Episode_4-Greg-Ready

Liz Crescenti and Marco Bonilla host the Lean into Excellence podcast. In this episode, they interview Greg Marciano, a Senior Consultant, about the benefits of the process capability approach. Greg explains that improving processes is key to fixing any issue or problem a company may have. He emphasizes the importance of identifying which processes to address and which steps within each process to modify. Greg defines process capability as the metric that describes how effectively a system of operations provides the desired outcome. He discusses the two capability metrics commonly used, CPK and PPK, with a focus on PPK, which can be easily calculated using Microsoft Excel. Greg encourages all companies to determine their process capability as a first step in launching a successful improvement program. He also provides examples of how process capability analysis has been used to solve problems in various industries. Welcome to Lean into Excellence, a Workstream Consulting Podcast. I'm Liz Crescenti. And I'm Marco Bonilla. And we will be your hosts as we embark on our continuous improvement journey. Welcome back to another episode of Lean into Excellence. I'm your host, Liz Crescenti. And I'm Marco Bonilla. And today we have a very special guest with us. We have our very own Senior Consultant, Greg Marciano. Welcome to the podcast, Greg. Oh, I'm glad to be here. We are thrilled to have you. For the audience listening, do you mind sharing your background? Sure. I'm a Chemical Engineer and a Certified 6 Sigma Master Black Belt with additional certification in Lean Manufacturing. I've worked on electronics for commercial satellites, the Space Shuttle and Mars Rover, as well as military defense weapon systems such as Tomahawk, Copperhead, and Harpoon, in addition to the F-16 and Harrier Jump Jet aircraft. Recently, I designed and manufactured the liquid hydrogen and liquid oxygen fuel duct systems for the ULA Delta and NASA's SLS rocket ships. Fantastic. What a background. That's fantastic, Greg. Thanks for joining us today. Well, I'm excited to be here today to discuss the benefits of the process capability approach. Yes, we're going to do a deep dive into that, so get ready. Hey, Greg, it's fantastic that you're here. Tell me a little bit more about process capability and why it's important. Sure. I've often been contacted by companies seeking to improve their profit margin or needing assistance resolving issues with their customers, regardless of whether those issues were related to quality problems or on-time deliveries, they want help and they need it now. One universal truth that I emphasize is that one or more processes must be improved in order to fix anything. Every issue, every problem has a cause, and that cause is a process that needs updating. If you don't break eggs, you can't make an omelet. The key to success is to identify exactly which processes to address and which steps within each process to modify. In an earlier podcast, we heard all about process mapping. So here's the path forward. Determine the capability for every step on that process map. If you know the specifications or even just your expectations, you can measure anything to get the process capability of that operation. Everyone knows that change is hard, but knowing where to start is actually the first challenge. This podcast is all about using the concept of process capability to identify and monitor process improvement. Absolutely. Knowing where to start, that can absolutely be the most difficult part of the equation. Greg, you bring up a really good point. Every step in the process has an effect to process capability, right? So from beginning to end, you just can't focus on the very last step, because the very last step was probably the least, had the least effect on the process. Right. Just because final inspection says it's bad, you have no idea where that happened. Exactly. It could have been 20 steps prior. Right. Right. So you got to turn over every stone in that case. Correct. Correct. You know, Greg, process capability can mean different things to different people. How would you define it? You know, you're absolutely right. I'll define process capability as the metric that describes how effectively a system of operations, like from the process map, provides the desired outcome. The benefit of this approach is that in addition to rating the overall process, the capability metric identifies exactly which process steps are most urgently in need of fixing, as well as enabling clear numerical tracking of the impact of each and every process change. A bonus for adopting the process capability approach is that the metric will signal when each process step has been optimized enough so that efforts can then be redirected to the next process on the priority list. I encourage all companies to launch a successful improvement program by first determining their process capability. I have seen successful companies build their entire business around determining the capability metric for each step of every process to gain an accurate understanding of exactly where to target upgrades. Greg, that's fantastic. Can you kind of do a deeper dive on what the process capability metrics are and how are they important to the company? Yeah, that's a key thing, this word, the metric, right? The number, how are we going to measure the thing that we're talking about instead of just having a feeling? Right, because if you don't measure, you can't improve, right, Greg? Exactly. Just say, I don't like it. Well, it's hard to improve that, right? Right. Or it doesn't feel right. Yeah. That's not enough. And how can you say one thing, you know, is more in need of help than another part of the process? Yeah, you can't go off of a feeling. Yeah, exactly. We need metrics. We need numbers to talk about, right? We need a baseline of some sort, right? Yeah. So the process capability metric, actually, there's two capability metrics that are typically used in an improvement program. CPK, it's capital C and then a small pk, is the short-term ability of a process to meet a specification. While PPK, capital P, small p, small k, PPK is how a process actually performs in the long term. CPK is for tracking impacts of day-to-day process adjustments. And then PPK provides the ongoing performance that the customer will experience. In today's podcast, we're going to discuss PPK because that metric is very easy to calculate with Microsoft Excel. No special statistical software is needed. So for the whole rest of today, we're going to be talking PPK, something that everybody with Excel could do for themselves. Perfect. Note that for CPK, remember, that's that other capability metric. Remember that one, the other one? The one we're not going to talk about today? Note that for CPK and for specialized cases involving attribute counting types of data or non-normal skewed distributions of data or subgroups of data such as taking five measurements every hour, to do any of those special things, you will need statistical data analysis software such as Minitab, QI Macros, or Sigma XL to calculate the CPK metric for your data. So for today, we'll just stick with Excel PPK, okay? And that's the long-term process performance metric. I think that's a great idea, Greg, because we might be here all day doing a deep dive, right? Exactly. I think a lot of the audience would prefer Excel over Minitab, but that's just me. Well, it's most accessible, right? I mean, most people have access to Excel. You already have Excel. You don't have to go out and buy anything. Right. Exactly. Exactly. So use the tools that you have in front of you. This isn't create more cost for nobody. As Marco said, you don't have to make a science project about it, so. Exactly. Yeah, yeah. Exactly. There's a need for Minitab when it's needed, but not right now. Yeah. I mean, there are some special circumstances and blah, blah, blah, and maybe I'll hire somebody to help you with those, but my point here is capability is for every man. Everybody can do capability, and all you need is Excel. It's actually quite straightforward. And should do capability, as we talked about, right? It shouldn't be a feeling or a guess. Right. Everybody should be doing it. You should know where you are in the world. We don't want a barrier. Exactly. Right. We don't want to tell people, yeah, you've got to go out and buy software for $200 or $1,000 or whatever these software programs cost these days, right? We don't want to tell people you can't do capability because you don't have the money to buy extra software. Exactly. You should be doing capability because it doesn't cost you anything. You already have Excel. Exactly. And non-financially, you can't afford not to do capability, right? You can't improve if you don't know where your baseline is. Exactly. Exactly. So let's talk about some examples, Greg. There's probably a million examples out there, probably a ton that you've used capability analysis on, but can you give us a couple examples that come to mind? Absolutely. Well, you know, there's hundreds of examples, but we don't have all day, right? Right. So here's a couple. We can do more podcasts, right? More examples. Part two. Part two. Just examples. I know. So actually, here are a couple of my favorites. The new modernized heads-up display for the F-16 fighter jet was a wonderful electronic masterpiece. Everybody loved it. But the electronic module for it was mounted close to the plane's M61 Vulcan Gatling gun. When firing at 6,000 20mm rounds per minute, vibrations were so severe that electronic components were actually knocked off the circuit board. Not surprising. Not surprising at all. I've never seen that coming a mile away, Greg. Exactly. Keep in mind, so the idea was we had to fix the problem because then the pilot would say the heads-up display was working until I fired my guns, and then it stopped working. So that's the kind of customer complaint. A little problematic. It's a woman's gun, pretty much, right? You don't want that kind of customer complaint from a pilot, right? Yeah. In a fighter jet. Anyway, so it had to be fixed. Now, the interesting thing was they told us we had to fix the problem, but we're not allowed to change the electronic design of the module. Now, can you imagine? You have to fix the problem, but don't change anything. I get that all the time, Greg. In my history, it's just they expect this magic dust or this magic wand. Exactly. Don't touch my design books. Just put some duct tape on it. You mean that doesn't work? Just put some duct tape on it. You'll be okay. Duct tape fixes everything. So the solution came forth, finally, after a lot of things were tried. Epoxy was used to secure the components. You know, glue them down with epoxy, right? But the epoxy viscosity across the entire module had a lot of variability in it, and there were actually too many failures. It certainly made things better, but there were just too many failures, too many customer complaints, too many pilot complaints. Yeah, quality is one, and quality consistency is the other, right? Yeah, exactly. So it kind of helped, but it didn't fix the problem, right? The initial PPK of this epoxy process was only 0.9. Remember I said we want at least 1.33? Remember that? Yeah, 0.9. This is only 0.9. This is a large fallout in your capability. Right. So different formulations were tested, you know, mix this, mix that, mix it this way, mix it that way, cure it this way. All those process parameters for epoxy mixing and curing, right, were tested until finally an acceptable capability metric was achieved. And when that happened, you know, the pilots never again noticed a problem. So that was, there's aerospace, planes, right? Another example was to optimize the weld quality of the Inconel Super Alloy used in liquid hydrogen and liquid oxygen fuel ducts for modern rocket ships. Now, these are rockets. Some are unmanned rocket ships that just launched satellites, and some are, you know, the upcoming NAND rocket ships that are going to go to Mars and the asteroid belt, right? So the Inconel is really difficult to weld, I got to tell you. It's called a super alloy because it has all kinds of special properties, and I like to say special properties that make it almost impossible to weld. So this was a big deal. And as you can imagine, there were many, many welding process parameters which must work in concert to produce the perfect welded joint. What we did here was made a process map of the welding process and then optimized the capability metric of each variable in the weld process, one after the other, perfecting one variable, move on to the next one, get the PPK for the next variable, move on to the next one, get the PPK for the next variable, and those variables for the welding machines could be, you know, the voltage going into the weld, the amperage going into the weld, the temperature of the environment, you know, where the welding was happening, the amount of oxygen in the weld. Yeah, all those things, one after the other, get a good PPK, get a good PPK, get a good PPK, until finally they were all, every process variable, every adjustment that the operator could make was perfected, right? And then, I was going to say like magic, but it wasn't magic, it was a lot of work, right? And then these welds would pass, finally, every NASA test. Greg, I appreciate you plugging process maps again, so people, go back to listen to Episode 2. Episode 2. Right, well, it's important, right? Yeah. You know, a lot of guys say, well, here's a flowchart of what we do, but now what do you do with that? You know, just having a flowchart of what you do, you know, is really only the first step in process improvement. Yeah. Absolutely. It's the knowledge, now you've got to execute. And now, exactly, exactly the right thing is we have to execute on that process map, and that's where process capability metrics come in. So, Greg, I am concerned. You used two examples that seem like you need top-secret clearance to be like an entire, hopefully we're not going to come down on that. We'll dumb it down a little bit. Hopefully the government's not going to come after us for sharing some of this information. You're the professor. Yes. Is public knowledge great? That was a nickname at two previous companies. But it's public knowledge, I hope. That's true. Well, you know what, I mean, you know, those are high-end aerospace, rocket ship kind of examples, right, you know? But, you know, remember I said process capability is for everyone? Absolutely. So let me give you some commercial examples that have nothing to do with rocket science, right? And this is not rocket science. These are commercial companies. So there was a large commercial company that produced custom corporate-branded swag. You've probably seen it, right? Mugs and pens and notepads and these people made umbrellas with the company logo on it. I think all three of us are wearing swag right now, right? Yeah, exactly. Exactly. And they did this at high volume, right? And what they wanted to do was increase throughput. They were getting a lot of business. They had people working shifts well into the night, a huge amount of overtime. I mean, so on the one hand, you know, you have a company that had a lot of business, right, getting a lot of orders, making a lot of profit. But they were really stretching their workforce into working super long hours, and people get tired of working super long hours, right? And so they wanted to increase throughput so that there could be, like, weekends off maybe, something unheard of. What a luxury. You can't have a weekend off if we're behind on filling the orders. So the idea was don't be behind on filling the orders because we've had higher throughput all week long. You see, there's a motivation behind here, right? So in this case, you know, there were thousands of part numbers, all these company logos, right? Hundreds of operators, scores of machines in this gigantic factory. It was like 300,000 square feet. I mean, a huge place. What we did is we started, just like I said, we used capability to identify the processes with the worst performance against specifications for two things, both for quality and for production speed. So we had a spec for how good quality each item had to be, and that's like it had to pass a test, it had to pass inspection, whatever, right? But also we said, here's the goal for production speed. Remember I said the metric capability spec can be an expectation as well? So we also said we also had a production speed. How many minutes should it take to make one of these things? If everything was perfect though, Greg, right? We had two PPKs. We had a quality PPK for how good is the quality of the product, rework, blah, blah, blah. And then we also had a performance, a speed PPK. Are we making it fast enough? So we actually had two PPKs for each thing there. There were a lot of key variables to address. The hardest one was the mixing of the printing inks to achieve exactly the right color shades for corporate logos. Customers were extremely concerned about that because they were very, I mean, this is like they're putting themselves out there, right? And this lightest shade, you know, this blue doesn't look like that blue, right? The whole mixing routine, you know, had to be really right, right? So what we did was, you know, we focused all the improvement efforts until each of those processes had acceptable PPKs. You know, the ink mixing, everything else, right? Application, curing, everything. Now this process wasn't overnight as you can well imagine, right? It went on for several months. And during that time, interestingly enough, we were trying to increase throughput, right? But while we're doing it, the customer demand also increased because the sales department decided to optimize their process at the same time so that the manufacturing group wouldn't get all the glory. No doubt. No doubt, Craig. So that was kind of, you know, it was an unexpected consequence. And just to reiterate what you're saying, Greg, you know, before you make things move faster, you need to improve the quality first, right? Because if you make things move faster, all you're doing is producing more nonconforming, right? So quality over speed first, and then once you get the quality down to a science, then you can tailor your speed until you don't damage, right? Yeah, I've got a great example for that, you know, going faster and not paying attention to quality. You know, there was another strictly commercial company that made pumps for swimming pools. They had been trying to reduce warehousing across the country by implementing just-in-time lean manufacturing. Great. We haven't introduced just-in-time yet, but this is great. Great. This will be a future project. Yes, we'll dive into that. So at this swimming pool pump company, they had very pretty U-shaped lean cells. Everybody's standing at their machines, and, you know, it was – they had videos about how wonderful this all was. These were lean cells, you know, for making, you know, several part numbers, one-piece flow. That's a lean manufacturing thing, term, right? Yet they were still struggling to keep up with customer demand due to inconsistent quality. In other words, they were very efficiently, very quickly making pumps that needed rework. So that's exactly what you said, right? You can't just focus on quality – on speed and not quality or quality and not – you have to have both. The question always comes, Greg, if you didn't have time to do it right the first time, why would you have more time to do it the second time or rework, in other words, right? Right the second time. It adds cost, right? That process adds cost. Time, cost, resources, yeah. And some of their operations were actually okay, but they were failing because of too much variation in earlier steps of the process. So it was complex, right? Some, you know, an operator would say, I'm doing my job just right. It's just that that person, you know, two hours ago with their process, they're handing me all this stuff, you know, it just doesn't work, right? Now, this is where process capability comes into play, right? You get the PPK of every single step in the process, right? Another excellent case for taking the process capability approach is the medical industry, where very high reliability is a given. Here's an example. A company decided to utilize its microelectronics assembly expertise. This is where components are smaller than a grain of rice, tiny. All the assembly work is done under microscopes, right? So they had this expertise for doing this kind of work, right? And the company wanted to branch out into making medical devices. You know, and these devices were really special. They were designed to be implanted in people for pain management, and this is a device that gets implanted in the hip. And for hearing, these are devices that get implanted inside your head, inside your ear, right? And since these devices were going to be inside human beings, the reliability requirements were extremely high. And you hope so. Well, we hope so, right? I mean, nobody wants to go, I mean, these are surgically implanted devices. You don't want to have a recall and tell people. Time to switch that out. Exactly. And the designers for these special medical devices wanted proof of capability before placing any assembly orders. They heard in one of, you heard, right, about process maps. We've talked about process maps a couple times, right? Yeah. Can you guess how this company actually convinced their prospective customers that each step of every operation of the process map would produce extremely high reliability devices? Can you guess, Marco? What did we do? Liz? Could it be a very high process capability metric? Exactly, process capability, but really high numbers, really big numbers. That was a nice softball pitch to Liz. That was very nice. Five points for me, so. You deserve it. You were paying attention. You were paying attention. Exactly, exactly. And, you know, because this is what they wanted. They wanted to know, you know, are we really going to be able to do the job, you know, with the super high reliability that they needed, or is there a risk? Is there going to be variability in our devices? And, Greg, in this case, this is a long-term, right? Yes, because it's a plan for life. Yeah. Can it meet the same specs over a long period of time? Really long period of time. I mean, you could take, you know, I mean, there might be a child, and they get one of these hearing implants, and they're going to have that hearing implant in their head for 70 years. Yeah. Correct, correct. Absolutely. Yeah, so long-term reliability, long-term high process capability, it was a big deal, as you can probably well imagine. Okay, so I think we're sold on the value here, but can you go into some specifics about exactly how to set up and conduct a process capability study? Yeah, and this is where, you know, a lot of times, you know, you see articles, you know, on the Internet or whatever about, yeah, you should do this, you should do that. And I'm saying, yeah, you should do capability, right? They often stop short of where you're going today. How do you do it? The mechanism. That sounds great, but how? We're not just talking about what or why, right? We're talking about how do you actually go about doing it, right? You're doing it well the first time. So just to show that every process can have a capability metric, in order to show you how to set up a capability study, right, consider a new teenage driver, a family car, and a two-car garage with a large post in the middle. This sounds nightmarish. Nightmarish. Each garage entry width is only six inches wider than the side view mirrors that stick out on the sides of the car. That's only a three-inch margin on each side, if the car is perfectly centered. Now, what I did was put pieces of blue painter's tape at the center of the bumpers and at the center of the garage. It was easy to measure by how much my daughter drove the car too much to the left or right of the center mark. Many attempts later, and she never hit the mirrors once, but many attempts later, capability was calculated in Excel, showing a poor PPK of 0.8 due to too much variation of parking efforts, even though the side view mirrors never actually touched the garage entryway. But they made you sweat, though. Yeah. They made you sweat. Yeah. Because this capability indicated that unless there was dramatic improvement, sooner or later, a mirror was going to get hit. Yeah, absolutely. That's a one-time event, too, right? Really. Destructive testing. Did we want high capability? You betcha. Right? What I did, I promised to buy my daughter a car if she could achieve a capability of at least 1.33. Wow. I think all parents listen to the podcast. Greg, can you be my dad? That's amazing. Exactly. So, Greg, that's great, because everyone listens to the podcast, trying to figure out how to incorporate process capability with their children. With teenagers. Right. So what she did was she put a vertical strip of blue tape in the center of the back wall of the garage that aimed for it during subsequent parking attempts. Target practice. Yeah. She earned her very own car. It was used, but she was happy. That's okay. That's fantastic. There's no damage to the garage, right? Everyone's happy. Right. So now you're going to set up a project, right? So now it's time to check to see if the new set of tires she just bought will truly last for the 70,000 advertised miles. With this podcast, you can now set up a capability study. Measure the new tread depth. Subtract 2 32nds of an inch to get the usable tread depth. That's the legal standard, right? It has to have at least 2 32nds left, right? And then divide by 10 to calculate the maximum tread loss spec if you plan to check the tires every 7,000 miles. So 7,000 miles times 10 checks, that's your 70,000 miles, right? Now, to measure tread, you'll need a tread gauge. Amazon has them. You can buy all kinds of gauges at Amazon for tread depth. And be sure to measure at multiple locations all around your tire. Right, to make sure it's balanced, right? Right, because you want to measure the middle, you want to measure the edges, and all around, right? And this will, by the way, give you lots of data points for your Excel. Remember I said make a column of data? You'll get a lot of data points every time. And there's four tires on the car. So you'll get a lot of data points of each tire and four tires on the car. And every 7,000 miles, you take your Amazon tread gauge and you measure. What you're really going to do is you're going to enter the tread loss data since the previous check, right? How much tread did you lose against how much tread is okay to use, you know, based upon, you know, a tenth of 70,000 miles. Every 7,000 miles, then you can update the PPK to get an idea of the likelihood of these tires achieving the advertised 70,000-mile tread life. This is a fun capability study. You can do it all. Yes, and if you get it correct, Greg will buy you a new pair of tires. He'll buy you new rims. Yes. Greg, here's a fun fact for you, and maybe you don't know this, but I think it was last year or the year before, you would think field goal kickers are very accurate to a field goal post, right, when they do extra points or three-point kicks after, you know, scoring in a football game. There was a cowboy kicker, I think last year or the year before, that missed four extra-point field goals in one game. What do you think the capability of his analysis was? So just to give you an idea, that hasn't been done in 90 years. So this was really a one-off, but this actually happened during a game, during a playoff game. They still won, but I know that kicker was sweating because his capability analysis turned out really bad. Yes. You see, what I would have done as a coach is measure how far off center, each kick was in practice. And if you could see what the variability in practice was, you could use peak decay to predict what's the probability that you can actually miss the goal post altogether. Well, Greg, in fairness to him, I think he hit almost every field goal during the regular season. I think the stress of being in the playoffs, I think got to him. He choked. Now, the point is not, did the rearview mirror not hit yet? The point is, how much variation was there? Because that variation is what's going to predict that badness will happen at some point in the game in the future. Right. It's the variation that's important. So it could have hit it a hundred times and never missed it once. But if the variation was poor, the peak decay will indicate a high probability that he's going to miss it in the future. So, Greg, where were you when this kicker was – Well, if they'd hired me, I would have – He needed to be on the sidelines there. And then we could compare the peak decay of the different kickers. Because every team has more than one kicker, right? Yeah. You have to decide who's going to be the prime time kicker, who's going to be the backup. Right. I would say the higher peak decay goes to the prime time kicker. Sure. I'll make mathematics out of this issue. As it should be, right? You remove all emotional bias. Right. Excellent. So, Greg, just to close out the podcast, do you have any final thoughts you want to share with us regarding capability analysis? Yes. Process capability is the only statistical data analysis tool that will also predict the future. And you'll need software packages for this piece, but they can predict the long-term reject rate in either percentage or parts per million based on the current process capability. And that's what I was talking about, like with the football game or with the tire track, right? Or with parking in a garage. This prediction, right, is this really key piece of process capability. And it's the only tool that will do that. Finally, I guess my last comment would be, if you can measure it, you can calculate its process capability. And the specifications don't have to be dimensions such as length and width or temperature degrees or angle degrees or pounds or grams or ohms or volts or any of those things. You can actually use time, minutes to complete a task, seconds to do this, hours to finish a unit, right? You can use time to be a measurement spec for capability. Absolutely. So kind of in summary, in comparison to maybe, let's talk about the stock market real quick. This is a leading indicator. It can actually predict. It won't tell you when, but it will happen if it's outside. It will give you a probability. Exactly. Percentage, like how many bad units out of 100, how many bad units out of 1,000. Exactly. So you'll see it coming. There won't be any surprise. Exactly. Well, thank you so much, Greg, for joining us today. This was beyond informative. It was fantastic having you, Greg. Well, I just hope we'll provide guidance for how to develop, you know, for all the listeners, how to develop your very own process improvement efforts. And the message here is you want to improve something? Start with PPK. Start by understanding the capability of the thing you want to improve, and then every time you make some kind of improvement, collect some more data and see what the new PPK is. Right. And you can actually watch the PPK climbing. Maybe it starts at only 0.8, and then it goes to 0.9. It's not good enough, but it's better. And then it goes to 1.1. It's still not good enough, but it's better. And then it's at 1.3, and then you decide, no, we're doing medical devices. 1.33 is not good enough for us. We need 1.7 or 1.9 for a medical device. But at least you have numbers. Yeah, and they'll also tell you if you're making improvements, you know, it's possible you go in the opposite direction. That's right. It's going to stop whatever improvements you're working on that you think it's helping. Oh, that's true. And, you know, that's happened where a company thinks they're making a change. Somebody says, you know, some engineer will come along and say, well, here's what we should do. Right. Make this change. Right. You know, we're going to cure it at 150 degrees instead of 125 degrees, and that's going to solve the whole problem. Right. You know, watch the PPK, and sometimes it goes backwards. That's right. Stop what you're doing. Sometimes it goes down. Exactly, exactly. You're not creating more chaos in this case. Right. But isn't it nice to have a metric? I mean, everybody can see that, you know, 0.9 is worse than 1.1, right? Yes. I mean, that metric makes it real easy to understand. Did I make the process better or did I make the process worse? Exactly, Greg. Well, this has been fantastic. We're going to have to get you back on. So, Greg, let me ask you something. If someone wants to reach out to you, what's the best way of getting a hold of you? Workstream Consulting. Awesome. Yes. So I would say feel free to reach out to us if you have any questions or Greg, and you can find us at workstreamconsulting.com or info at workstreamconsulting.com. And just a reminder, new episodes are released every other Wednesday, and we will see you next time. Thanks again, Greg. Thank you, Greg. It was my pleasure. I had lots of fun. Thank you, everyone. Bye. Bye. Bye. Bye. Bye. Bye. Bye. Bye. Bye. Bye. Bye. Bye. Bye. Bye. Bye. Bye. Bye. Bye. Bye. Bye. Bye. Bye. Bye. Bye. Bye. Bye. Bye. Bye. Bye.