Welcome to the Trend Detection podcast, powered by Senseye, an industry leader in using AI to drive scalable and sustainable asset performance and reliability. This is a new publication designed to help you go away with ideas on how to achieve maintenance efficiencies.
For this 3-part series, we are joined by Vasilis Karamalegos, CEO and Co-Founder at Smarter Chains, a company that is helping manufacturers achieve Industry 4.0 Transformation at Scale.
In this episode, we discussed whether manufacturers are adopting predictive maintenance technologies, the key challenges they face achieving successful digital transformation and the how to create a joined-up approach to rolling out new technologies
Key topics covered (click to jump to the section)
- Are manufacturers adopting predictive maintenance technologies?
- Key challenges to achieving successful digital transformation
- Deploying technology across the enterprise
- Benefits of digital transformation to society
Niall Sullivan, Senseye: And that's a really interesting answer. And thank you. And I realize that question, we could just have a whole podcast on that question actually, I think personally, but might go on for a while.
Vasilis Karamalegos, Smarterchains: I fully, I fully, I fully agree. And I tried to make it as simple as possible but it's a massive question, really.
Niall Sullivan, Senseye: And of course it depends on the setup, how far along their digital transformation journey, what the issues they're experiencing.
While we're talking about technologies and you mentioned predictive maintenance, which obviously close to Senseye and my heart let's say, but how are you seeing manufacturers adopting that sort of technology? Are they engaged with it or do they understand it or is there still a level of education that you're finding for that particular type of technology?
Vasilis Karamalegos, Smarterchains: I mean, education is key, 100%. In most of the technologies, in our framework we have a whole pillar which is called educate because it's very important to harmonize the level of understanding in the organization.
You have always different guidelines of expertise and knowledge. Some people read more than others, some people they like to experiment more than others. So it's very important that you have a harmonized understanding.
So you bring everybody to the same page and this is for all the technologies. Okay. It's not only for predictive maintenance or for us, a health type of interventions.
If we talk specifically for this, absolutely. There is so much to be done. We have clients that, they have historzation but they don't use it, which is a tremendous amount of intelligence, because all this type of software from the moment that you do have, you can talk to the machine, right? So the machine can talk to you. So you can really get the data, historize the data, and then start making sense of the data.
There is tremendous education for the client to how this would really try that internal work processes, because that's a very big thing as especially for the maintenance function, even if it is indirect, or even if you have tasks that your operators are doing from a maintenance point of view.
On the line, is going to radically change the way that they're doing the work. It's going to be more fun. It's going to be far more valuable, but still there is a learning journey that needs to happen in order for this to come to fruition and eventually drive value.
Niall Sullivan, Senseye: Absolutely. Absolutely. And I want to take the conversation back to digital transformation briefly. There was a couple of questions here.
So I know you've summarized this to a degree but it'd be good to have your view on the key challenges of achieving successful digital transformation, first of all. And so that's a really good place to start, just to summarize your thoughts on that, because I know you've mentioned a few issues there already.
Vasilis Karamalegos, Smarterchains: So we are now launching a white paper which is called the Industry 4 Framework for Smart and Sustainable Factories, in which we talk about the four pillars or challenges if you like, for successful transformation.
Number one starts with all things leadership, meaning of course we have a lot of islands of excellence across the organization driven by the curiosity of local leaders, but they want to experiment.
But in many cases they do this without having a common enterprise-wide vision. And then this makes it impossible to overcome the inertia that comes with habits. And we are human beings, right? So it always comes like this.
So a cohesive strategy that engages both the plant and the enterprise, but then is enabling the plant to do its own journey, but based on specific enterprise process is the way to go.
And this is really requiring a very different mindset, especially on legacy type of organizational designs that the plants, they were always holding the P&L so they can take decisions.
But the reality is that the value you can take from a technology, especially from the investment front can be 30 to 40, maybe 50% less, if you adopt it on an enterprise scale, rather than doing it locally, which is going to be maybe a far more lucrative business case. So leadership hindrance is the first pillar.
Second pillar is technological and vendor complexity. So as I usually say, the pace of change now and of new technologies now, is the slowest it will ever going to be.
So this means that a lot of new technologies, new business models as I described before, for example, for robotic, and many other type of things that you don't have to buy, but you can in a way lease. So it becomes cheaper and much faster to adopt.
So the landscape is becoming very complex. Hundreds of different technological choices, thousands of different vendors that you have to be following up.
So it's very important to understand exactly why you need the technology, and why you need the technology not only for one plant but across the enterprise, so you can really make the right choices, that you can be streamlining and getting the most out of it.
Then we have the application, and of course avoidable cost. Of course, when you do things in isolation from the enterprise you will have this. So you're not able to really synergize and platformize opportunities.
And then of course, last but not least is all things change management, in many cases because the fundamentals are not there. So you don't have an enterprise strategy, you haven't communicated the vision. You don't have an appealing storytelling. You haven't allocated specific good and strong and respectful ambassadors of the change.
Because let's not forget, this is going to have huge impact on how people do the work. Actually it's going to really amplify how much better they're going to be doing the work. But nonetheless, is important that there's clear communication of what it means down to each individual on the shop floor.
Now, another talent of change management is how do we scale the learnings across plants, across operations, across different partners. Meaning, how do we drive an orchestrated, quicker execution that leverages data and technologies that we're investing in that can unlock new opportunities.
Because each organization always, regardless of what we recommend them and what it might be like, low hanging fruit, they always find a lot of opportunities in synergistically, meaning when they see their operations and the problems on the plant with other plants across the network, even with partners as well.
Niall Sullivan, Senseye: And I think the point I wanted to pick out there, that's a really good answer, thank you.
The point I wanted to pick out is, and it's something we see as well is, a lot of rollouts of tool technology or digital transformation we see with manufacturing plants. It's usually a plant by plant basis so there's not really a joined up approach a lot of the time.
Do you acknowledge that fact as well and how do you actually overcome that and be able to deploy some of these technologies over a whole enterprise or multiple plants rather than on an individual basis, which obviously creates issues around data silos and lost knowledge and all that side of things.
Vasilis Karamalegos, Smarterchains: All our framework, all the smart for change, platformize framework, is built to drive enterprise value.
We go from the plant, understanding the needs, technological and value creation needs of the plant, but then we put all plants together to the enterprise in order then to select the technologies that have the biggest applicability, but also the biggest value impact. And only when we are very clear on that, then we create the roadmap that is driving the execution.
So like this, we completely avoid the typical mistakes that you have just described, but this means that by design, we are engaging all the organization and we have built a platform, the smart for change platform, to do exactly that in a very easy way, very data driven way, so everybody is engaged.
We have all the insights, so when the strategy definition happens, we know exactly who needs it. We know exactly the applicability. We know exactly the value. We know exactly the priority. And we know exactly what's going to be the different organizational interventions that need to happen as well to make the value of the technology be as much as possible.
Niall Sullivan, Senseye: Fantastic. And also think about digital transformation as well. So it's not just a benefit to different manufacturing plants but there's also a benefit, and I think you mentioned this in the report I read as well, there's actual benefit to society as a whole as well. And so maybe you could define some of the benefits to society of successful digital transformation as well.
Vasilis Karamalegos, Smarterchains: I would start with focusing resources where they really matter by eliminating the losses. Empowering and connect the workforce, upskilling everyone. Improving the sustainability of the operations. And then of course be able to really help companies scale to other countries, to other products, better, faster. And of course at the end of the day, provide greater propositional value to everyone.
Now, in this report has a lot of things right, a lot of things, and is really enabling a radical transformation. So it's helping us with organizational agility, upskilling, building a digital mindset. Eventually will really enable us to go to modern demand manufacturing as well, by having the intelligence to understand where we can and where we cannot. Providing synergies between human and the machine.
And of course, drive closed loop thinking and decision making like the centralized systems so we can drive far more speed and collaboration by empowering our people on the shop floor to drive better decisions, which of course drives more motivation for them to do their work and drive better business benefits.
From a society point of view, we see clearly from a society point of view. So we take out the business, if you like, elements. Industry 4 is going to really help us upscale from a matter of doing stuff, using more data, using technology to collaborate better, having a far more agile way of working, but also the mindset as well, being more open to new things.
Learn to be working in a more continuous changing environment, which of course as humans by design, we prefer to have less uncertainty than having more certainty. But I think it's going to be far more balanced which eventually, even on the personal level is going to be far better on how we live our lives in a world especially that is changing all the time.
Niall Sullivan, Senseye: Exactly. And it is, and like you mentioned before earlier in the podcast or earlier in the episode, about society is changing and at the minute there's a lot of turbulence at the moment as well which is causing a lot of issues around the world as well so that obviously contributes to it too.
So I wanted to move on. You've mentioned a few times about your framework and we've heard some really useful insights into that, but I thought I'd give you the opportunity as a set question I guess, to actually dive into that a bit more.
So you've created this framework for Industry 4.0 digital transformation. So what's the story behind it. I mean, why did you create it and what was the challenges you were seeing that led to its creation?
Vasilis Karamalegos, Smarterchains: It's a very good question. First of all, we didn't start by creating an overall framework. We started with focusing on how we can really drive technology adoption more by providing an outside-in perspective on companies, meaning benchmarking and opportunity identification.
Then based on demand from clients, we moved on correlating the demand of understanding the value of the technology on the software.
Then we moved on providing what are the different interventions and what is the business case. And the business case, not the generic top-down that many other frameworks, they have, which you just take some high level KPIs of a business and you make sense of it, because this cannot drive a decision.
You really need to go down to operator activity, production line level, to really come bottom-up with a clear understanding of what is the value. Otherwise, it's impossible to understand which technology, and it's only accelerating, how many technologies will make sense.
Once you have the strategy then you need to operationalize it. So you need a master plan. You need to know exactly with whom you are working, how the timelines and the value and the learnings.
So there we developed also a PMO framework inside the framework in the software that you can really be able to really templating the execution pathway. So you don't have to be replicating and reinventing the wheel for this technology every time.
Then we were doing a lot of education but as part of the sales process if you like, of the education process, right? But now, it's quite a few years now, so we were trying to bring Industry 4 as the future of manufacturing.
We collaborated a lot with IMD University in Switzerland, which has one of the premier distance supply chain courses. We have educated more than 80 different companies, mostly blue chip clients, consulting companies as well, on the framework and digital transformation.
And from that we published, together with IMD back in 2019, a case study that we were using for executives, senior executives, to go through the process to understand the multi integrative nature of Industry 4.
So we published this to the Global Clearinghouse and we won in 2019, the Best Global Supply Chain case study on that. And this is where we realized that, okay, you know what, there is a need for education as well, but structural education.
The education that you can really try to standardize, whatever it can be standardized because there's a lot of things that of course, company specific, industry specific, but from a technological point of view, most of the technologies are pretty standard. They're accelerating, yes, but they're pretty standard. So then we developed the last piece of the framework, which is the education.
So our framework now has four elements. The educate, which is we have it on the beginning, not because it can only be at the beginning of the process, because you can educate your people after you have a strategy or through doing the strategy or even when you start execution, or different personas. But the educate is a beginning of the framework.
Then we have the prepared phase, which is where we do the technology assessments and the value creation assessments. We never visit the plant, by the way, we are a platform. We do this everything virtually and full data driven, so we enable full visibility and we take out any subjective perspective. So we are completely focused on the objectivity of the operations.
Once we have the prepared phase complete, and we know where we are, and we know the value, we are moving into a data fusion to understand exactly what makes sense from a financial point of view to implement. And I'm talking financial point of view because at the end of the day you have to pay for it. So you need to make sure that there is a value, there's a clear value, and you can drive accountability and ownership of the value. And then of course is what I described before, the execute.
So we have the four pillars of educate, prepare, define, and execute. But the challenge is how do I go through this journey while I have so many different personas and so many different functions and so many different operational areas that have different interests. There we have developed the compass as we call it, which is the 10 Industry 4 dimensions that I taught in the beginning, which is the compass that acts as the way to understand how each operational area and person in the plant is impacted.
There we have three different pillars on the compass, the people, which is the fact of the future leadership and digital organization dimensions. We have the processes which is all things raw material to finish good, intelligent quality, data-driven maintenance, automated material flow, and zero touch production. For example, Senseye, you are under data-driven maintenance.
And then we have the tech dimensions, which is all enabling technology dimensions, like connectivity, 360 factor visibility, sustainability, digital infrastructure, and the tech augmented workforce. So the compass follows the user on each part of the journey. So we educate our clients on the 10 Industry 4 dimensions. We benchmark and understand the value of our clients around the 10 Industry 4 dimensions. We define the strategies and interventions around the 10 Industry 4 dimensions, and we execute on the PMO on the 10 Industry 4 dimensions.
So this provides a holistic framework that is touching all performance. Is virtual, everybody can use it. Is value driven and fully data driven so you can measure progress. And of course you engage everybody on the organization, as well as being a tool of a continuous learning and recalibrating strategy and execution. Because as I said in the beginning as well, that's not a one off journey. Is not that I have a strategy, that's it. You need to all the time track where you are because the pace of change on the external ecosystem is far bigger than the internal.
I'll give you an example, last year we didn't have integrated process health and machine health, but when a vendor is acquiring another one, when you have two vendors having one offering, so maybe your roadmap that had two different steps, you don't need two. So you didn't need to know and be on top of it. So when you are investing, because a roadmap is the thing that you're doing for years, you always need to be in sync with the changes of the external environment to make good decisions.
Niall Sullivan, Senseye: I mean, first of all, thank you for the answer. I think you actually answered three of my questions in one, Vasily, so thank you for that. That's a really good answer. Really good overview as well.
I mean, the area I wanted to dig into, or one of the areas I wanted to dig into is, you mentioned about defining value and how important that is. So maybe you could open up a bit more about that and how do you actually define value at that stage in the process?
Vasilis Karamalegos, Smarterchains: So on the prepared phase we have two products, the maturity assessment and the loss analysis. The maturity assessment tells us where you are from a technological maturity point of view. What are the opportunities you have and how do you benchmark? The loss analysis tells us bottom-up, where is the value down to the operator activity? So we know exactly at this stage of maturity that you are, where is the value. Is the value on activities that have to do with maintenance, for example? Is the value on material waste? Is the value on quality? Where does the value lie?
Once we understand this, very detailed, very granularly, then we are creating the roadmap, and the roadmap is going to connect the losses that we identify, with the technological maturity that you are, with the interventions that they make sense for you at this stage of the journey that you are. So you have a very clear understanding of exactly what technology you want and what are the losses you are going to be solving, how much they are, in which line they are, so you can drive clear accountability.
Niall Sullivan, Senseye: That seems to make it very clear all round, all transparent I guess, for everyone involved.
Actually, the other interesting thing about this framework, so I wanted to dive into, and I think, again, in the report I saw it mentioned this, but it's more around what level of maturity does a manufacturer need to be in order to take full advantage of this framework? And I know you break this down into low, medium and highly mature manufacturers. So maybe you could describe those different stages and the approach for those manufacturers that are at those different stages.
Vasilis Karamalegos, Smarterchains: So that's a very good question. The approach is the same. The output of the approach is different.
That's why we have built the process to be exactly the same in order to be standardized for any manufacturer, regardless of the states of maturity. Let's not forget that someone that is a beginner now, will be advanced in the future.
We have created specific archetypes that reflect the level of maturity that you have. And in these archetypes are specific characteristics that you have. Of course, on the archetypes there are also eventually specific interventions.
For example, it's very different the story for someone that they have no strategy at all around Industry 4, to someone that he has a strategy that he's not happy with because they don't have a very clear granular and top-down, bottom-up synced business case.
To a far more advanced manufacturer that they have a strategy, they have business cases and they want to be re-calibrating their roadmap. All those are very different scenarios, but our framework and product is capturing all of those different scenarios.
The output that they will do is going to be different based on the different inputs that they have on the specific maturity journey they are.