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Lauren is a Continuous Business Process Improvement consultant, coach, trainer, and speaker. She specializes in helping business owners and leaders from mid-size organizations uncover and solve their business problems with Continuous Business Process Improvement (Lean, Six Sigma, etc.). She helps your business and organization become simpler… faster… BETTER.
She was previously a guest in Episode 376.
Today, we discuss topics and questions including:
- Why is it important not to jump to solutions with technology (Robotic Process Automation, AI, Machine Learning, or the new Hyper automation)?
- What is RPA?
- What do you mean by “digital transformation”?
- Bridging the gap – people, process, and technology
- Don't automate a bad process
- Why should you start with Value Stream mapping and then process mapping the current state and future state?
- VSM vs. process maps? Differences?
- Current state observation vs. future state creation?
- Virtual suggestion box situation – technology adoption?
- Virtual Gemba walks?
- Why are Gemba walks so important with understanding the current state and then the future state?
- Putting two things together — Lean transformation and digital transformation?
The podcast is sponsored by Stiles Associates, now in their 30th year of business. They are the go-to Lean recruiting firm serving the manufacturing, private equity, and healthcare industries. Learn more.
This podcast is part of the #LeanCommunicators network.
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Automated Transcript (Not Guaranteed to be Defect Free)
Welcome to the lean blog podcast. Visit our website www.leanblog.org. Now here's your host Mark Graban.
Mark Graban (12s):
Hi, it's Mark Graban. Welcome to the podcast. It's episode 447 for May 11th, 2022. My guest today is Lauren Hisey. She's our returning guests. She's a continuous improvement coach and consultant. You'll learn more about her in a minute. We're going to be talking about the interfaces and the interactions today between lean and people and process and technology. Technology is not a cure. All not all technology is bad. You got to make sure you don't automate a bad process. We're going to talk about that. And some specific technologies that if you're like me, you've heard of maybe you don't know a lot about, but I think it's a interesting and helpful conversation here today with Lauren.
Mark Graban (55s):
So to learn more about her, for link to her website and more, you can go to lean blog.org/447, and now on with the show. Well, hi everybody. Welcome again to the podcast. Our guest today at returning guests is Lauren Hisey. She is a continuous improvement coach and consultant. She has a continuous business process improvement consultant, coach trainer, and speaker Lauren specializes in helping business owners and leaders from midsize organizations uncover and solve their business problems with continuous business process improvement, using methods, including lean and six Sigma. She helps businesses and organizations become simpler faster and better.
Mark Graban (1m 39s):
So Lauren, welcome back to the podcast. How are you today?
Lauren Hisey (1m 42s):
I'm doing great. Thanks for having me.
Mark Graban (1m 44s):
I love that. I mean, you know, that, that purpose or that synopsis of, of what you do simpler faster, better. I, before we dig into the other topics we plan on talking about today, I'd love to hear kind of your synopsis of why those three words are so important.
Lauren Hisey (2m 1s):
It's usually a lot of times in organizations, you know, you come across a lot of the red tape or we got a lot of things are happening and it's not just with processes, but it's also with technology. So what I would really love to do is help organizations and businesses to understand that sometimes it's better to do things simpler so we can be faster and then become better, not just for the company itself, but also for the employees and the customer in your customers or clients.
Mark Graban (2m 30s):
Yeah. And that's when we, when we do this well, that, that, that those benefits are there for, for all stakeholders, for sure. And it's good to keep that, that all imbalanced, right?
Lauren Hisey (2m 41s):
Right. Exactly. Exactly. Sometimes doing it simpler as, as bad as some of the better things to do versus trying to do like really trying to, there are a lot of technology at the problem or complicating things. Sometimes it's just better to start with something very simple.
Mark Graban (2m 57s):
And we have, we talked about technology the time when Lauren was previously a guest back in July, 2020, that was episode 3 76. We talked about lean and six Sigma and technology, including AI or artificial intelligence. And, you know, I think we can take a deeper dive here today on some of those topics. It'll be good to learn from you today. Looking at people, process and technology, you know, maybe, you know, one other question before we dive into some of the, the integration or application of these technologies, we might be preaching to the choir here with the audience, but I'd love to hear your thoughts on why we w we, we need to avoid automating a bad process.
Lauren Hisey (3m 44s):
So a lot of times I'm finding there's. I think the main reason why we find problems with automating bad processes, when we will see how bad that process is a lot faster. But when we automated that process, especially when you don't include the employees or anyone within, within solution for that is because you'll get low adoption rates. A lot of times what I'm seeing with my clients, that they are spending so much money on a technology and putting it in into a process that is, that is a bad process and they what's happening is they're not realizing the ROI with all that very, very fast enough. And so only the customers alienating the employees.
Lauren Hisey (4m 28s):
And then at the end of the day, the bottom line was affected by implementing that technology and not getting you that, that ROI. And so what I'm seeing is a lot of organizations are not understanding how to maybe first go slow and then figure out the right place to do it, improve things. But then also then they are losing, they're losing traction in the digital transformation. So losing traction within their strategy that they had put out for themselves, you know, within 2020, 2021 to 2022, and two has things are still really crazy in the marketplace right now.
Mark Graban (5m 4s):
Yeah. So we'll, I think be able to dive into that a little bit deeper, you know, during the discussion here. And I forget if I use this example last time, but, you know, I can think of examples of not automating a bad process, even without software technology being involved. Many hospital laboratories for example, would have their old layout of the laboratory based on a process silos. So this is not unlike a ma manufacturing facility back in the day or a job shop that would have all the grinding machines and an area. And all the welding machines in an area laboratories might be set up where all the chemistry analyzers are in one area and all the hematology analyzers are in a different room.
Mark Graban (5m 48s):
And, you know, I've, I've, I've seen times when then people would put in robotic automation kind of, you know, carrying tubes, this really bad layout instead of maybe first coming in, it sounds obvious. And then you feel almost like a jerk for pointing it out, like the need to rearrange the layout. And then let's see if we even need to automate it once we've improved the layout in a way that improves flow. So, sorry, I'll get off the soap box there, but it's a mistake. A lot of organizations may, right?
Lauren Hisey (6m 19s):
They do, they do. I've, I've been called in with a bunch of my clients where they've bought this technology and you know, they're not seeing it work as they expected and what age you'd like to coin. They're throwing the new flashy tool or any flashy too wide, a problem without really understanding what's going on in the point where you're just talking about, if sometimes if you just change the layout, you don't necessarily don't need that automation. The same can hold true within services as well. Or it's, if it's either front office, back office, any of that, if you don't have a good process, it's just, you're just going to see how bad it is a lot faster. Like you said, sometimes you don't even need that automation in there.
Lauren Hisey (6m 59s):
You make it simple first.
Mark Graban (7m 1s):
Yeah. And I know you're going to have other examples of that today. So, you know, last time we talked about AI artificial intelligence, thanks for the opportunity. You're going to share with us about some other technologies. So maybe we, you know, before thinking of examples or, you know, how best to integrate these technologies, if you can help us with some definitions first RPA, rapid process automation. I've, I've heard this discussed a couple of times at conferences. I'm still not sure if I really understand what it is. So how would you define rapid process automation,
Lauren Hisey (7m 35s):
Robotic process automation,
Mark Graban (7m 37s):
Robotic process. I'm mixing up my acronyms. Sorry.
Lauren Hisey (7m 42s):
So robotic process automation. It's just, I like to think of it just as a term or as are the nation's been around for a very long time. We all know that, but the robotic process automation is really just creating a different type of bond. And it's really a simple bot and it doesn't have to be a physical body. It can be something software based. And basically what it's doing is taking a very easy task in just automating it. So it's taking, taking away the human doing that. So a good example would be something along the lines of data entry. A lot of times, even if you get, if you have a Moody's a CA accounting might be a good, a good example, you have something come in off of a, you know, fax or a bill, you know, some type of bill come in and within your own accounting department, you have to pay that.
Lauren Hisey (8m 33s):
So basically you're putting in all the man you just putting in being manually, or sometimes an email comes into what happens here is that a, an RPA could just be used to take that email and then it scrapes the email and then it inputs it into the system for you. So that relieves the manual task, but it also can reduce some of the, some of the error human error that would be there. And then we'll go, oh, I'll just get right into assume machine learning, machine learning, or even AI is just like, so RPS is usually the first entry into using any type of automation.
Lauren Hisey (9m 15s):
Then the next step is, and a lot of people to start talking about AI machine learning. But I think the next step after that is creating what's called intelligent automation or intelligent automation is just the next evolution where it start, where the automation starting to learn. So think of it as a kid. So you have a cage, we have to teach a kid. And as they go through school, they start to learn new things. That's really what all the intelligent automation is. You just build it, you just build in the tools for the automation to continue learning as it develops. And that just then leads into machine learning and then the AI as well. And then of course, now we had this whole new thing called hyper automation, which is another coin, but I think hyper ambitions, Marver frameworks, it really just depends on where your evolution is at and that's yeah, I wanted to go down.
Lauren Hisey (10m 2s):
It's probably the best way to start with RPA first. Then we go all the way into AI and high-powered in the hybrid and missions in the machine learning.
Mark Graban (10m 11s):
So going back to just follow up question on RPA and, and, and I'm used to acronyms with the, our rapid improvement event. For example, I got tripped up there. W when we talk about automating simple tasks, is there less risk than where we're not automating a process? Are there, is there there's less risk of sub-optimizing something with that type of automation?
Lauren Hisey (10m 37s):
Yeah, there is, there is a lot less risk at risk at doing that first. And that's why you see, when we say, let's start with the simple, simple tools first, and I'm not, I hate using the tools. And I know, and a lot of times people throw around the toolbox. They now use that a lot too, right? Cause I like to use the toolbox because it's using the right thing for the right time. And that just resonates with people, but doing something simple first before trying to get to the more complex stuff is the, is the path is the path to go. So usually when I'm working with clients, it's more than that going in an industry and process improvements it's really is going in and looking at what exactly is the strategy that they want to do, understanding what their current state is.
Lauren Hisey (11m 20s):
And I think that those, those are the first two key things that need to, we need to understand because if you try to do a whole big digital transformation, I think a lot of people get lost and they're thinking, oh, we want to do this whole big thing. But instead of let's be good to start slow and then build, build on, build on the simple things before we need to complex things.
Mark Graban (11m 40s):
Yeah. Maybe it's just as another definition there. And then maybe this is a really vague, broad term digital transformation. I mean, what, what, what, what, what does that mean?
Lauren Hisey (11m 51s):
Digital transformation? So a lot, so a lot of people have been thrown into digital transformation has been, become very speedy over the last couple of years because of the pandemic. But digital transformation is really taking the, is really taking away. The it's taking away the mundane tasks at the, at the, the gist of things is what I like to say. So when I think of like the hype it's, that's where the, I guess the new, new thing out now, out there as hyper automation, basically I take it as a framework. So usually you have this digital transformation at somebody up in the C-suite has this vision. It usually starts with the CIO.
Lauren Hisey (12m 32s):
And then also the COO is usually involved with it as well now. And even the CFO is like, how much can we, how much things can we take away from like say mundane tasks? How many things can we digital ties to make things better? And at the end of the day, it should theoretically cost the company less money to do, or used to be able to be more productive with the same number of people or less that you already have. And it's just, it's, it's, it's just being very, very fast and way the technology has grinded. Some of these, for example, we were all used to being in an office. Now we all had all very scribbled at the beginning of 2020 to figure out different ways from working from home.
Lauren Hisey (13m 13s):
Now we're looking at ways to do things hybrid. So you have to have a lot of things instead of having physical paper things and physical things that are not usually done in person, we're not to think about how do you put it up on the cloud? How do we get all of our people to work together in different locations now? Cause everyone it's, you know, remote is, is part of the whole workforce now, and it's not gone away. How do we get people to work together in a hybrid environment when we're all over the world too? So it's digital transformation is just the transformation of a company from Jane, very physical, to being very, very fluid with it, with the technology that's out there and all the digital things that are available to us now.
Mark Graban (13m 55s):
Yeah. So is it, you know, we talk about lean transformation that set aims high. It sounds like digital transformation is really a more holistic rethinking of everything. It's not just turning phone calls into zoom meetings or turning in-person user conferences into virtual events. Well, yeah, it's, it's, it's more than just turning something from analog to digital or
Lauren Hisey (14m 21s):
Right. That's correct. That's correct. Yeah. And a lot of people don't and that's, I think that's where a lot of people get missed, get hung up on the digital transformation. It is. It's just, it's just that. And that's where I think, I think the digital transformation and lean kind of go together because it helps because it's, by doing that double trends, maybe not even adult transformation overall, it changes the way culture and it changed the culture in the company. It changes the way we do business and the change of the way, how rapidly we can really change. There's different if there's different things going on in the market or if I work force changes as we've seen too, right. The workforce is very fluid right now.
Mark Graban (15m 1s):
So when it comes to these technologies, you know, a high level, I imagine there's a risk. I mean, any of these labels or technologies or a new shiny thing, Y you know, w what are some examples or warnings of, you know, like not jumping, not falling in love with the solution, not jumping into a solution because it's trendy or because competitors are doing it. Like what, what's a good example of trying to think through some better problem solving.
Lauren Hisey (15m 31s):
Yeah. So I've got a couple of good examples. I have a client that was working on their sales function. They bought this technology for their sales folks, not the throat. And I could tell the technology because I'd want to put any technology or any technology under the cause. There's so many different tools out there, but they, they originally, they started with something home ground, and then they figured out, Hey, this RPA could really, really, really help us in our digital transformation. So delicious. There's some patches on this homegrown tool that we have, and then maybe we'll, and then they started purchasing different RP solutions from different providers and just trying to piecemeal it. And so they were just trying to throw together solution without really, truly understanding that the old technology and old process could not handle the new technology that they're trying to throw at it.
Lauren Hisey (16m 22s):
So what they saw was low adoption rates, I think only about 20% of their Salesforce and, and, and, and accounting, because it was quote to cash or using that there's no trans there's no trend. The headnote that traps I've used the wrong word. They had no visibility into what was going on in the system, right? So no visibility with sales sales didn't know what was in operations, but did they have in their backlog, but they had an inventory, but they also didn't realize what was going on with, with accounting. And they weren't getting things where bills, the bills weren't getting paid and the vendors weren't getting paid.
Lauren Hisey (17m 2s):
So what they realized is that they had to stop what they were doing with their RPA, with their RPA, which would they attract coined as a digital transformation and realize they had to take a full step back, held all this stuff that they were doing, and really just go in and start process mapping something very, very simple and understanding what is the current state look like? I'm using a value stream map. And then you're using the really detailed process maps to understand the data flows and understanding the customer journey. Cause they had probably 50 different types of personas in their customer journey. And then they also had probably about a hundred different ways they could receive an order from a customer.
Lauren Hisey (17m 43s):
So realizing it was just too complex to where they had to completely do a rebuilder the quote to cash. And so doing a rebuild, having, you know, different, different types of workshops to build out this new, this new model. And then when it came, finally came up with that future state, they had a future state value stream map, but then on top of that, they also had a technology roadmap. So that's a perfect example of it's still in process today. So they're still working through it. It's not E small, it's not a two month journey. This is going to be a, this is a two year, a two year journey that they have to go through to get to where they want to be.
Lauren Hisey (18m 24s):
And you know, within about six. And I think in about six months is that they're going to start having the technology put in. They've already implemented any processes, even though they're still manual, it's got, it's a much better story than what they were trying to do for.
Mark Graban (18m 39s):
And so it sounds like there's a reminder to be had when I heard you saying was rapid re I keep saying rapid robot, old habits die hard. Robotic process automation is not digital transformation, maybe as a parallel to no offense to 5s. 5s is not the same as a lean transformation.
Lauren Hisey (19m 1s):
Mark Graban (19m 3s):
Lauren Hisey (19m 4s):
Mark Graban (19m 6s):
So can, can you tell us a little bit more about personas like that? That's a term I've heard in software land kind of trying to understand users and their needs, even in marketing, talking about personas of who it is who's buying your products or services. Tell us, tell us a little bit more about personas and how that's helpful.
Lauren Hisey (19m 30s):
Yeah. So understanding the customer persona. So, and this persona is don't have to necessarily be all external. They can also be internal, which we all know that in a lean in the lean world is that understanding it's it's when a lot of times we'll go through the persona developments, w what is your customer look like? What, what would it, what are their needs that you need to meet? What needs or problems are you trying to solve for them? Who are they? I mean, they can be in different parts of an organization. It doesn't necessarily have to be that CEO. It might just be the manager and the frontline manager needs something, or it could be it understanding what their job titles are, what they are, what keeps them up at night a lot of times, and then understanding what their habits are.
Lauren Hisey (20m 16s):
So ease for the example of my client that was doing the quote to cash, where they had all these different personas. We came up with the five major five major personas because they realized 80% of that business was only coming from like 20% of these customers. So what, what happened there was creating more of a streamlined process for quote to cash for those particular personas. And then the ones that they didn't necessarily, the ones who twosie people like, you know, the percentage of the bottom would still come in through the same channels. Now, there was, they did have some personas that were old, like in the old days, still using fax machines to send in their orders and so understated.
Lauren Hisey (20m 60s):
And so by understanding those personas, and then that helps with, as you're changing their process, then you can work with your, with your clients or customers and help teach them the new ways of doing the process, because it's great to have any process it's great for the company, but if your customers aren't going to use it, then you're going to lose your customers. So that's the biggest thing is understanding these personas. Now, if you think about the personas internally, who are the internal customers, it's, it's the same thing it's just doing. Just maybe mapping out who is who those people are, cause that really does help with the adoption rate when it comes to using the new technology, new, using new processes, but also helps the change management and teaching both internal, external customers, how to use that new process and bringing them along for the ride.
Mark Graban (21m 50s):
So my understanding of personas is it goes beyond demographics, But I think they, they use the term. So it's not just, let's say, you know, age, job, title, gender, things like that, that you might use to Sigma segment or differentiate in terms of people's needs, but psychographic data, which, which goes deeper in terms of
Lauren Hisey (22m 14s):
Mark Graban (22m 14s):
Needs, their priorities. It really, it's a deeper level understanding where demographics might be a little bit more superficial.
Lauren Hisey (22m 23s):
Yeah. That's exactly it is. Yeah. That's getting down to an even if it's, even if it's, it could be even very B and just make me be industry specific as well. Right. So I had a client as a wholesaler. We had used some persona development just based on what they do with wholesale. And then they also looked at, you know, looking at what their competitors that as well as it helps them to define what's the, what's the best process or journey for their customer.
Mark Graban (22m 53s):
Yeah. And then, you know, come back to the point of not just leaping into a solution, it seems like there'd be an opportunity there to, to, to use a three problem solving or a three thinking, are there times where you actually certain, you know, get a client or an organization to kind of pump the brakes on the technology and step back and ask those really good upper left-hand corner of the eighty-three questions of what's the background, what's the situation, making sure they've defined the problem. Can, can you kind of tell us more about that?
Lauren Hisey (23m 28s):
Yeah. So I had a client where I was a financial client that is recommended at the beginning of last year, understanding it was a call center issues. So they had high call center calls coming in and they thought that was the problem. Was they needed a for or get, or how could they get people stop calling it? Well, after we started understanding like, okay, that's great, but really what's the business problem you're trying to solve for why, why are you having this issue? Or why do you know what's the business problem? And the business problem was they just, you know, there was a lot of different ones and they didn't have enough people to staff the call center. They couldn't bring people into the live call center areas as well, because you know of the pandemic, they were doing routine cycles, but also then their customers, they didn't understand their customer demographics or understand what the customers really needed.
Lauren Hisey (24m 19s):
So just taking a step back and understanding what was the business problem and really what the business problem came down to is when they were losing their customers. So they were losing revenue because they're losing their customers, but then their costs were going up high because they didn't understand the customer. And then they were also because they were B2B and B to C, they are paying they're they're, they're paying their clients a lot of money because they were missing those calls. They're missing their KPIs, right. So people were seeing on hold for way too long. So they had to turn around and just all that money. So, and then of course, a lot of overtime costs come into that too. So by understanding what the business true business problem was, then helped us to define, okay, this is the problem.
Lauren Hisey (25m 5s):
And then we had, I think we had five problems through, oh, we had five problems in the, we had five things we worked toward to produce, right? So it was like that whole times, the reduced cost for overtime hours reduced losing the customer churn as well. And of course their employee churn. So instead of just looking at a call center process, we looked at them cause it was, it was two products doing a full product value stream map for each product and understanding the cycle of what the customers had to go through, what people had to go through internally. That helps by just understand what the business problem was. And that's part of the strategy we had to do first versus just jumping right into what the problems were.
Mark Graban (25m 50s):
I can imagine maybe there's different scenarios, let's say with a call center where people might want technology to better handle the calls. When Part of good a problem solving might be looking at well, what, what's the customer confusion? What are the customer issues that are leading to the calls? I could even think of, let's say a doctor's office, they'll embrace technology where they almost it's more effective than just message through the app than it is to try to call. So there's some technology there, but let's say, you know, patients are always are very frequent, not always, but very frequently calling with followup questions from their appointment.
Mark Graban (26m 33s):
At some point you might double back and say, well, wait a minute. It seems like there's a high percentage of people are confused with the care instructions. Could we go back and change the way we're communicating it in a way that will eliminate the need for calls for messages?
Lauren Hisey (26m 46s):
Yeah, that's exactly. That's exactly. It's the same thing. Same thing at the call center, like what was prompting? They couldn't figure out there's no predictability when these calls were coming in. And so we found the predictability actually data's there. You just had to dig. You just had to dig for it in piecemeal it together. But we were able to predict what was calling and that's what, that's the same thing with, with the doctor's office, right? You can predict, okay, why are we getting this many calls? Well, maybe that point of communication is not the best communication. Maybe that's where the customer personas kind of come back, as well as understanding that journey and then asking the questions, okay, is the technology really working?
Lauren Hisey (27m 28s):
No, it's not. Let's take that technology out of the equation first and then figure out what exactly we need to do with processes. And then you add in the technology as part of the solutions at the end.
Mark Graban (27m 40s):
It's funny that, that what you said there about, we can't predict, or we don't know, I've, I've seen people shoot down that argument, different environment, emergency rooms. And I remember seeing an ER doctor was really, you know, deep in, into lean who pointed out, you know, people would say, we can't predict actually, you know, if you look at the data, it's quite predictable, you don't know exactly how many, but you can predict it hour by hour, day by day, Well enough to then change your staffing levels in a way that better meets demand. And I remember that there's this the surgeon it's actually somebody you interviewed a long time ago, Joe Carasco, you know, he would overlay their demand pattern against that of another hospital.
Mark Graban (28m 32s):
And like the absolute peak, the number of patients might be different. But yeah, we, we, we, we fool ourselves or we convince ourselves things aren't measurable. Aren't predictable. And then sometimes it really is.
Lauren Hisey (28m 46s):
It is. And yeah, that's when I, we know that this call center, this one was interesting was that the call center itself and the other org or other organization we're working together with their data. So they were always in, this is where it's interesting when you put the two data and when you put data points together, sometimes you have to put those together instead of just isolated different data pools. And so, you know, everybody was putting fingers and I said, no, let's just take a deep dive into the data. It took, it took me a little while to do it with the help of some of their business analyst. But once we started looking at the data, like there is this unpredictable things that we could see. So these announcements would go out and depending on how the person received the announcements in naked, sometimes they were put in snail mail.
Lauren Hisey (29m 35s):
Sometimes they were in email. Sometimes it was just something that you saw on TV. So if you see, and then I was like, well, let's, let's figure and put all that together to take the, where the spikes were coming from, put the data from all the stuff is going out. And you could predict is either within hours, two weeks, depending on the mode of transport, the mode of transportation, I guess, has been ready to play it. Right. The transportation of the data going these things going out and you could predict it.
Mark Graban (30m 4s):
Yeah. Yeah. So, Lauren, I I'd like to hear more, you know, earlier you mentioned the need or the opportunity to do process mapping or value stream mapping, you know, for, for one, how would you define or distinguish between process mapping and value stream mapping?
Lauren Hisey (30m 22s):
Yeah. So I'm going to say, I'm going to steal some words from Karen Martin. I think she was, she put it in a blog and a LinkedIn post. This is probably last year or like a value stream map looks more of, it's more of a, it's like the map itself. So think of it like a Google, you're looking at Google, right? It shows you all the different systems, like the, all the interstates that are coming across, and then I want to get down into detailed and then you get down into cause that's high level that you can see what high level of what a process processes. You should be able to see data flows in there too, but it also shows you the customer journey and then cycle time and wait time and, and all that information.
Lauren Hisey (31m 4s):
But then the detailed process map is more of your directions, your directions you're right, right. Turn here, left turn here, go down two miles. Yo that's turned the corner store. Right. That's where I think detailed process map is it's usually a box out of that bias your map and that's the next layer down. So that's how I, like, I usually like to define it. So when I'm working with clients, doing the value stream map at first opens their eyes, they're like, oh, I didn't realize the customer had all this data coming at them and all those other days go in here and then they could see the numbers. But then when you get down and do it with the detailed process map, a lot of sense, they don't even realize how detailed and w and the different decision points and winning points are along the detail process as well.
Mark Graban (31m 50s):
Yeah. Yeah. I like that distinction for one, you know, like when you look at the high level, you can then understand maybe where you needed to go and take the deeper dive strategically. I think there's risk of, of getting, getting down into the weeds, or do you use different plant analogies losing the forest for the trees? I think, I think is the expression of understanding the high level first. And I would add, you know, what I've seen with process maps very, very detailed, and it kind of assumes magically that this happens, then this, then this, then maybe there's a decision point then that where a value stream maps at that higher level, help us understand the delays Between the high level steps, which can be that, that, that often shows far more potential than just trying to improve different steps, which show
Lauren Hisey (32m 43s):
Exactly. And that, and a lot of times when I'm working with my clients, they want to just go in into one specific area. And I said, well, how about we look at it more holistic and let's look at everything from an end to end perspective. And that's where like, and that's where they, sometimes they don't realize, okay, let's go tackle the finance area first or the sales area. And I said, we, we need to map out high level what this looks like first, before we even get into one certain area, because we're, sometimes they think the problem is really, isn't the right. Isn't usually the right place. Sometimes it is sometimes it isn't, but it's usually it takes the data and it's not takes the data, but it also, I think the got your gut feelings are a great to have that the data helps tell the true story of what's really going on.
Mark Graban (33m 28s):
Yeah. And I think you touched on this, the other really important thing in a value stream would include those information flows, starting from the customer. How are they communicating, understanding all of that is really important.
Lauren Hisey (33m 44s):
Yeah. It is it, the data flow and a lot of times some companies, and this is where, where it's important for, for a digital transformation is understanding those data flows for the different parts of the organization. Cause sometimes they don't realize how many different systems are involved with those different data flows as well.
Mark Graban (34m 2s):
And so, yeah. So the recap a little bit, you know, I'm thinking of a real example of driving from the Dallas area down the San Antonio, there's the high level view and the strategic decision of am I going to take I 35, which is shorter, but probably more dangerous and probably more frustrating and more variation versus taking the country scenic route that I know like best cases longer than the best case. So you make that high-level decision, then you get down into the weeds of even with that scenic route to we go through that small town or that other small town that's that's to me, the more detailed process map.
Lauren Hisey (34m 44s):
That's exactly it that's exactly it. Yeah,
Mark Graban (34m 47s):
Definitely That analogy. So, okay. Can you share some other examples where, you know, it was really beneficial to do that mapping both, both current state mapping and how that map at some point gets transformed into a future state that people have to dream up kind of observing here's the real reality current state versus let's think to what could be better.
Lauren Hisey (35m 13s):
Okay. I had a client, I had a client for their account in their accounting area where we mapped out what the current state looked like. So we started the value stream map first, and then we, and then we went into down each unit. We went down to the detailed process map for each box of the, of the value stream. And while doing that, either UN's covering, it helps with, you know, problem-solving root cause analysis buy in from the front line of workers, because you got to understand what they're doing for their day-to-day job, but then also understand that technology that they're using or lack of using, even if it's already been implemented.
Lauren Hisey (35m 54s):
And then once I do that, when we, when I work with my clients, then we do, you know, course we do a lot of problem solving and root cause analysis to gemba. You do gimbal walks, of course, at along the way, I'm training, I'm training the leaders not to sit in their offices, even if you're in a remote environment, you could still do gemba walks with your folks each week and try to understand what's going on in once we did that problem solving and understand what's going on. And then what ha what solves, what, and then doing that, the solutioning, when you do the future state, a lot of times the waiting time is taken away. A cycle time is reduced. It's just, it's a lot. So it's a simpler map I like to stay. Then it was, you know, then it was when we first started, but out of the, that's how I move into the future state.
Lauren Hisey (36m 40s):
But when we're doing the few students solutioning, I also like to say, okay, once we implement and let's say, make everything as standard as possible, how did the best data that we can use? Cause that's irritating too, when it comes to any type of technology, we have to have really good data. Otherwise it's nothing's really going to work. Right. And once we get there, what's next, what's the next steps, the future for the, for the future. So it's not just process improvement, but how do we incorporate that technology into that future state? So we have a technology roadmap that aligns with a future state. Yeah. And that's, it's usually start and it usually is starting out strategy.
Lauren Hisey (37m 21s):
What's the business problem we're trying to solve for what are the issues that we see? And that helps us determine where we need to go.
Mark Graban (37m 29s):
Yeah. And, and not to hijack the conversation or turn this into an ad for KaiNexus, but that's one technology that I'm familiar with and have been involved with for over a decade and, and kind of ex-US uses that same language, really around process people and technology. What is your improvement process or methodology? How are you engaging your people and leading them? And then what is your technology? So I'd be curious to hear your thoughts here, where somebody might, whether they to use this language or not digital transformation, where we are going to digitize or transform our suggestion box process.
Mark Graban (38m 10s):
And, you know, there are a lot of people, there are software companies that will basically create a digital version of a suggestion box, but I think we could step back and challenge like, well, are we just digitizing the suggestion box? So let's map out your process of like, well, people put things into a box once a month or once a quarter, we open the physical box and then some sort of committee management team level maybe reviews the suggestions and then rejects most of them. Like, why would you want to digitize that? Like you could then step back and say, well, maybe we need to turn our suggestion box process into more of a Kaizen process where it's more continuous.
Mark Graban (38m 50s):
It doesn't flow up to a committee or leadership who might not really understand the situation. You know, you could map out and thinking through, well, here's what we want our improvement process to be. And now let's find a technology that facilitates that I think is a much better thought processes. It leads to better results.
Lauren Hisey (39m 10s):
It sure does. It's and that's what the suggestion box and remind me of AI. Was it the office they're using a suggestion box and he hadn't looked at it in like three years.
Mark Graban (39m 22s):
Well, you mean the, the Michael Scott character and all of them, the office. I don't remember that.
Lauren Hisey (39m 28s):
Yeah. I just saw, we just, I had said, I just watched that the other day when we were at the, when we were traveling, but what's interesting is yeah. That's one thing that people are always like, oh, they won't take, they won't listen to my suggestions or they don't do anything that I say, or, you know, my manager just doesn't understand or the VP doesn't understand. So I think automating that process, and I think there's a few things it's not just automating it, but it's also keeping the leaders engaged with their frontline workers and opening that door of communication. So when they receive a suggestion or see that there is a problem, let's fix it now instead of, you know, six months down the road, I think that's part of the whole Kaizen continuous improvement culture is let's fix the issue now and having that open door communication instead of, you know, the vice president sitting behind his closed door every day.
Lauren Hisey (40m 27s):
How about you get out there and do you do gemba? And that's, I think that's really important to you when it comes to technology, because I think the frontline workers need to, they need to know how to use their technology, but they also need to know how it says, make suggestions to continually improve that technology. Cause it's, you know, it's not a one-stop shop when you implement well, we, we both know that it's not a one stop shop. Once you've done the approvement, we improved it, that it has not become your new current state. So you get to continually improve as the future state because the world is so more fluid than it's ever been. And I think, I think the CSO, we started to understand that the, the frontline workers starting to see that.
Lauren Hisey (41m 7s):
So I'm hoping as the future, as we evolve in the future, we start to see more of that fluid environment.
Mark Graban (41m 13s):
Yeah, yeah. Earlier you used the phrase technology, adoption rates, you know, I've seen it, unfortunately, you know, organizations where the adoption rate of the suggestion box is really low because people say, well, they don't listen to me is probably not worth the effort or I'm afraid I'm going to get blamed. You know, there's those factors of not just fear, but utility. Unfortunately, I've seen a lot of really nice looking huddle boards put up in organizations were thinking even of a bulletin board or a white board as a technology or thinking of some of these Kaizen approaches as a technology.
Mark Graban (41m 53s):
If the adoption rate is really low, when it's analog, like we probably shouldn't expect, like we digitize that we sh we shouldn't expect the adoption rate to be any higher really. Right.
Lauren Hisey (42m 4s):
That's correct. Right. Yeah. If you put, yeah, if you digitize something, it's not necessarily going to increase the adoption rate or improve things, and that's where automating something or implementing or digitizing a bad process is not the way to go.
Mark Graban (42m 19s):
You, you mentioned earlier the idea of doing virtual gemba walks. So I was wondering if you could tell us more about that. If you have an example, if you have thoughts on how that could or should work, let's say if somebody has got now a distributed team of remote working from home employees, how, what, what does a gemba visit or a gemba walk mean in that context?
Lauren Hisey (42m 40s):
Yeah, it, so I know there's been a lot of debate on doing these virtually versus in-person. So I've done, I've done, I've done them virtually for probably the last 12 years, different organizations. I mean, it's great to have if you could do physically, but really what it is is, is it's, it's the same, it's the same thing as doing an in-person given walk is going out there and talking to the frontline employees and understanding how are things going? That's just, I think a lot of it's just listening and a lot of times they're the ones that are going to have the solution. So how do you usually do that? There's different ways you can have, I usually say you have those teams doing those standup calls once, you know, once, once a morning or maybe three times a week, depending on how, depending on it really depends on time zones and everything.
Lauren Hisey (43m 30s):
But then also having the leaders meet one-on-one with our folks is also very important. So it's great to have the team environment and doing that. The stand-ups in different, different modes, depending what and how it works best for you. I've seen a client where we are, we did stand ups. We did three days, three times a week. We did start doing them once a week. I'm sorry, once a day. But it realized that the time zones, it was just got to, it got too crazy for the operations, the operations team to do that, to be starting at doing three times a week. And they really Monday was okay, what, what, what are you working on this week? Wednesday was Howard things going. And the Friday was really just a retrospective.
Lauren Hisey (44m 12s):
It was supposed to be fine, like, and it was no camera. I had a client that one where they did it was, they had no camera Fridays. So Fridays, you didn't have to be out dressed up if you cause they were all remote, let's just, you could work into PTs all day if you wanted. Nobody has to see it.
Mark Graban (44m 27s):
Yeah. I mean, I don't know if people are really fully dressed up With the camera on, or at least, you know, we might be wearing the dress shirt and workout shorts. I've been guilty of that, but
Lauren Hisey (44m 39s):
Yeah, I've been guilty of that. I think, I think that those types of those are just one way of doing it. And then of course the one-on-ones and then just, I, you know, meeting with the teams and having leaders meet with their teams, you know, on a regular basis. Right. So having that door communication and that, and it's really important for the leaders to understand that they, they have to, they have to initiate that with their, with their folks. And while it may seem really hard to do, especially when we're all time-crunched, it is, I think one of the most important things to do and with a gimbal walk is just listening to your employees, listening to the frontline workers, because they're the ones that are going to know what truly is going on.
Lauren Hisey (45m 24s):
And they're probably going to have an alarm like, Hey, this customer is spilling this way before it even reaches the C-suite, they're going to know. And so by doing a virtual gamble walk is just, it's really just getting out there and just meeting with them on a regular basis.
Mark Graban (45m 42s):
You, you said go and listen, I just jotted down a note there to, to, to bring up that idea. Cause a lot of times people talk about, you know, the related term to, to gemba, you might say again, she gumboots, which, you know, go and see is often how that's translated. So you could go and observe how work is being done. If you're a vice-president or a leader, you could observe a virtual huddle meeting, you could observe and you, and you can listen to the conversations people are having about improvement. So, you know, maybe, you know, just generally speaking, going understand
Lauren Hisey (46m 19s):
Mark Graban (46m 20s):
Be a useful concept where I could think there might be a trap where somebody has got a dashboard executives, love dashboards, right? So I could see at my desk, I can see the number of improvement, ideas being implemented every week or every day, and kind of drill down by departments or areas. Well, you could see the data, but then if you see some Oregon, some departments are underperforming others, the data doesn't tell you why.
Lauren Hisey (46m 46s):
Mark Graban (46m 49s):
Like my, my, my coauthor from the healthcare Kaizen books, Joe Schwartz is used real examples where you could see, let's say a department or a team had been performing really high on Kaizen. And then this is a big drop-off. That's good to know, but the chart doesn't tell you why. So these, these, what do you call it? You know, a virtual gemba visit or a phone call or a zoom call, like going to, to better understand the situation, to grasp the situation instead of making guesses or making assumptions, or just getting upset about the result. Like we've got to understand what's going on in the process or the team or the system that leads to the result.
Lauren Hisey (47m 30s):
Exactly, exactly. I think so. I think the two go hand in hand say, so you could see the data and you know what, if you're out there having those, those, those, get those, give a walks all the time and unders and understanding you understand that what truly is going on. And a lot of times it's not, I think sometimes people want to play blame the people, but it really is the process or the it's usually the process. And then the technology then the people, right? So people only follow what they are being are being told to pretty much hold it not being pulled, but the process that they're supposed to be using. And if there's an issue with that, then you can easily remedy that when you do those gemba walks and having that continuous improvement culture that also allows for learning and allows for the exit, the big communication and teamwork.
Lauren Hisey (48m 19s):
I think it's collaboration. It's not just, you know, here, go do this. It's understanding, really understanding, truly understanding people.
Mark Graban (48m 27s):
Yeah. So we're trying to understand the current state or understanding. We're trying to better understand what's happening on one thing you talk about is process mining. How is that different than process mapping or gemba visits to go and understand what, what do you mean by process mining?
Lauren Hisey (48m 44s):
I says, mining is a tool is a, is, is a technology tool. So back in the day, we would have to sit there with a type, with a stopwatch, right. And do cycle time. Well, you know, now that things are more, we have more technology, more in the, we have a lot of service based stuff going on. You don't necessarily have to do there at the stopwatch. You have these process mining tools out there. I think apple Moore's. One of them is one of it's a good one to name off It's called Atma more So will they. So basically what that does is it goes in and look, it takes the data out of the system and it tries to map out the processes at best can.
Lauren Hisey (49m 26s):
It it's automatically done. There's there's not a lot of human intervention. Once you set it up, I'm going, it just looks at the different transactions. I think it, it really helps it. So I think that's just a piece of that. It's just the piece of the pie or the piece of the puzzle, right. When you're doing your current state, I think it just speeds up the data analysis a lot faster. And then I like to use that with, with doing the process mapping. So looking at the future, I'm sorry. Looking at the value stream map, current state and a detailed process map, and it helps plug those two, those two together help plug help create a more holistic end to end map.
Lauren Hisey (50m 7s):
I mean, the process mining, like I said is just all tool-based, but it doesn't look at the people's feelings. It doesn't look at what are the true costs. Is it just kind of paints, it starts to paint that picture for you. And it just does it a lot faster than if we had to sit there and stopwatch.
Mark Graban (50m 23s):
Yeah. Final question for a Lauren. You know, it's talking about putting two things together. I was wondering if you know, of a good example or even a scenario of what would be a really powerful combination of both lean transformation and digital transformation.
Lauren Hisey (50m 44s):
Good combination. That is so that I do that all I'm going to say. I try to do that all the time with my clients. So usually when I'm with my client, they've been frustrated a lot of times we usually start with, usually we start in the easiest area first and I'm going to say that's an, we should put the digital transformation into an area first. So finance and accounting, or even the quote to cash sales areas or some of the easier areas to start first. And that's where we put in. If you can put the transformation, the transformation of lean and digital transformation together, you're creating a kind of a continuous improvement culture, right? Or lean culture includes technologies.
Lauren Hisey (51m 27s):
Once you start with those areas, it bend it and you have really successful in those, those first few areas. Then the rest of the company or organizations are going to want to do the same thing. So I think that's part, that's the best way that I approach that and put those two together is start in one area that's easy. And then when we have the more complex areas, as, as we go along on that journey,
Mark Graban (51m 49s):
It seems like a different dimension to decide where to start, could be sure what's easiest. Where is there agreement or alignment or pull from the leaders versus what do we think is the highest impact on the organization? I mean, it saying in my experience, there's something to be said for starting small proof of concept to then help build up the energy or the courage to tackle something bigger and or more meaningful.
Lauren Hisey (52m 14s):
Exactly. That's usually how we do that's the best way to do it is to start there and then get it out there. Sometimes I know people want to go, our operations is all crazy. Okay. Oh, well, operations is, is, is not, is, is a bunch of areas. So let's pick one area of operations and start there. And that's where a lot of times when it comes to strategy and our standing, what the business problems are first and under and getting everybody in the same, on the same terms in the same boat of understanding who we're going to start here, we want to get here, but we have to take those incremental steps to get there.
Mark Graban (52m 49s):
And then maybe a final, final question. I'm a guilty of doing this. Sometimes post prerogative. I don't have to say final question until I really made it. Is it fair to say that know you mentioned continuous improvement. So with lean, we may have step function, improvements or redesigns. We may have a lot of continuous improvement. Even with that process redesigned, we can then continue to improve. It sounds like digital transformation maybe is more inherently a big leap. So am I wrong in that assumption? Or can we also layer continuous improvement on top of technology?
Lauren Hisey (53m 26s):
You can't. Yeah, I see layered on top of, so I think it's continuous improvement and then you're laying on the digital there, the technology or digital transformation on top of that. It's not, I don't, I, I, I, I truly feel that you can't have one. You can't just have one without the other, because it really does help with a strategy in it. I think it continues to permit really does a really good job of connecting people, process and technology together. I think you need all three in order to have a successful business and have happier customers too. So that's our thing. If your, if your employees are happy, usually your customers are gonna be happy to.
Mark Graban (54m 5s):
Yeah. And I think w we view these things in threes, like, you know, it says in your bio simpler, faster, better People, process and technology. And then the other trilogy that I really like is in whatever order it's good for the employees. It's good for the customers. It's good for the organization. Another powerful trilogy,
Lauren Hisey (54m 31s):
Very much so.
Mark Graban (54m 33s):
And I'm hungry. And I'm thinking now of only if you know the term Texas trilogy,
Lauren Hisey (54m 38s):
Mark Graban (54m 38s):
Texas, Texas Trinity is actually so in barbecue circles, brisket, sausage and ribs, Texas, Trinity, Sorry to take the food detour. I need to go, go eat something. But Lauren Hisey has been our guest today. Her, her firm, as Lauren Hisey consulting, you can find her website at LaurenHiseyconsulting.com. I'll make sure that there's a link in the show notes. If you want to learn more about Lauren and the work she does and the help that she can give your organization. So, so Lauren, thank you for, you know, introducing some new terminology. Thanks for your patience with me, butchering robotic process automation.
Mark Graban (55m 24s):
So you helped me. You help me learn something. I know you helped the audience. I think connect some dots between familiar concepts, new technologies. Thank you for working through that with us again today.
Lauren Hisey (55m 34s):
Thanks for having me.
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