Building Operations That Run Without You — with Dr. Huri Mendoza

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Whenever you learn, for example, something that is so like lean manufacturing or Six Sigma, it's not rocket science, but you still need to make it happen.
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And then how do you make it happen?
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Very few companies are successful using the tools.
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But the tools are there.
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The tools were since 1950.
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And it's still not everybody's successful.
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But why?
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Because they don't think how.
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Welcome back, everybody, to another episode of the Allied Advisors Podcast, the podcast for mid-market manufacturers looking to scale operations and improve that ever-important bottom line.
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Joining us today is Dr.
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Yuri Mendoza, a global operations executive who has spent more than two decades turning around and scaling manufacturing organizations across the automotive and nutrition sectors.
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Holding a doctorate in business management from Swiss International University in Zurich, Curie has led operations and complex product launches on the ground in Germany, the United States, Mexico, Brazil, Romania, China, India, and Lithuania.
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Most recently as director of operations with the private equity firm Aquita, and before that in senior global roles at Balkham and Forvia, where he oversaw production capacity across hundreds of lines and$100 million plus in annual capital investment.
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A Six Sigma black belt and lifelong champion of continuous improvement, he's known for building cultures of operational excellence to deliver real results, think worldwide programs that save more than$500 million and drove double-digit annual productivity gains while mentoring the teams that make it stick.
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He's an award-winning leader, a board advisor to an AI software startup, and speaks five languages.
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And today he's here to share how disciplined execution, lean thinking, and people first approach turn struggling operations into high performers.
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Dr.
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Mendoza, really appreciate you coming on the show.
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Thank you so much.
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Thanks, Justin.
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Thanks for having me.
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Thanks for the wonderful introduction.
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So I never heard about myself like that.
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But it's it's um yeah, it brings a lot of energy.
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Yeah, positive energy.
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So thank you very much for quite the career.
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And uh yeah, I can't wait to dig into this thing with you because I think you have a lot that you can share with our listeners, and I hope uh at the end of this episode that they all all will agree.
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But let's jump right into it.
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You know, at Equita, you were am I saying that right, by the way?
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Is it Equita?
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Equita, yeah, it's uh from uh Latin.
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Yeah, it's so in Equita, you were brought in to turn around a tier one automotive supplier.
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You reduced the manufacturing footprint by 50% and eliminated 20% of non-value added activities.
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When you walk into an underperforming operation, where do you actually start?
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Where are the first things you look, or what are the first things you look at?
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And how do you tell a quick win from a change that's going to take you know six months or a year or more?
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Yeah, it's a very good question.
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Um so when when you join a company that um that is struggling, so there is a lot of uh opportunities, not everybody uh sees these opportunities.
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So um what I typically do is I observe a lot.
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Uh I learned this in in my past.
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Uh I learned directly from from Japanese people to go to the shop floor and just observe, spend hours in the shop, talk to the people, talk to the operators, so the the people that is handling the the material and observe what they do, how they are struggling, or if they are not struggling, if they are really performing value-added activities, non-value-added activities.
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And one thing that uh when I joined the the company, it was very clear for for the for the team, they said this area has a problem, but we don't know what to do.
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We have ideas.
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And also I came with ideas right away.
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And uh my ideas were the same ones that they had, so that was nothing new.
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But the ideas required a lot of investment.
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And um try to spend a little bit more of time, and and I come to the conclusion so there are there there is a lot of inventory, so they are building for inventory, uh a lot of overproduction, and then once you have um so the product was quite large, so then you use a lot of space.
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So and and and then you spend time just looking for parts, because they are they are somewhere in a in a in a valley of of racks with parts.
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And and then I I I come to the conclusion, so this is the first thing that I'm going to try to do.
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And I move I move the the the parts closer.
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So I did a mini value stream map, and I said, I'm going to reduce this, I'm going to eliminate this process.
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So I'm going to have a little bit of one-piece flow.
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Um I am a strong, uh strong believer in one piece flow, but also I believe that not every process functions with one-piece flow.
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So you need to find the right one.
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But for most of them, it it really works.
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Or uh or you can make an an adaption of it.
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So just by by cutting the amount of racks that they were allowed to have and the amount of space and moving uh the final operation closer to uh it was a paint booth, it was a paint line, just moving it closer.
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Didn't have people didn't have a space where to put dra more racks.
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So there they were like like a little bit forced to have the one-piece flow.
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And just by doing that, you reduced a tremendous amount of space because you are not building for inventory.
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So this one was a little bit I I got into the company and I was told this is the problem.
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And I I went with it.
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But once you go with it, so I I dig out my own information.
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I found my own information, I went uh did my own research.
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Uh by doing uh by standing in the line, I observed also the other side of the line, which it was not really uh considered a problematic area.
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Um so the loading and offloading.
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So the loading was like this is how we always have done it, so don't touch it.
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I love these words because it's uh when when processes have been like that in years, that means that continuous improvement has not knocked the door.
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And um, yeah, opportunities are there and um did some calculations with the with the team there, so cycle times they were very different, so different products that they ran through the same line, so cycle times, volumes, they were a little bit different.
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Um but then I introduced the the the topic Chaku Chaku.
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So I divided the the um the process, so I make everybody expert in every process.
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So they had dedicated people.
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I said, no, we are going to use the so we're going to go around.
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Yeah, so how how it uh it goes.
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So everybody's doing it uh in different lines, in different paces, and um it's not only so heavily uh physical, also it was mentally challenging.
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So it was very different.
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At the beginning, a lot of resistance from everybody, um as usual, but uh as after some time they got used to it, and then they realized they didn't need so many people, and then that would that's it, then reductions are happening.
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Um it was so for me it's about uh observe uh processes in the shop floor, learning to see, like the book.
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Um, so it's not only sitting there and then staring at things, or it's uh you have to train, so how what are you looking for?
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And uh that was a success.
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Yeah, I think you're you hit on something really important there is that silent observation piece.
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You know, I think too often leaders or or or office folks they think they know the problems, right, from their perch hit the desk, but they don't take the time to go out to the shop floor and go to the Gimba and do that silent observation.
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I remember um during the course of my lean training, we had a we had a TPS for executives course.
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It was a week-long course, and you were expected to make like 450 improvements in this one little cell, right?
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This one 10 by 10 workstation.
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You had to make 400 you know improvements.
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And the first thing they asked you to do was go out there for four hours and just watch.
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Don't say anything.
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You can ask clarifying questions, right?
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Hey, um, what is this?
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But don't make suggestions, just watch what they do, and then the next you know, three and a half days you've spent doing um you know small improvements, rapid, rapid uh implementation, rapid testing, right?
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So you might move uh bin from here down to here, uh just affix it with tape, right?
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And just try to make some some improvements really quickly, and then what work, you would permanently affix it or whatever.
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But but yeah, I think that's a such an important piece of continuous improvement for for you know folks like us is shut up, get up from the desk and go watch and go learn, right?
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Humble yourself to be able to learn.
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Absolutely.
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So the information is there.
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So there is there is drawings, there is specifications, there is specifications of the machines.
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So uh drag the pencil.
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Uh it it's you need to be out there, you need to look at the at the information that you have, which date uh which data is available, which data do you think that you need, because data costs money, so it costs time, and time is money.
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So and and then go with ideas.
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And sometimes ideas are a little bit crazy, but uh when you explain Chaku Chaku to people that never even hear about it, it's the craziest idea ever.
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And I you know, so and and it it takes time to to to explain this, to implement this, but once you do it, um it works and and it it's it's not that crazy once it's implemented.
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That's right, that's right.
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You know, I I've had conversations with other lean implementers uh around 5S, right?
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And initially, whenever you go out to the floor and you try to do 5s with a a team that's never had it, there's a lot of pushback.
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Like, hey, what are you doing?
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Why are you moving things around?
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But after you've implemented it and after they've lived in an organized world for a little while, then other people around start coming up and saying, Hey, when are you coming to my area?
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When are you going to get my area done?
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Because they see the benefit of it.
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And you know, I think that that applies to a lot of lean tools, right?
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Once people can see the value they deliver, then it's like, oh, okay, well, let's do more.
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Let's do more.
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But you, you know, you got that initial phase of resistance until you've proven that, hey, this this does add value.
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This works, yeah.
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Absolutely.
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Or these could work.
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Absolutely.
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Well, you know, Yuri, you told me about tools like a camera-based system that gives you a full time and motion study in a week instead of months, and machine data platforms that build your dashboards automatically.
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A lot of mid-market manufacturers assume that kind of AI and digital simulation is only for companies with four-vious sized budgets.
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Where would you tell a$50 to$200 million manufacturer to actually start?
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And what's realistic on a modest budget?
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Yeah, this is an interesting question because uh when I've been involved in in um artificial intelligence um startup companies uh for a long time now.
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So not quite 10 years, but almost, so probably eight years.
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Um and what artificial intelligence is giving you is is giving you uh more data, more ideas, more accurate information, speedy uh information.
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It gives you all that, but it doesn't give you execution.
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Now, back to your question.
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So big companies like Forbia or other uh big tier ones or OEMs, they have people in hundreds.
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So not three people doing this job worldwide.
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So they have people in hundreds doing this job.
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So when you provide this information, uh they can touch the ground and run.
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Now, many of these companies they already have this information, right?
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So it's very difficult to sell these products to companies very large because what is the value added?
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But mid-sized comp mid-sized companies, they are struggling to get data.
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So if they want data, they have to uh uh ask their people, uh, you know, so take a paper and then start collecting this information, uh, read from a screen, read from a plc.
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Uh and then you are we are ending asking the people that that it's supposed to build parts to also make reports and and think why the why this is not working, and and and then at the end of the day we say why we didn't produce so many parts.
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Well, because uh people was busy doing uh a hundred other things.
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Um so this is a uh a very good solution for this company, so for these mid-sized companies.
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Um where where are you going?
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What are you going to do with this with this information?
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Because it it costs money, you know, so it costs money uh to have AI.
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Uh the business model usually runs uh under subscription, so you have a constant uh payment to do, and the value creation doesn't happen right away because you you need to execute the ideas, you need to know what to do with the information.
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So once you are executing the ideas, then the value creation, of course, then turns around, you get to an even point, then you start making money, you start substituting um tasks or people, people is more efficient, you produce more parts, less downtime.
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So all the normal results of improvements.
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And this the the key here is is uh how much it costs so in the lower five uh figures, so as as a ballpark, you know, so is uh everything starts with a proof of concept.
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But uh you need to f see uh what are you going to save and you need to have it clear and who is going to execute and if you can breach that from the side of the of the artificial intelligence company and from the side that is a customer, then it it it's going to succeed.
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But if you are expecting that a machine is going to tell you, you know, this screw is loose, and you're expecting a robot to tie her up, it's not going to happen.
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And that's um that's what uh also um I learned through all these years.
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So not every customer is a good customer, uh, there is a certain level of maturity for these companies, uh, and you need to know what to do with the information.
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So I think that mid-sized companies they have a great opportunity, they need a project manager for it, you they need the the mindset of continuous improvement.
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And if you if you put all these elements that they are not so rare, so it's I'm I'm I'm not asking for an alignment of the planets, so it's a very simple uh understanding of what to do, then uh you can you can have uh you can match AI features with use cases for time savings and optimization.
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Yeah, you know, I I think you're exactly right in terms of there's some basic requirements that you gotta have in place before you can look to automate or or put any of this technology on top of it.
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You know, I tell people all the time, if if your process is just chaos, if you try to automate it, all you're gonna get is more expensive chaos or more chaos, right?
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You're gonna get more chaos more more rapidly.
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You know, if if you really want to be able to take advantage of all of the benefits that automation and this industry 4.0 and and now AI can offer, you have to start with a baseline process, right?
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There has to be some consistency in the way you're performing the work, right?
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Because that's where AI can really jump in there and help streamline.
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Once you have a defined workflow, then these tools can be put on top of that and make it so much better.
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It can, it can find your leaks, right, in terms of where you might be losing some money.
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Um, it can it can help streamline it so that you can do it more more quickly with less resources.
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It's great.
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But if you don't have a standard to start with, it's not it's not gonna work.
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So that's what I tell a lot of these mid-market manufacturers too is let's start with a standard, let's get a standard workflow, and then let's find tools that can automate that standard workflow and make it more efficient.
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Yeah, you're absolutely right.
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So uh there is you need to have certain certain uh level of of uh um maturity.
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Yeah, it's it's the same, uh I'm coming back to the same uh concept.
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Uh something that I repeat quite often is is data exists since Henry Ford or before.
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So it's not that that AI is bringing data and then we are all discovering America again.
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So it's it's it's the data was there.
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If you didn't do anything before, you're not going to do anything uh after.
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So you need to understand what that what are you going to do.
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You need to understand which feature you are trying to get faster uh and more accurate that is going to help you in your operation.
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And uh this is um yeah, this is where where where the tools they can help you uh quite a lot, yeah, in my opinion.
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Yep, absolutely.
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All right.
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Well, you know, in the pre-meeting, you and I talked, and and you mentioned that you built a lean academy where you trained over 10,000 people and ran something like 2,000 improvement projects a year.
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And you've said the hard part is change management, making the results stick.
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So many CI programs fizzle out once the consultant or the champion moves on.
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How do you build a lean culture that actually sustains itself?
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That that's also an uh excellent question.
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So and and every question that you are placing, we can talk for the next three hours.
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Uh um yeah, uh training, um you need to find uh the the sweet point.
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So in the companies they don't have time for training uh or or budget for training, so you cannot turn you you cannot turn an organization that is a manufacturing organization into a school.
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But you need to have a certain amount of training.
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You you want to have the people being efficient and create productivity, and for that they need to have a certain amount of training.
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So we we work quite heavily creating this material, so identified who is responsible for what.
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That's a I I mean that's that's key, and and I'm going to touch on something that that many organizations struggle.
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So a lean comes, lean manufacturing tools come, and then it it comes, oh, uh how we're planning the production, and then there is a pool system.
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Yeah, somebody says pool system.
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And then you have the lean experts trying to implement pool systems, and then the logistics guys, or the production planners, they are not even involved, they are not even butt-in.
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So what happens is now you have two running systems.
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So the traditional one in the ERP, whatever it is, with the with the flaws and with however, or whether it runs or not, plus another one that is with with cards and and uh with a board and and so on.
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So now you have two systems.
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So the very first thing, and then it was very hurtful was uh when I when I I took over this department, is to say I don't own pool systems, they are owned by logistics.
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And if logistics asks me to train them, I can train them, but I will not implement it.
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You know, so that's to give you an example.
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I never heard anybody else doing it.
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So everybody goes there and then says pool systems, and we are going to have cards and a combined board, and so and um so first we we defined who is responsible for whom, for what we had an LM LMS, so a learning management system.
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So then we established this, we established also standards for the training.
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So we didn't want to have trainings everywhere in the world.
00:21:34.559 --> 00:21:39.839
So when you have uh dozens or or hundreds of plants, every plant has their own training.
00:21:39.920 --> 00:21:44.079
So you have people building the same slides over and over and over.
00:21:44.240 --> 00:21:51.200
So we say, nope, we have the the standard uh training because that's optimization of the resources.
00:21:51.680 --> 00:21:59.759
Um then uh we combine uh people without experience or uh novice here.
00:22:00.880 --> 00:22:05.440
With people that was already trained with experts, and we combine them.
00:22:05.680 --> 00:22:12.400
So we create situations where people was always learning from experts.
00:22:12.559 --> 00:22:17.920
So we identified our experts, and then we said, please train others.
00:22:18.000 --> 00:22:19.359
So train the new ones.
00:22:19.599 --> 00:22:21.920
You complain, people come and they don't know anything.
00:22:22.000 --> 00:22:23.200
Well, train them.
00:22:23.519 --> 00:22:24.480
Teach them.
00:22:24.640 --> 00:22:25.039
Yeah.
00:22:25.200 --> 00:22:28.720
Spend time and tell them what you are expecting to do.
00:22:29.920 --> 00:22:35.200
We identified for every job description, role, and so on.
00:22:35.279 --> 00:22:37.359
So what is the learning that we were expecting?
00:22:37.440 --> 00:22:40.960
So the minimum requirements, loads of minimum knowledge.
00:22:41.279 --> 00:22:45.359
And what is the is, so what every person had, and what is the should.
00:22:45.519 --> 00:22:49.279
And then it's it there is usually a gap.
00:22:49.519 --> 00:22:55.519
And then this gap, you you take it and then you see it from the other side and say, okay, what training plans are we going to have?
00:22:55.680 --> 00:22:57.279
What training budget we are going to have?
00:22:57.440 --> 00:22:59.119
How we're going to close this gap.
00:22:59.279 --> 00:23:02.960
And we're not going to close the gap in three weeks.
00:23:03.039 --> 00:23:06.960
So we're going to make a plan for months and years and quarters.
00:23:07.920 --> 00:23:15.119
So that was the training because we wanted also to create a learning ladder.
00:23:15.359 --> 00:23:24.400
So how you can perform in a higher uh in a higher level every every quarter.
00:23:25.359 --> 00:23:27.839
So how can you be better?
00:23:28.319 --> 00:23:39.680
So one thing is is to have 10-15 years of experience of the same year, or 15 years of experience of different years.
00:23:39.839 --> 00:23:41.279
And we try to do that.
00:23:41.839 --> 00:23:55.119
So to have experience and that you are not the same person because you got training, because you experienced, because you try, you practice, you went to the shop floor, you you you learned the methods.
00:24:04.079 --> 00:24:15.920
So and it what we what we have we have um a quarterly project where we picked our proactive projects.
00:24:16.000 --> 00:24:18.880
So we divided what is reactive and what is proactive.
00:24:19.200 --> 00:24:26.400
Reactive projects, they were always out of the production meetings, the daily production meetings, everyone has a daily production meeting.
00:24:26.640 --> 00:24:32.880
And then we create a ticketing system, and that's how we divide these topics.
00:24:33.200 --> 00:24:37.839
The idea was not to fix every problem, the idea was to control the firefighting.
00:24:38.079 --> 00:24:47.039
So once you control the firefighting, then you have a time in your own people, because it's the same people, to work in proactive projects.
00:24:47.279 --> 00:24:52.319
So then we divide big projects, Six Sigma projects.
00:24:52.480 --> 00:24:58.559
So projects that they they last months, so launching projects, launching new products or new lines.
00:24:58.720 --> 00:25:04.480
So it these are massive projects and always required uh the same people.
00:25:05.119 --> 00:25:25.519
Um we divide into workshops, and then we have uh so let's say hundred uh projects was a good number, five, six hundred workshops per year, lean workshops, or or small uh um, if it was not lean, but it was always continuous improvement uh workshops.
00:25:26.000 --> 00:25:34.000
And there was small measures, like okay, we're going to you refer to something, we're going to change the bin from here to here.
00:25:34.160 --> 00:25:39.039
So did that come out of the workshop, maybe, or maybe it was just an idea.
00:25:39.359 --> 00:25:41.279
But then we captured all these ideas.
00:25:41.359 --> 00:25:50.160
So we we said, you know, so we are going to explain to everybody that all these ideas are improving the bottom line.
00:25:50.559 --> 00:25:53.519
And then there were thousands of measures.
00:25:53.680 --> 00:25:58.640
So there was a savings program where we collected all these uh all these measures.
00:25:58.960 --> 00:26:01.039
And for all these, you need training.
00:26:01.119 --> 00:26:07.920
So if you want to uh uh do Six Sigma, then you need to have Six Sigma engineers and green belt and black belt and and yellow belt.
00:26:08.079 --> 00:26:12.240
And uh if you want to have lean manufacturing, you need to train the tools.
00:26:12.480 --> 00:26:25.200
If you want to work uh with um um pool systems, with flow systems, you need to train the people and the people that is actually doing performing the job because you want it to perform right.
00:26:25.279 --> 00:26:33.680
And they need training also how it works in the ERP, how it works in the system, that you do it and you do it right, how you handle deviations.
00:26:34.319 --> 00:26:42.160
And this culture, so once you build it into a culture, the culture stays so and runs without you.
00:26:43.039 --> 00:26:51.359
So I've been out of uh for Via for many years, and many things that that I did is still remain.
00:26:51.680 --> 00:27:01.440
Because it was not about me doing it, it was about a system taking care that it's maintained through the years and through the time.
00:27:01.920 --> 00:27:03.200
And sorry.
00:27:03.440 --> 00:27:05.039
No, no, no, I'm sorry, I didn't mean to catch you off.
00:27:05.119 --> 00:27:05.359
Go ahead.
00:27:05.599 --> 00:27:10.799
No, uh uh yeah, so that's that's how how uh culture was was built.
00:27:11.039 --> 00:27:16.960
It was uh taking care of the people, because at the end it's the the the biggest asset that that any organization has.
00:27:17.920 --> 00:27:23.039
And um and to understand what is the expectation of the people.
00:27:23.920 --> 00:27:32.160
Very concrete, so not just like run and and work, make it work, make it faster, improve it.
00:27:32.240 --> 00:27:33.839
It's that's so generic.
00:27:34.000 --> 00:27:36.480
So we thought, what does it mean?
00:27:36.880 --> 00:27:37.759
What does it mean?
00:27:37.920 --> 00:27:48.799
How can we translate these general statements into concrete area into concrete measures and to concrete um tasks and projects?
00:27:48.880 --> 00:27:50.400
And this is what we did.
00:27:50.640 --> 00:27:55.839
Yeah, yeah, I uh you you said so much there that that I think really deserves repeating.
00:27:56.000 --> 00:27:59.119
Number one is you gotta have defined roles and responsibilities.
00:27:59.279 --> 00:28:08.400
You know, that is always amazing to me is how many manufacturers don't really have well-defined organizational structures, right?
00:28:08.559 --> 00:28:18.640
When you look at their org tree, it's just it's just crazy with different people reporting to different people that doesn't make a lot of sense, and nobody really understands where they stop and somebody else starts.
00:28:18.799 --> 00:28:25.519
So I think having that racist chart filled out, roles and responsibilities well defined, that is critical.
00:28:25.680 --> 00:28:41.440
And then having a system in place to help drive these continuous improvement initiatives, which is kind of what you described, and then making sure everybody's got the training and the skill set that they need to be successful implementing these things.
00:28:41.599 --> 00:28:54.640
You know, so many times, and you mentioned this earlier, so many times companies try to do continuous improvement with the second shift supervisor, and that just doesn't work because you know they've got other things to do, they're trying to get parts out the door.
00:28:54.720 --> 00:28:58.880
You you can't make them responsible for writing standards and shipping parts.
00:28:58.960 --> 00:29:02.880
I mean, that just you know, one of those things is going to suffer.
00:29:03.039 --> 00:29:05.359
Um, and we don't want either one of them to suffer.
00:29:05.519 --> 00:29:07.839
So, yeah, I uh I love that answer.
00:29:07.920 --> 00:29:16.000
I I think um it's clear that you've got a lot of experience doing this and have uh run off against the same problems that a lot of us have.
00:29:16.319 --> 00:29:39.920
Yeah, one thing and and I I just to to to to to summarize, and I this I learned uh so I had these quarterly um reviews uh to to to define projects, and the most difficult part is not to define what we want to do, it's to to decide what we are not going to do because there is always more problems and projects than people.
00:29:40.559 --> 00:29:42.000
Yeah, this was the most difficult one.
00:29:42.160 --> 00:29:56.960
And that and I had an epiphany whenever I joined the the private equity because there were so many so many topics, but they were talking about this uh hundred-day uh um plan.
00:29:57.440 --> 00:29:59.119
Yeah, the first hundred days.
00:29:59.440 --> 00:30:01.359
The first hundred days, and it's so common.
00:30:01.440 --> 00:30:03.200
And then I said, you know what?
00:30:03.680 --> 00:30:10.480
I'm going to call my quarterly review a rolling hundred days, because this is at the end what it is.
00:30:10.799 --> 00:30:25.279
So before the quarter, I do a portfolio planning, I define what I want to do in the quarter, then I run the quarter, so 90 days, 91 days, so and then at the end of this, I make the evaluation, what happened and and not, and they overlap.
00:30:25.440 --> 00:30:40.480
Yeah, so they they overlap, and then you have the 365 days, but then there is a rolling 100 days, and I coined this, and it's it works so well because because now people understand what you're trying to do.
00:30:40.720 --> 00:30:46.000
Yeah, it sounds very similar to our fractional CI manager program that we have here in Allied Advisor.
00:30:46.160 --> 00:30:46.640
Same thing.
00:30:46.720 --> 00:30:48.640
It's a quarterly cadence, right?
00:30:48.720 --> 00:30:56.720
We're defining projects at the beginning of the quarter, we're executing them throughout the quarter, and then we're summarizing how we did at the end and getting ready to start it again.
00:30:56.880 --> 00:31:11.279
So, you know, getting on that on that you know timeline of hey, we're doing projects every 90 days, just that has if you do that over the course of time, my goodness, the impact you will have, you know, over a five or 10 year stretch.
00:31:11.519 --> 00:31:14.480
Which that's that's where the the where the millions came.
00:31:14.640 --> 00:31:18.319
You you refer to all the all the uh the savings that I achieved.
00:31:18.400 --> 00:31:24.319
Uh and it's it's not that I did, so it's it's it's me and the group and and and the the whole organization achieved that.
00:31:24.480 --> 00:31:24.720
Yep.
00:31:24.880 --> 00:31:28.319
And it this is how how you get to it.
00:31:28.559 --> 00:31:32.000
So there is no silver bullet, yep, or magic wand.
00:31:32.160 --> 00:31:32.880
That that that's it.
00:31:32.960 --> 00:31:42.319
So you need to create these these uh uh cycles, and the first cycle will run horribly, and then you learn out of it and until you get it right.
00:31:42.880 --> 00:31:43.920
You're exactly right.
00:31:44.079 --> 00:31:46.400
Golly, I couldn't have said it, couldn't have said it better.
00:31:46.640 --> 00:31:58.880
But you know, early on in your career in Germany, you you you were telling me that you actually wrote the specs for an entire production line, but you sourced suppliers worldwide, and you were on the hook for validating that the equipment performed a spec.
00:31:59.119 --> 00:32:07.839
And later you use digital simulation like Flex Sim, so new lines launched on time for a mid-market manufacturer about to sign off on a big CapEx project.
00:32:08.000 --> 00:32:12.160
How do you de-risk it so the line actually performs the way the supplier promised?
00:32:12.480 --> 00:32:14.400
Another good question, uh Justin.
00:32:14.480 --> 00:32:26.559
So um, when we had these these um capex strategies, um we had um strategies for a high-cost country, mid-cost country, best cost country.
00:32:26.720 --> 00:32:28.559
So this is what the very first thing.
00:32:28.720 --> 00:32:29.440
What are we doing?
00:32:29.599 --> 00:32:43.200
So we cannot build a line uh the same for a country like Germany or the United States or a line for uh India or Mexico, different uh expectation.
00:32:43.359 --> 00:32:53.200
Now, the next level, because it starts so there is not a simple answer, and and again, this comes back to there is not silver bullet, there is not like this is the solution.
00:32:53.279 --> 00:33:01.039
So you it it's everything that starts to get a matrix and complicate and so on, and uh how complicated you want it, yeah.
00:33:01.200 --> 00:33:05.279
But um then we had regional solutions, yeah.
00:33:05.440 --> 00:33:11.519
So because they are not the same suppliers or vendors in Asia that they are in America or in Europe.
00:33:11.839 --> 00:33:15.359
So and and the the the brands and so on.
00:33:15.440 --> 00:33:16.880
So it's it's different.
00:33:17.119 --> 00:33:22.160
Even global brands they don't work uh like one-to-one.
00:33:22.640 --> 00:33:44.400
You know, so then to understand that, so what what we had we create frameworks for for writing the specifications to bridging between the product and and the um and the process and where the line was going to be established at the beginning.
00:33:45.039 --> 00:33:48.240
So that's one thing.
00:33:48.720 --> 00:33:55.039
Then the use of um digital solutions, so like flexing.
00:33:56.079 --> 00:34:11.920
What was the the so we thought okay, that was the next step in our maturity journey, and uh we wanted to to implement a digitalization, so we had all these strategies, but now we we wanted to know okay, what happened if we simulate a line?
00:34:12.079 --> 00:34:16.639
How is it going to affect the line itself and the other line surrounding?
00:34:17.280 --> 00:34:26.480
Because uh are you going to add another another technician, or are you going to expect the same technician to maintain the two lines?
00:34:26.719 --> 00:34:38.480
And whenever we simulate this, for example, we learned that sometimes we were asking operators, technicians, or material handlers to walk eight miles in a shift.
00:34:38.880 --> 00:34:41.760
And it's like it will never work.
00:34:42.800 --> 00:34:47.280
So we are not we cannot expect people to run a marathon in a shift.
00:34:47.599 --> 00:34:49.599
So it it's it just doesn't work.
00:34:49.760 --> 00:34:52.480
So and and it was so much learning out of it.
00:34:52.719 --> 00:35:02.000
But I think the most value added and it it was not the simulation itself, it was the front loading, it was the questions.
00:35:02.880 --> 00:35:09.280
It's like it it's the the simulation asks you how you are going to pack the parts at the at the end.
00:35:09.440 --> 00:35:11.360
So what what are you going to use?
00:35:11.599 --> 00:35:17.440
How many parts in a box are you going to put in, or in a tray, or in a bag, or whatever.
00:35:18.400 --> 00:35:21.519
And then everybody started around and says, Oh, we don't know.
00:35:23.199 --> 00:35:31.599
And and uh and these questions, this was the real value added of having these simulations.
00:35:32.159 --> 00:35:33.440
So not the simulation itself.
00:35:33.599 --> 00:35:34.719
There is a lot of learning.
00:35:35.920 --> 00:35:36.880
So don't get me wrong.
00:35:36.960 --> 00:35:42.079
So it it it's a it's a tool, and if you use it right, uh it will work.
00:35:42.239 --> 00:35:54.239
So but um we learned that through the simulation, through the data in ERP, in MES, we create an optimum solution, the perfect solution.
00:35:54.480 --> 00:35:58.400
We had questions for design for manufacturing, for design for cost.
00:35:58.639 --> 00:36:02.480
So we had all these questions before the steel was cut.
00:36:02.719 --> 00:36:09.039
And and where you can still make modifications to the product, to the process, to the interactions of things.
00:36:09.440 --> 00:36:13.119
Uh, that was really the the value added.
00:36:13.199 --> 00:36:14.800
And the result of this.
00:36:15.199 --> 00:36:19.039
It was not just a file that was stored somewhere in a server.
00:36:19.199 --> 00:36:24.320
So we transformed this solution because it was always looking for the perfect solution.
00:36:24.559 --> 00:36:27.760
We transformed this into the future state value street map.
00:36:28.480 --> 00:36:31.199
That was the goal because we already defined it.
00:36:31.280 --> 00:36:32.559
That's the perfection.
00:36:33.199 --> 00:36:35.039
And and that was it.
00:36:35.360 --> 00:36:59.840
And when the line was created, and then it was it was uh transferred to the to the place where it was going to be launched and start of production, then you realize all the things that you thought it was, you thought you you planned it perfect and it's not working, or not working as planned, or or uh all the difficulties that you have along the way, and then that becomes the current state.
00:37:00.159 --> 00:37:02.559
So the value stream map, the current state.
00:37:02.800 --> 00:37:06.559
And then you start defining uh the targeted state level.
00:37:06.719 --> 00:37:11.519
So in how many iterations you are going to reach this future state.
00:37:11.920 --> 00:37:23.519
But the having an idea how the future state looks like before anything is done, also fantastic value added from the lean perspective.
00:37:23.840 --> 00:37:26.800
So it's it's not what is left to get there.
00:37:26.960 --> 00:37:31.199
So it's it's to really create an utopic solution to say this is the perfection.
00:37:31.280 --> 00:37:32.559
How do we get there?
00:37:33.039 --> 00:37:43.920
What I hear you saying is it's not really about the simulation software, it's about defining and answering all of the questions that you need to run a simulation.
00:37:44.239 --> 00:38:01.039
So if you're a mid-market guy and you don't have Simeo or Flexum, or then what you should do instead is try to force your teams to think through, okay, what information do we need to define in order to launch this production line successfully?
00:38:01.199 --> 00:38:01.360
Right.
00:38:01.519 --> 00:38:08.480
So packaging, uh number of target, target cycle time based on your assumed tack time.
00:38:08.639 --> 00:38:09.199
Yeah, right.
00:38:09.360 --> 00:38:23.440
All of those things is how you really force your team to think through these, you know, each of these um processes so that you you end up with a with a well-defined uh process that can run.
00:38:23.679 --> 00:38:25.199
Is that essentially what you're doing?
00:38:25.440 --> 00:38:26.559
Exactly right, exactly right.
00:38:26.639 --> 00:38:32.960
And and uh it it's it's planned for every part, and then you don't do it after the fact, you do it in it's a front loading.
00:38:33.039 --> 00:38:34.800
Yeah, what do you want to have?
00:38:34.960 --> 00:38:50.159
Yeah, and and then there were there were topics like a label, and a label uh I don't know, so two by five point three seven, whatever, and and it's like okay, the the the supplier has a two by six.
00:38:50.400 --> 00:38:51.199
Does it work?
00:38:51.360 --> 00:38:53.760
Yeah, because that is off the shelf, yeah.
00:38:54.000 --> 00:38:57.519
And then they are like, oh, okay, yeah, you know, it works.
00:38:57.840 --> 00:39:04.079
And and there were so many simple solutions, but nobody thinks about it.
00:39:04.159 --> 00:39:14.239
Uh a designer planned the perfect uh label for it for each component, and it never thought what it means for the rest of the system.
00:39:14.480 --> 00:39:17.280
When you bring all the people together, that's the value.
00:39:17.599 --> 00:39:24.079
That's a mid-sized company asking these questions, then you don't need to place it in a simulation.
00:39:24.239 --> 00:39:25.519
So simulation will help you.
00:39:25.599 --> 00:39:33.280
I absolutely so it it's it's a process that works, but what it makes it work is the collection of the information.
00:39:33.599 --> 00:39:34.239
Yep.
00:39:34.880 --> 00:39:36.000
Yeah, absolutely.
00:39:36.159 --> 00:39:36.480
Okay.
00:39:36.880 --> 00:39:46.960
Well, you know, you told me a story earlier, Yuri, about an American uh general manager who instead of just handing you a quote asked, What do I have to do to get us in business?
00:39:47.119 --> 00:39:52.480
And how that question really shaped the way that you think about relationships and networking.
00:39:52.719 --> 00:40:01.519
For operations leaders who see themselves as execution people, not relationship people, why does that side matter and how has it changed the way you do business?
00:40:01.760 --> 00:40:07.519
This was a this was a very interesting story, and then it's it's interesting that you pointed out because we have talked about a lot of things.
00:40:07.599 --> 00:40:19.199
Yeah, but um, but this is um this is one of them that um as a young professional, you're trying to do the job like everybody else.
00:40:19.440 --> 00:40:28.159
And and there was this this is a gentleman with with some years already, so um you can tell the experience.
00:40:28.719 --> 00:40:32.239
And it was the how how we make this happen.
00:40:32.320 --> 00:40:38.559
So and it was in a positive way, so not uh uh negative connotation or anything.
00:40:38.800 --> 00:40:57.199
And what I learned out of out of the teams that I have been involved, out of uh discussing with other executives and so on, I think we we are focused or quite focused on on the execute, do, do, do, but we don't discuss the how.
00:40:57.920 --> 00:41:01.280
And then we discuss the how in the wrong environment.
00:41:01.519 --> 00:41:04.960
So then we want to discuss how with 20 other people.
00:41:05.599 --> 00:41:09.760
And uh quick example, so production meetings.
00:41:10.239 --> 00:41:23.679
So we don't this so you can discuss, okay, yesterday we ran 60%, and then it's the is you can discuss what and and uh why happened, a little bit of the issues or the top issues and so on.
00:41:23.840 --> 00:41:30.960
But in the moment that you start discussing how you are going to fix that, you are losing everybody else.
00:41:31.199 --> 00:41:39.199
So people start going into their computers, into their phones, and so because it's not touching them, it's not relevant for them.
00:41:39.519 --> 00:41:44.639
So how is it's a key question, I think.
00:41:44.880 --> 00:41:51.119
So you need to understand also the basic questions of the what, the why, when, who, with whom, and so on.
00:41:51.199 --> 00:41:58.800
But finally, how we make things happen, what we need to do, what are the steps, and then this starts the connections.
00:41:59.599 --> 00:42:02.079
So, how do we change a document?
00:42:02.239 --> 00:42:04.000
Okay, then we need to discuss it.
00:42:04.079 --> 00:42:10.800
So the manufacturing engineer needs to discuss with the quality engineer, and they need to get together, and that's it, and they need to discuss it.
00:42:10.880 --> 00:42:12.880
And once it's discussed, then that's it.
00:42:12.960 --> 00:42:16.079
They don't need uh 10 other people.
00:42:16.559 --> 00:42:28.320
So for me, this was uh this thinking how we can make things happen, and that was what shaped my life and my my world.
00:42:28.400 --> 00:42:38.880
And and uh whenever you learn, for example, something that is so like lean manufacturing or Six Sigma, I mean it's it's not rocket science, but you still need to make it happen.
00:42:39.039 --> 00:42:40.639
And then how do you make it happen?
00:42:40.800 --> 00:42:52.079
How how you uh very few companies are successful using the tools, but the tools are there, the tools were since 1950, and it's still not everybody's successful.
00:42:52.320 --> 00:42:52.800
But why?
00:42:52.960 --> 00:42:54.480
Because they don't think how.
00:42:54.719 --> 00:43:01.360
How I can make a plan, a step plan to say this is my first step, and this is the second and third.
00:43:01.679 --> 00:43:10.400
And this was so back then, I was very young when I learned this to ask this question: how would we make this happen in a positive way?
00:43:11.199 --> 00:43:19.920
And that was uh what I find um like a way of living and a way of relating with other people.
00:43:20.079 --> 00:43:38.320
So I I am an engineer and I have my own struggles to socialize, but I um uh nevertheless it's it's um I try to connect with people and say what is the it's not only what is in for me, because that's that's very shallow.
00:43:38.880 --> 00:43:46.079
It's how so who who is going to get the benefit, and then if it's a common benefit, how do we get it?
00:43:46.800 --> 00:43:48.400
And yeah.
00:43:49.199 --> 00:43:59.760
No, I I was just gonna say, I mean, I what I hear you saying there is really you're taking what happens so often in teams when they're faced with a challenging product.
00:44:00.239 --> 00:44:04.639
Or challenging project, rather, is they say all the reasons why it can't work.
00:44:04.800 --> 00:44:05.599
Why it can't work.
00:44:05.760 --> 00:44:13.440
And what I hear you doing is you're kind of flipping that on its head and saying, okay, well, let's get creative and you tell me how it could work, right?
00:44:13.679 --> 00:44:15.280
Don't bring me problems.
00:44:15.360 --> 00:44:17.039
Let's let's brainstorm solution.
00:44:17.119 --> 00:44:20.960
And you're phrasing it in such a way that it's including people, right?
00:44:21.039 --> 00:44:28.000
You're bringing others into that, into that effort where you're not going to them and saying, hey, this is how it's going to work and this is how we're going to do it.
00:44:28.159 --> 00:44:40.159
You're asking an open-ended question and help and hopefully taking advantage of their knowledge, their experience, their expertise to help develop a all inclusive solution.
00:44:40.800 --> 00:44:41.360
Absolutely.
00:44:41.519 --> 00:44:45.440
So I I I am myself, I am a product of globalization.
00:44:46.159 --> 00:44:49.039
So I've been in multiple countries and and multiple projects.
00:44:49.920 --> 00:44:52.239
And there is smart people all over the world.
00:44:52.880 --> 00:44:54.000
And you need to include them.
00:44:54.320 --> 00:44:55.119
You need to include them.
00:44:55.199 --> 00:45:06.079
And also in your in every organization, from the CEO to the janitor, to the to the operator to everybody, the supervisor, the the warehouse uh clerk.
00:45:06.480 --> 00:45:12.880
Everybody has ideas because everybody has eyes and they think and they observe and then they solve for the problems.
00:45:13.679 --> 00:45:16.079
So how you include everybody.
00:45:17.119 --> 00:45:19.199
Not to put the rocks in front of you.
00:45:19.360 --> 00:45:32.159
How you include everybody to provide solutions, to provide ideas, to uh make them participate on on you are part of the solution, not part of the problem.
00:45:32.880 --> 00:45:37.519
So I I also say quite often, so there is two kinds of people.
00:45:37.599 --> 00:45:43.840
So people that that find solutions to problems and pro and people that find problems to solutions.
00:45:44.559 --> 00:45:47.119
So on which side do you want to be?
00:45:47.920 --> 00:45:51.840
My goodness, there have never been truer truer words spoken.
00:45:52.000 --> 00:45:53.679
Yeah, you're exactly right.
00:45:53.920 --> 00:46:01.199
Well, you know, Yuri, once again, I want to thank you so much for taking the time out of your day to come share your knowledge with our audience.
00:46:01.280 --> 00:46:11.920
Uh, I know there's tons of people out there that are going to hear this and they're gonna have some takeaways that they're able to come back with to their organization and hopefully make make themselves and the people around them better.
00:46:12.000 --> 00:46:14.480
So again, thank you so much for taking the time.
00:46:14.639 --> 00:46:17.679
Uh, for those of you listening, I will include uh Dr.
00:46:17.840 --> 00:46:20.239
Mendoza's contact information in the show notes.
00:46:20.320 --> 00:46:22.559
So his LinkedIn profile email address.
00:46:22.639 --> 00:46:24.800
Uh you reach out to him if you've got questions.
00:46:24.880 --> 00:46:28.960
I'm sure he'd love to take the time to talk with you and and help you work through them.
00:46:29.039 --> 00:46:32.159
So again, Yuri, thanks so much for for carving out the time.
00:46:32.400 --> 00:46:34.639
Yeah, thank you, Justin, for having me.
00:46:34.719 --> 00:46:36.480
So it's it's it's been a great pleasure.
00:46:36.559 --> 00:46:39.199
So we can talk for probably for the next three hours.
00:46:39.519 --> 00:46:45.920
And and um, yeah, so if somebody wants to reach out, uh I would I would love to to keep contact with the with new people.
00:46:46.000 --> 00:46:55.679
So this is how relations happen, how knowledge is created, and I would love, I I would love to to to learn from from people and to learn from from problems.
00:46:55.920 --> 00:46:59.920
Uh Justin, again, thank you very much uh for giving me this opportunity.
00:47:00.239 --> 00:47:00.800
Absolutely.
00:47:00.880 --> 00:47:06.800
And folks, if you enjoyed today's episode, please be sure to like and subscribe, leave a comment, leave a five star review.
00:47:06.960 --> 00:47:17.039
It really helps us get the message out so that others might, you know, others in the mid market manufacturing space might also learn a little bit and hopefully uh bring a little bit more value to their organizations.
00:47:17.199 --> 00:47:19.760
And uh until next time, see you later.