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Industry 4.0 is a crucial concept for the modern business but how do we ensure businesses are ready for the digital future? IgniteSAP would like to draw attention to some of the great content available for SAP professionals on LinkedIn that can be used to keep up to speed with our ever-changing industry.

The SAP LinkedIn live chat webcasts cover a wide range of SAP subjects. This week IgniteSAP has selected the live chat from SAP Digital Supply Chain entitled #industry40 Insights Live: Getting the Foundation Right.

The chat is with Andy Hancock and Ronald Van Loon of Intelligent World, and covers material around how to prepare for, and implement changes to businesses and best practices to make them ready to take advantage of all the benefits of IoT, Automation, AI and Machine Learning.

The video content can be found here, and for the convenience of our community we are making a transcript of the chat below which can be used to jump to search for specific topics within the conversation.

[Andy Hancock]
Hello, everybody. My name is Andy Hancock and today we’re gonna go live with industry four insights live and getting the foundation right. And today in the conversation that I’m going to have, I’ve got Ronald Van Loon who, Ronald, Why don’t you introduce yourself to everybody?

[Ronald van Loon]
Thank you, Andy, for having me. It’s a real pleasure. I’m Ronald Van Loon. I’m the CEO and the principal analyst of the Intelligent World, which is a platform where domain experts share their knowledge from the tech industry on a daily basis, and it’s a pleasure to be here.

[Andy Hancock]
Wonderful. So you know, I want to go through a few questions that we can have a discussion about that are very topical at the moment. And the first one really is talking about the challenges that our customers were seeing in the supply chain and manufacturing, you know, because of all the constant disruption, what are you seeing out there with your customer base?

[Ronald van Loon]
If, we looked to, let’s say, the last 18 months, COVID-19 has really put some kind of spotlight on the impact of the disruption as supply chains were struggling with, with all kinds of issues from employees working remotely, but also raw materials shortage, of course. And when employees needed to work remotely during this pandemic, they didn’t have the right tools and the right technologies that helped them to collaborate or to bring them the visibility into the entire end-to-end supply chain so that they could better manage the disruption to the supply chain network, which is it’s quite a challenge.

But also what we’ve seen in the last 18 months, but also I think before is the legacy it and the OT infrastructures that are limiting supply chain capabilities, they’re creating bottlenecks. And they create other weaknesses that are stalling the industry 4.0 type of investments that are necessary to responsive, and on the other hand, to adaptable processes and to adaptable operation.

So that’s, that’s a couple of them. And also, when you look at the supply chains, that didn’t implement 4.0 Solutions prior to the pandemic, they had already, I think, a hard time catching up without digital solutions. And really, they had hard times when the disruption hit during this pandemic, but supply chains: they are dealing with all the challenges. Well, you can think about cash constraints and funding issues, for example, and having the teams and the employees focusing on other problems and struggling to solve the issues outside of their existing job responsibilities, and especially when they had to shift work from home, and the job roles did change as well. And when it comes to driving the the industry 4.0 and the industry 4.0 type of solutions, I think they have an overlap an overall lack of of skills and knowledge. And we see as well and understanding of the technology and understanding of the process, and understanding of the operations and strategies that are necessary for successful digital adoption. And I think Lastly, organisations are challenged by cybersecurity capabilities that are necessary to safeguard the quality of the product and the service delivery, the processes and of course, the systems. So, like mentioned before, we have the legacy of IT and OT that are contributing to these type of weaknesses in the supply chain. And this extends to the cybersecurity challenges. And we see that businesses struggle to unite their business under it operation so that they can secure the business network govern the access to data analytics, which is a key for your supply chain nowadays, and monitor the behaviour.

So supply chain networks receded they are complex, and especially on the global scale. And when businesses have to manage the partners and suppliers, they are increasing the risk and controlling the data access. That seems to be very difficult. So that’s what I see as the main challenges from this last, let’s say about 18 months, but also of course this was there before as well.

[Andy Hancock]
Right. Yeah. I mean, we, from our perspective, from SAP’s perspective, we’re seeing a lot of companies being forced or even compelled to do things differently. Exactly to you know, with the OT IT Convergence that we’re seeing, and various other things that you mentioned.

Now I want to remind everybody that we are live and I want to say hello to France, Germany, US, India and Tunisia. So please put your comments and questions down and either myself or Ronald will hopefully answer them.

So Ronald, you know when we’ve seen a lot of news, you know, we’ve got the chips shortage in the motor industry over in the US. We’ve seen issues around oil, petrol tankers in the UK, are you seeing all the challenges across the board? Or are there just particular industries that are calling out to you that are suffering more than most?

[Ronald van Loon]
Now, of course, some are suffering more than most. But I think these are very common challenges for organisations across the industries amidst this disruption. And amidst this digital transformation, every step that we have seen, so industries, you mentioned already on oil and gas, but also automotive, travel, transport logistics, they have issues well, but I think they’re doing really well and implementing industry 4.0 type of solutions, and they were able to better respond to to this disruption.

On the other hand, what you were mentioning energy, consumer packaged goods and consumer packaged materials, they are struggling more I think then than others. So some industries are impacted differently than the other industries.

If we look, for example, aerospace, to have to deal with demand of suppression, energy and materials, what do you mean, I’ve seen both the prices demand decrease as well. And, and now it’s increasing, at least in Europe, we see an explosion of gas prices. With CPG. And with medical, we see a lot of high demands, and they have really difficulties in keeping up. So it’s different type of problems. But companies, I think they’re really trying to put their perspective into the value of flexibility. And they trying to be resilient as much as cost and efficiency, focusing on the cost and efficiency.

Maybe they take one more industry, for example, the medical industry, if you look to the pandemic, I think the pandemic has proven medical companies need to be adaptable, while at the same time preparing for this new normal, they have to switch during this, this Covid pandemic all the time, and they have to adjust the inventories, they have to account for high volatility, and changes in demand for supplies and for patients that they have. And this really impacted patient care. And they really were challenged, I think to the utmost and they are struggling, I think with visibility, like many organisations are in the supply chain, and they need to access this centralised real-time data if possible, from all the different silos that they have, and all the different data sources. And that’s quite a challenge. And especially if you look from an healthcare perspective on a national scale, so it’s difficult to know for these type of organisations, what items and what resources are in stock, what they need to procure, due to this change in, let’s say, the supply and demand. And during the pandemic, as well, we see medical supplies and we see protective equipment demand and cost became very high, basically exploding. And since there’s a lot of lack of visibility, alongside I think with the data integration challenges that these organisations have from the different disparate data sources. Also, you’re driven by a regulations like GDPR, and privacy regulations, we see that materials either being wasted, so to have them in stock don’t use anymore, or inventories at maximum capacity

So it was quite hard for these organisations to manage that. And I think what’s more, a unique type of challenge for the medical industry is that they also have the mergers and acquisitions. And this has been accelerated as a result of the pandemic. And as a way to help them with cost savings. But that makes it even more difficult to get the visibility in the supply chain. And yet this created even more fragmented team more fragmented processes and integration challenges.

So yeah, to conclude, I think some suffer more than others, some seem to have, let’s say, rather well, and they can thrive right now if they have been prepared with a platform for industry 4.0 and these organisations, so they, they thrive Well, I believe.

[Andy Hancock]
Yeah, I mean, if you imagine if you take from a supply chain perspective, that the original model was OK, then let’s reduce costs to everywhere in order to give us growth. And you know, that has definitely become a vulnerability during the pandemic, as you know, there’s been restrictions with labour and resources that cite raw materials actually getting to places, those sort of things.

I also want to say, a call out to Canada, Australia, Nigeria, London, France. So we’re getting a global audience right now. So, you know, you did mention something about, the foundation. So let’s, let’s talk about that, just like building a house, a strong foundation really is is important. So, you know, when you talk to your clients about these problems, and what are they asking, What are you seeing? And then, where do you start suggesting that cloud is the answer to the problems?

[Ronald van Loon]
Cloud, indeed, is a very important, I think foundation for thriving, and not only in the supply chain, but on all different kinds of aspects. And adopting cloud is not like, okay, I switched the button. And now I’m a cloud driven organisation, cloud is a journey, and organisations that experience problems in the infrastructure that create all kinds of constraints that make it difficult to embrace transformation, such as the ability to scale your products or your services. Or they struggle with with storage, or they struggle with compute capacity as well.

So if I speak to these organisations, I suggest that organisations start with building an IT strategy, and its IT strategy that connects their business goals, to their IT goals, so it’s up to the C level to work with, with other leadership teams within the organisation to set these type of objectives. And they have to create a relevant use case, and start using the cloud to enhance all these different kinds of ways that they work as well as using the cloud platform itself.

But I think it’s important to start small. So for example, if you look in retail cloud can be used for use cases such as inventory optimisation, or you can think about product and service development using sentiment analysis for your prediction. But you can also think about oil and gas, where they can use Cloud for use cases such as parameter optimisation or automated forecasting. Other cases, which we see is in banking, and they can use cloud to improve on the digital advertising and enhancing the product or recommendation and service recommendation.

So we see that IT strategies, they can use cloud, break away from these traditional legacy processes in order to want to lower the cost, but also their associated IT or risk in their IT systems and in their IT structures. And traditional methods for managing applications using an on-premise infrastructures. They are inefficient.

So one of the problems is that moving existing applications to the cloud, it can be costly. If there’s, if they’re not optimised correctly. So you have to have a proper plan in place but the cloud enables ways to work much more productively, and then you can think about productively working with API’s or with self-service workflows and automation as a foundation. And the focus should be should remain basically on business development when starting with the cloud, and not so much on the infrastructure. Really look from a business perspective and organisations need to build a culture The teams around it and built on the literacy of technology and the literacy of cloud, and as employees are more introduced to new cloud-based type of workflows, they will see the benefits.

They will see the benefits for example of reduced downtime from security breaches, because security process can be automated much better in the cloud. So what we see if digitisation accelerates, organisations, they have to rescale they have to upskill the employees so they can focus more on high value type of skills that are required high value type of projects, such as more customer service driven or maybe even more product development type of activities that they can work on. And organisations can be prepared to to innovate with clouds using advanced analytics and using automation. And to give an example, they can use predictive maintenance for product quality management or using demand forecasting for for healthcare, for example.

So using the cloud: start with strategies that connect IT to the greater business goals of your organisations, and then implementing cases that that use the cloud to help your employees realise the potential of their own capability. So it has to support them and not scare them, of being redundant. Help them with the upskill as well and help them with it: managing their workflows better. And this way they can use the clouds as the foundation for new technological, technological adoption and for more and better innovation.

[Andy Hancock]
That’s wonderful, we actually have a first question here. So Rohan from Accenture says “will SAP do something related to green projects to overcome the problems related to the environment?”.

I guess that will be for me to answer it. So the way SAP is looking at it, particularly, you know, when we think about cloud solutions, is through industry cloud and looking at circular economy. So really connecting all aspects of the supply chain from design, through manufacturer, to the logistics delivering of it, to operate. And by connecting those through a digital thread, you then get visibility. So when you do the cradle to grave scenario of an individual product when it comes to actually decommissioning that product, without having an understanding of, you know, what can be reused in something else? What is recyclable? And then unfortunately, you know, what is what is landfill? So if you go on to onto sap.com, there’s a section on there about sustainability, which will then explain what are the green projects that we’ve got going on at the moment.

Let’s have a look. Next question. So, you know, we talked about the legacy. And so when we talk about legacy processes, we always come across the first stumbling block of anything, which is, you know, pilot purgatory, everybody, you know, it was good ideas to start, but really, you know, scaling out from that, that boardroom pilot out into the enterprise, you know, what are you seeing, that’s actually a successful method to address that?

[Ronald van Loon]
Yeah, it’s a globally recognised challenge. So it’s not in one industry or the other and companies, what we see is that they are re-evaluating the digital capabilities across the business, across the technology and also operations the systems or applications and their equipment. And what we see is that they’re not synchronised and they are not running on the same system. So, it makes it quite difficult to scale if you have a pilot programme, if you have not got running on the same platform basically.

So Cloud capabilities are acting as a foundation for organisations to introduce this new type of solution and new type of applications which are part of these transformation journeys that basically every organisation is in and this drives innovations across the workforce. As all this new type of digital capabilities are introduced and employees are upskilled you hire new teams and you are retraining your people to shift and implement to basically improve your business results.

At the same time, we see that industrial IoT infrastructures they need to become future ready. So they can be scaled and they can be secured across all the different sides. They can be linked together with all the data systems and that basically with your entire ecosystem, which you have in your supply chain, which is a big challenge for most organisations, and organisations need to be able if they want to avoid this, to use AI capabilities for the continuity, but also for improving their efficiency for supply chain management for the inventory management, for the risk management.

But indeed, what we see is that businesses are struggling to move past this pilot purgatory and implement the right AI technologies as well because they don’t have the right talent, they have no single technology platform. And once they start costs are piling up and up and up and up and they become too high.

So the clouds capabilities they can really help businesses to deploy and to use AI. So that they can meet customer needs and they can adapt to this disruptive environments which are continuously changing, but they can also for example, maintain availability.

And successful organisations and they are taking I think steps to overcome this pilot purgatory by starting small, focusing on the business lead initiatives which we discussed already in the beginning rather than the technology lead. And then demonstrating this proof of concept to the stakeholders, the key stakeholders, so they can see the immediate value and showing the immediate value is is an important part of the success as well, and then they can decide where the pilot can have the biggest impact, and also how the technology can be used to connect our infrastructure, to connect our networks. And if you see at this stage, they can explore further the the ecosystem partnerships that help them to implement basically, the whole pilot.

But they’re still focusing on specific business goals. So using metrics to measure your success by measuring the effectiveness of your equipment, or, for example, by security or database monitoring, for example, you need to have criteria for to for success. And then you have to evaluate how to scale in the future. And cloud helps organisation to scale. And to evaluate this, these data initiatives, which are related to the pilot, such as, you can think about data collection, you can think about data storage, data security requirements, of course, as well, and then they can think about how to connect the infrastructure and use a single platform to connect all their data and connect basically all the networks together.

So now after the pilot is successful, then they can take the steps, and they can take all the touch points along with the journey that that helped them to reach a successful pilot implementation, and then start to duplicate and scale it. And as they have this cloud foundation, they don’t have the hurdles, which they initially had in the past with all the legacy systems which were not connected.

So in summary, I think, focus on cloud, and the cloud platform, and focus on small business schools that can overcome this pilot purgatory. That’s the main steps that organisations have to take.

[Andy Hancock]
Right, well, if we, if we talk about that visibility element that you mentioned, we’ve seen supply chains wanting to, become more agile, and the way that they’re actually seeing this is through synchronised planning, where all the planning entities are interconnected to, from, supply demand network. And they’re really looking for a complete view of the supply chain, and to actually evaluate the impact of one particular part of a business unit or to another, and it’s all about mitigation of risk. Are you seeing are you seeing similar things in Europe?

[Ronald van Loon]
Yeah, so for many organisations, it’s a dream to have cross-supply chain visibility, but it’s an area where you can really save tonnes of money, can become much more agile, much more adaptive and, and what we see is that organisations are using management and planning tools to connect the people to connected technologies across the enterprise in the supply chain network.

And this helps organisations to react faster to changes and to adjust to the production planning, which is key, especially if the demand is changing quickly, whether it’s going up or whether it’s going down. And what we see here is that the digitisation, helping your organisations to become more adaptive, to become more resilient in such a way by giving the workers more tools on one end to work remotely like we did during the pandemic, which also helped them to improve the planning and improve the preparation. And having the synchronised planning: that’s all about improving transparency in the supply chain management.

So being able to make forecasts into your pricing forecasts into your demand and using data for procurement, for supplier integration, but also for optimising your material usage, for example, or using additional control trials now, so that you can see the end-to-end Supply Chain Management operation.

For logistics on the other hand, you can improve your routing or you can have visibility into what we were talking about, the ecological supply chain into carbon emissions, for example, which is very important, more and more, and to get that visible as well. So you can really make this environmental impact and I think that the question was directed to that already. And this even impacts as well the production for your planning and its impacts the production for your scale.

So having this level of transparency from additional capabilities: this brings all kinds of new levels of controls for organisations so they can mitigate risk as you were addressing already Andy, which is an important aspect, but also synchronised planning is some kind of evolution of the supply chain network function that we see right now.

So there are more capabilities to get this visibility, so that business’s planning is fully integrated. And it’s centralised, not on local scale, but even on a global scale. Not on one department, but combined with multiple departments and companies.

They are able to predict this demands across the region, across the geode they often use them AI technologies to enhance the data quality, to predict basically the demand, and to execute the plans in cases when it changes when it when it disrupts. I noticed statistic from McKinsey, they say effectively implementing Supply Chain Management allows early adopters to enhance logistic cost efficiencies by 15%. So you can see what kind of impact that have, and they say as well as inventory levels by this visibility can be improved by 35%. And the service levels can even be improved by 65%. And that’s then compared with their slower, let’s say competitors, who don’t have the visibility soda, the impact of this the supply chain visibility is substantial. And therefore Yeah, it’s some kind of dream for many organisations.

So, we see that solutions have emerged to optimise this end-to-end supply chain operations and SAP is working on that as well from demand planning from real-time inventory management, but also for example from using digital trends. And although we see that supply chains are very complex, and company-wide synchronised planning using these digital tools and digital capabilities, is really helping organisations to manage and to optimise their supply chain network so that they can improve the resilience, they can improve the continuity, but also benefit from the economical benefits. So in to answer it: yes it focuses on synchronised planning on one hand, but we see it’s a big challenge for organisations as well across the industries.
[Andy Hancock]
Right before I ask there was a point that you actually raised, I want to follow on, I just want to remind everybody that we are live and to ask your questions in the comments in LinkedIn, it’d be great to get some questions for Ronald or myself.

So Ronald, you know, you talked about predictive analytics and, when we know that in there are different views required within an organisation. So if you can imagine, a CFO wants to have a look at the data set in one particular view. The VP of Ops wants to have that in a slightly different view, but we all we know this, you know, there’s diminishing returns when we start to build our models out and I guess what I want to ask from you being the expert is, where do you draw the line of getting that, you know, to stop refining that model and really just use it in anger?

[PART 2}

Yeah, the question is if you want to stop refining your model, or it’s a continuous process and journey, so if we look to data management: data management helps organisations to concentrate on the data. And it’s important for business to focus on the IT functions when it comes to data collection on the storage, on the moving the data, data on the security, on the data lineage.

And businesses need to keep their attention on the data outcomes, like product or service differentiation, or you can think about customer satisfaction. So if you keep your end goals in mind, then the data is not about being used for later use. The data is there to meet the existing needs of your organisation of each individual department and each team looking at it. And indeed, then you have different departments, whether it’s the CFO or your marketing, or it’s your sales, they all have their requirements.

So if you look to organisations, they need to, on one hand, I think to to share the data and create and establish a clear data language articulating how the data is being used by different people across the different teams, across the different departments, across the different functions. And when data is shared organisations have to take the time to explain all the subtle differences and the changes in the data.

So when it’s accessed by others, it can be used effectively to avoid redundancies in data, and not built on one end data silos or create a data duplication. So there needs to be a central view of your data and global data management view to make that work, and when using external data sources, data quality assessments are often overlooked. That’s what we see a lot this day as it’s quite common, that data is not managed properly. And if you have poor type of data, and if you get poor quality data in your results are affected negatively

So, I think what’s important is really emphasising data management and data lineage: from the collection, to the end, to how it’s used. And then striking the balance between weighing the benefits of the data that’s common, that’s unique, or that’s customised, to bring the best results. And to draw the line between getting more data and on the other hand, refining the model, start with the use case. Start with the use case that brings the business value to your organisation, and then define for which department and which requires minimal data. So start with a simple model minimal data. And afterwards, you can add different data sources step by step until you achieve business results. And you can start step by step improving your model by adding extra data sources or by improving your data models and your machine learning models.

So make sure you establish your data management responsibilities, identify and maintain your data, track your data lineage, measure your data requirements, and monitor and identify the improvement so that your business can determine the best type of data sources, and maintain the quality of the data. And hat’s the way you when you are deploying your analytics, such as we were mentioning about, your predictive analytics, and you can keep models really focused on the outcome. And keep your data minimum and step by step grow it as, as you create business value.

[Andy Hancock]
Right. I actually have a very good comment in from Oscars. Let me just read it to you. And then because I think it’s very pointing to the conversation that we have: “from my point of view, any company can get successful if the people who work for the company enjoy the work, they are getting a reward for work they do. And also they understand why they are doing things that they have been told.”

So, I mean, from my perspective, you know, when we talk about empowering people, it really is getting the right information at the right time. You know, when we talk about what you’ve just been talking about data hubs and predictive analytics, it really is just, getting that aggregate data and really refining it so that people understand the information that they’ve been given and also the, the greater goal of the organisation: “why are we doing this? It’s because ultimately this will give you greater customer success or increase profitability throughout the organisation.” And when we when we talk about “it’s to increase profitability” there’s an interesting thing that’s starting to come through Ronald, which is, IoT sensors have really come down. And when we’ve even got to the point where, they’re less than 65 cents and disposable.

With this opening up of profit, use cases that aren’t really viable from a few years ago, where are the areas that we should be starting to look at to bring that innovation into an organisation?

[Ronald van Loon]
Before moving into that IoT part, and I truly believe, let’s say, we talk a lot about technology here, but it’s about the people. You have to define the strategy, define the implementation, and collaborate with the people, define the teams, and implement it together. And yes, we talk a lot about technology but in the end, it’s the people that need to do it.

With regards to your IoT question: if we look to some market research, there’s my market research from Deloitte, the spent on software and hardware related to IoT is an anticipated to grow substantially. So it was already more than 720 billion in 2019, and 1.1 trillion in 2023. Maybe these figures don’t say immediately something, but it’s a substantial market. So IoT sensors is really an important new type of foundation in your supply chain in your manufacturers and businesses can really look at many different types of IoT examples, to help them inspire their own journey and to find their own use cases, and prioritise their own use cases by the financial impact.

And that will be different per industry that will be even different per organisation. And the way businesses can make money quickly and find new type of use cases is by defining these cases, and basically line up with the business strategies.

And it shouldn’t require a lot of, let’s say, impact on your current operation, if you’re running an organisation, in manufacturing, it shouldn’t, for example, impact any downtime to start with working with IoT devices.

So ideally, we see cases that they should be able to be created once, and then they can replicate as well. So start small, again, test it. And based upon this test, see how you can further roll it out, and can look at how you can scale this initial initiatives and it might have more cost. And it can take even more time and more effort to do it this way. But this way, it’s often most relevant and most successful. What we see is that it can be quickly adopted, it can be replicated in all different kinds of situations, if you want to roll it out.

So if you have a use case, you might not even have the immediate returns. And if you in implement an IoT use case, a central use case. But I think it’s important that you start thinking about your future and the use cases that can bring value, mid-term, long-term. And based on this, define your priority of use cases.

And if we look to specific areas of businesses that should be looking for these IoT cases, I think you can think about areas of production, you can think about areas of logistics, whether it’s assembly lines, supply chains, quality controls, or maintenance, for example.

So your use cases should evaluate what kind of sensors you have, what kind of data sources you have, what kind of data availability you have. So you can basically on this data define Okay, what kind of improvements can you can you define, and at the same time, have, again, a core platform where you can collect this data where you can manage this data, and where you can convert it basically, in, in automation and in actions, either its insights or whether it’s automated actions. And depending on the use case, you can decide whether to deploy it on the cloud, on the edge, on-premise or in hybrid clouds. I think that’s more decision that that you can take in on the later stage. But I think the architecture, the architecture should be prepared, your foundation should be prepared to manage it in different kinds of environments, whether it’s on-premise, whether it’s in the cloud or hybrid cloud or on the edge.

So I think they there’s quite some areas where you can deploy it. And I think that really organisations really have to take a look at this as a part of their strategy for the future of IoT 4.0 type of strategy.

[Andy Hancock]
Yeah, I mean, from my perspective, I see the influx of IoT use cases very similar to Enterprise Mobility was about 10 years ago. Everybody was very, you put a very ruggedised device in their hand, and it was disruption. The way that they actually did work changed, you know, the wasn’t going back to the break room, filling in pieces of paper, the end of the shift, it really changed the way that people actually did work. And I see this happening, again, in the IoT space is that,, it’s, it doesn’t replace it will augment the business process, and it will provide, empower those people by having additional information. At that point, I also see, some of these tasks are going to be automated, through the use of IoT sensors, which will actually, release these skilled workers to do those higher complex elements. Now, when we’re talking about IoT, the other, big technology that’s sitting around is 5g, there’s a lot of noise about it. And what sort of use cases can you see bring value today and in the future?

[Ronald van Loon]
Yeah, indeed, if you start combining IoT and 5G, you getting an exponential type of possibilities. If we look to 5g: I think it’s going to be transformative technology, as you mentioned, in the supply chain in manufacturing.

For the ones who don’t know, 5G is 10 times faster than 4G. And at least the network speeds, it has a very low latency compared, for example, to 4G, and it can help you to connect your devices wherever they are in the world. So you don’t have to have the network cable anymore. And it makes it more much more flexible.

So if we consider the use of the connected devices in the supply chain environment, you can see having consistent, fast, uninterrupted type of connections, and they’re going to bring quite some some benefits, I think, into the supply chain. So we have 5G and you have IoT they’re going to want to digitise and to automate supply chains much more than they are now warehouses, factories, but also transportation and logistics. And I think it’s it’s really important to talk about efficiency, it’s important to talk about safety, when it comes about 5G use cases.

To give it a couple of examples when 5G is combined with edge computing and IoT, it’s possible to detect problems in in real-time. For example, workers, they can be alerted. And if they are in a potential hazard situation, if they’re in a coal mine and something is happening, they can be alerted much faster. And based upon this actions can be taken, and the next best action can be taken to the door and say send to the person with the right responsibilities.

Also computing power it’s more directed to the edge: where we can see robotic machinery will use a lot less energy and they cost less to operate. So, these will be exponentially used in the future where 5G can also be used for your asset management for example for global tracking. And for asset condition monitoring we can use sensors that can be equipped with tonnes of different machines and packages so that they can be monitored and they can be tracked using temperature fluctuation for example: if you have certain cooling systems that needs to be monitored are another really popular use case for 5G.

VR and AR I like that a lot, even with mixed reality type of applications for a one and using cameras for geo-positioning, but also for maintenance workers who need to make these critical adjustments to a particular device, or piece of machinery. And they on one hand can use this these type of goggles, or using their phone and then they can receive instructions from another technicians who is offsite or they can use predefined instructions, and just can follow what’s on the goggles and repair machines without knowing all the details. And that’s where technologies like 5G really helping with this augmented reality: to do all kinds of maintenance, repair, maintenance, and reduce the level of required skill on site for urgent repairs. So I think that we have only scratched the surface with all the applications that we see with 5G in the supply chain. And for organisations, its defining case, use case by use case from a business perspective, and implemented step by step. And then you can really see how sensors plus 5G create all kinds of new opportunities and all kinds of new business cases to help you improve your organisation.

[Andy Hancock]
Yeah, I mean, at SAP, what we’re seeing is around predictive quality, the way that is happening because of the non disruptiveness of, you don’t have to run cable to a particular point, you can use 5G with computer vision to then look at cameras, look at the quality of the camera, quality of the product as it comes through at high speed. We’re also seeing links between, on a prime brownfield site, there’s an additional building, rather than laying fibre optic cable. We’re also seeing 5G being used as that interconnection between buildings.

We actually do have a question for you Roland in the chat here. So Padrini from Valero says, “What do you think of the future of tracking the products in supply chain from raw materials to finished products, when the client can scan a QR code, and get all the information he needs?”

[Ronald van Loon]
Yeah. So on one end, I think we were talking about this ecological supply chain, supply chain visibility, I think it’s critical, I think it’s one of the main drivers right now, for getting supply chain visibility. And if it becomes easier to scan, we’re easy to track where the products are from, what kind of materials are in the products, that’s a very important trend, and scanning this and tracking, it makes it easier to get supply chain visibility, but also work on the environment, and work on a new type of KPIs that initially were not even possible because we simply couldn’t track it. And we didn’t know.

Now you see also from legislation perspective, that European legislation, I’m not aware about the US, but it’s putting much more pressure on getting supply chain visibility, where are your products coming from? What type of materials do you use, what is allowed, what is not allowed? And if you cannot provide these type of details, you’re basically you’re not allowed to deliver anymore. So it’s, it’s becoming a crucial part for businesses to use and to jump into this.

[Andy Hancock]
Right, we’ve got a comment. So whoops does refresh Victor’s mentioned efficiency, sorry, no, no one we managed to maintain a net zero with supply chain end to end process production with IPA, this helps us scale and customise the multi channel marketing. So, I wanted to talk about and this prompts me to talk about AI around that. So, while I was doing my homework on you Roland was doing I was googling you mentioned companies need to be prepared to weather the digital tide tidal wave and the AI hurricane. What does that mean? Whether companies start and scale AI?

[Ronald van Loon]
Yeah. So, the digital hurricane, the AI hurricane, every organisation is a data organisation and if if you are a data organisation, you have to analyse your data getting inside, start predicting and in the end, start taking actions with the help of machine learning algorithms with the help on your data.

So, every data every organisation is an AI company and if organisations start using AI in their process, they automate a lot and the competition is increased substantially. So you get a hurricane and some industries are much further than others telecom or media is much further for example, than oil and gas. On the other hand, they are picking up as well and develop AI in different sectors.

So what we see is that organisations they need to think about reimagining their processes. They need to think about reimagining the functions using technology using AI technology and it makes it easier to get the most out of your AI while at the same time reduce your costs, and reducing your development time, and basically improving your business outcomes.

So, use of AI within your company can be in different ways unifying can be within the existing software. So companies like SAP, every organisation, every software organisation implements now AI machine learning algorithms to automate certain tasks. And often you don’t even see it anymore, because it’s all behind the scenes. But that’s, I think, a very easy way to start using AI. Because you’re maybe you negate need some training, or maybe you don’t even need training as it’s much more user friendly, and you are guided by the AI: how to use the application without you even knowing that you’re using AI. A very simple example, of course, is speech recognition. People
maybe don’t even know that they’re using AI if they talk to the phone to have certain actions if it’s Siri or other speech recognition.

I think a second level of how you can use and scale AI. If you’re more advanced, and you start developing more competitive edge, with the help of data, you can start thinking about using AI API’s. So you can use API’s to create new applications to create new services. And these API’s can do one or two or three functions very well. Often they are quite advanced, quite far developed. And these organisations, they are the best in that one type of a API. And this way, it saves you tonnes of development time. And thumbs up, let’s say implementation time if you want to do it yourself.

So it’s an easy way to reuse expertise in a very specific domain for models. And the most simple one, as I was talking about voice recognition, if you want to build in voice recognition in your device, so you can talk to a device and it’s converted into action, you’re not going to develop this AI yourself, you’re going to use a voice API.

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The third level, which is I think, the most difficult one, but that’s the one where you really should think about before you start it: building your AI capabilities yourself. And this is really where you can make a difference. And where you can really create a competitive edge, which is unique in the market. And then you need to start thinking about, okay, what is the unique type of service that I need to provide? What data do I need? What algorithms do I need? What kind of customer experience do I need to provide and this route? You can go in that direction, but this route is the most difficult one. And it’s on the other end to the one that can really differentiate you, if you always let’s say make a buy, if you start redeveloping the voice recognition API, it doesn’t make sense because it’s already there. So always look what’s there in the market, but start try to find out what’s unique about your business and try to develop data and later on and insights, prediction, and an AI strategy on that particular segment, to create this, this competitive edge and to improve your customer experience.

So that’s, I think, quite important. It’s also important to designate your leadership that’s responsible for leading your AI initiatives and define the teams who understand how to bring the value of using AI. So it’s all initially it’s I think, a top down type of approach, which is important.

And your team should be composed from areas from different expertise from business, from technology from analytics from IT, even if you want to do it socially responsible, it should be different geographic ethnical backgrounds, gender backgrounds, because you try to limit the bias, but it becomes quite complex to create these type of teams.

So people will need to be taken from other departments, from teams, and they need to be assembled into the single group so that they can work together without any disruptions on these type of new type of activities. And those teams should think about the business goals such as, for example, improving the customer experience, like we mentioned before, and then map out how they can use AI to make that happen.

And it should be as mentioned, equipped by leadership. Leadership should provide the tools and the capabilities, and the firms and the empowerment to these type of teams to make this job done.

And, emphasise how it could be a scalable type of solution, not as a siloed approach for one department. And when it comes to technology, they should implement it, preferably on the cloud platform and API’s, because these can speed up the AI development.

So start with your strategy, start small, start creating the team based on your business goals, and then start scaling step by step, create your data, your insights, you start predicting with it, and then start modelling it more to advanced machine learning algorithms.

[Andy Hancock]
Right? Yeah, I agree. And I think Steve Hoffman actually says something in the comments, “organisations need to rethink their structure to have roles and responsibilities around the immense amount of data that we need to be managed: think data scientist, and/or data stewards to properly marry IoT solutions with automation, algorithms”. Now, I was thinking about, when we think about automation and autonomous systems, we all know that the human being is never going to be replaced. As we become more complex, so does the decision making naturally becomes more complex, and that can only be done by a human. So, how do we identify where to deploy automation and realise it’s full potential for those particularly, particularly the skilled workforce?

[Ronald van Loon]
Talking about automation with with advanced AI or talking about autonomous systems?

[Andy Hancock]
Let’s talk about what you choose, I think probably automated algorithms.

[Ronald van Loon]
If you talk about automated algorithms, at least I talked about, I call it deep learning, where it’s unsupervised learning, an algorithm that you use for advanced applications in AI, whether it’s in the supply chain, or in manufacturing, or in speech recognition, or different types of possibilities.

And some of the most innovative, the most creative type of technologies, they are driven by, by deep learning can be predictive analytics, and especially if you have predictive analytics through the whole supply chain.

But it can also be a demand forecasting. If you have, let’s say, demand forecasting for your full supply chain. So there’s predictive maintenance, which helps to ascertain the health of systems and equipment so the business can predict the failures. So it’s more or less a IT type of algorithms and deep learning to monitor all your IT systems, which is automation, which is hard to do yourself, on one hand, and especially if you talk about security and automation, and security monitoring: you definitely need automation, and you need deep learning algorithms to basically track your security, and to detect if there are either attacks, or certain issues appearing.

We see also, for example, robotics steps, where you use the deep learning, which are improving efficiency, and where they are using productivity. Where the robotics are totally, let’s say, automating simple tasks on one hand, but they are driven as well by deep learning.

So I think there’s a whole series of cases where deep learning is used, if we look for, for example, to consulting firm McKinsey, they, to state the importance about deep learning in the automation part is that they say that 40% of all the potential value that can be created in analytics today is by deep learning.

So if we talk about automation, especially automation in the analytics domain, deep learning is really the most important part. So thats let’s say if we look from an automation perspective, from analytics and from deep learning.

[Andy Hancock]
Okay, well, I mean, the hour is almost up. So what I wanted in closing, my final question to you Ronald, and thank you very much for all the insights that you’ve had, it is how to build the right foundation for industry for 4.0 projects with respect to supporting supply chains?

[Ronald van Loon]
It’s the question that three we had in our title. So it’s the most important question. And I think if the right industry 4.0 foundation needs to be flexible, needs to be agile. And the reason is the expectation from the district consumer from the end user is changing all the time.

And being flexible and agile helps supply chains to be prepared, and helps them to respond to any type of disruption. And whether it’s your system with disruption, or its supply chain disruption, whether it’s a ship in the channel that’s that stuck.

And there will be many different types of supply chain disruptions, more organisations need to be able to respond quickly and get the supply chain visibility and be prepared with an industry 4.0 foundation for this.

So companies need to consider if the industry 4.0 technology is able to provide value beyond the business as usual. And especially during challenging times that we have seen during pandemic but as I said, there will be tonnes of events coming years here, where you have an impact of the supply chain, and where you need to be able to adapt.

So the right foundation: I think it’s digital. It’s grounded in data analytics, and it combines advanced manufacturing capabilities with IoT that helps to connect the systems. And it drives the intelligent AI initiatives, but also connects IoT devices, sensors, via 5G with the central system. So you have to be able to enable these digital initiatives from different perspectives: from automation perspective, from production perspective, from planning perspective, from logistic perspective, all on a single platform.

It’s gonna be, I think, a huge factor in the technological foundation for industry 4.0. But it helps to connect your machines, it helps to connect your equipment, to connect all your web-enabled devices, your whole supply chain, and your whole logistics supply chain.

So I think if we summarise it, the right foundation for industry 4.0 projects are derived from digital capabilities of IoT, cloud AI, edge computing, and 5G and, I know it’s a lot, but these are important technologies right now to create your industry 4.0 foundation.

[Andy Hancock]
Well, thank you very much, Ronald for that summary. And I want to thank everybody for taking the time to listen to us. I hope you found it useful. Continue to add the comments and we’ll get back to any unanswered questions. For that, I would like to say thank you very much Ronald.

[Ronald van Loon]
You’re welcome. Thank you for being here.

[Andy Hancock]
And see everybody next time.

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