Small Problems, Big Levers: Lean, AI, and Growing Pains with Jamie Flinchbaugh

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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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My guest today is Mr.
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Jamie Flinchball.
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Jamie is the founder of Jay Flinch, where he works as an advisor, coach, and board member to leaders trying to build organizations that actually hold up.
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He started on the flat floor at Chrysler, went through MIT's Leaders for Manufacturing program, spent 15 years co-founding and building the Lean Learning Center into one of the top lean transformation firms in the country, and more recently has served as corporate vice president of Corvo's Lean Journey.
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Along the way, he's worked with more than 300 companies from Harley Davidson and Intel to Mars, Amazon, and Whirlpool, along with helping build close to 20 companies as a co-founder, board member, or investor.
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He wrote, Here, People Solve Problems, The Power of Every Person, Every Day, Every Problem, co-authored with Lean Bestseller, the Hitchhik and co-authored Lean Bestseller, The Hitchhiker's Guide to Learn to Lean, Wrights Reforms, and hosts the People Solve Problems Podcast.
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Jamie, thank you so much for carving out the time to come on the show.
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Can't tell you how much I appreciate it.
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Yeah, very happy to be here.
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Thanks for the introduction and uh yeah, glad to get into it with you.
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Yeah, as somebody who has tried to moonlight as a writer, I have I can't tell you how much respect I have that you managed to successfully sit down and write not one, but two books.
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I you know, it used to take me a week to bang out a thousand-word article.
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I you know, I I have so much respect for people that can actually sit down and take the time and and put in the effort to write write an entire book.
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I mean, that's that's so impressive to me.
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Well, it's I'll I'll say I always tell people I write selfishly because writing is how I clarify my thinking.
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And and so uh so I gain a lot even if I never produce a book.
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Um, but uh so I I've kind of learned it it's it's it makes me better, so I I do the I put in the work.
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Well, I uh I'm so envious.
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I mean, I I just sit in front of a laptop and watch that cursor blink and think, now what?
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And oh, it's so painful for me to try to get thoughts on paper.
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But so anyway, somebody like you, I am I'm so envious and and just in awe.
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So thank you.
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But you know, speaking of writing, you wrote recently that most big problems aren't really one problem at all.
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A budget shortfall is really a hundred spending variances wearing a trench coat.
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And yet the three levers everybody's pulling right now are AI, reords, and return to office mandates.
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For a mid-market manufacturer with a real problem and limited bandwidth, how do you tell the difference between a lever worth pulling and a lever that just moves the way somewhere else?
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Yeah, well, I I think um there's there's a lot of magnetic pull to those big levers, right?
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And it could be other big levers, right?
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Uh, but uh I'm gonna go buy a company, yeah, that's gonna solve all my problems.
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Uh replace the CEO, that'll solve all my problems.
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But pulling big levers are often an act of desperation.
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Um and they're often uh an act of kind of just coming in over the top versus taking the time to understand what's really going wrong.
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So, you know, the the idea is nobody wants to not make progress, so they want to make big progress, therefore a big solution.
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Fundamentally, there's often more momentum in lots of smaller problems.
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Now they don't have to be tiny, right?
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When we get down to micro problem solving, that's often around capability building and culture building, and and I'm all for that, right?
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But um, because that that's where you build the culture and capability that allows you to go solve the big problems.
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But fundamentally, you kind of, I think the sweet spot's often somewhere in the middle.
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If you have to make progress first, what are some of those uh you know medium-sized problems we can break down and and and go after?
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They may not be sexy, they may not be super exciting, but I have a high confidence of the ability to to move the needle forward.
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So to me, breaking down the problem and then getting to understand cause and effect, those are the two two ingredients needed most in those moments.
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Yeah, I kind of like to go down what you said there at the end about breaking down the cause and effect.
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Uh, you know, before the podcast, we were talking, and I was mentioning that I I was just with a client in New Jersey.
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And at the end of the workshop, the COO told his team, and when he said it, I was like, man, that's a that is a great line, and I'm gonna steal it.
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So here I am stealing it.
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But he said, you know, we've got a lot of big problems out there on the shop floor that didn't start off as big problems.
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They started off as a bunch of little problems that went ignored, and now they're big problems.
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And if we're gonna solve them, we're gonna have to get more diligent about solving those little problems day to day, not letting them compound and not letting them drag on.
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And I thought, man, that that is that is wisdom right there.
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Um, so I stole it and now I'm I'm gonna try to impart it to you to to the you know listeners out there.
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But one of the things that I think makes that that process a little bit easier is two things.
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Number one, having structure for reviewing those problems, right?
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Having an organized daily leadership routine where we're gonna we're gonna meet as a team every day, review how we perform, and then talk about the disturbances that we experienced yesterday, and then actively solve them.
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So I think that's that's step number one.
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And then the second step is understanding the the metrics, right?
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So we talked about the levers, or you were talking about the levers.
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One of the things that I think a lot of mid-market manufacturers don't understand is the executives meet once a month and they review the KPI results, usually in the form of some bowler chart where you know it's an Excel spreadsheet that says, here's my target, here's my actual, I either hit it or I missed it.
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But what's missing there is the relationship that that like a KPI tree that visually explains what lever underneath that that you know higher key performance result, what lower level was missed that caused you to miss that that that higher level?
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They most mid-market firms don't dig that deep or don't have the resources in fairness uh to dig that deep.
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Do you agree with that?
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And and if so, how do you suggest folks start addressing it?
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Yeah, I I agree with it, although I see big companies struggle with the same thing.
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They might have more systems that make the data available, but it doesn't mean they have a structure around it, right?
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So that's the the key, the key word there is the structure.
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The structure, you know, who's gonna review what, when, make what decisions.
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Um, you know, I don't care if it's somebody opening up their email and you know, twice a day and then they make these decisions or it's a huddle.
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I mean, I do care, right?
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But but but it's what's the structure, who's gonna look at what, when, and and then react to it.
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Um, to me, every you know, every metric uh that we care about should have how are we performing, why are we performing there, and and then what are we doing about it, right?
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So those to me the the three levels.
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And and you know, we could say organizations don't have the resources for it, but they also don't have the resources to waste on fake problem solving and chasing chasing half solutions.
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So to me, they don't have the resources not to do it that way.
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Yeah, um, yeah, but even that point of sort of connecting the daily huddle to the sort of monthly review, if that's the cadence.
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If if I'm sitting in a monthly review and I look at, oh, the performance is red, um, but here's why, and here's what's already happening.
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Well, now I have faith in my team, but they've got it.
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They've got the ball, they're running with it.
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Um, I'm not compelled to come in over the top and suggest some big, why don't we try to do X?
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Um, but then I see the opportunities in that, you know, that's where I get to see and understand the uh, you know, the occurrences happening is in that sort of micro daily, daily huddles.
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I mean, every injury started off as a trip hazard, right?
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So um, you know, if I have a hundred trip hazards, one of them turns into an injury, but I can't predict which one.
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So, you know, let's solve them while they're while they're small, while we're detecting them, while we're we're analyzing them.
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So, so so you know, ultimately, if I can, if I can find problems while they're small, if I can show that we're we're you know, we're working on them, these are the solutions, then the role of the leader becomes basically A, do you have what you need to solve them?
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And B, what's the culture, capability, process, metrics?
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Is it serving them all well and making them able to go do that?
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Um, but again, if I just look at a metric and see it's red, I feel compelled to jump in and start doing problem solving from the top down.
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And that's generally not going to be the most the most productive.
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You know, that comment you just made about every injury started as a trip hazard trip hazard, you know, in our consulting business, we talk about those versus process KPIs and department KPIs.
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And the process KPI is a behavioral-based KPI.
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It's something that you can go out there and look at and see is the person behaving in a way consistent with the standards of the business, right?
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And and if the answer is no, then how do we get them back within the standard?
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And then, and then if they do, if they are behaving in a way that conforms with the standards, then what's that next level uh metric that's going to be impacted?
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So in your example, every trip, you know, if I reduce trip hazards, the injuries go down, right?
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I mean, that's that same relationship.
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But but what I'm always surprised at, not surprised, but what I always try to encourage people to do is take the time to to chart that out, right?
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So that people understand those relationships because they're they're not always obvious, right?
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It's not always just you know, hey, clearly, it's not always as obvious as trip hazards produce injuries, right?
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Sometimes you got to dig a little deeper into that.
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Um and I think to me that's where like KPI trees and other lean tools come in come into play and that that folks again they when I and I guess when I say they don't have the resources, I agree with you that they really can't afford not to.
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But sometimes, or especially in the mid-market, they don't have anybody on staff with the skill set necessary to execute it, right?
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I mean, they're trying to do everything with a second shift supervisor, and yeah, it's just difficult.
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And and and to that point, and I'll come back to the the process metrics, is um, you know, that's one of the benefits of working on smaller problems, is you get more repetitions and you can build the capability faster.
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Um, you know, if you if you try to learn to play golf by going out in the golf course and swinging a club every 150 yards, you don't get as many repetitions as on the practice key where you can just you know swing away and adjust.
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Um but I but I think that you know the difference between those sort of output metrics and process metrics, you know, first of all, behaviorally, the output metrics are often around accountability, or the process metrics are more often more about curiosity.
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And and so they they kind of, you know, my process metric doesn't need to hit a certain level.
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My output metrics do.
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I need to hit cost, I need to hit output.
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My process metrics are telling me why.
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So I can just approach it from curiosity so I can get some of the right behaviors, and it's also more likely to lead me to hey, why did that flip?
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Right there's a cause.
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Why did this flip?
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Right there's a cause, where the mathematical exercise, the engineering exercise, the uh uh analysis exercise to get from an output metric to a root cause is a couple steps removed and fundamentally harder.
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So let's make it easier, let's see it earlier, right?
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So forgive the drama of this, but if if I I can measure my heart health based on whether or not I have a heart attack, um, I could measure, you know, plaque and blood pressure and and and cholesterol, and I could also measure diet and exercise and things like that.
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So, you know, I I can see very clearly, you know, what affects things at a at a diet and exercise level.
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I just know it affects things up here, but if I wait to measure things at a heart attack level, it's like, well, what was it your diet or your exercise?
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Well, it's really hard to start to break things down there.
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So a little dramatic, but it's kind of what we're doing when we're trying to make everything better just looking at output metrics.
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Uh that's another great example, and I'm just gonna tell you now I'm stealing it.
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So all the uh allied advisors, clients, you can look forward to hearing that example in the next VSM VSD workshop.
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But you know, before the show we were talking a little bit and we were talking about AI, and and you've kind of staked out a position that that you're not necessarily pro-AI or anti-AI, you're pro-thoughtfulness, and you put words to the failure modes, you know, work, work slot, token maxing, boxing.
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If a 300-person manufacturer wanted to be thoughtful rather than either breathless or paralyzed, what's the first thing you have them fix?
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And is it even an AI thing?
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Well, I think with AI, you know, part of that thoughtfulness begins with curiosity, right?
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And so um, you know, since we're stealing things, I'll I'll steal something from Ethan Moloch, who's a University of Pennsylvania AI uh expert, uh if there is any such thing.
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And and one of the pieces of advice he gives is take a day in your office where you've got a bunch of stuff to do and try to do everything with AI.
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And you know, it it will be a really weird day, but you'll be amazed at some things and crazily disappointed and frustrated at others.
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And you just start to get curious about what do what do these tools do?
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How do they work?
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And that's just the gen AI tools.
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Um, you know, I will often take the same activity and put it into two different tools just to see how they deal with it differently, right?
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Um, it's like you know, giving a uh something to two different vendors and see how they would approach it differently, um, just plugging it into my screen.
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But so that that's kind of an individual level.
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But what I would kind of suggest is you know, pick a problem that's uh, you know, a little messy, a little, a little nuanced, um, a little uh sitting in the back of our minds that we're not um because we don't know how to go solve it, and take a whack at it with some AI effort, right?
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And and it's just a small experiment.
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It's just a stepping stone towards trying some things to see where things benefit.
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I think, especially in manufacturing, you have to be very clear about the difference between sort of generative AI versus deterministic machine learning, right?
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So if I want to develop machine code um, you know, based on these inputs, plug them in, generate machine code, um, I plug that into, build something around generative AI, I'm likely to get a different answer every time.
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I want something more deterministic that gives me consistency.
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Um, but if I want to uh uh take a lot of manually written quality reports that our teams put together and uh look for, you know, there's lots of handwritten stuff, there's lots of words that don't always match up.
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Um somebody counts the negative, somebody counts the positive, take all those reports and start to look for patterns, right?
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That might be something that generative AI could start to give me.
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Um if I get you know lots of uh you know spec reports from different uh clients, and I want to start to put them all into a consistent format, look for inconsistencies, look for missing information rather than somebody trying to pour over it.
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I could build that.
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So don't try to solve the world, just start solving some problem that kind of nags at you and hasn't gone anywhere.
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And the whole point is learn what you can do.
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Um I think for you know a small, small, medium-sized enterprise, you're the I kind of break AI solutions into three buckets.
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One, efficiency gains.
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I think that's one of the last things you should go after.
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Um because there's only limited things there, and you really have to have good process control around what you're doing already to get the process, the efficiencies out using AI.
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Second, make something better, make ourselves smarter, make ourselves deeper, do a little more analysis, go do competitive analysis.
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That's a second category.
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And third, go do things we weren't even doing before, right?
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Maybe it is going through, let's go pour over reports that we weren't, you know, we were just following away and looking for, you know, mining the gold and whatever that might be.
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And so doing some things that we would never take the time to do, but might actually prove prove useful.
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So a lot of it's going to be in those second two categories.
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Um, and and we could unpack this for a couple of hours, but I I the other thing I'd say is you don't need an AI strategy.
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Um, you you need to kind of just take some steps.
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And I like to say, think about uh uh uh pruning a growing tree rather than building a roadmap, right?
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You don't you don't even know where the tools are going to be in a year and a half, so don't try to be deterministic and predictive about where things where you take things.
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Explore, allow things to grow, be transparent, experiment, and then you know, prune what doesn't work and try to shape things over over time.
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Uh so uh and and you're never too late, right?
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It's the tools are tools are always advancing.
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So you can jump in, the tools can help you jump in halfway through.
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So if you feel like you're behind, it's okay.
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Your next step is your next step.
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You know, I I had a conversation with a client this morning, and um I I was meeting with him more as a as a friend than somebody I respect than you know as a customer.
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And uh we had developed this this tool.
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It was actually an automated capiatry that you know, because of how much work it took to build it.
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We we put together this automated capiatry, and I wanted his feedback.
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And you know, he looks at it and he says, Yeah, that's great, but it doesn't really give me what I'm looking for.
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Here's what I'm looking for, and he pulls up this report that he's put together with with Claude.
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And basically what he did was he took to what you were talking about earlier, he took a lot of uh reports out of his ERP system that nobody ever looked at because they were just you know just so dense, right?
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I mean and he fed it to Claude and just basically said, Here's what I'm trying to do.
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Give me your feedback.
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And man, the the report that this thing generated, right?
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He put it in an HTML file.
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I mean, it it was just amazing.
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He's looking at it and he goes, you know, I can see on this product line I'm doing really well on material costs, they're trending down.
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However, on this other one, I'm trending up.
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When I dig into that, I'm able to see that the result the reason that this product is trending up is because of these components and these suppliers and you know all the premium freight attitude to that.
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I'm able to look at my run rate expenses with labor and see the same thing in this product line.
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I'm okay in this product line, I'm up.
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I mean, the level of just knowledge that this thing was able to you know siphon out of these tones of of ERP reports.
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I mean, it was to me that's the power.
00:20:50.319 --> 00:21:07.279
It's it's producing actionable data that you can give to to executives to then make better business decisions and better put in place better strategies as opposed to I don't know, we're just gonna go out here and kind of figure it out, right?
00:21:07.440 --> 00:21:09.839
I mean, that's that's that's the real thing.
00:21:10.240 --> 00:21:14.480
And and that's where you know that falls in that third category, something we weren't gonna do anyway.
00:21:14.640 --> 00:21:19.279
Nobody was gonna, we weren't gonna hire five 15 people to go start going through that stuff.
00:21:19.599 --> 00:21:22.720
So let's let a tool do it for us.
00:21:22.880 --> 00:21:35.119
And and you do have to be prepared for it being wrong, um missing some things, imperfect, imprecise, all those things, but so are our employees, so are we, right?
00:21:35.440 --> 00:21:48.160
And and so you know, you want to challenge, you don't want to take it for granted just because I think this is one of the uh I really wish uh AI tools uh could imply tone of confidence, right?
00:21:48.559 --> 00:21:59.759
Um, like we do this as humans, like somebody said, Hey, you know, here's my information, but uh, you know, uh, we kind of just with some groans, we can imply I'm not fully confident in.
00:22:00.240 --> 00:22:05.759
This, but everything you get from AI is with full confidence and accuracy.
00:22:06.480 --> 00:22:07.599
So until you point it out.
00:22:07.920 --> 00:22:18.319
You can't be dazzled by that, and we have to challenge, we have to question, we still have to go investigate, just like this was an intern doing it, an employee doing it, or ourselves doing it.
00:22:18.559 --> 00:22:19.200
Yeah.
00:22:19.599 --> 00:22:27.039
But you know, just and he and to your point, he told us, he was like, you know, I've spent the last three days putting this together.
00:22:27.200 --> 00:22:31.359
So it's not like he just typed four sentences in and it spit out all this magical report.
00:22:31.599 --> 00:22:34.160
He spent time putting this together.
00:22:34.400 --> 00:22:47.119
However, three days from what he got is still uh I mean, universities would have used a team of people to do that level uh of analysis, and it would have taken them weeks.
00:22:47.519 --> 00:23:01.039
So anyway, and I'd only add to that, you know, if it was an intern or employee, how many of us would spend three days worth of time helping them be successful at a project?
00:23:01.359 --> 00:23:02.799
Not often enough, right?
00:23:02.880 --> 00:23:05.359
So we're willing to sit by ourselves and do it.
00:23:05.599 --> 00:23:11.440
Um, but there's, you know, are we investing the same energy into helping our people be successful?
00:23:11.680 --> 00:23:20.000
Um sometimes it's the investment of effort that was the key to success, um, not the tool on the other side.
00:23:20.160 --> 00:23:24.960
So I as we as we are dazzled by AI at the same time.
00:23:25.200 --> 00:23:33.680
Well, did I just was I just more thoughtful in how I approach this activity than I ever have in the past because I was playing with this AI tool.
00:23:33.839 --> 00:23:34.079
Right.
00:23:34.240 --> 00:23:43.440
And I don't want to dismiss the power of the tools, but sometimes it just gives us a platform to be thoughtful, and that's its own benefit, right?
00:23:43.519 --> 00:23:45.920
That's that's that's really the work that was important.
00:23:46.319 --> 00:23:47.279
Absolutely.
00:23:47.519 --> 00:24:00.720
Well, you know, in our previous discussions, you had a line that that I really liked, and you said that growing pains show up at the joints, the handoffs, decision rights, the relationships, not inside any one department.
00:24:01.039 --> 00:24:16.880
Is one a lot of our listeners, you know, this is what a lot of our listeners will recognize the morning after a good year, when a mid-market manufacturer doubles, what breaks first and what is hiring almost all why is hiring almost always the wrong reflex?
00:24:17.839 --> 00:24:29.039
Yeah, I mean, you know, there's there's this idea of we'll just add more resources, but every time you add somebody, it's it adds all sorts of connections and extra handoffs.
00:24:29.200 --> 00:24:33.039
And every handoff is an opportunity for a delay or an error.
00:24:33.279 --> 00:24:44.559
Um and so and and it it adds to potential misalignment, it adds to potential entropy and added you know chaos to uh to to the system.
00:24:45.119 --> 00:25:05.759
And so um, you know, so yeah, you might get more work done, but you won't get, you know, linearly, you won't get uh the amount more done equal to the resource that you just added, because at the same time you added some waste and some some inefficiency because of those added resources.
00:25:06.079 --> 00:25:20.079
So so fundamentally, you know, if you're at a certain size, and you know, one Joe talks to Sue, and and you know, they've worked together a long time, they have shorthand for how they communicate, they know where each other sits.
00:25:20.319 --> 00:25:24.319
Um uh they can throw a paper ball over the partition, right?
00:25:24.480 --> 00:25:25.119
Whatever, right?
00:25:25.200 --> 00:25:26.799
But it's just it just works, right?
00:25:26.960 --> 00:25:28.640
Things start to work over time.
00:25:28.880 --> 00:25:32.880
All of a sudden they're in two different departments with five people each, right?
00:25:33.359 --> 00:25:37.759
And you know, how consistent and how nuanced is that handoff?
00:25:37.839 --> 00:25:39.200
Does it happen more in meetings?
00:25:39.279 --> 00:25:40.880
Does it happen more formally?
00:25:41.279 --> 00:25:48.079
Um, does does Jeff and and and Rebecca do it the same way as Joe and Sue?
00:25:48.319 --> 00:25:49.759
Um, no, not quite.
00:25:49.920 --> 00:25:53.359
So now there's some inconsistency in that.
00:25:53.599 --> 00:26:11.440
And so it's it's it's each time we add those, you know, grow a department size, uh, grow a new function, add more product lines, um, it just adds to the complexity, it adds to uh you know the handoffs, the alignment.
00:26:11.759 --> 00:26:18.000
And you know, I I spend a lot of time talking about process around activities, connections, and flows.
00:26:18.079 --> 00:26:20.640
Those are the building blocks of all process.
00:26:20.960 --> 00:26:23.519
But connections are the hardest to get right.
00:26:23.920 --> 00:26:31.920
And and so growth not only strains those connections, um, it also fundamentally changes how they often have to work.
00:26:32.160 --> 00:26:35.519
So the activities often remain structured.
00:26:35.759 --> 00:26:41.200
Um, if I go from one to two, that's usually where it starts to fall apart.
00:26:41.279 --> 00:26:50.559
But if I'm going from four to five, like, all right, the activity itself, okay, we're gonna even if it's just tribal knowledge, we're just, you know, hey, watch how they do it.
00:26:50.640 --> 00:26:54.160
Okay, we're still doing the activity in a consistent way.
00:26:54.400 --> 00:26:56.400
Uh the flow is the flow, right?
00:26:56.480 --> 00:26:58.720
It's kind of how we do the work and how things go.
00:26:58.799 --> 00:27:07.680
But those connections, they change the most dramatically, I believe I observe as as organizations grow, and they're the hardest to get right.
00:27:08.319 --> 00:27:38.240
Yeah, you know, that's kind of why we started our fractional CI program, was because what I see is, especially in the mid-market, is this this growth pattern of you know, family-owned shops sell a great product, and they get to this point in their their trajectory where you know the processes they used basically they have a very small team, they're able to communicate very rapidly and and and kind of direct resources very quickly to accomplish tasks.
00:27:39.119 --> 00:27:45.279
They've grown so much they've had to bring others in, and now that way of doing business, it just doesn't work, right?
00:27:45.519 --> 00:27:57.119
You have to standardize the processes, and and that's very frustrating for a lot of these folks because you know the truth about standards is it it kind of makes you slow down, right?
00:27:57.200 --> 00:28:03.599
I mean, you gotta fill out the form, you gotta submit it to the right person, it has to be approved by the right director or whatever.
00:28:03.759 --> 00:28:05.119
Well, well, this slows you down.
00:28:05.200 --> 00:28:15.200
And if you've grown up in this uh, you know, very small organization where you just get it done, that feels wrong, that feels bad, that feels like waste.
00:28:15.359 --> 00:28:17.200
You know, what do you say to those folks?
00:28:17.519 --> 00:28:22.079
How do you convince them that no, you know, you you gotta you gotta do this.
00:28:22.160 --> 00:28:25.839
We've gotta standardize these connections, otherwise you just can't scale.
00:28:26.319 --> 00:28:34.319
Yeah, I I think first I I do try to avoid the, well, I'll say first is is the idea you are standard.
00:28:34.480 --> 00:28:36.720
Um you know, you were standard.
00:28:36.880 --> 00:28:44.400
Uh your standard was just embedded in small amount of resources who have habits and knowledge about how to do things, right?
00:28:44.559 --> 00:28:50.880
Um, I mean, you can watch a great chef um not measure anything, right?
00:28:50.960 --> 00:29:07.839
They're just cooking, they're doing this, they're doing that, but they're so experienced that when they grab a spice and throw it in into a dish, one dash to the next dash to the next dash is probably more consistent than me trying to measure, right?
00:29:08.319 --> 00:29:11.519
So, yeah, it's super standard, it's super consistent.
00:29:11.759 --> 00:29:18.079
It's just embedded in the knowledge and abilities of one person, and and and it's more maybe more intuitive.
00:29:18.400 --> 00:29:22.160
So it's not do we want consistency or not, we want consistency.
00:29:22.319 --> 00:29:31.920
You had consistency, but now to scale and to grow, you need more tools to provide that consistency across an enterprise.
00:29:32.559 --> 00:29:37.440
Um, the second thing is I try to avoid standard equals good.
00:29:37.920 --> 00:29:53.359
Um, because while it, you know, I'll say lean thinkers will often say that's true, it it can lead to overuse and abuse of that premise, but it also kind of misses the point, which is what problem are we trying to solve?
00:29:53.519 --> 00:29:54.079
Right?
00:29:54.319 --> 00:30:00.319
And so that's where I get down to, well, you know, what's the what's the what problem are we trying to solve?
00:30:00.480 --> 00:30:02.000
Is it a risk, right?
00:30:02.240 --> 00:30:05.440
Is it we introduce risk without consistency?
00:30:05.759 --> 00:30:12.640
Uh do we introduce variation and inefficiency with um with inconsistency?
00:30:12.799 --> 00:30:16.880
Is it harder to add resources without consistency, right?
00:30:17.119 --> 00:30:23.519
So is it harder for you know other people to interface with a group without consistency, right?
00:30:23.839 --> 00:30:41.599
So if I have a maintenance org, right, that was like three people and now it's 30, if everybody gets help from their maintenance resources different ways, and one guy likes to do it one way, another one shows up and asks what help you need, another one says, Come and find me, how do I operate?
00:30:41.680 --> 00:30:41.839
Right?
00:30:42.000 --> 00:30:46.559
So you're like, oh, we have a shared resource, we need a consistent way to operate.
00:30:46.799 --> 00:31:07.359
So when you get crisp and clear about what gains are we trying to see, what problem are we trying to solve, then it's it's okay, it's less likely to become bureaucratic, it's less likely to go too far, and it's more likely to actually provide the benefit that we're looking for.
00:31:07.519 --> 00:31:16.240
So um, so I like to lean into the standard equals good, but then I like to say, well, why why this, why now?
00:31:16.319 --> 00:31:17.680
Why this standard?
00:31:18.160 --> 00:31:19.279
Why not go further?
00:31:19.440 --> 00:31:20.319
Why not go less?
00:31:20.480 --> 00:31:22.079
What are we trying to solve?
00:31:22.559 --> 00:31:23.920
Yeah, I I hear you.
00:31:24.319 --> 00:31:29.759
In my head, I'm I'm trying not to be offended by the potential idea that standards could be bad.
00:31:31.359 --> 00:31:38.160
But but you know, I'm working in the big companies as well, and I've definitely seen the over-engineering that I think you're referring to, right?
00:31:38.240 --> 00:31:40.880
The the bureaucracy for the sake of bureaucracy.
00:31:41.279 --> 00:31:48.160
Uh but if I take a step back and I say, okay, well, let's let's make it less bureaucratic, right?
00:31:48.240 --> 00:31:50.640
Let's let's take out some of this structure.
00:31:50.880 --> 00:31:53.680
Am I gonna get the same results?
00:31:54.000 --> 00:31:54.240
Right?
00:31:54.480 --> 00:31:59.759
Because you know, I guess I'm a firm believer in entropy does always increase.
00:32:00.000 --> 00:32:02.880
And I would also say that it increases a lot faster than you think.
00:32:03.519 --> 00:32:16.480
Um my experience would lean lend me to believe or lend me to advocate for yeah, yeah, I hear you.
00:32:16.640 --> 00:32:25.519
This is this is painful, and maybe it's a little m more painful than it needs to be, but I think if we take it away, that's gonna be way worse.
00:32:26.960 --> 00:32:28.799
Yeah, and and I what would you say to that?
00:32:29.599 --> 00:32:37.279
I I certainly don't think we would start taking away standards, and and some of what I said is really around prioritization.
00:32:38.000 --> 00:32:43.759
Um, and and some of it is how far do I go now versus how far do I go tomorrow?
00:32:44.000 --> 00:32:44.240
Right.
00:32:44.480 --> 00:32:47.680
So let's say I've gone from one site to three sites.
00:32:47.839 --> 00:32:53.680
Let's just say I've done it inorganically, meaning I've acquired two other sites, and so now we're bigger.
00:32:53.920 --> 00:32:59.920
Um you know, so so now we have three different ways of doing things because they were already doing things differently.
00:33:00.160 --> 00:33:05.119
Um do I want to standardize how I schedule those plants?
00:33:05.680 --> 00:33:18.720
Um if they're using, if if they're not serving the same customers and they're not leveraging the same supply chains, there's limited benefit to scheduling the same way.
00:33:18.960 --> 00:33:22.160
So, do I want to put my time right now into that?
00:33:22.400 --> 00:33:33.599
Now, if they're leveraging the same supply chain, hmm, all right, now the benefits of consistently scheduling all three plants are the same way, has more benefit.
00:33:34.160 --> 00:33:42.400
Um and then just to use an extreme example to make the point around let's not go standardize things that don't need it.
00:33:42.559 --> 00:33:49.119
If one plant has a cafeteria and another one has food trucks outside, do I need to standardize that?
00:33:49.279 --> 00:33:55.759
You know, not unless one plant really feels underserved because the other guys have something better, right?
00:33:55.920 --> 00:33:58.720
And we have a cultural problem solved, but now we have a problem, right?
00:33:58.799 --> 00:34:01.119
Now we can say, yeah, we do have a problem.
00:34:01.279 --> 00:34:04.480
They feel like that plant gets better service than they do.
00:34:04.799 --> 00:34:06.240
That's bad for morale.
00:34:06.319 --> 00:34:12.639
So, but most of the time it's going to be, well, what you know, do we need to standardize the food service at all three sites?
00:34:12.800 --> 00:34:13.599
Probably not.
00:34:13.840 --> 00:34:24.079
So that's that's the thing of it's it's not just to standardize or not to standardize, but how far, how fast, and what what first and what next.
00:34:24.320 --> 00:34:24.960
Yeah, okay.
00:34:25.039 --> 00:34:27.199
So that makes that makes more sense to me.
00:34:27.360 --> 00:34:33.599
So, you know, what what what I hear you saying there is it doesn't make sense to shove square pegs and round holes, right?
00:34:33.679 --> 00:34:38.639
You know, if this doesn't make sense to do this, we shouldn't go changing it just to conform.
00:34:39.280 --> 00:34:46.000
I wouldn't even use the word standardize, I would just say to conform to another process that there's no added benefit.
00:34:46.159 --> 00:34:51.840
Yeah, I guess when I say standardize, you know, what I tell people is I don't really care.
00:34:52.079 --> 00:34:55.599
I mean, I do, but I don't care how you do it.
00:34:55.760 --> 00:34:59.280
I mean, if if if this way is the best way to do it, then do it that way.
00:34:59.360 --> 00:34:59.920
That's fine.
00:35:00.159 --> 00:35:01.599
But just write it down, right?
00:35:01.679 --> 00:35:09.679
Just have it documented so that when there's a problem, we can ask ourselves what failed, and we have something to reference, right?
00:35:09.760 --> 00:35:11.360
This is how the process should work.
00:35:11.519 --> 00:35:12.559
Did we follow that?
00:35:12.800 --> 00:35:15.679
Well, no, okay, well, then we just we should go follow the process.
00:35:15.920 --> 00:35:17.760
Or yes, and it still failed.
00:35:17.840 --> 00:35:18.639
Well, well, why?
00:35:18.800 --> 00:35:21.519
And then we kind of have a starting point.
00:35:21.679 --> 00:35:29.199
Whereas when you don't have that, it's like trying to improve your hundred-meter dash time without ever running, you know, 100 meters.
00:35:29.599 --> 00:35:34.400
And what you articulated there very clearly is one of those benefits, right?
00:35:34.480 --> 00:35:41.920
So again, is it standardizing for the sake of standardizing, or is it standardizing for a purpose to solve a problem?
00:35:42.400 --> 00:35:56.960
And and if I have an example of how work is done that is embedded in the experience of two people, um, then I can't analyze it, fix it if it's broken, or make improvements to it.
00:35:57.199 --> 00:35:57.519
Right?
00:35:57.760 --> 00:36:03.119
So, so that's kind of well, but if I if I do write it down, now I can do those things.
00:36:03.199 --> 00:36:06.480
And I can make it better, and I can fix it when it's broken.
00:36:06.719 --> 00:36:13.519
So, so that but that's a again, it's a prep prioritization, what's first, what's second, what's next, what's after.
00:36:13.679 --> 00:36:16.719
But that would be a what problem are we solving?
00:36:16.960 --> 00:36:20.239
Well, we can't troubleshoot when we have a failure.
00:36:20.719 --> 00:36:30.079
Okay, well then we should standardize it, we should write it down, we should understand it so that we can in the future troubleshoot when we have a failure.
00:36:30.320 --> 00:36:30.960
Yeah.
00:36:31.440 --> 00:36:31.920
Understood.
00:36:32.079 --> 00:36:32.719
Yeah, yeah, yeah.
00:36:33.360 --> 00:36:36.639
And let me let me get into that, because I think sometimes there's other go ahead.
00:36:36.880 --> 00:36:41.679
Yeah, I was gonna say one, you know, some of this is just how to bring people along.
00:36:41.840 --> 00:36:49.280
And and and somebody wants to describe me as a pragmatic zealot, which I I kind of like because I I advocate for these things, right?
00:36:49.360 --> 00:36:57.920
But if you come at people who have done work really well for a long period of time and saying, Lean says we got to standardize, like, but why?
00:36:58.159 --> 00:37:02.159
It's like, well, the pragmatic part is let's get down to why.
00:37:02.239 --> 00:37:10.960
Let's let's really get down to what are the gaps, what can we do, what can't we do, what are the benefits, and and not make it because lean says so.
00:37:11.119 --> 00:37:17.679
And yeah, and really get down to let's let's understand what we're trying to accomplish with this particular instance.
00:37:17.840 --> 00:37:25.519
And I just think for some of the people out there that are good at what they do and might be a little skeptical, it's how we bring them along.
00:37:25.920 --> 00:37:31.199
Yeah, no, I mean I I definitely I used to get so frustrated when I first started at at Bosch.
00:37:31.519 --> 00:37:36.079
Um, we would do projects and I would ask, I was like, why are we doing this?
00:37:36.480 --> 00:37:40.719
And the answer that would come back to me would always be, oh, true north.
00:37:41.119 --> 00:37:41.679
True north.
00:37:42.159 --> 00:37:43.280
It's the you know, true north.
00:37:43.440 --> 00:37:48.559
Lean says this is it's always better to move things in smaller quantities faster, right?
00:37:48.719 --> 00:37:49.280
True north.
00:37:49.840 --> 00:37:51.920
I mean, yeah, but we should do better.
00:37:52.320 --> 00:37:56.320
We're spending$200,000 more than we were to because of true north.
00:37:56.400 --> 00:37:58.960
Like I thought true north was to maximize the profit.
00:37:59.039 --> 00:38:00.960
I thought that was that was true north, right?
00:38:01.039 --> 00:38:12.400
I mean, without sacrificing long-term, you know, opportunities, of course, but but spending$200,000 just for the sake of spending it because Lean says it's better, that's just stupid on a stick.
00:38:12.480 --> 00:38:14.639
Like, I I can't I can't take that.
00:38:14.719 --> 00:38:16.880
I so I think yeah, I think we're saying the same thing.
00:38:17.280 --> 00:38:18.800
Yep, yeah, we can do better.
00:38:19.119 --> 00:38:30.639
You know, one thing that I really I really want to get to is you've sat on boards from startups to industrial companies like Robinson Fans and SNS Cycle, and you've invested in about 30.
00:38:30.719 --> 00:38:36.079
You know, most lean experts have never had to sell an improvement program to a board or a PE owner.
00:38:36.239 --> 00:38:39.280
What does the boardroom see that the plant floor doesn't?
00:38:39.440 --> 00:38:45.119
And how should an ops leader translate lean gains into language their owners actually care about?
00:38:45.199 --> 00:38:55.760
I you know, I have this conversation more often than you think with industrial engineers who come up with this great improvement and and it's great.
00:38:55.840 --> 00:39:06.480
And I'm like, okay, and and and the but the metric they use to justify it is always utilization or you know, minutes per changeover or something operational.
00:39:06.639 --> 00:39:11.519
And I'm like, guys, you're gonna present this to your PE owners next month.
00:39:11.679 --> 00:39:16.320
You need to translate this into dollars and cents that they care about, right?
00:39:16.480 --> 00:39:22.239
They don't understand what you cutting off 10 minutes per changeover, why that matters.
00:39:22.320 --> 00:39:24.800
You gotta, you gotta, you gotta translate it for.
00:39:25.199 --> 00:39:26.960
You know, how do you approach that?
00:39:27.280 --> 00:39:28.000
Am I wrong?
00:39:28.159 --> 00:39:29.679
Should I be telling them something different?
00:39:29.840 --> 00:39:30.880
What do you think?
00:39:31.280 --> 00:39:39.519
I think for starters, it's it's helpful to understand the the nature of shareholders and and boards for each instance, right?
00:39:39.679 --> 00:39:46.400
So so I've been on boards where there's lean thinkers on the boards and they want to know about the lean efforts, right?
00:39:46.480 --> 00:39:53.280
They're gonna ask questions or they're an operationally minded leader, so they're gonna ask operational questions with some savvy.
00:39:54.079 --> 00:40:12.880
Um and I've sat, I I've I've been around boards and and I guess I've probably sat on boards where it's mostly financial experts and maybe growth market-focused, you know, MA experts that are focused on how we go get the wins, and then you all figure it out how you're gonna service them.
00:40:13.119 --> 00:40:16.400
So so I think you have to understand who you're talking to, right?
00:40:16.559 --> 00:40:21.440
And and there's PE firms out there that are extremely operational focused.
00:40:21.519 --> 00:40:26.800
They're made up of sort of lean thinkers and people who have run operations, been on the plant floor.
00:40:26.960 --> 00:40:28.400
They want to know this stuff.
00:40:28.559 --> 00:40:30.320
And they know cause and effect.
00:40:30.400 --> 00:40:32.800
They know if I do this, I'm gonna get that.
00:40:33.039 --> 00:40:35.440
So I think that's sort of step one.
00:40:35.599 --> 00:40:37.280
Understand what I'm working with, right?
00:40:37.440 --> 00:40:42.480
A detached, more financially focused board, gonna want, gonna want different things.
00:40:42.719 --> 00:40:48.480
I think it's also helpful to understand um kind of what some of the motivations are, right?
00:40:48.639 --> 00:40:51.920
And it's it's not all profit, sometimes it's sustainability, right?
00:40:52.000 --> 00:40:59.280
If you talk about a family-owned business, goal number one is not maximize profit, it's sustain the business for the next generation.
00:40:59.440 --> 00:41:01.199
That's almost always goal one.
00:41:01.440 --> 00:41:10.960
So they take on a different mentality around risk and reward because you know, last thing they want to do is lose the family, you know, the family legacy.
00:41:11.599 --> 00:41:16.639
So, so um, so it so it helps to understand the motivation.
00:41:16.960 --> 00:41:32.079
And and then along with that, it's it's um, you know, a lot of financials at a sort of board level are different priorities than perhaps at an operational level, right?
00:41:32.239 --> 00:41:34.079
So I'll use this as an example.
00:41:34.159 --> 00:41:40.000
I think more and more, I think I wrote this just in a post in the past few weeks.
00:41:40.239 --> 00:41:51.760
I think more and more operational leaders are gonna have to learn about capital efficiency because interest rates are not going to be going down anytime.
00:41:51.840 --> 00:41:55.280
You know, I'm not talking incrementally, I'm talking about going back to zero.
00:41:55.440 --> 00:41:58.320
That's not gonna happen in the rest of our careers.
00:41:58.800 --> 00:42:03.440
Um they're gonna have to learn about capital efficiency.
00:42:03.599 --> 00:42:10.400
Um, how do I preserve capital, working capital, capital spending, a lot of capital you can't unspend.
00:42:10.719 --> 00:42:18.159
Um, so yeah, there's a quick math here, but how capital efficient are we as an enterprise?
00:42:18.400 --> 00:42:24.559
Um that's a different set of questions than we usually ask as we're running an operation.
00:42:24.960 --> 00:42:37.440
So, you know, you come in and you say, yeah, we're we're running at this efficiency, we're we're uh, you know, we have these this quality level, we have these margins, we're gonna spend this money.
00:42:37.519 --> 00:42:40.559
It's like, okay, what does all that mean for capital efficiency?
00:42:40.639 --> 00:42:42.800
What does that all that mean for return on assets?
00:42:42.960 --> 00:42:45.920
What does all that mean for free cash flow?
00:42:46.239 --> 00:42:50.639
Um, you know, somewhere in the middle there has to be some translation.
00:42:50.800 --> 00:42:52.880
And and I do think it can go both ways.
00:42:53.039 --> 00:42:59.360
I think operational leaders have to get more savvy about some of those metrics and what they mean.
00:42:59.679 --> 00:43:10.079
I also think my financial folks have to get more savvy about the operational side and what's going on there and how it translates to what they're seeing.
00:43:10.320 --> 00:43:24.960
And it's it's why, I mean, back when I was running an operation, I had my controller filling in as vacation replacement shift manager, just so he would get lots of time seeing how the place ran.
00:43:25.360 --> 00:43:28.480
So he'd ask much better questions as a financial leader.
00:43:28.639 --> 00:43:30.880
So I think all that goes both ways.
00:43:31.039 --> 00:43:38.719
But um, so it's not all about the financials, but when it is about the financials, it's not always the same sets of metrics.
00:43:39.360 --> 00:43:40.159
That's a good point.
00:43:40.239 --> 00:43:47.519
You're talking about the operational leaders and the and the financial leaders, being able to speak the same language and talk to each other.
00:43:47.679 --> 00:43:51.760
I was recently leading a TPATri development workshop, right?
00:43:51.840 --> 00:43:57.679
We're starting at Net Profit, trying to break down all the metrics that went into that for this for this business.
00:43:58.000 --> 00:43:59.760
And we had the CFO in there.
00:44:00.480 --> 00:44:03.840
And the CLO in there, and we were looking at quality metrics.
00:44:04.159 --> 00:44:14.400
And they were talking about the CFO was telling the CLO, hey, I send you this every month and have for years, and you keep telling me that you know you can't impact it, you can't do anything about it.
00:44:14.559 --> 00:44:27.440
And they keep talking, they keep talking, and and come they came to figure out that the CFO was talking about the metric the CFO was sending was X, but the COO thought it was Y.
00:44:27.760 --> 00:44:31.599
And they had been talking past one another for years, right?
00:44:31.760 --> 00:44:36.800
Not talking about the same thing, not you know, not singing off the same sheet of music.
00:44:37.039 --> 00:44:41.679
One thought the metric meant this, when in reality it was actually this other thing.
00:44:41.840 --> 00:44:48.239
And when they had that kind of aha moment, the COO was like, Oh, oh, yeah, I got that.
00:44:48.320 --> 00:44:49.599
Sure, here it is.
00:44:50.400 --> 00:44:52.480
So, you know, it's yeah, you're right.
00:44:52.559 --> 00:44:53.119
It's amazing.
00:44:53.199 --> 00:44:55.760
And and that had gone on for a long time.
00:44:55.920 --> 00:45:07.920
So getting those folks on the same to speak the same language so that the operations folks can kind of know what the CFO wants, and then vice versa, it's important for sure.
00:45:08.159 --> 00:45:14.480
Yeah, I'll add in one other dynamic, and that is uh the infrequency of touch points.
00:45:14.719 --> 00:45:18.800
Um, you know, when you're when you're in an operation, especially if you're on the floor, right?
00:45:18.880 --> 00:45:21.199
You're used to seeing the same people every day.
00:45:21.360 --> 00:45:37.519
You you you you have some vibes, you can speak with shorthand, you you know, you know each other's moods, but if you only show up at a board meeting, you know, every two to three months, um they don't they don't get all that, right?
00:45:37.599 --> 00:45:41.280
They don't get all that uh to read between the lines.
00:45:41.519 --> 00:45:49.119
So a specific uh challenge that shows up is I want my operational leaders to be calm under pressure, right?
00:45:49.599 --> 00:46:04.079
But at the same time, if they're showing up calm under pressure, reporting you know, 80% on-time delivery, um, and I'm wondering why they're not canceling all vacation as a board member.
00:46:04.239 --> 00:46:06.960
Why are why are you not more wound up about this?
00:46:07.119 --> 00:46:07.440
Right?
00:46:07.679 --> 00:46:12.000
Um, no, no, I am, but I'm calm, right?
00:46:12.159 --> 00:46:21.760
I can't tell the difference between lack of urgency and calm if I only get to, you know, sit with you for 30 minutes every, you know, every quarter.
00:46:22.079 --> 00:46:27.599
So, and the same thing can happen between an operational leader and a commercial leader inside the company.
00:46:27.679 --> 00:46:31.119
It's like, are you calm or do you not get that this is a real problem?
00:46:31.280 --> 00:46:32.639
What's the difference, right?
00:46:32.960 --> 00:46:43.360
And so, you know, kind of uh conveying the how do I convey, um, yeah, no, we we are in we are in serious trouble what we've got it.
00:46:43.519 --> 00:46:46.000
We're in serious trouble, we don't yet have it.
00:46:46.159 --> 00:46:49.280
Um, everything's good, everything's not good, right?
00:46:49.440 --> 00:46:58.320
How do I convey that without you know sounding like the sky is falling and without, you know, um, without looking panicky.
00:46:58.559 --> 00:47:03.519
So so so again, when we're used to, yeah, everybody knows this is a problem.
00:47:03.599 --> 00:47:13.440
We look at the metrics every day, you know, we know it's red, we're doing stuff about it, we're working with urgency, but then I go in for half an hour to present some results.
00:47:13.679 --> 00:47:15.679
Are they going to see that same stuff?
00:47:15.920 --> 00:47:27.840
So that's where sometimes, especially operational leaders and boards, there can be some, you know, whispers to the CEO, I don't think your operational leader understands how important this is.
00:47:28.159 --> 00:47:33.199
Kind of kind of misalignments that that can can uh get the best of you.
00:47:33.519 --> 00:47:42.639
Yeah, you know, I I think it's been my experience, I think a lot of those judgments are made about operational leaders in the Q ⁇ A session, right?
00:47:42.719 --> 00:47:46.960
So you get there's a presentation, you give the presentation, and then there's questions.
00:47:47.039 --> 00:47:49.199
And it's how do you respond to those questions?
00:47:49.360 --> 00:47:50.480
You know, are you dialed in?
00:47:50.559 --> 00:47:51.840
Do you have the details?
00:47:52.000 --> 00:47:59.840
Are you able to give coherent uh responses that that make you appear managerial for lack of a better word, right?
00:48:00.000 --> 00:48:04.320
Or are you kind of evading, are you kind of talking around things?
00:48:04.559 --> 00:48:09.679
You know, I it seems to me that's really where the rubber meets the road in in those environments.
00:48:09.760 --> 00:48:11.039
I don't know, maybe you see it differently.
00:48:11.360 --> 00:48:16.079
No, I I I I think that's that's where you have the chance to be the most authentic, right?
00:48:16.159 --> 00:48:26.239
You're you're done with the PowerPoint, you're now into the conversation, and and and that's where you can convey most authentically what you're really doing and how you're really approaching it without it.
00:48:26.480 --> 00:48:26.559
Right.
00:48:26.960 --> 00:48:28.639
And it's easier to see through it too, right?
00:48:28.719 --> 00:48:36.639
I mean, I've been in those town hall meetings where you've got the executive team standing on a stage with you know all the shop floor guys, and and the shop floor guys see it too, right?
00:48:36.719 --> 00:48:44.079
I mean, they're asking questions, and depending on your answers, they're gonna walk back and go, yeah, they um he didn't want to answer that, so so he didn't.
00:48:44.159 --> 00:48:44.480
Right?
00:48:44.559 --> 00:48:49.760
Yes, so but Jamie, thank you so much for carving out the time to come on the show.
00:48:49.840 --> 00:48:50.719
I really appreciate it.
00:48:50.800 --> 00:48:54.079
And thank you also for sending me copies of the books.
00:48:54.159 --> 00:48:55.360
I can't wait to dig into these.
00:48:55.519 --> 00:48:58.000
Guys, we'll link uh to the books in the show notes.
00:48:58.079 --> 00:49:01.599
So if you're interested in learning more about Jamie, check him out, jayflinch.com.
00:49:01.760 --> 00:49:05.119
We'll put links to the books on Amazon where you can get your own copies.
00:49:05.280 --> 00:49:10.320
Uh you know, thank you so much for being willing to come on and share your experience, your knowledge with our listeners.
00:49:10.400 --> 00:49:15.039
And guys, if you enjoyed this conversation with Jamie and I, please do like and subscribe.
00:49:15.119 --> 00:49:16.960
You know, share the episode with a friend.
00:49:17.039 --> 00:49:24.480
It really does help us get the message out there so that others might might learn a little something and be able to carry back lessons to their operation.
00:49:24.639 --> 00:49:27.199
So again, Jamie, thank you so much for the time.
00:49:27.280 --> 00:49:28.559
Um, really appreciate it.
00:49:28.880 --> 00:49:31.519
Justin, I appreciate it, and thanks for the conversation.
00:49:31.679 --> 00:49:32.880
Keep doing what you're doing.
00:49:33.119 --> 00:49:34.320
Absolutely.