Tag: manufacturing

ChatGPT chat screen
AI

Exploring Generative AI with ChatGPT: A Deep Dive into Supply Chain and Manufacturing Applications

As I was gearing up for an exciting new episode of my Digital Supply Chain podcast, where I’ll be talking to Mike Sigler from Nexer, I decided to give ChatGPT a try to learn more about the use of generative AI in supply chain. To my delight, the conversation was incredibly insightful and informative. ChatGPT provided valuable information on the applications, potential risks, and first steps for implementing generative AI in supply chain and manufacturing. So, without further ado, let’s dive into this fascinating conversation with ChatGPT, and don’t forget to tune in to the upcoming podcast episode for even more insights!

So, the first question I put to ChatGPT was a very basic “What are some potential uses for Generative AI in supply chain / Manufacturing?”

ChatGPT responded with:

Generative AI can significantly impact supply chain and manufacturing processes by improving efficiency, reducing costs, and enhancing overall productivity. Here are some potential uses for generative AI in these sectors:

  1. Demand forecasting: Generative AI models can analyze historical sales data, market trends, and other factors to generate accurate demand forecasts, helping businesses optimize their inventory levels and production schedules.
  2. Inventory management: AI-driven algorithms can optimize inventory levels by predicting stock requirements based on demand, lead times, and other variables. This reduces the risk of stockouts and minimizes storage costs.
  3. Supply chain optimization: Generative AI can identify inefficiencies in the supply chain and suggest optimal routes, transportation modes, and shipment consolidation opportunities, leading to reduced logistics costs and improved service levels.
  4. Supplier selection and risk management: AI models can analyze supplier performance data, industry trends, and other factors to recommend the best suppliers, predict potential disruptions, and assess supplier risk.
  5. Quality control: Generative AI can identify patterns in manufacturing data that may indicate potential quality issues, enabling manufacturers to address problems before they escalate and result in costly recalls or customer dissatisfaction.
  6. Predictive maintenance: AI-driven systems can analyze sensor data from machinery and equipment to predict when maintenance is required, reducing downtime and maintenance costs.
  7. Production scheduling: Generative AI can optimize production schedules by considering factors such as machine availability, raw material constraints, and demand forecasts, ensuring efficient use of resources and meeting customer expectations.
  8. Product design and customization: AI models can generate innovative product designs based on consumer preferences, industry trends, and technical constraints. They can also be used to create personalized products or make real-time adjustments to designs based on customer feedback.
  9. New materials discovery: Generative AI can predict the properties of new materials or suggest novel material combinations, accelerating the discovery process and reducing the time and cost of R&D.
  10. Workforce planning: AI-driven tools can optimize workforce planning by analyzing factors such as employee skills, shift preferences, and productivity levels to create efficient work schedules and match employees to tasks that best utilize their skills.

By leveraging generative AI in supply chain and manufacturing operations, businesses can achieve a higher level of efficiency, agility, and competitiveness in an increasingly dynamic global market.

I then asked it “What are some potential risks of using generative AI in supply chain / manufacturing?” and it responded:

While generative AI offers numerous benefits for supply chain and manufacturing processes, it also comes with potential risks that need to be addressed:

  1. Over-reliance on AI: Excessive dependence on AI systems can make organizations vulnerable to unexpected disruptions if the AI system fails or malfunctions. It is crucial to maintain a balance between human intervention and automation.
  2. Data quality and accuracy: AI models are only as good as the data they are trained on. Inaccurate or biased data can lead to incorrect predictions and suboptimal decision-making.
  3. Security and privacy concerns: The use of AI systems often requires the sharing and storage of sensitive data, which can expose organizations to data breaches and privacy violations if not handled properly.
  4. Black box problem: Many AI models, particularly deep learning systems, can be difficult to interpret and understand. This lack of transparency can make it challenging to identify and address potential errors or biases in the AI’s decision-making process.
  5. Ethical considerations: The use of AI in supply chain and manufacturing can raise ethical concerns, such as job displacement, worker surveillance, and biased decision-making. Organizations must carefully consider these issues and implement fair and transparent AI systems.
  6. Legal and regulatory compliance: As AI becomes more prevalent in supply chain and manufacturing, it is essential to stay informed about evolving legal and regulatory requirements to ensure compliance and minimize the risk of penalties.
  7. Integration challenges: Integrating AI solutions with existing systems and processes can be complex and time-consuming, requiring significant investments in infrastructure, personnel training, and change management.
  8. Misaligned expectations: Overestimating the capabilities of AI systems can lead to unrealistic expectations and subsequent disappointments. It is essential to have a clear understanding of AI’s limitations and to manage expectations accordingly.
  9. Skill gap: Implementing and maintaining AI systems requires a specialized skill set. Organizations may face challenges in recruiting and retaining talent with the necessary expertise in AI, data science, and related fields.
  10. Environmental impact: Training and running large AI models can consume significant amounts of energy, contributing to greenhouse gas emissions and other environmental concerns.

To mitigate these risks, organizations should adopt a proactive approach to risk management, carefully evaluate AI solutions before implementation, and continuously monitor their performance. Additionally, fostering a strong collaboration between AI experts, supply chain professionals, and other stakeholders can help ensure that AI systems are implemented and managed effectively.

My final question for ChatGPT was “What first steps should supply chain / manufacturing organisations take to embark on the use of generative ai?” and it replied:

To embark on the use of generative AI in supply chain and manufacturing, organizations should take the following first steps:

  1. Assess current capabilities: Conduct a thorough assessment of your organization’s current supply chain and manufacturing processes, technologies, and data management capabilities to identify areas where AI can add value.
  2. Set clear objectives: Define specific, measurable goals for AI implementation, such as improving demand forecasting accuracy, reducing lead times, or enhancing product quality.
  3. Build a cross-functional team: Assemble a team with diverse expertise, including supply chain professionals, data scientists, IT specialists, and other relevant stakeholders. This collaboration is essential for effectively integrating AI solutions into your organization.
  4. Develop or acquire AI expertise: Invest in training your workforce in AI and data science or recruit skilled professionals with the necessary expertise to develop and manage AI solutions.
  5. Identify use cases: Based on the assessment and objectives, identify high-impact use cases where generative AI can provide tangible benefits. Start with smaller, manageable projects to build experience and generate quick wins.
  6. Collect and preprocess data: Gather historical and real-time data relevant to the chosen use cases. Ensure the data is clean, accurate, and representative of the problem you want the AI to solve.
  7. Choose appropriate AI models: Evaluate and select suitable generative AI models for your use cases, considering factors such as model complexity, interpretability, and computational requirements.
  8. Develop a pilot project: Develop a pilot project to test the chosen AI models on a small scale, allowing for iterative improvements and adjustments before full-scale deployment.
  9. Monitor and evaluate performance: Continuously monitor the performance of the AI system, comparing its outputs to predefined success metrics, and fine-tune the model as needed.
  10. Plan for scale-up and integration: Once the pilot project demonstrates success, develop a plan for scaling up the AI solution and integrating it into existing supply chain and manufacturing processes. This may involve addressing infrastructure needs, change management, and workforce training.
  11. Address ethical and legal considerations: Consider potential ethical and legal implications of AI implementation, such as privacy concerns, job displacement, and regulatory compliance, and develop strategies to address these issues responsibly.

By taking these initial steps, organizations can begin their journey toward leveraging generative AI in their supply chain and manufacturing operations, ultimately improving efficiency, reducing costs, and enhancing overall competitiveness.

In conclusion, ChatGPT showed itself to be an incredibly valuable and versatile tool for exploring the world of generative AI in supply chain and manufacturing. Our conversation shed light on the numerous benefits, potential risks, and the essential steps for successfully rolling out generative AI solutions. What’s truly remarkable about ChatGPT is its ability to dive deeper into any specific point mentioned in the responses, providing virtually limitless insights tailored to your interests and needs. As we continue to explore and understand the impact of AI on various industries, tools like ChatGPT offer an accessible and powerful way to tap into the wealth of knowledge they possess, helping us make well-informed decisions and stay ahead of the curve in an ever-evolving landscape.

Photo credit Focal Foto on Flickr

Kuka manufacturing robot
Internet of Things (IoT)

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

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

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

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

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

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

Man putting on surgical mask
Digital Supply Chain, Podcast

Digital Supply Chains and the impact of the #Covid-19 #Coronavirus – a chat with Richard Howells (@HowellsRichard)

It is early April 2020 and the world is in the middle of the Covid-19 coronavirus pandemic.

The contagion has hugely impacted supply chains, and in some cases supply chains have hugely impacted the contagion, stepping up to allow automobile manufacturers pivot to building ventilators, airplane manufacturers switch to 3D printing protective visors, and drinks makers start making hand sanitisers.  And that doesn’t even start to get into the challenges facing grocery stores maintaining stock levels.

In the midst of this Richard Howells wrote an excellent piece in Forbes titled Business As Unusual: Resiliency In Times Of Supply Chain Disruption examining how supply chains are coping with the outbreak so I thought I’d invite him on the show to discuss this and we had a fascinating conversation on the topic.

Click on the player above to hear our conversation and/or check out the transcript below:

 

Richard Howells [00:00:00] So there’s lots of areas where we’re seeing companies addressing short term challenges, but also looking at ways to rebalance their supply chains, moving forward and having risk mitigation strategies. I think supply chains will, if they don’t already in every business, will have a seat at the table of every business moving forward because they’re both an opportunity and a risk.

 

Tom Raftery [00:00:27] Good morning, good afternoon or good evening. Wherever you are in the world, this is the digital supply chain podcast and I am your host, Tom Raftery.

 

Tom Raftery [00:00:38] Hi, everyone, welcome to the Digital Supply Chain podcast. My name is Tom Raftery and with me on the show today, I have Richard Howells. Richard, would you like to introduce yourself?

 

Richard Howells [00:00:47] Hi, Tom. So I work for SAP in the area of digital supply chain and I spend a lot of time writing about business challenges, trends and opportunities for supply chain executives.

 

Tom Raftery [00:01:00] Yeah, you write a lot of stuff on Forbes as some great some great articles. And you wrote one because, you know, we are; this is, what, the second of April 2020, we are in the middle of a global pandemic. The Covid-19 Coronavirus virus pandemic. Today is the day that we are going to reach 1 million people infected and 50000 dead. And, you know, it’s presenting a lot of challenges. And you wrote a blog post about this on Forbes called Business as Unusual Resiliency in times of Supply Chain Disruption. And you made some, you know, great points in that and talked up some interesting stories. So I thought it’d be cool to have you come on the podcast, because, you know, this is a supply chain issue big time globally. And you address a lot of those challenges there in that article. So would you like to talk a little bit about that?

 

Richard Howells [00:01:53] Sure. So, I mean, I start I started the article off about talking about some of the challenges from a supply chain perspective that this pandemic has caused. I mean, it’s hard to believe that when we were celebrating New Year’s Eve for three months ago that this didn’t was a figment of wasn’t even a figment of anyone’s imagination. We couldn’t believe that we’d be been this case three months later. And what’s happened is that I mean, we’re seeing supply chain at the centre of everything at the moment. It’s both the challenges in some cases and the opportunities in others. I mean, when we started off with the issues in China, it considered it created a huge supply issue because China is the manufacturing factory of the world. So when you’ve got uncertain supply of critical materials, it has a knock on effect throughout the whole world. And then as the pandemic spread, so did the demand volatility as people started panic buying. I mean, we’re seeing huge demand for medical equipment, medical devices and of of of key products from a from a consumer goods standpoint. And the demand for luxury items and discretionary items is nonexistent. Now, it’s amazing to me that we are reliant as a globe now on 20 or 30 items that everyone’s looking for in the stores and… toilet paper of all things, who thought there would be a rush on toilet paper.

 

Tom Raftery [00:03:23] I think that was a I think there was a social media thing more than anything else, because I went to I we had our lockdown announced on the 14th and I went to their local supermarket and there was plenty of toilet paper. What was missing was all the meat. The meat counter was stripped bare. Now that was fixed in a matter of a couple of days. It was a supply chain issue again. You know, they didn’t anticipate that big demand, but they and they got it fixed in a couple of days. So there aren’t any shortages here. There are sometimes if you go to the shops, there might be a short term shortage of an individual brand, but not of that, not of the class of goods.

 

Richard Howells [00:03:57] And I’m based in the US. And we’ve still got I mean, you’re you’re a few weeks ahead as far as the pandemic is in in Spain. And we we still have shortages. And those shortages are now because of capacity constraints. There are shortages because we don’t have enough manufacturing capacity to increase the production of toilet paper, for example, which was running at full production anyway. And we’re having logistics challenges of getting goods from point A to point B. What if they’ve got to come from foreign foreign ports or foreign countries? There’s no transport that the flights are down by 80 plus percent. Some of the ports are closed or there’s less or less capacity going through it. And then we’ve got the challenge of drivers and the risk that those drivers are taking without the proper security and humanitarian coverage. And that’s the final challenge I think we see from this at the moment, is that humanitarian risk, the balance of of labour shortages, but also of ensuring the health and safety of employees who are doing the vital jobs, who are doing the “required jobs”. How we’ve changed manufacturing processes, for example, where there can be less people on the plant floor. So to make sure that we’ve got the social distancing during working environment, working processes and working environments as well.

 

Tom Raftery [00:05:22] That’s going to be a huge challenge for manufacturers. I mean, they they’ve set up their manufacturing lines in a particular way. And to your point now, they have to do social distancing between the employees and the floor and just for health and safety.

 

Richard Howells [00:05:33] Yes, it’s it’s it’s things that you wouldn’t think about in normal circumstances, I’m sure it’s never been thought through as a as a plan of how to do this. And people are having to come up with solutions literally on the fly.

 

Tom Raftery [00:05:47] I went grocery shopping yesterday just for the second time since lockdown because the grocery shops are tending to push us towards online deliveries and in the grocery stores now, they have markings on the floor to say where you should stand when you’re in a queue for the checkout counter you know, and there is, you know, two meters between each mark so that you’re two meters behind the person in front of you. You know, again, for social distancing and they have to have a glass Perspex barrier between you and the person at the checkout counter, which was never there before. And again, it’s just to protect the employees from potential infection from shoppers. Yes, and vice versa, I suppose.

 

Richard Howells [00:06:27] Is that just they’ve just started introducing in some of the stores here one way systems around the supermarkets as well, which I haven’t seen up until now in the US.

 

Tom Raftery [00:06:36] Wow, wow, wow

 

Richard Howells [00:06:38] And we’re seeing lots of repurposing as well of manufacturing. I sent you a link this morning to the Airbus plants here in Spain. I mean, Airbus have several factories here in Spain and they have over 20 3D printers because they I mean, they were they were the first commercial airline company to use 3D printed parts and commercial flights back in, I think was 2015. So they’ve been playing a lot and working a lot after playing working a lot with 3D printers. And now they’ve turned that around into using those 3D printers to make the Perspex masks that the health workers, the health care workers are using to keep themselves safe when they’re dealing with people who are very sick. Actually, there’s a there’s a consortium that I’ve seen online of 3D printing companies who are sharing the designs of these 3D masks for that very purpose that they’re crowdsourcing and sharing the information. And we’re also seeing other companies doing some similar things. I mean, I read about Medtronic’s are opening up, or making that does the designs of their ventilators so that they’re simple ventilators, their basic line of ventilators open to other people so that they can manufacture those ventilators. And they’re also partnering with with Tesla to to to increase their production. You’re you’re seeing automotive companies becoming outsourced, manufacturers for medical device companies to increase the production, because there’s a lot of very small ventilator manufactures that just can’t scale.

 

Tom Raftery [00:08:15] If I had said that to you in December thirty first, that the car companies would be making ventilators in April of this year, you’d said, Tom, you’re smoking crack.

 

Richard Howells [00:08:24] That’s exactly what happened. Yes. And they’re becoming the contract manufacturers rather than working with lots of contract manufacturers for their parts.

 

Tom Raftery [00:08:31] So how do they how are these automotive, for example, companies sourcing the parts to manufacture these ventilators? How would that work?

 

Richard Howells [00:08:40] Well, that means that that means having improved visibility across the supply chain. I mean, first of all, I mean, SAP is doing a lot of work in providing offers to our customers to access some of our, some of our systems in these times of need and mapping, mapping the visibility of where the suppliers are that have the inventory with your demand and in-building and having visibility across the network of that is a huge, huge first step. I mean, I would imagine that there’s as I said, there’s a lot of partnerships going on. The also the the the the medical device manufacturers will be sharing their partner information and their supply information and supply sources to satisfy that demand for additional materials that these companies may never buy. I mean, we’re seeing other examples. We’re seeing perfume manufacturers and liquor producers making hand sanitizers. I mean, at the moment, the medical device, medical companies need three or four sections of things. They need we need they need the public to have and they need hand sanitizers to reduce the spread of the virus. They need the masks, the testing equipment and the robes for testing people and treating people. And ultimately, in the worst case situations, they need ventilators and an unparalleled amount of ventilators to actually treat the most critically ill. And companies are coming together to help support that. As I said, I mentioned the hand sanitizer example. We see the ventilator example with car manufacturers. We’re seeing other companies. Another one of our customers, actually Decathlon are are repurposing this, their the devices for their breathing, snorkelling devices and adapting them to be ventilators, working with with partners to adapt them to be ventilators. So we’re we really are thinking out of the box and and building partnerships that you wouldn’t have seen. And it’s it’s actually good to see companies coming together to solve solve some of these problems.

 

Tom Raftery [00:10:45] I came across a thread of tweets a couple of days ago and again this morning because someone else tweeted, not me, where it was. I think a psychologist talking about how in times like this, people are afraid that there’s going to be a breakdown of social order. Whereas in fact, in times of crisis like this, it seems to bring out, in fact, the best of us, the likes of the people in New York in 9/11, all coming together to help each other out. And, you know, we’re seeing it again in this situation where rather than, you know, everything falling apart, in fact, we’re getting to your point, unprecedented partnerships between businesses that would never work together before, to try and all come together to produce the goods that are in short supply.

 

Richard Howells [00:11:31] Yes. I mean, you see it at a personal level with with neighbours helping other neighbours. And we’re seeing it at a business level as well at a larger scale. And it’s it’s good to see. But the wrong circumstance. Wish we didn’t have to see it, but it’s good to see when it does happen.

 

Tom Raftery [00:11:47] Richard, what are some of the strategies that companies are coming up with to address this situation?

 

Richard Howells [00:11:53] Well, what we’re seeing across all areas of the supply chain, different, different needs and different strategies. If we start at the basic level over the last 10 to 15 years, we’ve stripped a lot of cost out of the supply chain. We went to a global supply chain to reduce the cost of raw materials. For example, we’ve outsourced a lot of our manufacturing to have cheaper labour. And this has done a great job in cost reduction. But it’s also increased the risk involved, which… Exactly, it’s coming home at the moment as a huge cost implication and a customer service implication. And in the short term, I think we’ve got to work out where the from a supply standpoint, where the inventory is, how can I access that inventory? Which which partners do I have that already have it? Which other companies have available inventory that I can source? How do I get the goods to the right place, to the hotspots when we’re talking about medical supplies to the to the areas with the most shortages? When we talk about supermarkets, we’re seeing so so alternate sourcing strategies are one of the areas in the short term that I see a lot of supply chains looking to to solve. Also, where to position inventory in a in a global supply chain. I can’t be totally reliant on having all my finished goods being shipped and it takes a week for me to get the finished goods. I need a source of inventory of finished goods locally. We are seeing a lot of companies start thinking or will be thinking a lot about the balancing of offshoring versus near shoring versus on shoring, even though it may cost more to manufacture locally, but you need that to reduce that risk. The whole area of employee safety, of ensuring you have the environmental, health and safety processes in place to ensure the safety of your people working on the plant floor. The people working in the distribution area and and and your customers safety of making sure that the products are of good quality and having visibility of demand, I think is critical. I mean, this may be a case. It’s taken a long time to for the retailers to share the point of sales information with manufacturers. Now is the time to share that information. We need to know where we have shortages. We need to know what is going off the shelves, although it’s pretty obvious what’s going off the shelf as a consumer. But maybe the manufacturing companies could have had advanced information of that to get more goods of the right sort to to the to the retailers that needed it the most. So there’s lots of lots of areas where we’re seeing companies addressing short term challenges, but also looking at ways to rebalance their supply chains, moving forward and having missed risk mitigation strategies. I think supply chains will if they don’t, already in every business will have a seat at the table of every business moving forward because they’re both an opportunity and a risk.

 

Tom Raftery [00:15:03] Yeah, absolutely. And so that that brings up a good point. Where do we go? Post pandemic? You know, in whether it’s six or 12 or 18 months time, what is the supply chain world going to look like?

 

Richard Howells [00:15:18] Well, I mentioned I think we’ll have still have global supply chains, but maybe with local execution we will be balancing our inventory so that we keep a certain percentage of inventory locally. We will be balancing our manufacturing, outsourcing vs. and offshoring to to maybe doing some of the manufacturing ourselves and at least having it local, local manufacturing capabilities and capacities. I think that we will not be reliant on single sourcing strategies. We won’t put all our eggs in one basket. We will we will have multiple suppliers to provide the same critical the critical components that we need and balance that. Maybe we work with one but 20 percent and 80 percent with the other at the moment, but have the ability to switch so that you can go to local sourcing as and when required. And it’s going to cost a little bit more, but it will reduce risk. And I think sustainability actually will be a huge thing moving forward. I mean, it should be a huge thing anyway. But we’re seeing the in the environmental impact of this pandemic is actually a positive impact on the globe. We’re seeing less pollution in certain areas and we’re seeing cleaner waterways due to lack less less distribution and fumes being put into the atmosphere. And I think that as companies start to think about how they are global but execute locally, that will reduce the carbon footprint of our supply chains automatically. But we also want to ensure that we we are still sourcing ethically, that we are having good labour manufacturing environments to work in for working conditions and we are designing sustainable products and recyclable products for the good of the planet anyway.

 

Tom Raftery [00:17:22] I actually have a very practical example of that. I have a personal air quality meter. It’s made by a company called Plume. Plume Labs. It’s called a Flow air quality meter. It’s it’s a device you wear on your belt loop or somewhere like that. And it measures five different air quality indices. There are things like VOCs which are, you know, volatile organic compounds, NOx, pm 1, pm 2.5, and pm 10, that’s particulate matter at different sizes. And it has an app which comes with the phone, which syncs with the phone. So it matches up the air quality, which it measures once every minute along those five measurements. It synchs that with the G.P.S. coordinates and then uses mapping data to give you a map of the air quality for everywhere you’ve been for 24 hours a day, seven days a week, 365 days of the year, etc.. So, I only get out of the house now to walk the dogs because we’re on lockdown and walking the dogs is literally the only… Well that and grocery shopping, you know. But what of the groceries are, you know, online deliveries? So just walking the dogs. I used to walk the dogs anyway before the lockdown. So I have before and after data for the air quality where I live and for the walk that I take every day. So I’ve perfect A.B data and these the the difference in air quality between, you know, before the lockdown and since the lockdown is just amazing. And even even before the lockdown, you know, I used to in presentations talk about this, talk about, you know, you get air quality in one area, which is terrible and in another area, which is better. But it’s not just it’s not just it’s not just a question of where. It’s also a question of when. And what I mean by that is… Rush hours? Yeah, exactly. The the I used to take the dogs out for a walk in the morning and the evening and in the morning it was, you know, just before 9:00 a.m. and I’d be walking past a local school. And of course, all the SUVs would be outside the school as the parents were delivering their kids. I’d walk past the same school at eight o’clock in the evening and there wouldn’t be a car from miles. And the air quality difference between those two times a day for the exact same place was incredible. But now that there have been almost no cars driving by there in three and a half weeks, it’s it’s flat. You know, there’s almost nothing there at all. It’s just like almost it’s not it’s not exactly zero across all five measurements, but it’s close enough.

 

Richard Howells [00:20:15] And it’s interesting, using personal devices like that would be a great way of getting the information across the globe or the country. You know, about how that has improved because that information is is stored centrally in the cloud some whereand that information can really add value. And that’s another example about that. We’ve been seeing this in the news about we we can see where the hot spots are and where that they’re reducing a little by people who were using electronic temperature. That’s right. The company has visibility across the North America at the moment of the temperatures are coming down in certain areas, which implies that people are getting a little healthier in those areas or the pandemic isn’t as is reducing in some of those areas or increasing as the case may be. Saw that. That’s fascinating. A type of information from Smart Assets is very valuable in today’s climate and it’s very valuable from a business perspective moving forward as well.

 

Tom Raftery [00:21:17] It is. And the company who make that air quality meter know that, they’ve been mapping air quality across cities globally since they started. It was a, you know, one of the one of the business drivers of creating the air quality meters. Richard, we’re at about 20 minutes. We’re just over 20 minutes. So we’re coming towards the end of the podcast. I like to keep it about the 20 to 25 minute mark. Is there is there anything else that we haven’t touched on that you think that we should have?

 

Richard Howells [00:21:44] I think we’ve covered most of the topics or all the topics, I think. I’d just like to. I hope that everyone stays safe and adheres with the different mandates and guidances from the different governments around the world, and hopefully the next time we we do a podcast Tom, we’ll be talking about in happier times and about happier subjects.

 

Tom Raftery [00:22:05] I hope so. OK, everyone, thanks a million for your interest. Richard, thanks for coming on the show. And to everyone who’s listening. Stay happy. Stay healthy. Stay safe. Stay sane. Because, I mean, you know, we’re on lockdown right now. It’s very easy to kind of go a bit out of your head, do stay sane.

 

Richard Howells [00:22:24] I’m not sure if I can do that.

 

[00:22:30] OK, we’ve come to the end of the show. Thanks, everyone, for listening. If you’d like to know more about digital supply chains, head on over to SAP.com/digitalsupplychain or simply drop me an email to Tom Dot Raftery at SAP dot com. If you’d like to show, please don’t forget to subscribe to it in your podcast application to get new episodes right away as soon as they’re published. And also, please don’t forget to rate and review the podcast. It really does help new people. To find the show. Thanks. Catch you all next time.

And if you want to know more about any of SAP’s Digital Supply Chain solutions, head on over to www.sap.com/digitalsupplychain and if you liked this show, please don’t forget to rate and/or review it. It makes a big difference to help new people discover it. Thanks.

And remember, stay healthy, stay safe, stay sane!

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Digital Supply Chain, Industry 4.0, Podcast

Digital Supply Chain, Industry 4.0, Discrete Industries, and the Covid-19 Coronavirus – a chat with Stefan Krauss

We are in a very strange times! On this fourth Digital Supply Chain podcast on the theme of Industry 4.0, I had a chat with Stefan Krauss. Stefan is aSenior Vice President and he heads up discrete industries at SAP, so I was keen to have a conversation with him about the impact of Industry 4.0 on discrete manufacturing.

Of course, given the time we are in right now, we couldn’t avoid discussing the current Covid-19 coronavirus pandemic, but we also discussed Industry 4.0, and its effects on industries like Automotive, Industrial Machines and Components, and the Shared Services economy.

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

 

Stefan Krauss [00:00:02] This whole crisis also shows that there will be a significant impact on the whole supply chain in the world. And I think this will go way and beyond this crisis that I think companies have to deal with this new world and we need to really rethink the supply chain processes.

 

Tom Raftery [00:00:24] Good morning, good afternoon or good evening, wherever you are in the world. This is the digital supply chain podcast. And I’m your host, Tom Raftery.

 

Tom Raftery [00:00:35] Hi, everyone. Welcome to the Digital Supply Chain podcast. This is one of the series themed around Industry 4.0. And my guest on the show today is Stefan. Stefan, would you like to introduce yourself?

 

Stefan Krauss [00:00:49] Yeah. Tom, thank you. And hello, everybody. My name is Stefan Krauss. I’m heading up discrete industries at SAP and I’m very happy to talk with you guys about, you know, how we perceive Industry 4.0. OK. You people. Yeah. Go on. Yeah, but maybe before we start, I think as you know, we are I think all in the middle of a, you know, serious crisis. Let. Allow me to really, you know, wish everybody listening to this broadcast, you know? All the best. Let’s all stay healthy. Let’s make sure, you know, we take care about ourselves and our families. On the other side, I think this whole crisis also shows that there will be a significant impact on the whole supply chain in the world. And I think this will go way beyond this crisis that I think companies have to deal with this new world and that we need to really rethink the supply chain processes.

 

Tom Raftery [00:01:48] Yeah, that that’s. It’s a good place to start, actually. Stefan, thank you for me for bringing that up. We are in the middle, as you said, of the Coronavirus pandemic at the moment. This is March 18th we’re recording this. I’ll be publishing this early next week. So, some things could even change between now and then. But from everything we’ve been reading, it’s looking like this is going to last a while and, you know, I wouldn’t like to be an airline pilot right now, as I said to you before I turned on the recorder, or I wouldn’t it to be a waiter in a restaurant right now or a chef or a restaurant owner. That’s huge implications all around. You said there in your opening that supply chains are going to be massively impacted by this as well. How can we help there?

 

Stefan Krauss [00:02:41] Yeah, I think and again, due to this this pandemic, I think we already see that some manufacturing facilities have closed. I think they have already a shortage on parts to really, you know, keep production alive on the other side. It’s also about, you know, do you want to have all your employees coming, coming to the factory? So maybe we as a software company have it a little bit more easy as we can really work remote from home. But I think in all those places where really people are coming together, it’s it’s a tough time. And as I said, I think we all really see some impact on the whole supply chain that there is a shortage. So, I think overall, if I look then into the future and and they this term, Industry 4.0 is heavily used around the world. And there are also other names like Smart Manufacturing or Manufacturing 2025. I think the fundamental thing is really in my opinion, about how can companies best serve the individual customer demands their customers have. I think this is for me the trigger, which causes really the that’s a challenge both on supply chain and manufacturing processes to be very flexible, agile, and elastic to really react on changing customer demand. And of course, this is in this crisis even more obvious. How can we react? And really, you know, produce the right things as long as we can really now produce and fulfilling here the customer demand.

 

Tom Raftery [00:04:20] OK. Very good. You mentioned discrete industries, can you for people who are not familiar with the term, tell us a little bit about discrete industries. What are they? Who are the customers you’re dealing with, and what kind of concerns do they have?

 

Stefan Krauss [00:04:35] Yeah, that’s a that’s a very good question. And I think we are famous for using those kinds of abbreviations. So discrete Industries are industries like automotive, industrial machine and components, High-Tech, Aerospace, and Defence. And when I look particular to industrial machinery and components and high tech industries, what I find very interesting is those industries or those companies, you know, being part of those industries have a two kind of roles in Industry 4.0, because on the one side, I think they want to optimise, of course, their own manufacturing process, their own supply chain. But on the other side, I think with their products, they are selling to their customers. And this is, of course, very often a B2B business. I think they are also helping their customers to then establish industry 4.0 scenarios, to connect machines products, to embed more and more software into the machines. So, I think this is a very interesting or two very interesting industries to look at right now, where we see tremendous change in the, you know, the business processes, the business models and how they operate.

 

Tom Raftery [00:05:49] OK. And in what kinds of ways are industry 4.0 helping these companies?

 

Stefan Krauss [00:05:59] I think, as I said before, it is really about end to end pro or end to end processes, we want to look at starting with really the customer demand, the customer order, which you then want to drive in a very again flexible way through your whole manufacturing supply chain processes. And I think we see more and more companies who want to shorten, let’s say, the freezing time where you say customer cannot change order anymore because now it’s really going into the production process. And you want to be maximal flexible to say, I can still take last changes. And, you know, executed through the whole, you know, production process. And this is something where I think Industry 4.0 will help cost our customers to really change those business processes and create the transparency and the flexibility to react. And this goes also, in my opinion, very much from top to down. So very often we say from top floor to shop floor. So, you want to really create full transparency through your entire production processes and facilities around the world, down to an individual factory and then even down to the individual machines to really have that kind of information and transparency, you need to really steer the whole processes.

 

Tom Raftery [00:07:28] So this transparency is this is something that companies are thinking about exposing to their customers?

 

Stefan Krauss [00:07:37] Yeah, of course. I think because an additional trend which we see is that more and more, you know, business models are saying we are not necessarily selling the product to the customer anymore, but we see more and more this operating model the outcome based business processes, which means a manufacturer of a machine, may not sell the machine, but they will install and operate it for their customers. And then, of course, you can take data out of machines IoT data basically out of sensors and end to end to optimise of course, on the one hand side, the performance and the output of the machine, but I think it is also very much of course used for predictive maintenance processes, for example, when billing. Right. And it’s about the uptime. It is about the uptime and productivity of machines. So, you can avoid, you know, long lasting repair time and so on. And then, of course, the billing, which is basically the interesting challenge later on to say, hey, I pay by the hour, I pay by the output, I pay by, you know, the number of products which has been produced with the machine and so on. So, yeah, it’s very interesting how those business models are evolving and changing the entire landscape here.

 

Tom Raftery [00:08:59] Yeah, and can we speak to some good use cases? Cause, you know, we have lots of customers and that there must be some really fascinating stories you can talk to about some users of industry 4.0 technologies.

 

Stefan Krauss [00:09:14] Yeah, absolutely Tom and I think one nice example, it’s a German company called Gephardt Fördertechnik. They are a leading company in internal logistics and they have really created an IoT platform which allows not only again in their own manufacturing facilities, but also when they of course sell their products to their customers to create this transparency and have those, you know, machines and products really connected and have a dashboard visualisation to really observe all, you know, the the the activities going on in the machine. And as I said before, really run predictive maintenance processes and so on. So I think this is a nice example where Gephardt Fördertechnik is using SAP products like SAP Asset Intelligence Network, which allows you to really connect all those assets at the customer site in a network. And here you can track both structural and unstructured data to share it with the I call it the right ecosystem. So, with whomever you decide you want to share those information that can be employees on the customer side, it can be people from Gephardt Fördertechnik who, you know, offers services, could be a third party service providers. So, I think this is, of course, fully managed to say who has access to those information to really, you know, have full transparency about the machines.

 

Tom Raftery [00:10:50] Ok great for our customers. And again, you’re interacting with a good number of them. What are the… I don’t want to say forcing factors, but what are the things that are moving them into this space most? And what are the kind of challenges that are coming across once they start going down, you know, the route of rolling out one of these projects?

 

Stefan Krauss [00:11:16] Ha! This is another very interesting topic. And I just recently had a meeting with our senior management of industrial machinery company. And they are super successful, let’s say, in their current business. So, they are growing every year. Nice business. Still, of course, top management is saying we cannot just lean back and say, hey, this will be the future. So, for them, it’s really about rethinking. Also, you know, what will be our product offerings here in the future? It’s going even beyond saying, you know. Today they very much sell individual products into we sell solutions. We sell something which the combination of products and services, embedded software. We operate it. So, this this this business model. And I think are a major challenge those cost companies face is I think they might be all very experienced in innovation when it comes to, you know, develop and innovate the next product. Most companies are not necessarily, you know, used to say, I also need this business model innovation. How are we changing the company? And there’s a lot of resistance, of course, on middle management, on let’s say employee level, because for them, they still say, hey, why do we have to change? We are so successful today. This is something, I think where I think top management, and this is also a lot of discussions I think where SAP comes into the game. But also, you know, the strategy consulting companies to really help customers on what I think a lot of people call digital transformation. And how can we really define and and let’s say, articulate those changes through all the entire company. And it really starts with the employee level and then it starts with the skills we need here in the future. So, I think we also see that companies, of course, hiring more and more, for example, I.T. experts, even if they are a machinery company or an automotive company. So, they need a shift in skills.

 

Tom Raftery [00:13:23] I saw the CEO of Volkswagen, whose name has just gone out of my head. Say yes. Herbert Deiss. He said just the other day. Well, that is a couple of weeks ago now. He said that Volkswagen is going to have to become a software company. I mean, that’s a huge change and I mean, he’s been forced into that position by the likes of Tesla and the complete upheaval of the automotive industry. But it just to exactly your point to hear Herbert Deiss say that Volkswagen needs to become a software company. That’s amazing.

 

Stefan Krauss [00:13:57] Yeah. I think he is right. And there are other companies also when we look to some of these Start-Up companies building now the e-cars. I have talked to one. I think they are located in Asia and they say. Our goal is not to produce a car. Our goal is to produce the next screen, the fourth screens, so you have the iPhone and you have maybe the desktop at that stuff. But the car will also act as an environment where people can either work or, you know, of course, enjoy movies and whatever. And then, of course, it’s somehow driving. And I think this is a totally shift in mindset. And yes, of course, Tesla is it’s nicely leading this nowadays. It’s also very interesting when you compare so normally, I think I don’t know how long you drive your car, but, you know, we buy a car and we drive a car for three, four, five, six years. And in the past, you know, you had the car like you bought it. Maybe little accessory here and there. But the features, I think was built in how you ordered the car. Now, in this this software world, you can activate certain components later on. Maybe you have some money left and then you want to invest here into this and that. And I just what you know, funny enough, somebody was was selling or let’s say another one was buying and such and such an E-car and all of a sudden, certain software pieces were deactivated. That’s right. That’s a discussion about use rights. Then later on. So, you get a physical car. But let’s see what really software options are activated or gets deactivated. Yeah.

 

Tom Raftery [00:15:39] I was on the game changers radio show yesterday talking about the future of automotive. And I said we’re seeing I called it the iPhonification of the automotive industry. And I referenced exactly your point about how Tesla are now converting also into a software as a service company, where, to your point, they’re able to turn on or turn off the utility of parts of the car. And it’s where they turn it the car into a platform for software sales. And obviously, it makes it easier for Tesla if they have a single SKU of model and they say they differentiate by the features that are turned on or off in software. So that that makes the manufacturing far easier for them and it gives them a completely different sales model that they sell you a a car, and based on how much you pay, you get X features turned on and or not, and then you can have them turned on later. And of course, I suspect it will be a matter of time before like the iPhone, they open up an app store to developers to develop apps to sell on the car. And this this will completely change how automotive the automotive industry works. And it’s only possible through the likes of the the technologies that we’re talking about.

 

Stefan Krauss [00:17:08] Yeah, I think you’re absolutely right. And I think this has a lot of pros, but it may have also some cons. And we have discussed this also with other, you know, customers of us, because I think we also need to consider maybe whether you are in the volume business, like of course you, you have one SKU and then of course, you sell it in a high volume. The question for, you know, industrial machinery companies where of course, we don’t actually have that kind of volume in all the different segments, is it still, because the business fundamentals are still valid right? It is really about, you know, top line and bottom line at the end of the day. And to just say now I have maybe a machine where I have built all the options in, and the options cost money, of course. And then the customer may activate it or may activate it later or even not, it’s not necessarily a good business case if you’re not really in a volume business. So, I think that is not the one answer to everything right now. And this is why, again, I think customers or companies really have to throw a think through on, you know, what of those new business trends and models will really stay relevant, relevant in the meaning of creates, you know, business value and business outcome for them later on. And we see already first all the automotive companies who started, for example, with mobility services, and they stopped it already by saying, oh, looks doesn’t look like a good business case for us. So, this very interesting times where I think it’s very much about also, you know, testing, trying failure, you know, adopting and then and it’s not the continuous improvement business. Many companies have been in for so many years.

 

Tom Raftery [00:18:59] Yeah, it’s it’s challenging. And something just occurred to me the other day as well. The whole idea of the shared services industry is going to be, I suspect, massively hurt by Coronavirus, I mean, are you going to want to get into a car that you don’t know who’s been in it before you?

 

Stefan Krauss [00:19:18] You’re right. Just thinking about it as you said it. Yeah, because I was just reading this morning in the newspaper that, you know, people are asked to, of course, use more and more their cars and not maybe, you know, public trains and buses and so on. And then, of course. Yeah. That’s also very true what you said on those kind of, you know, mobility services. Yeah.

 

Tom Raftery [00:19:39] Yeah. Yeah. That I suspect they’ll take a huge hit. Stefan, we’re coming to the end of the podcast we are at about 19 minutes now, I just said I’d ask you; is there anything that I have not asked you that you think I should have?

 

Stefan Krauss [00:19:57] I think we could talk about this this very interesting topic for hours and hours. I know. I know. Happy we if you want, we can also follow up. But no, no, I think for today, I think we covered the main points. And maybe to summarise it from my point of view. What we see this is not about technology. It’s about really business value. I think companies want and need to achieve. And this is where I think we see leading companies already, you know, heavily in and where, of course, laggards may need to follow. And it’s all about not only the processes, I think it’s also how to use all this data which are available nowadays coming from IoT sensors and so on and so on from the Internet and make good business usage and value out of that. I think this is my, you know, maybe suggestions or, you know, kind of credo companies should look at. And this is also, of course, where we as SAP want to help many companies on this digital transformation, both on a business process talk, but also then, of course, with our solution and service offerings we bring here to the table.

 

Tom Raftery [00:21:13] Super, Stefan, if anyone wants to find out more about Stefan or about discrete industries or about any of the other things. Where should I direct them to go and any links you give me, I can embed them in the in the in the description of the show notes. So, fire away. Where should you, where would you like me to send people?

 

Stefan Krauss [00:21:36] Yeah, I think of course, happy to share with you. I think you all can find me on LinkedIn, of course, Stefan Krauss and Krauss with double S. So, I think it’s a very common name. But also, I think please join SAP’s, you know, SAP.com and then you can find via the link to industries. A lot of those kind of, you know, trends and of course, of solution offerings we have. You can find nice whitepapers which we have written for all of our industry to translate basically those trends which we see in industries into, you know, how SAP can support here. So, I think that what would be my two main sources I would like to point you to.

 

Tom Raftery [00:22:18] Perfect. Perfect. Stefan, that’s been great. Thanks a million for coming on the show today.

 

Stefan Krauss [00:22:22] Thank you very much Tom. See you soon again. And have a great day. And please all stay healthy. That’s is most important.

 

Tom Raftery [00:22:30] Indeed. Indeed.

 

Tom Raftery [00:22:33] OK. We’ve come to the end of the show. Thanks, everyone, for listening. If you’d like to know more about digital supply chains, head on over to SAP.com/DigitalSupplyChain or simply drop me an email to Tom.Raftery at SAP.com. If you’d like to show, please don’t forget to subscribe to it in your podcast application to get new episodes right away as soon as they’re published. And also, please don’t forget to rate and review the podcast. It really does help new people to find the show. Thanks. Catch you all next time.

 

And if you want to know more about any of SAP’s Digital Supply Chain solutions, head on over to www.sap.com/digitalsupplychain and if you liked this show, please don’t forget to rate and/or review it. It makes a big difference to help new people discover it. Thanks.

 

 

 

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

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

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

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

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

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

Good morning, good afternoon or good evening, wherever you are in the world. This is the digital supply chain podcast and I am your host Tom Raftery.

 

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

 

HT: Thank you very much.

 

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

 

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

 

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

 

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

 

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

 

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

 

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

 

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

 

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

 

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

 

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

 

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

 

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

 

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

 

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

 

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

 

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

 

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

 

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

 

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

 

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

 

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

 

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

 

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

 

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

 

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

 

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

 

HT: Thank you.

 

 

And if you want to know more about any of SAP’s Digital Supply Chain solutions, head on over to www.sap.com/digitalsupplychain and if you liked this show, please don’t forget to rate and/or review it. It makes a big difference to help new people discover it. Thanks.

 

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

The advantages of Digital Supply Chains – a podcast with Johannes Drooghaag (aka @DRJDrooghaag)

I started a podcast series called The Digital Supply Chain podcast over on DigitalSupplyChainPodcast.com (because I have no imagination and that can’t hurt the search engine rankings!).

For the most recent episode I used Lately‘s transcription service to output the text of the podcast so I could add it into the post but Buzzsprout, my podcast host doesn’t allow posts with a lot of text, so I decided to post the podcast, and the full text of the conversation here. I hope you like it – do let me know in the comments how I could make it better.

This is episode 17 of the Digital Supply Chain podcast. In this episode I interviewed Dr Johannes Drooghaag (also known simply as JD, and @DRJDrooghaag on Twitter).

We had a wide-ranging conversation on Digital Supply Chains covering many aspects including Manufacturing, Industry 4.0, and cybersecurity.

Check out the podcast above, and the transcript below:

TR: Good morning, good afternoon or good evening, wherever you are in the world. This is the digital supply chain podcast and I am your host Tom Raftery.

TR: Hey everyone. Welcome to the digital supply chain podcast. My name is Tom Raftery with SAP and my special guest on the show today is JD. JD would you like to introduce yourself?

JD: Well, thank you Tom. First, first of all, thank you for having me on your, on your podcast. I’m really appreciate this opportunity. Um, my name is Johannes Drooghaag but it’s shortened to JD because that’s much easier and it doesn’t hurt so much to pronounce. Um, I started my career in industrial automation, the classical way, putting a lot of robots and a lot of sensors and a lot of PLCs in a factory. And through time I learned that there are other options and that we can do a lot more with the, with the data we are collecting and turn it into information or what I prefer actionable information. After some 25 years career in corporate roles, I decided to start my own consulting company and I’m focusing on those two fields on the, on the one hand and the organizational side, do human being that is working with the information. And on the other side, the technology that is creating the data out of which we can create that actionable information. I’m 30 years on the, on um, on the road now and I keep learning every day. And that’s one of the reasons why I’m with you today, Tom, to keep learning from you as well.

TR: Oh dear. No, no pressure on me. So no. Okay. So I, I typically start the show asking the guests on the show to give me their personal definition of what a digital supply chain is. Because you know, everyone has a kind of a slightly different approach to it. It’s a broad topic. So how do you define digital supply chain JD?

JD: Well, for me, the digital supply chain is basically the digital twin, so to speak, of the classical supply chain, which as we all know it with, with all the parts moving and the orders. And the digital supply chain is, is the digital twin in which we can do two things. We can constantly respond to what is happening because we need to respond much faster than we used to do in the past. In the past we had mass production, we had large batches, we had orders which were sent out months before we start producing. Nowadays we have to, we have much more dynamics. Orders are changed, we have smaller volumes, we have smaller production batches. We even want to avoid production batches. We want to create, um, single piece flows in our factories. And the second thing we can do is we can start simulating in our digital supply chain. We can do real what scenarios without actually having to touch the process. So we can start looking for opportunities and for optimization, uh, items. We can also look back to the past and see what failed, what didn’t do, what we were expecting that it would be doing and how can we prevent it and what can we learn from that. And that for me is the digital supply chain. The information that we on the one hand get from the existing supply chains, which are much more complicated than they were in the past. And on the other end, the learnings, the organizational handling of that digital supply chain.

TR: Excellent. Excellent. Very good. Very good. You, um, you started off saying that there were kind of two aspects to, uh, your, looking at digital supply chain. One was the human side and the other was the actionable items. Uh, you know, I’ve, I’ve often said that, in these kind of scenarios that the technology is generally very straightforward. It’s getting people to change because the hard part is, is that, is that your, inkling as well that, you know, technology is generally straightforward. People are hard?

JD: Well, we can make the technology as complicated as we want, but that doesn’t lead to anything, right? So if we put, if we start with a straightforward concept and then make sure that the people who we expect to work with it also actually understand what we are expecting from them, which, which kind of responses we want, then we see that there is a, um, an enormous gap because most people are already pretty much loaded with their actual work. Um, and, and we need them to first of all have the mindset then what that when the system is telling them something, they should take it serious. And now on the other hand, they need to understand what the difference is between some kind of general status update and an urgent item that they actually need to respond to. Now having three decades of experience, I have learned a couple of things. First of all, people do not really trust the system because there’s always something which is not right. If we take a closer look, that means we can learn and we can say, okay, we found something in the system, which is not correct. Let’s improve it. Yeah. But the human behavior is to use that as an excuse almost to also ignore all the other things that they see in the system. And the second thing that I’ve learned is when you’re busy going from A to B and somebody is telling you there’s a smarter way you could go through C and then to B, okay. You were focused on going to B, so you’re not paying attention to that additional information. And that’s an enormous challenge on top of the normal change management and organizational challenges we already have.

TR: Yeah,indeed. And how do you overcome that?

JD: Well, the first thing that I always do with my clients is start with the people and look at what their routines are and look at what kind of information they would need instead of the information that they have. Because what I see in my experience is that most service providers make the mistake of just sending more information to the already available information. And production manager or a scheduler or a planner doesn’t need a new report on top of all the reports they need to report or an information overview that tells them what to do and where they should respond to. So I start by filtering. I start by asking them, if you have 20 reports and I take 10 away, which one would that be? Yeah. And the interesting thing is that in most of the time when I ask for 10, they give me 18 because they’re going to use me.

TR: Yeah. There’s a professor of journalism New York whose name is Clay Shirky and he’s got this great quote that I love. He says, there’s no such thing as information overload. There’s only filter failure.

JD: Exactly. I love that.Yeah, yeah, yeah, yeah. No, that’s great. That’s great.

TR: You, you talked as well, uh, not just about the, the people aspect, but of the actionable items. What do you mean by that?

JD: Well, an actionable item. I always take the example of the, of the scada world where I’ve, I’ve spent five years, um, all over the world. If you look at the scada system, you will always have a state to screen where where the operator can see entire refinery or the entire pipeline or any other utilization of that scada. But as soon as the operator is expected to take action, that is automatically put in focus. So at the moment that the operator is expected to take action, the operator sees that action item and that can be a small decision. That can be a big decision, but the system automatically, um, focuses the attention of that operator on that particular item where an action is needed. Okay. Providers of SCADA systems have learned over over the years and they have learned that if you keep that action item in the entire status screen of the refinery, operator won’t notice it because it’s just one little thing in sometimes they have up to a thousand different aggregated devices in the overview and an actionable, actionable item. And an actionable, actionable piece of information means that first of all, the person who shoots take action is informed in the proper way without any kind of distractions. And secondly, the person has a couple of options or has supporting information to make that decision. Now, if I then compare it to what I see, especially in production facilities, that there’s an operator is overloaded with a lot of status written information, which that person should not respond to. And hidden in that stream is that one item where the person should respond to, well then I cannot blame him for not seeing it or ignoring it or pressing the standard button. So the, the popup goes away. Actionable information means to me, I see it when I need it. I get the information I need to take a decision or that actionable information informs me that something is not the way we wanted it to be and I need to do some, some optimizing or it means I need to get some additional resources.

TR: Right. A lot of that sounds like it’s, um, it’s design led issues potentially are maybe not maybe issues with the wrong word, but uh, properly designed screens and user interfaces should do away with a lot of these issues.

JD: Exactly. And then it’s also a system thing because if you look at a supply chain, then it’s not just a screen on a, on a machine. It is a whole stream of information. And if I have somewhere in my supply chain, the change, which was not part of the current, um, planned activities, I cannot wait until that arrives at my facility. I need to respond to that with the appropriate lead time. And if that means a change over in the production planning and that means that I need to schedule some additional machine change over, I need to know that in the proper appropriate time. So we also need to add some intelligence to it. We need to add, um, which timeframes we need. We need to add which kind of materials we need. And if we start figuring that out at the moment that it has already happened, well we are too late, especially when our supply chain is a bit more complicated then the local grocery shop.

TR: Okay. And so you, we have some customers with some very, very complex supply chains. So yeah, like tying all those disparate pieces of data together can prove challenging.

JD: Exactly. I always use this, this lovely example from my own automotive experience. If we look at at the classical, at a car, we have up to 40,000 components. If we look at an electrical vehicle, your favorite topic, we still have about 10,000 components for just one car. Yeah. Now if make one change, just one change, we might have to reschedule, um, a couple of, of those components in the assembly. Now the further we go down the line in that supply chain and we make that significant change, well the more others will have to respond to that. So supply chains are complicated and supply chains are no longer, um, single or dual parties. The same car with, with 40,000 components has up to 1,500 suppliers of those components. And that needs to be managed and it needs to be managed very actively.

TR: Yeah. Yeah. If I needed them or delayed and getting parts to you. Maybe there’s a Coronavirus outbreak and they can’t get their workers to their factories and they have to hold production. It throws everything out.

We are managing the past. With a digital supply chain we are capable of learning how to manage the future

JD: Exactly and if you do that in a in a smart way, and this is what I really enjoy about the digital supply chain because the Corona virus is an example. We have a crisis that might impact our supply chain. Now if we have a properly built and properly designed digital edition of our actual supply chain, that’s the moment where we are capable to say, okay, what happens if we, for example, slow down this line of supply and what does that mean for the other parts? Can we make changes in the capacity or can we increase some full human from another supplier and decrease some folio with this supplier and navigate around that crisis and that crisis never establishes the way we thought. So we can then the next day updated again and we can really start looking forward instead of what most people in the supply chain business always tell me. We are managing the past. With a digital supply chain we are capable of learning how to manage the future.

TR: It’s a, it’s an amazing change isn’t it? In in going from older, more analog technologies where as you write these, say people ran a lays in the past to the digital where we’re analytes in the future. It’s, it’s, it’s, um, I don’t know how to, how to phrase that exactly, but it, it’s, it’s, it’s a huge, huge change in the way people are now able to do business.

JD: It’s, it’s an amazing change and it’s, there’s the simple, in English, we have a wonderful, in German it’s, it’s, it’s almost as wonderful in English we can say, it makes the difference between reacting and acting in the classical analog supply chain management, UI reacting. You’re always reacting to things that have already happened in a digital supply tent. You can act based on the things that you know that will happen because that’s the information you receive. And that’s how you can build your scenarios.

TR: Yeah, that’s it. Exactly. Um, JD. Looking forward the next five, 10 years, where do you see the, the, the biggest, we’ll say potential for change. Um, where do you see the biggest changes that are going to happen? How will they impact?

JD: Well, the biggest changes that I will see, there’s one thing that we are not yet aware of the up to 80% of the production facilities we currently have are built in the previous century classical, uh, built for big batch batches built to, to produce a lot of the same. And companies are starting to learn that you can still use those industry 4.0 and the IOT and the smart supply chain solutions. You just have to be a bit more creative about how to implement them for those, those classical old things. So one of the things that I am already seeing and it’s developing, fortunately that companies are moving forward with their infrastructure, which is in some cases they still plan to use it for the next 20 years. So people stop. I’m believing that all those, all those, those technologies are only available when they build something new or Greenfield facility or to purchase a new machinery. We see that rolling out into the existing infrastructure and that I believe is a wonderful change.

TR: Yeah, yeah, yeah. We, we had an example, I mean, we have, you know, a bunch of examples with different customers, but there was one that, uh, really kind of blew my mind and it was with Harley Davidson. It used to take them 21 days to create a custom motorbike and when they shifted over to digital manufacturing, they brought the time of manufacture from 21 days down to six hours. Just incredible.

JD: That’s incredible. But, but that’s possible.Yeah. Yeah. it’s going back to what you were mentioning, uh, going from facilities which are built to just build lots of, one type of thing. And then when you try and do custom, in this case, motorbikes, it takes a lot more work and takes 21 days. When you switch to a facility which is built to be completely customizable and your lines could be completely fluid, uh, then you can do mass customization and then kind of lot sizes of one and you can drop the time to manufacturer again, in this case of bikes down to as six hours for a custom Harley.

TR: It’s, it’s, it’s really impressive.

…that’s also what industry 4.0 is about. And that is what, what a smart supply chain is about. It’s not just about more data and more technology, it’s especially about becoming more flexible so you can respond to what happens on the market

JD: That’s, that’s, that is really impressive. But it also demonstrates what is possible if you move away from the classical, from the classical patterns. In some cases, that will mean that you actually need to invest in your existing machinery in some cases will mean that you, uh, that you must must reduce some capacity for the mass production, which you don’t need any way, uh, anymore. And in some cases it means that you actually discover that your equipment is doing, is capable of doing much more than you thought it could. You just have to sit down and, and with, with concepts like design thinking, most of it is logical thinking. You need to be able to investigate, to explore, um, to do some, some testing and discover how flexible you can become. Because that’s also what industry 4.0 is about. And that is what, what a smart supply chain is about. It’s not just about more data and more technology, it’s especially about becoming more flexible so you can respond to what happens on the market. Right?

TR: Yeah, that’s true. That’s true. And in the case of Harley, it wasn’t that they did it in the same facility, so they kind of, I won’t say they cheated, but it took a kind of a hybrid approach. Uh, they built a second facility beside their existing facility and then they transferred all of their staff and all their machinery into the new facility. But it was two thirds the size of their existing facility. And yet, and yet, because it was completely digitized, they were able to then, as I say, bring the, the lot times down from days to hours.

JD: Yeah. But, but this is, this will happen in, in many cases and sometimes you have the luxury to say, okay, I’ve got a second production facility and I can basically redesign my existing process with a single piece flow concept in mind instead of batches and long production. In other cases you will have to do that. And we did it at one major automotive supplier, which unfortunately I cannot mention by name. We did it. We did the same thing we did in the existing facility. We started with machine number one and, and eliminated all the batch containers and, and uh, the batch flow, um, and created a single piece flow structure around that and then took it to the next level. And it was very fortunate that we have a very good tie in of the ERP system from, from SAP at that moment. So we could get all the production data, we could get, um, all the, all the settings, uh, the proper product identifications from the system. And we were capable of building a single piece flow throughout the production facility. It took two years because we had to do it step by step and we could not, um, go from, from, um, from the old school to the new school, uh, by just closing down the factory. But one of the results is, is that we decreased the capital on hand to time, which was around 18 days. Um, we’ve decreased that to two days. So from purchasing the material to shipping it to the next facility was reduced by, by more than 80%. That is serious money.

TR: That’s a lot, yeah. That’s impressive. That’s really impressive. Yeah. That’s amazing. Okay. Look JD. We’re coming towards the end of the podcast and uh, typically at this time of the podcast I’ll ask people, uh, is there any question that I haven’t asked you that you wish I had?

JD: Um, one question Tom, and that’s my favorite second topic. Cybersecurity. Um, so if you ask me, um, JD, what would be your top priority in digital supply chain? Besides all the technical opportunities we have and the organizational opportunities we have? I would say cybersecurity has to be the top priority because the more digitized we get, the more risk we have that something bad happens to the digitized world. So cybersecurity, big picture approach, make sure that it is by design and not by coincidence.

TR: Very good, very good. Very good. Yeah, no, hugely important. As we are, uh, opening up our manufacturing facilities and our logistics and everything as we’re opening them up to the internet, we are massively increasing the threat landscape. So yeah, absolutely. Very, very important to consider cybersecurity from, as you say, from the design phase, right through not, you can’t be something that you kind of cobble on afterwards dead right?

TR: So JD, if people want to know more about yourself, what’s the best place they can go to find information about JD?

JD: Well, they can visit me always on my LinkedIn profile or on my website under your JohannesDrooghaag. My website is JohannesDrooghaag.com. Unfortunately, jd.com was already taken, so I kind of,okay. Um, I am on Twitter. I am on, on Facebook, Instagram. Twitter is my main social media exposure. They can find me there under JohannesDrooghaag as well. Um, and otherwise, uh, drop me a note at my website and I will, uh, reply as soon as possible.

TR: Superp, super JD. I will put those links in the description of podcast when I publish it so everyone can have access to them. Thanks a million for taking time and joining me on the show today.

JD: Well, thank you for having me, Tom. It was a great discussion.

TR: Okay, we’ve come to the end to show thanks everyone for listening. If you’d like to know more about digital supply chains, head on over to sap.com/digitalsupplychain, or simply drop me an email to Tom dot raftery@sap.com.

And if you liked this show, please don’t forget to rate and/or review it. It makes a big difference to help new people discover it. Thanks.

This episode was originally published on the Digital Supply Chain podcast.

Internet of Things (IoT)

IoT, and the transition to the digital services economy discussion with Constellation’s Andy Mulholland

Over on the IoT Heroes podcast I recently had a chat with Constellation Research analyst Andy Mulholland. Before coming out of retirement to head up IoT research for Constellation, Andy was Global CTO for Cap Gemini, and so he knows a thing or two about IT!

Andy publishes extremely insightful articles on the Internet of Things regularly over on his blog, so I was keen to have him come on the show.

In the podcast we had a wide-ranging discussion on the implications for (primarily) manufacturing organisations of the Internet of things, the transition to the as-a-service economy, and how people can get up-to-speed on happenings in the IoT space.

If you have any interest at all in the Internet of Things, and how it will effect our society, you should check out this episode of the show – you can subscribe to the RSS feed, subscribe on iTunes, or simply click Play on the player below to hear our discussion

 

Photo credit Toyota UK

Technology / Software

With great power comes great responsibility – or, Cloud companies need to get on-board

Spiderman
With great power comes great responsibility

This great quote from the movie Spider-Man, is just as true for technology, as it is for superheroes.

Technology has made possible tremendous changes in our quality of life in the last couple of decades. Everything from surgery to transportation, education to construction, space exploration and most other fields of human endeavour now depend heavily on IT. However, these great advances in our knowledge and abilities comes at a cost.

Information Technology’s carbon footprint, estimated by Gartner to be 2% of global carbon emissions in 2007, is rapidly increasing and by some estimates may even double by 2020. This is obviously an unsustainable situation. ICT, which can help so many organisations to reduce their carbon footprint, should itself be an shining example of low emissions.

To this end, the EU commission’s new ICT Footprint initiative is to be lauded. The announcement of the project on EU Commissioner Neelie Kroes blog gave the following details of the initiative:

This is why the European Commission has persuaded three leading standards development organisations and a prominent greenhouse gas accounting initiative to pool their measurement efforts. Under our new initiative these organisations will examine the whole sector, the whole lifecycle and the scalability of these methods.

That means measuring everything from the supply of raw materials to their recycling. Measuring not only what it takes to make products like a laptop, but also the impact of services like hosting data in the cloud. It means that in the near future we will be able to measure the ICT environmental footprint of whole cities or countries, including the positive environmental effects that ICT enables.

Several major ICT companies and organisations from Europe, Asia and the US are now trialling such measurement solutions. And from this month onwards, nearly 30 players have joined the European Commission to broaden and speed up the effort. We call on more and more such players to get involved.

It is tremendous to see this kind of global leadership from the EU. While this only applies to the EU, it does require the development of measurement and reporting systems for whole IT ecosystems and that can only be a good thing. In time, the hope would be that these systems are used well beyond the EU and by all IT providers…