Episode_8-Aidan-Ready

Lean Six Sigma can be applied in the service sector to improve efficiency and eliminate waste. In Ireland, 80% of the workforce is in the service sector, while in the USA, 91% of the workforce is in the service environment. Lean Six Sigma can be used to make service environments faster, better, and easier for customers. Examples of environments that can benefit from optimization include airports, logistics and supply chains, and the food sector. The goal is to match supply and demand, optimize flows, and react quickly to changes in order to improve overall performance. 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 Liz Crescenti. I'm Marco Bonilla. And today we have Mr. Aidan Magner, who is the founding partner and head of Operational Excellence at 360, based out of Cork, Ireland. Yeah, it's great to have Aidan here. We're going to be talking about utilizing Lean Six Sigma in the service environment. Aidan, thanks for coming on board. Why don't you tell us a little bit about your background and what you do? Hey, Marco. Hey, Liz. Good to be online with you guys. So, yes, as you mentioned there, I'm with a company called 360. Myself and two friends formed it over five years ago. Our aim and intention was to provide a holistic review of business opportunities with the SME industry in Ireland. So we partnered with Ireland's most ambitious Irish companies to help them grow and prosper. And within that, then, I am the head of Supply Chain and Operational Excellence. And I focus on delivering improvements on the supply chain and operations excellence side of things. I'm a Master Black Belt, Certified Master Black Belt in Lean Six Sigma. I have a Master's in Supply Chain. And probably for the last 10 or 12 years, my focus has been on elimination of waste in the supply chain environments. And that has sparked my interest in the transaction environments because there's a huge element inside there that we can focus on. That's fantastic. You know, I've known Aidan for the past two decades. We worked together across the pond for a company that focused on semiconductors. But as Aidan has talked about, you know, it's not about just manufacturing. We can leverage continuous improvement in all types of environments. His strength happens to be in supply chain. So, Aidan, tell me, so why would we even focus on Lean Six Sigma outside of manufacturing? I suppose, Marco, one of the key things that you and I have faced over the last couple of decades is when we go and we start looking at Lean Six Sigma, people say, well, that doesn't apply to us. That only applies if you're Toyota. That only applies if you're Motorola. That only applies if you're making cars. That only applies if you're making semiconductors. That only applies if you're making ultra-high volume of parts. And one of the key things that jumped out at me, Marco, was when I was looking into this, I realized some very interesting statistics. In Ireland, 80% of the workforce is in the service sector. 20% is in industrial manufacturing. In the USA, then, when I did some dipping into numbers over there, 91% of the workforce is in the service environment and, you know, 9% is in the manufacturing environment. And even if we peel that onion ever so slightly, in the manufacturing environment, we can actually see that those that are making the widgets and those that are doing the doing inside there are really only about half of that number again because you've got HR, you've got executive management, you've got finance, you've got IT, you've got supply chain, you've got logistics, you've got purchasing, you've got planning. You have all of these ancillary functions in a manufacturing environment that even change that number of those of us that are in the service environment are more important. So when I started looking then at opportunities for improvement, if we focus on that side of the business, we can make significant improvements. If you think about in that manufacturing space, what companies want is the product. Therefore, if we make improvement, if we make changes to the product, we're changing with the value-add proposition. If we can change and improve the service environment, we make it faster, better, quicker, and easier. Likewise, in the service environment, we've all stood in restaurants where we were left waiting for 35, 40 minutes, so we couldn't see a reason why. There were tables awaiting. We've stood in airports where the security, you might have had 24 x-ray machines and only two were staffed. Meanwhile, the queue was as long. Meanwhile, when you're in the queue, people are standing and they're queuing. Could we be taking our laptop out of our bag earlier? Could we be taking our belts off earlier and getting ready for that so that it's a faster, better, quicker, and easier environment? Queuing in a bank. If we're going to any of the service environments we're actually working with, booking concert tickets, these are all things that we all automatically assume on an ongoing basis that they should be better, but we complain about the performance. We complain about how the system works. We complain about everything else. What are the opportunities for Lean and Six Sigma deployment that we can make the service sector better, faster, quicker, and easier? Absolutely, because we live in a service environment. We just don't think of it that way. We definitely don't live in a day-to-day manufacturing environment. You've identified a larger portion of our day that can leverage continuous improvement tool sets and techniques, right? Correct. If you look at some of the Lean analysis that has been done over the decades, 95% of what we do is not value-add. We'll convince ourselves that a certain portion of it is necessary non-value-add, but the vast bulk of everything we do is non-value-add. One of my favorite conversations when I work with organizations is to say that value is created at the coalface. If it's a contact center, if it's a call center, if it's a manufacturing environment, if it's a fast food outlet, it's the people that are engaging with the customers that are creating the value. The rest of us add no value in that. It's important that we are more efficient, that we are right first time every single time. If you think about the conveyancing of legal documents and the time it takes to actually get legal paperwork through a system, opportunities are lost. If you think about onboarding, how many times have we worked with clients in the past where talent was lost? I think you were talking about this in a recent webinar, Marco, where talent is lost, where employees engage, they start the recruitment process, and then it's actually lost and they have moved away. They've lost interest. They've got a different job elsewhere. This has lost opportunities for organizations. Then you've got to go back to the start of that cycle, and it's a sunk cost that nobody's calculating. Yeah, absolutely. I just had this conversation with a group of talent acquisition people. How many people do you lose along the way? First of all, all the effort you put to try to get them, but then the delay, the wait, and they're gone. It's not that they're ghosting you. They've moved on. They can't wait months. The situation you were talking about before, Marco, how many touch points were there originally for new hires? It was like 30-something? Yeah. No, it was more than that. I think it was in the 40s, and we cut it down to something in the low double digits. Right? Yeah. It wasn't just a touch point. Well, it was touch points by movement and touch points by people. Again, inefficiencies, non-value added. Once you address, Aiden, as you realize, once you appreciate that you might not be the non-value added part in that process, there's got to be a way to eliminate yourself or at least minimize that interaction. Correct. Aiden, can you give us some examples of environments that could benefit from optimization? Well, I think, Liz, if you think about every environment that we go through on a daily basis, one of my pet peeves is the airport. Most of us have had the pleasure either on vacation going through the airports or on professional going through airports, and that queue that forms at the airport where you're literally standing there and there's hundreds of people in the queue, and you see one, maybe two x-ray machines that are open, and you stop and you question yourself, why? Was it a resource allocation bit? Was it a training bit? What part of this was unknown? Just as an example, in Ireland, a couple of years back, post-COVID, when travel started recovering, there was huge problems in the airport because the numbers of people was a surge capacity. And of all the industries everywhere, you're looking and you're wondering, what part of that was unpredictable? Because the flights are lodged, the tickets are sold months in advance, so you might have, and most of the airlines are actually flying and are recovered at a 90% capacity, so you know down to the person whose name is on the seat who's actually coming through, and that ability to actually match supply and demand, match the flows, and optimize the flows was just absolutely crazy for a period of time. And that's just one example. Now, if you now look at that into some of the other service sectors that we talk about, logistics and supply chains, the global movements of products, if you take what happened in Baltimore last week, you have ships that are inside the port, you have the container ship itself, and you have ships that are outside. The knock-ons from those into a supply chain are going to be huge, and it's the speed and the ability at which supply chains can react is vital for our sectors. So we need to make them faster, better, quicker, and easier. We need to be able to optimize those so that we can see exactly what's actually happening with live data and being able to see it. If you take the food sector, for example, 30 years ago, Domino's Pizzas, you would ring up a telephone where there was a person at the end of a telephone, and they would guarantee delivery in 30 minutes, and they had MapQuest, or they had a roadmap on the car, and they would actually deliver. Nowadays, with all of the advanced technology and all of the advanced manufacturing and everything else, we're still struggling to deliver in 30 minutes with live tracking, live apps, live every other piece of information. So in that situation, there's significant lean improvements that have been made where you can actually see your driver almost coming down the road, your Uber driver you can see coming down the road. That's a great example of lean efficiency. So it's one thing to wait for a cab to turn up. It's another thing to actually see exactly how far away the cab driver actually is. So the journey hasn't changed. The wait time hasn't actually changed. But what has changed is the value from the customer's perspective. So they can see exactly how far away they are, what their queue time actually is, and being able to see real-time data. So we view client data on an ongoing basis without even realizing that we do. Yeah, they pulled us into the relationship, right, Aiden? It's really what they are. So just adding to that domino... I was just going to say dominoes. You can track and see when the pizza goes in the oven. Exactly. So there's no question, right? It's not accurate, though. Just FYI. But yes, they make it seem like we're a part of it and we're okay with that. Exactly. Instead of having people call every three minutes saying, you know, where's my pizza? The answer is there, right? It's their natural way of pushing back. Correct. You keep them in the loop, right? You keep the customer part of the process. Right. The information gets disseminated easier. Yeah. But lean is in our life, whether we even realize it or not. If you go on to Netflix right now, you have Marie Kondo with the, you know, tidying up with Marie Kondo. In the lean environment, we would call that a 5S activity, you know? And if you look at what she does, on day one she goes in and she clears out the closets and everything is laid out on the yard and this is what we're going to keep and this is what we're going to donate to charity and this is what we're going to do. And then we go back and, you know, while the closet is empty, we're now going to repaint it, rebuild it. We're going to put new floors in. We're going to put new doors in. And then we only bring back in what we actually need. And we're going to put a system in place so that we know exactly how old and what the age of everything is inside there. That's our classic 5S environment. We do it on an ongoing basis. There's another TV show, Extreme Makeover, where they rebuild the house in five days. It's a Kaizen event. You know, we're doing this on an ongoing basis. We're buying this. We're actually bought into this process on an ongoing basis. And, you know, we can make these changes and we can see these changes in our life and in our businesses around us. And if we can apply the same principles in our office, if we can apply the same principles in our schools, if we can apply the same principles in everything we do, it will be significantly better. One of the key areas that I'm looking at at the moment as well is delivery of training courses. So if I'm delivering a training course across five different locations, how do I know that all five of those are exactly the same? If I deliver the course five times in the same location, how do I know that everybody has the same learning experience? And it's being able to measure that efficacy and being able to ensure that we've got a standard approach to everything we do. We've got a clear and cohesive value add for the customer. And then being able to use data at the end of it all to actually measure the, you know, the mean, the standard deviation for the exam results and being able to say, well, actually statistically, they're exactly the same. So location A, B, C, D, and E are exactly the same. And, you know, in a recent course that I did, the newest, latest area were scoring higher than everyone else, which means I have to go back and look at either my training method because I'm either delivering a better product or something else has changed. But it stands as being a statistical outlier and I can use that data to say, am I getting better or am I getting worse in my training delivery? Aiden, one of the things I've noticed is people have a misconception about lead. And, yes, it's more efficient so things tend to move faster. But just because we move faster, we're not allowing things to get poorer in quality, right? So our goal is not to move things faster along and lose sight of what that quality of delivery, right, that value add you were just talking about. Do you run into a lot of that with that misconception of lead? And, again, if you take that lean into digitization environment, there's a huge push at the moment to digitize everything and have everything online. And one of the key things there, if we don't make our processes as lean as possible beforehand, we're just automating a bad process. Absolutely. And then you get a bad decision faster. Exactly. So we haven't changed anything. So I would routinely turn around and say, let's stop. Let's review exactly what we're doing. Let's make sure that we're delivering the maximum value for the client. And then automate the best purpose. Right. And in many cases, it means slow down to go fast. That's right. And that can be a bit of a mind bender for some people when you're talking about lean, which is about faster, better, quicker, and easier. And to say slow down to go fast can force people into a discussion that they might not necessarily be ready for. Aidan, you know we've run into a lot of production managers where we're behind deliveries because the quality has been poor, but they haven't addressed the quality issues. And it's not necessarily their issue, but they start saying, well, we've got to produce more. So they start adding a second shift and a third shift and weekend shifts. So they're throwing more costs at this, but they're producing more bad material sooner just because they're trying to make deliveries. So now they've got to stockpile stuff that they can't use or they have to send back through the loop, right? So, again, perfect example, right? I mean, this happens all the time. Going faster doesn't mean better in this case. Sometimes you've definitely got to slow down. Yeah, slow down, perfect it, then you can move forward. Yeah. And if you think about in the service environment, so we've got the manufacturing type environment. And, again, I can name a client who saw a massive increase in their sales, 25%, 30% increase in their sales. And they were looking at adding a second shift. They were looking at building an extension onto the facility and building a new warehouse. And when I actually looked at the data, I said, actually, you do realize that, what's it, 35%, 40% of what you're making is not right first time. Therefore, if you make it right first time, you don't need to hire new staff. You don't need to put on a million-dollar extension. You don't need to build a warehouse because all you're going to do is store bad material for a longer period. But in the service environment, it's exactly the same. If you look at some of the processes that are around what we do, and if you think, again, I'm going to pick on an easy target here, IT help desks. Go easy, Aidan, go easy. I'm going to do a deep breath now. But on the IT help desk, how many times do we submit a ticket, right, and it gets closed down? Nothing has happened because the ticket is closed. Or it gets closed citing a question that was never asked in the first place. So when you look at some of those environments, you can actually see that three, four, five help desk tickets are actually closed erroneously out of every 10. And that's a huge inefficiency. And what it does is it actually drives multiple bad behaviors. So if I'm responding to that, if I've got a contact center to respond to that, I'll end up hiring more people. I'm going to hire faster, which means that my training process may be degraded. And so now the person who was doing it wrong last time around is training somebody else to do it wrong. So now it's at a 5 out of 10 being incorrect. It might shoot up to 7 or 8 out of 10 being incorrect because I've got somebody who was… Snowballs. Yeah, correct. It's snowballs. And if I can look at making that so that it is right first time, that my value proposition is known, then I can actually resolve that one. You just picked out a thorn in my side. I'm dealing with the car I own. I've been dealing with customer service for about three or four months. And they keep passing it on to another person, so I have to retell the story. And I'm like, don't you record all this? So I'm with you 110%, David. I feel that pain. Yeah. So it's, again, another example of it. Recruitment companies, we touched on it earlier on there with this recruitment chain you were talking about. But if I want to look at the recruitment company itself, the efficacy of the recruitment company, how long does it take to get the person on board if I use company A versus company B? If I'm comparing the customer complaints on there, if I'm looking at the duration that somebody has actually stayed in employment after taking a new position, I can use all of these inside there because that's going to give me data to say, right, I'm going to choose a better performing company. And most places we don't even look at that. We just turn around and we say, it is what it is type of environment, and we react to that. But we can use Lean, and we can get data out of the system to actually start driving data through our decision-making process. Yeah, and everyone in the process is reactionary. It just makes it longer and worse, right? Because we're always trying to compensate for the process, not the other way around. Yeah, we talk about proactive being versus reactive. Yeah, and I think every guest you've had on here on the podcast so far has said that everything is a process around us. So if we look at that process and we say what portions are working, what portions aren't working, we can apply the same principles. So again, life is just a series of processes. Your first webinar or your first podcast, you made that reference inside there, that's taking the kids to school. It's a process. And if anything varies on that, if there's variance inside there, traffic Monday versus traffic on Wednesday are the exact same thing. And we can start studying the variances that are attached to that and being able to make better decisions as a result of that. I think Liz and I have still PTSD when driving the kids to school. I don't think we've fixed that process yet. That's still going to be ongoing. Yeah, that's an ongoing battle we just experience every single day. Yes. So Aidan, this whole conversation is focused on lean. We know it's important. So does that mean Six Sigma is not important or it has no place in transactional type of environments? It's an interesting question. If we can start making lean inroads into service environments, that's a great starting point. But so much data is circulating around nowadays that we can actually really start doing a lot of Six Sigma analysis. If you look at the Six Sigma environment, it's about using data to understand the variances in our process. We can actually start understanding what each individual portion of our process starts to look like. And with the amount of apps that we have now on our phones, we're leaving data trails everywhere. We're looking at every keystroke is actually leaving memory someplace. And if we can start harvesting that data out, we can now really start looking at getting information on the process flows and the variances within there. If I'm a restaurant chain and I've got multiple locations, I can now start measuring the time taken for seating clients. And I can start seeing is one restaurant chain outperforming another. I can start to look and see is there a difference between Monday and Tuesday and Wednesday and Thursday and Friday. I can start to see that seasonality factor inside there and understand if there's seasonality by geography, by region, that will be different from everywhere else. And in a lot of situations, we work with clients and they say, well, you just have to know. And this tribal knowledge that we talk about, you just know when it's there. But the data would actually tell us. And if somebody knows it when they see it, it means that there's data someplace they're unconsciously reacting to. They can see queues forming outside the restaurant. They can see a queue forming at 4 p.m. where it traditionally wouldn't form on 6 p.m. So there's something different inside there and they react differently to that. So if we can start getting information out of the system, we can start looking at that. If I start looking at my Amazon tracking details, for example, I can see, depending on which warehouse is actually going to fulfill my order, the lead times from warehouse to my house. I can start looking at that individual thing and I might start choosing specific routes that are going to get me my Amazon Prime even faster than it was. So, you know, one day may not necessarily be good enough. I might be able to get a half a day depending on the warehouse that I want to get fulfilled from. If I'm looking at global supply chains, I can now start measuring and optimizing routes globally and saying, right, well, what happens if, right? I can start looking at the data from port to port and I can start looking at the different shipping lines. I can start looking at the different routes. And I can say, well, what happens if there was to be an issue in a major port in the USA? I can start modeling that. I can start looking and we, you know, go back to two or three years ago. We saw the issue in the Suez Canal and how the ramifications kicked on then to New York and Los Angeles and everywhere else. We were able to very quickly react there recently to the Red Sea environment and being able to model our supply chains. But that only comes by having data and being able to actually pick up on the individual variances and the nodes and that value stream alongside there. So it's a long-winded way of saying there's a lot of data in the system right now. And if we can pull that data out, we can really start making decisions that will support our Lean Six Sigma journey faster, better, quicker, right first time, every single time, and on time. So, Aidan, taking a look at this from the perspective of our audience, right, some of them are not STEM backgrounds. And some are in that transactional world that you talk about, right? They could be planners. They could be purchasing. They could be HR. Just not the typical technical person that, you know, would be looking at numbers and making decisions based on it. So a lot of people are listening and saying, you know what, I know I have a problem. My process is inefficient. But I'm not trained to look at the data to make improvements. Where should I start? Where should I go? Who should I talk to? Well, I suppose, Marco, the obvious answer to that one is you pick up the phone and you ring 360 and you ring Workstream, and we'll answer all your questions for you. But the easy answer to that one straight away is if there's data in the system, the first thing anybody can do is just start painting pictures with numbers. Simple bar graphs, simple, you know, if we're talking about time, show us, you know, week one, week two, week three, week four. Show how it changes over time, being able to just paint a picture. You can get a lot of data, very messy data, onto a graph very, very easily. And that will allow you to start seeing some signals inside of the data, right? That's the first part of it is. Second of all, then, obviously, you know, if there is training for Lean Six Sigma available, work into it. And everybody should be trying to become more data literate in what they do, right? Some of us thrive on data and getting into a huge amount of detail on it. More people just need to see the basic picture of what's going on. The other part as well that I want to play on that one is that no one person is a function or a silo all by themselves. So even in smaller organizations, people might feel like they are a single silo, that they're an island of excellence all by themselves. And if we take that HR function, for example, and people are saying, well, you know, I don't know how to react or I don't know what to do with the data over time. Maybe if I look back and say, well, we had sales campaigns that we ran with our customers. And what that did then was that actually drove increase in sales. And we ended up having to hire more people. And we got a bad reputation because we hired our people too late. If I had an earlier conversation with my sales regional sales manager and he says or she says, you know, I'm running a sales campaign here. And I'm going to increase our revenue in the steak restaurant in the southeast by 25% across the time frame. Well, as a HR person, I should be sitting there and kind of going, well, so you're expecting that you're going to run this campaign that's going to give a voucher for, you know, the month of May to increase football football coming into the restaurant in May. If I start my hiring process now, I should be able to have the resources on time and in full at that stage. What tends to happen is that we run the voucher, we run the sales vouchers. There's a huge queue forms outside of the restaurant. There's no staff inside to actually meet them. We don't do it. And that whole function inside there is called sales and operations planning. And it's not just a protocol for large volume manufacturing. It is equally relevant in any service environment because in any service environment, there's a sales function and there's an operations function. If the operations function and the sales function are moving in two different directions, you'd be completely misaligned. So by getting with that wider group of people earlier and by getting with that wider group of people sooner, simple data would make for great decisions earlier in the process. And then you can actually say, right, do we need to invest in training? Do we need to invest in upskilling our teams around that? Oh, absolutely. You touched upon something we keep talking about. Besides everything is a process, the communication between process steps is important, right? Talking to the owners and say, hey, this is coming down the line, right? What can we do? What can we do to make this go smoother? Or at least be as productive as possible and successful. In a lot of cases, we talk about how do we get in front of it. Well, we don't necessarily need to be in front of it. We just need to be on the same page. All right. So since we're getting towards the end of our time, Aidan, is there any key takeaways that you would want our listeners to walk away with? Thanks, Liz. Yeah, I suppose to summarize it in simple, easy ways, lean is all around us. It's everywhere we see it, everywhere we go, and we can very quickly identify the things that make us as customers upset around what we're doing, right? So they're just forms of waste. Poor decision-making, poor communication, they're all around us. So in our transactional environments, what we should be doing is identifying waste within the process. Look for areas to actually improve it. Look for the data that actually says, I can see if this happens once a day, it happens once a week, it happens once a month. Being able to see exactly what's going on inside there. Gather some data. It doesn't need to be very complex data-gathering techniques. Post-it notes and Sharpie markers are great for actually gathering data inside there. So just be able to do that. And I suppose the last part I would look at then is make your transactional process, make it lean before looking at automating it. Don't jump to the automation because in doing so then you just end up with a bad process with faster decision-making, bad decisions coming from that. And that's my final take on it. And as with everything else, communicate, communicate, communicate. Yes, absolutely. Eden, if someone was interested in learning more about this, where could they find you? Yes, my website or our website is www.3sixty.ie. And you can find me on LinkedIn also. Awesome. Thank you so much. This was a great conversation. Thanks, Eden. Thanks for coming on. We really appreciate it. Thank you for having me. Yes. And just a reminder, new episodes are released every other Wednesday. And you can find Marco and I at WorkstreamConsulting.com. Thank you so much and see you next time.