GA 590 | The Smart Factory with Nikhil Pal

When we talk about the smart, the smart factor is how we can ensure the real time data, the automated insights, some responsive workflows, how they are taken into account and you know, it's not just about digitizing the process, it's about rethinking them to be faster, more consistent and scalable across sites.

Today I am excited to welcome Nikhil Pal to the show. Now today we had a really fun topic. It's a topic that we haven't explored a whole lot I don't think over the years, but whole idea of the, of the so called smart factory. And, and so Nikhil has a lot of experience with operational excellence and lean, but also this, this, this smart factory idea. And so really today on the show we talk about sort of how all of these different, I don't know, I'll call it movements if you will, how they can and arguably should cooperate with one another. So we get into the whole idea of like first of all, like what do we mean when we talk about a smart factory? Sensors everywhere, what is it? What does this mean? And, and get into the role that this sort of information that we can get from these, from these sensors and these different aspects of a smart factory, how they play into lean and while we get into some really interesting stuff like will people even be needed down the road and that sort of thing. And the short answer is, and Nikhil's opinion, yes, people are always going to be needed. So don't worry, the robots aren't going to quite take over just yet. So it was really fun episode. I enjoyed it a lot. Show notes can be found over at Gemba Podcast. Just look for episode 590 again gembapodcast.com and look for episode 5 90. Okay, enough from me. Let's get to the show. Akil, welcome to the show. How are you?

I'm fine. How about you, Ron?

Doing great, doing great. Where are you calling in from?

I'm, I'm calling in from Toronto, Canada.

Okay. Beautiful, beautiful, beautiful part of country of, of, of Canada. I, I was actually, I don't know how many people know this. I was actually born in Winnipeg, Manitoba. So my father was a professor at the University of Manitoba for many years and, but then I grew up in the States mostly but, but yeah, we would spend the summers with my dad up in Canada. So I been to Toronto and we, in fact we would go to where they call it Lake of the woods there in Ontario. I don't know exactly what lakes it was but it was so beautiful to go, go camping and fishing. There in Ontario. So it's a beautiful part of the, of the world.

Yeah, it is actually. So I'm still exploring, I think. So this is the world's second largest country in terms of the land mass.

Yeah.

Plenty of places to explore, actually.

Yeah, for sure, for sure. Awesome, awesome. All right, well, hey, I know you know how the show goes. We like to begin with our guests sharing a quote. So do you have one?

Yeah, I have one. And this is an old time quote I learned during my in bachelor's as well as in mba. It's from Deming. So without data, you are just another person with an opinion. So this, this actually quote guided much of my work in Lean Six Sigma and operation excellence and in every Lean transformation I have led. So whether it is related to electronics manufacturing or maybe pharma, currently in which I'm working now. So leaders, engineers, operators, everyone has their perspective, but what anchors everyone together is the data.

Yeah, yeah. Another variation of that quote that I love is. Was something, was it? Yeah. In God we trust all others bring data. Yeah, yeah. Good stuff, good stuff. All right, well, hey, tell us a little bit about your background. Tell us how you got involved in all this continuous improvement stuff and what you're up to these days.

Actually. So I started my career with the company called jbil. So it was a contract manufacturing.

Yeah, I know him well.

Yeah, yeah. So it was back in India that time I was working for the industrial engineering department and that is where it was my first exposure with continuous improvement. Because as the industrial engineer, we were, you know, tasked to do the layout studies, headcount planning, machine planning. And that's where we're continuously, you know, driving the improvement there to make the factory more efficient. So that is a place where I got, you know, first exposure to the continuous improvement. Following that, I actually few, few years later, I, you know, started my career directly into the teaching Lean Six Sigma. So more like becoming the plant lean manager, that kind of role. And from there, during the pandemic, I moved into the healthcare field and right now, currently I'm working with the Roche. So Roche is like the world's kind of second largest pharmaceutical company. So in which I am part of the group which actually handles the external manufacturing. So that's where I'm driving the continuous improvement practices.

Got it, Got it. Okay. Well, I'm really excited for the topic today because I don't think it's something that we've explored a whole lot over the years on the, on the show, but really sort of talking about the idea of operational excellence in context of what some people would call the smart factor. So maybe we just start with some definitions when we talk about like the, the phrase smart factory. Like what are you, what are you talking about? What do we, what do we mean when we say smart factory?

So I always think about smart factory as a, as an entity audits of at a factory where we are actually making a very good use of data. We are using, we are driving the improvement. We are making the, we are doing the problem solving with keeping the data in the mind. And when we talk about the smart, the smart factor is how we can ensure the real time data, the automated insights, some responsive workflows, how they are taken into account. And it's not just about digitizing the process, it's about rethinking them to be faster, more consistent and scalable across sites. So I'm seeing this kind of trend also in the industries. Most of the companies are moving toward that smart factory. And one of the thought I had and I actually navigated my career also towards that is why don't our traditional lean people or the continuous improvement coach can take up this initiative. So this is the kind of one career turn which I have actually challenged myself to, you know, to take to, you know, become a continuous improvement coach and drive the factory towards the smart factory. Instead of, you know, we have typical consultant we hire from outside and then they give us a lot of things to do.

Okay, so talk a little then about the role or how you see it as it pertains to operational excellence in the context of a smart factory. So what does it look like when we're trying to continuously improve in the so called smart factory?

So one of the example is our daily tier meeting. Let's take an example. So daily tier meeting, what we did traditionally we have whiteboards where we put all the KPIs and maybe most of the time we used to write down green markup and red marker pen using that over the time because of the complexity of the business. Now we have evolved instead of just using the plain whiteboard, we have some digital dashboard along with that whiteboard. So there we are actually using the real time data, we are able to see much more into detail what happened. And that's where we are using these digital dashboards to drive this peer meeting. So that actually brought visibility, not just one shift or a site, but also we can see kind of an in network. So it was in this case the operation excellence or the continuous improvement was not left behind, but we used that to build this foundation actually where we have the now digital data to make the decision making.

Okay, so let's say we're in a Jabil factory and they're building, I don't know, cell phones. I just pick a random topic here. And I used to work at Nokia, so I know very well that JBL so built a lot of cell phones back in the day, at least for us. So you know they're buzzing off hundreds of cell phones per hour on this Jambol assembly line. So um, so is it just really as straightforward as you can look up on the, on the board and you see how many phones we made, how many were good, how many were bad? Is that what we were talking about? Or is there, is there maybe deeper analytics than just how many we're making?

So actually it's kind of both. So maybe at the supervisor level we don't need that much detailed information, we just need as a supervisor, as a production supervisor, I just want to know what is happening in my shift. How many are the good pieces, how many are the rejects, how many is the balance to go for? That kind of information for the supervisor and operator level is enough. But we have engineering team, we may want to look into detail what happened, what are the recurring issues that is happening. Do we have some real time pareto that we at the end of the shift we can review together with the next shift handover that we tell them in the previous shift these were some of the issues that we encountered. It's kind of mix of both depends on what are the need of the business. But, but this is what I see nowadays the business are headed towards. So we want to have much more detailed analytics available on the hand to make some better decisions.

I remember early in my career I worked at Motorola and then Nokia building cell phones. And back then, you know, many times we were just like literally counting, you know, how many parts were coming off the end of the line and you had a big whiteboard and you would just write, you know, how many were made, how many were defective? And you know, eventually, quickly it, you know, we did get some more automation. But I'm wondering like what benefit do you see these smart factories having over the, you know, the old traditional way of literally counting what you're making and writing it on a whiteboard.

I see the difference is particularly first in terms of the workforce which is entering. So if you compare the workforce which we had 10, 15 years back in that, you know, and, and compare it with today's one where we have lot of Gen Z people also working in the shop floor. So there is also a big difference. So they are already, you know, kind of tech savvy.

Yeah.

And they kind of feel outdated when, when they see the factory is just using, you know, some simple things.

Yeah. Whiteboard.

Yeah. Even though most of the cases I would say they are still effective actually.

Yeah.

Only thing is that, you know, when the data only can tell you is more like, you know, kind of a history based. She can tell you in the past how many times we have the issues happen. And also it can maybe sometimes can give you the better prediction.

Yeah.

So, so that's, that's one of the thing. We are using Six Sigma also there to have a real time control charts to, you know, predict if something going is wrong, something wrong going to happen.

Now to play sort of like a devil's advocate though, on the other hand, like I have, I have seen, you know, over the years some instances where there's a so called smart factory and everything sort of being, you know, automatically counted and calculated for you. And sometimes it gets ignored. Right. And, but, but I remember back in my early career when we're like gathering around and you're writing it on a whiteboard, no one's ignoring it. Right. Like we, I would say we were almost more invested back then, I sense, than, than we are sometimes today when we're relying on technology to do everything for us. What do you think about that? Do you think there's any truth to the idea that human beings might sort of like disconnect a little bit when everything is being sort of calculated and tabulated for you? What do you think?

So this is typically I have seen will happen when there is a lack of accountability or we can say we don't have the true culture or the true spirit of continuous improvement. In that case, these dashboards are just like our wall paintings, only so more like a show, more to impress the customers. You know, see, we have all this technology, but we are not making use of them. So I think that that's where the case is. We need to have a culture of problem solving. These dashboards are highlighting the basic fundamental thing which is like what is what went wrong?

Yeah.

And we have to put up a process in place to tackle if anytime something went wrong, what we are supposed to do. So what is the reaction plan? What is that problem solving thing? So that is something that is when it's missing, that's where they just become like wallpaper only.

Yeah. So, okay, well what do you see as some of the best practices then out there for Companies that are doing it well, using this digital, the power of the digital sort of platform and coupling it with strong continuous improvement behaviors. Like what are some of the things and some of the benefits that you're seeing?

I think so currently I will just share an example from the pharmaceutical world. So because since I have world in electronics and pharmaceutical, they are both in a way are very different. But when we talk about continuous improvement they are kind of the same. So one of the. My favorite topic is the smed single minute exchange of how we reduce the change over time. And especially when in the pharma where we have to do a lot of tank cleaning and everything, sterilization before we can start the next batch. So we can lose maybe many days in that process. So nowadays I'm seeing the sites, one of the example is that we have customized app where we have actually configured the checklist for this entire smart process. And also with the time against that. So how much time we should be taking anytime we are doing taking more than that. So you know, it kinds of alert the operator also that we are exceeding it. We have to go back and you know, maybe put some resources to get back on the schedule. So these are some customized apps which actually are right now a lot of manufacturing companies are using apart from traditional dashboards. So these are some of the manufacturing apps which are being used currently in the manufacturing industries to improve the productivity which could be related to change over time reduction maybe, maybe related to improving the output per hour. So these are the things traditional dashboards, I think they were still there. I know previously, you know, many companies, we still have a big product, big boards in the assembly line. How many cars has been done so far? How many are okay, how many are reject? So these basics were still there. But now because of this AI and these small applications which we can develop for customized use case this is actually impacting manufacturing in a very good way.

How do you roll this out more from like a human behavioral perspective with the operator working on a machine knows that nothing is hidden and there could be a lot of pressure because hey, the minute we slip up the AI robots yelling at us and our bosses down here and all the rest of it. So you, you in a way you, you can't hide, right? Not that you could 20 years ago, you probably still couldn't, but you especially can't now, right? Because this system is constantly monitoring every second of you know, of the day. So how do you, how do you sort of handle that from a change management perspective with the operator who may be stressed out by that.

So I think the key is to build from ground up. When we develop this kind of tools or application, it's very important to involve the operators and their feedback. At that point we understand what is the pain point that we want to solve for them. That's the thing. Instead of something I have fancy idea in mind and I want to implement in the shop floor, it will not work that way. I need to go to the shop floor, understand the problem, how, you know, discuss with the operator. Are you seeing this kind of problems? Are you seeing this kind of issues and how much is. Does it impact and take that as a problem and then build some application, then I think they will be more productively instead of, instead of hiding, they will be maybe providing the more ideas how, what we can do differently.

Yeah, they're part of the, they're part of the solution versus part of the problem. Right. Maybe that's a good way of looking at it. No, you're not the problem, you're part of the solution. And we work together. So really that's a lovely way of looking at it. So I'm wondering then, let's talk a little bit about this whole idea of these digital tools and then Lean and Lean fundamentals. How do you get these two things to sort of harmonize with one another? And you know, and again, we're not trying to replace anything. We're not trying to replace Lean. In fact, Lean is a very important part of this whole idea. So talk a little bit about that.

So I don't think Lean is going to be replaced also because all this current digital transformation, what is there in the market, it is just part of the continuous improvement. How we used to build 100 years back and how we are building today, the things have evolved. So that actually shows the continuous improvement and it's going to be evolving. So Lean is going to stay. So now the thing for the companies become much more important is to build that continuous improvement culture. Without that, then they cannot adopt the new technology also. Otherwise it will be just, you know, some outside project which, you know, people will not be that much engaged with. So that's where it's very important to have the lean culture in the company and making sure everyone is part of the change journey. And we have to evolve continuously because the things are going to change. Geopolitical situation is going to change the way we are producing that goods going to change, the consumer are going to change. So that is the thing actually.

Yeah, yeah. Everything's always changing. Right. That's one constant of our world change.

So without lean how to adapt to the change.

Yeah, exactly. All right, well talk a little bit about maybe some of the common pitfalls that you've seen when companies try to go to this whole idea of digital, but in respect to operational excellence and continuous improvement, like have you seen any sort of pitfalls or mistakes that have been made that you've learned from?

So I have seen, you know, one of some of the common examples are, you know, the top leadership decided, okay, we want to make our operation digital. Okay, so let's hire a company or consultants who will tell us what we need. Okay. Based on that we will start developing something and then we will implement the problem happens there is, you know, we don't get the, the same buying from across the different level of the organization. And that is the thing when we want to implement the digital change. But the bottom line, people are not that much involved so they are not able to participate in that. Then again, this change is, doesn't, doesn't give the benefits what the companies had, you know, anticipated in the beginning. So this is what I have, I have been seeing again and again many times the companies are making the same mistakes. They, you know, just rely on outside people to advise them how to do that. They will buy some expensive technology without even considering do we really need it or not. But it, just because we want to look fancy, it will give us, you know, good reputation in the market. That's where you know, it feels actually.

So a question my good friend Mark Graben often asks people is if you have, you yourself have a so called favorite mistake that you have made over the years. Like has there been something that you did and it was like, oh, and after you realized that was bad, but then it, maybe it turned out good because you were able to sort of turn it around and, and learn from it. Can you think of anything like that for you?

Like personally, I think one common thing I have seen or it happens, happened to me actually earlier part of my career also is like not grasping the current situation or not, you know, mapping the process correctly.

Yeah.

So when we don't map the current state properly and we introduce a change, it could be digital, it could be anything, then it's not going to work and immediately it will be, you know, fall apart. So that's where again we have to go back and to the board and then remap again and then think differently. This is what I have seen and, and I am seeing from some of the examples which is happening in, you know, in the companies they don't focus on grasping the current state properly, rush into implementing the change and you know, then the blunders happen.

Yeah. Our friend Mike Rother is shaking his head. Yes, yes. Grasp the current condition. Right. Yeah, it's very important, very important. It's so easy to know, you know, you see that things aren't clearly operating as well as they could and so it you, I think you go into it with good intention sometimes of well let's, let's fix it, let's make that better. But to your point, if you don't deeply understand how this thing is operating, you may not actually know if you really made it better or if it was just chance or luck. Right. That you made it better. So yeah, it's a, it's also frustrating though because you want to get on with it. Right? You want to make things better. That's what we do. But yeah, we have to take a, take a step back and grasp the current condition before we worry about moving forward.

And oftentimes because of the deadlines, pressure because every this digital project comes with a deadline. So we have six months, eight months to implement and that's where teams are just rushing into, okay, let's map whatever we have and then go back and then implement the digital solution. And nowadays the again the problem is that there is so much customization, it's very difficult to standardize everything, you know, so that's another challenge. Yeah, we want everything to be standardized in, in our operations but due to the complexity of the product and the process, things are customized accordingly.

Yeah, yeah, exactly. Okay, well hey, maybe to wrap things up, I'm wondering if you have any advice that you would like to give to the continuous improvement leaders out there listening and perhaps they want to begin exploring or integrating the so called smart technologies into their, into their operational excellence roadmaps. Like do you have any sort of advice for them?

Yeah, so I think the very first thing is to start with the problems not with the products focus on value stream mapping, identify where are the bottleneck and ask could this be solved faster with the right tool and what kind of right tool and also engage the stakeholders early, especially it when we talk about the digital technologies. So but keep the ownerships within the operations. Many digital transformation fail because they are treated as technical upgrades rather than process redesigns.

Oh, say that again, say that again now. It's really good.

Yeah, so I mean to say like many digital transformation fail because they are treated as like technical upgrades. So we just say maybe, oh I'm just upgrading some of the sensors in the equipment, but rather than the overall process design. Because now I have better sensors, I can get more data out of it and then I can maybe, you know, redo my process again and I can do some more improvement there.

Yeah. Oh, I love that. So in a way it's better to say it's not about the data, it's about the problems, you know, and allowing the data than to help us expose the problems or expose the opportunities for improvement. Right, but you're right, I mean sometimes you get a new toy, right, and you want to just deploy it everywhere and you have these beautiful dashboards all over the place but no one's doing anything with it. Right. And it's just looks fancy but yeah, it's not really driving improvement.

And the last point is don't forget the culture. Smart factory needs a smart workforce which is curious and adaptive and in modern day context are data literate and continuous improvement leaders has to lead that mindset shift.

Nice. I love it. I love it. Good stuff. Well, hey, if folks wanted to connect with you, Nikhil, like what's the best way? Are you LinkedIn or where? What's the best way to connect?

Yeah, so I'm available on LinkedIn. They can search me as Nikhil Pal and they can find me on LinkedIn and I also have my smart YouTube channel which I just started few months back.

Nice.

It's called Process Masters. And this one I have to give to you, Ron. My logo is very much inspired with the game by.

Okay, very good. I have to go. I haven't seen it yet. So we. Well everybody, we'll link, we'll link both your YouTube and all your other links up on the show notes. So everybody scroll down and go, go, go. Like the YouTube page, everybody now I'm excited to go check it out. That's great, that's great. All right, well hey, thanks again for coming on. This has been a lot of fun.

Thank you, Ron. Thank you for the opportunity.

All right, take care.

Take care.

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