI? Because then the speed wheels will start spinning. Is that truly happening? Please stay tuned, listeners. We’ll be right back and explore.

Speaker 0 [00:15:24]:

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Speaker 0 [00:15:51]:

Patient centered care requires a connected enterprise. Are you ready? If you’re looking to scale your health care IT efforts, visit RedMaine.com/health today. Whether it’s to connect data from multiple partner solutions or developing software for unique needs, RedMaine can help. To find out how RedMaine can help your company deliver on the patient centered care promise, visit RedMaine.com/health or call (773) 693-3919. Visit today.

Speaker 0 [00:16:25]:

Your growing business needs a highly productive workforce, effectively communicating and collaborating without exposing corporate data to cyber attacks. Are you looking to balance security and workforce productivity? Move beyond short term measures and securely scale your business with BlackBerry Enterprise Mobility Management Solutions. To learn more, please visit blackberry.com/enterprise. You are listening to CTN, CIO Talk Network with Sanjog Aul. To learn more about our program, please visit ciotalknetwork.com. Now back to the show.

Sanjog Aul [00:17:14]:

Welcome back. So, Rainer, there is, of course, not rejection, but at least reluctance to go all the way with AI because, either the supply chain manager is not able to figure out what use cases they could be using, or perhaps they have not seen as much success. So what is the reality on the ground? So let’s take a few examples maybe you can share some of the specific use cases with supply chain leaders thought or managers thought they could improve upon by using AI. What are some of those cases? And when you try to adopt AI to support those use cases, what was the result?

Rainer Steffl [00:18:00]:

Okay. I would just take the sales forecasting example once again. Sales forecasting is around, I would say ever since, and like 15 years ago, everybody did it with spreadsheets and calculations, and what we have done in that area, we just walked in and say, okay, guys, here’s some piece of technology which can help you, and we were running within a couple of days the entire sales forecasting through an advanced analytics platform engine and we’re showing them how we can forecast the next 12 months on IPIM level pretty accurately, and it was then pretty clear in a couple of days and that’s the beauty of most of these tools that you can make a pilot or a POC or a proof of technology within a couple of days, and you can then break the ice effectively, do it in a pilot factory and then we roll it out to all our factories and we have around 100 factories, and we go really from topic one to topic two and then topic three. In the sales forecasting, we have started, as I said, a couple of years ago where people needed to review the forecast manually, sales guys were looking at it. In the meanwhile, the systems are doing it completely by themselves and they are even feeding this sales forecast automatically into our production systems without any manual interaction, and with this example, you see that you need to really, I think, also give AI in small steps to the organization and not go from a brutal manual process to a fully automated process, because then you have lots of, I would say, discussions going on. Is this really true? Can it be happening? And then you have a discussion on the process rather than the technology. A second example would be that we have worked extensively on supporting with robotics automation our month end closing, and as in any big organization month end closing is a real hassle where people are under pressure and they have to close the books in 2 days and people work long hours, and we were just walking in and having a lot of, let’s say, hassle with the process because it’s pretty time consuming and say, what if we do the complete process with an intelligent robot during the night and then in the morning the accountants and controllers are just coming and looking at the work of the robot and doing exception handling. When we started that, everybody was looking at us and say this one worked, it’s pretty crazy, and we just then tried it out in 1 factory and let the people then look and see what the robot can do for them, and then the people understood the power of this application of artificial intelligence and since then basically it’s going from one factory to the other without any need of selling or convincing people. So what I’m trying to say, I think you need to convince the people with very small tangible projects and then scale it as fast as you can and then deploy it to the entire organization, and with these two examples, we see that people slowly understand what’s the power of these technologies.

Sanjog Aul [00:21:50]:

So one thing which definitely comes up when you talk about supply chain is the disparity in terms of the resources available, the profit motivation, or the strategy of individual players in a supply chain. I might have a different agenda than my supply chain partner. Yes. We want to work together. Yes. We want to make money, but we are not 100% aligned at all times. So if we are going to look for AI driven capabilities in, say, Mondi Group, then what about your distributor? Or what about your upstream and downstream players? Is everyone exactly on the same page? But if they are not, then how do you expect all of them to be able to come together and benefit from this technology? Because AI might support you in some use cases where your partner also should have adopted the same. You can talk about, say, you collect data from sensors or radars or video cameras, smartphones regarding weather or traffic congestion, etc. That might be important for you and also for your partner, but are they deploying the same technology? Are they working—suppose you are able to reduce your time for a response from 10 seconds to 2 seconds but if the other partner that you have doesn’t do anything your sum total is still 10 seconds so whatever that total number of seconds you need to deliver something. I’m just trying to make an example here, but are all links in the supply chain thinking like one entity or they are doing their own thing and then expecting miracles to happen by using a technology like AI?

Rainer Steffl [00:23:39]:

I think not everybody is on the same page certainly, and if you take a look at our customers and suppliers, we have, I would say, a big variety within that customer and supplier base. So we have a lot of organizations who are working with us in a very collaborative way to sort out the supply chain topic, but we also have a big group of customers or suppliers who simply don’t have the resources, being manpower or financial resources to go on the journey, and if this is the case, then it’s getting really tricky because you are, as you say, then you end up with different priorities and you have virtually no chance to be successful. With the organizations who are embracing technology in the supply chain, we are really working together in a collaborative way, and these are typically companies who have already invested a lot of energy into EDI and we start from, you know, going on a from a very IT driven process already and taking these processes to a higher level.

Sanjog Aul [00:25:06]:

So the way you explained it, are you in a way saying that there are different people working differently? So do you have a, like, a normalized expectation on what would be the outcome, or is it just hazy right now? Are you gonna just struggle through this and see whatever you get as value from adopting a technology like AI is just a blessing? You will not truly be working on optimizing so that all parts of supply chain are actually working together.

Rainer Steffl [00:25:41]:

I would say not bluntly or not just for the sake of working on it, but we are always looking for really a financial benefit or an improvement in the process and then we jointly agree with the customer or supplier to sort that particular problem or to increase that particular efficiency, but we always link it to financial benefits, and I think that’s the tricky thing at the moment. With the customers who are already pretty tightly integrated, the expected benefits compared to what you already have are pretty low. Just one example, if your value chain is working completely via electronic data exchange and all the interfaces and systems are already wired, then it’s pretty difficult to show really a benefit with additional technology on top of these processes if you compare the investment required for these technologies.

Sanjog Aul [00:26:56]:

Now looking at the kind of warehousing capabilities as we hear, say, Amazon has it or some other bigger players have it, they are using AI-powered robots. Would you think that AI will remain or continue to go in a direction where whosoever has the more dollars, more muscle are the ones who are gonna always stay ahead? Or do you think there will be some, not truly a socialization, but a level playing field of availability of this technology that everyone can use it no matter who, which in a way will help you optimize your supply chain as a whole versus only the biggest player is able to adopt AI and others don’t?

Rainer Steffl [00:27:41]:

I mean you will certainly see that the bigger players have the best technology in place. If we look at Mondi and if we look at our big factories they all have pretty advanced warehouses, a lot of robots and are pretty much automated.

Sanjog Aul [00:27:59]:

But these are really big places. These are really, let’s say,

Rainer Steffl [00:28:04]:

I would say that they’re money houses of the organization. If you look to our smaller factories and we have also a couple of them then it’s extremely difficult to calculate the benefit for an automatic warehouse for a pretty small factory, and if you compare that, I would say, if you take the Mondi comparison from a big company versus a small company, I think you will see the same. The question we have not answered for ourselves yet is will the need for automation in warehousing and logistics force us or other companies to implement bigger plans and to consolidate the factories? Because certainly with all the robots, I think it’s pretty difficult to calculate an ROI for a small plant with a need for an automatic warehouse.

Sanjog Aul [00:29:05]:

Now what you just shared, let’s talk about the ability for the smaller players. So when you always say that the larger players have the biggest technology, do you think AI will become available if you were to play like an industry analyst? Do you think we will go in a direction where the amount of money or overall clout we have will not drive the adoption of a certain technology, which could enable the whole supply chain, not just that one player. Is that where you guys are moving as an industry?

Rainer Steffl [00:29:49]:

I have some difficulties to see that honestly. I see that technology is getting cheaper. We have always seen it in the history of IT that that will certainly happen, but if the big organizations are using the advantage, we don’t see that at the moment. The question is for me the other way around, will the technology drive consolidation of the smaller players? I think that’s an interesting part which we need to observe.

Sanjog Aul [00:30:40]:

So when we are looking at AI and this is a very direct question that comes whenever somebody talks AI is that is it going to replace or displace people? And when one is to go to supply chain leaders and managers, who might start thinking whether this is going to displace their own people or even themselves? Do you think that is the reason for passive resistance or not really making the best use of this technology in supply chain management? Because frankly, those people are very used to doing things manually or with some automation and IT systems but not the most cutting edge, and that has kept their jobs alive for many years. Do you think AI is a threat to them?

Rainer Steffl [00:31:32]:

I don’t see it.

Sanjog Aul [00:31:33]:

Please hold your thought. Let’s take a quick break, listeners. We’ll be right back and then talk.

Speaker 0 [00:31:47]:

Your growing business needs a highly productive workforce, effectively communicating and collaborating without exposing corporate data to cyber attacks. Are you looking to balance security and workforce productivity? Move beyond short term measures and securely scale your business with BlackBerry Enterprise Mobility Management Solutions. To learn more, please visit blackberry.com/enterprise.

Speaker 0 [00:32:18]:

Patient centered care requires a connected enterprise. Are you ready? If you’re looking to scale your health care IT efforts, visit RedMaine.com/health today. Whether it’s to connect data from multiple partner solutions or developing software for unique needs, RedMaine can help. To find out how RedMaine can help your company or call (773) 693-3919. Visit today.

Speaker 0 [00:32:51]:

Predict your company’s future by creating it. Is your workforce able to connect, exchange ideas, and share brilliance simply and securely? Create tomorrow, today. Empower your people to innovate anytime and anywhere with secured BlackBerry Enterprise Mobility Management and document sharing solutions. To learn more, visit blackberry.com/enterprise. You are listening to CTN CIO Talk Network with Sanjog Aul. Now back to the show.

Sanjog Aul [00:33:32]:

Welcome back. So this question that I’m gonna ask was the one which I posed earlier before we got into the break, about the job loss or the potential job loss or the displacement of workers. Supply chain as a department and the people who work in there, they come from different levels of education, different levels of economic strata, but they all have to bring food to the table for themselves and for the families, and supply chain has traditionally been keeping people who are long timers. So now with such technology, which will and which is already showing examples at least in larger companies where, as I mentioned, like warehouse could have these robots which are AI powered and they are displacing quite a few workers. For you as an organization or anyone in your supply chain, this fear will exist among the very people who you are expecting to adopt and come up with ideas to best utilize AI. Do you think you are dealing with a lost battle because nobody is going to take food away from their family to make your organization more cutting edge in terms of what technology you use?

Rainer Steffl [00:34:54]:

I think the first part of the answer is the fear and I think the fear is certainly there. So that’s clear that with all that hype around robotics and artificial intelligence, people have fear, I think that’s a given, but if we look at what we anticipate as an organization how this will impact our employment setup, we think it will not be as dramatic as you might hear in the news. So for example, as I said earlier, most of the factories have already automatic warehouse. Or for example, if you take a paper machine, a paper machine is basically like 50 meters long and 3 stories tall, so that’s a big huge machine, and what you have on the shift right now are a few people to manage this paper machine. So it’s only 3 guys who manage this monster machine, and we are really light user way of reducing these 3 additional people because first of all you have the topic of safety. So you always need when you have big equipment, big machines to have people around in the case of emergency, and on the other hand, there is basically we are light years away, I would say, of artificial intelligence interpreting all the sensors, all the data from this machinery. Just as an example, a paper factory typically is around 40,000 sensors. So having this in an artificial intelligence solution and letting the solution automatically adjust and drive the machine, at the moment we believe this is pretty unrealistic, and what we are trying to do is explain these things to the workforce and, yes, building trust with them explaining what we do. We see more leverage in getting more out of the existing machine. So rather not replacing the workforce or reducing the workers, but increasing the output of running the machines better with artificial intelligence, and I think there is the leverage for our company.

Sanjog Aul [00:37:25]:

Anything like this where you’re trying to get people to start recognizing, start basically reemphasizing that they can trust you, that they will not lose their job or you’ll be able to help them retool. All of this is part of change management. Who, for the sake of making sure there is a good adoption of AI happening, and eventually supply chain flourishes, who should be or is taking the ownership of this change management? And in that whole change management endeavor, what role is the CIO supposed to play?

Rainer Steffl [00:38:07]:

In our organization, the CIO is playing a supporting role because the change management, if you really want to drive it into the entire organization, it starts with the CEO, that’s pretty clear for me. So wherever he’s talking to people in virtual employee meetings or whatever, he’s talking about those fears and trying to explain what we are doing, and then it really cascades down to the first line manager and they need to speak the same language and explain to the workforce what’s happening. Because people have fears as I said and you need to—you cannot just swipe away the fear. You need to explain it in a proper way, and therefore, you need the full hierarchy within the organization to sing the same song. Otherwise, you just amplify the fears of the workforce.

Sanjog Aul [00:39:01]:

So when you speak about this, since AI is a technology and I know CEOs will talk about, okay, you gotta have faith on us and things of that nature, but perhaps, if you educate people, their fear could go down or reduce. So do you think the CIO could play a role in truly educating how AI is going to help them and it is not truly going to take their job away, etcetera. So do you think in your role as a CIO, you are in a position to add value in that change management?

Rainer Steffl [00:39:40]:

Clearly, yes, because I need to explain also to the other managers so they can explain it to the workforce what’s possible with technology and what not, and I think we need to break it down and we are breaking it down to what this technology can do and what not because if people just hear robots and they hear artificial intelligence, they then just have horror stories coming up in their mind, but if you explain this in a proper way and make it then tangible for the people, then I think it’s pretty straightforward to help the organization, and this is certainly the role of the CIO.

Sanjog Aul [00:40:29]:

Talking standards and governance. So supply chain for it to be predictable has to have standards and has to have governance processes. If you were to look at what it was pre-AI era or the companies who are looking to adopt AI because you’re gonna fundamentally shift quite a few processes, you might automate some and you might rethink the others. So you cannot really be living the same old standards and same old governance processes when a supply chain is AI enabled. What would you say is a good blueprint or an approach someone can take in an organization when they are adopting AI to make sure that standards and the governance approaches are totally conducive after AI has been adopted?

Rainer Steffl [00:41:28]:

I would say first thing is you need to get yourself familiar with the potential of the technology. You need to understand what AI can do for you and what it cannot, and I think it’s more important to understand what it cannot do for you to understand it precisely. The second thing I would say, you need to look for the business value and not just do a pilot here, pilot there without any clear plan. So I think you need to have that in mind where the potential can add value because otherwise you would kill the technology with, I would say, useless pilots, and I think the third thing is you need to be aware where you are with your existing supply chain, whether you are standardized or you are not standardized, and if you are able to scale artificial intelligence company-wide or not, and if you’re not able to then I think you should refrain from it because otherwise you’re not creating the value for the organization.

Sanjog Aul [00:42:33]:

So what you just described is of course when you’re getting started you will take a few precautions, totally understand, but if you were to put say a comparison chart and you say this is how we used to standardize the ways we used to handle supply chain pre-AI era, and this is how we will do post-AI era, whether you talk standards, you talk interoperability among partners, you talk about governance, what material changes, say, Mondi Group may have adopted or you’re thinking of adopting or tweaking your standards and governance with respect to supply chain just because you are bringing AI into the mix?

Rainer Steffl [00:43:24]:

I think in our case one of our values is passion for performance. So we embrace change and we like to have people who love to change and improve the current situation, and I would only go in with AI if you have the feeling that the people who are involved in a specific topic really embrace change and are prepared to change their existing structures, and you get a good feeling when a certain manager or a certain team has changed the way of working in the last couple of years, because also in the pre-AI era there was change, and we’re not sure what the post-AI area will be. So the only constant thing in that area is that you need to embrace change and need to be passionate about improving the current situation. I think then you are pretty safe when it comes to AI.

Sanjog Aul [00:44:38]:

So now let’s talk about—or maybe what we should do is we should take a quick break, but when we come back, let’s talk about AI and security because security is of course on top of every leader’s mind, and when you bring AI it means you are essentially leaving the decision making and execution to a piece of software and it can very well be exploited and the damage could be way bigger before you’d even come to know. So what are organizations doing or are supposed to do before and during and once they’ve adopted AI to make sure they don’t lose their shirt because they adopted this otherwise disruptive technology. So please stay tuned listeners. We’ll be right back.

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Sanjog Aul [00:47:23]:

Welcome back. So, Rainer, when we talk about security, security in an AI-enabled supply chain environment, it means what you do within your four walls, what your partners do, the supply chain partners as the data is shared among all different parties, and all along making sure that none of those links are the weaker links which somebody can hack into and also make you vulnerable. So is this a battle worth fighting? Are you fighting it? If yes, how? And what successes are you able to showcase so that the business says, yes, I’m willing to go all the way with AI enabled supply chain initiative?

Rainer Steffl [00:48:16]:

Well, first of all, I have to say, in my role as CIO, security is my priority number one. After priority number one, there’s a big void and then comes priority number two. So whatever we do has to be secure and safe and sound. What we have decided pretty early when we started to apply these technologies is that AI has to be within the security framework of the organization. So there’s no shadow running somewhere not managed and operated by the IT department, because we want to make sure that it is safe, and we see the data we have within these tools as an asset of the organization. So we need to protect the data, that’s pretty clear. We need to make sure that Mondi remains in possession of this data and nobody is able to walk away with our data or to steal the data as such. When it comes to AI taking decisions on our behalf, ultimately it comes down to, I would say, a security net where you have structures in place which verify the decisions the tools have taken, might be some checks afterwards or a proper testing before, but as I said before it’s pretty clear it has to be within the IT framework and by no means can be outside the IT framework.

Sanjog Aul [00:50:06]:

So when you spoke about security and the way you responded, am I okay to assume that this is just the way your organization does it? Do you have any interfacing with all the different supply chain partners and is any coordinated effort to tackle security across supply chain? Because as you know, whenever you integrate systems in a supply chain, you’re only as good as the weakest link?

Rainer Steffl [00:50:37]:

We would only work together with partners in the supply chain where we have a mutual agreement about security and how we treat the data and how we treat the applications there. What we also see and what we also do with our suppliers is that, for example, our customers are coming and say, okay, we need to do an IT security check within your organization to see whether you are safe and once we agree that partner A and partner B are safe, then we deploy AI or any other tool between our organizations. So I think this comes as a really the basics. In the meantime, in many cases the first question before we start to collaborate is that we agree on the terms of security, we exchange the standards on how each of the companies is working, and what we also see increasingly is that within the legal framework between the two companies, we have the audit rights of the companies in the legal framework.

Sanjog Aul [00:51:53]:

So the question that I will have for you now would be around the specific changes if you were to recommend going as a consultant to another organization which wants to apply AI in their supply chain. What would be the top few changes you would like to recommend upfront so that the organization becomes the very conducive foundation for them to adopt AI? Because the responsibilities on the organization to adopt AI—if they don’t, their competitor will.

Rainer Steffl [00:52:32]:

So the first question I would ask is what do you want to achieve with AI? And I think it’s not about all the marketing and parts around AI. The question is what problem do we have and what situation do we want to improve and what’s the financial benefit of doing it? And I think if you ask that question at the very beginning, the likelihood that your project or application of AI will be successful is much, much higher than if you just say, okay, let’s do a pilot, let’s try it here and try it there, and therefore, if you do it in a way that you ask for the business value, I think then you’re pretty safe and sound, and the rest you can sort out.

Sanjog Aul [00:53:20]:

And the last question I have for you is around the leadership. So you are a leader. I’m sure your counterparts in supply chain are leaders themselves, but then would there be any shift that you would like to make in your leadership style and the mindset for you to help your organization embrace AI in the best possible manner?

Rainer Steffl [00:53:46]:

I think we are over that already. Our management team is really embracing the power of digitalization and the power of artificial intelligence, and now we are really running as a team in the right direction, but we hit this storming and norming phase at the beginning, which was pretty important because then we moved everybody onto the same page. So at the moment, I would say I’m pretty happy as an organization how we deal with these topics, and as I said before, we are a company who is really embracing change and has this passion for performance. So the natural reaction towards AI in our organization is how can we use this to improve the performance and then we have got it rolling already.

Sanjog Aul [00:54:44]:

On behalf of the show and our listeners, thanks so much, Rainer, for sharing your thoughts regarding the steps organizations can take to adopt AI for supply chain management. It was a really useful and meaningful insightful conversation. Thanks so much for your input.

Rainer Steffl [00:55:00]:

Thank you as well.

Sanjog Aul [00:55:01]:

Thanks so much and listeners hope you enjoyed it. Please like us on Facebook search for CTN and follow us on Twitter and join our LinkedIn community and please go ahead and find us on different podcast platforms. We are on Spotify, iHeart, TuneIn, iTunes, you name it. Please listen. Give us your rating so that we can learn and benefit, other people can benefit from this. So thank you again for listening to this segment on CTN. This is Sanjog Aul, your talk show host. Till next week take care and God bless.