Session Information:

Eliminating the Gap Between Process and Business. Technically Tie Process Improvements to Business Outcomes

Digital Transformation has taken the financial services industry by storm.  The rise of digital native challenger banks, direct consumer access to markets, and peer-to-peer platforms have created more ways than ever to borrow, save, and grow capital, resulting in heightened customer expectations and market saturation.   Organizations are spending billions on enterprise software and investing in employees that will take their business to the next level.  

Departments for processes excellence, operational excellence, and digital transformation are commanding more and more attention from executive leadership.  And yet, there seems to be a gap between how processes are assumed to operate, how they actually operate, and what effect they are having on an organization's business outcomes.  In this session, learn how to move the needle with your process investments by technically linking them to business outcomes, and bringing them straight to the doorstep of LOB personnel.

Key Takeaways

• Get grounded - Your IT systems and employee interactions have all the information you need to objectively show how your processes are operating in real time.
• Sense the friction - identify bottlenecks, unwanted variations, and extraneous manual work and make sure that you can intercept them as they occur
• Take decisive action - automate where possible, otherwise bring next-best actions with context to line of business personnel

All about the outcomes - make sure that the process improvements have a direct and measurable correlation to the overall company objectives 

Session Transcript:

Tied process outcomes to business outcomes, and I'm very excited to have Max Smith with us here. Max has been focusing on understanding customer pains, their causes and solutions for his entire career before joining the product team a salon is. He's spent four years as a product manager for a KYC software company helping financial services institutions remain compliant with regulations. Today as a product marketer for Salone, as he continues to investigate the challenges that face financial services in 20 20 and bring that insight to the greater product team to help develop solutions to overcome those very unique challenges.

Max, really grateful to have you with us today and sharing your expertise on this very important topic.

Thank you so much for having me here. Happy to be here. If, you know, I'm really excited to be a part of the show, and I'm happy to share what I've learned over time, and hopefully everybody can, can get something good out of this to take back with them.

So without further ado, I think I'm going to kick off the presentation.

And just just checking, everybody can see the screen, right?

Looks good.

Perfect, OK, awesome. So today we're going to talk a little bit about our process excellence in banking, and specifically how process excellence leads to better business outcomes. And some of the best practices and methodologies that we can use to ensure that things that we're doing to improve our processes, specifically in banking, are ultimately leading to those business outcomes.

So like Josie said, I'm Max Smith, I'm a global product manager, product marketing manager here at slowness. In my past life I was a product manager. And, you know, my favorite part of my day is interacting with prospects and customers and partners and industry experts and really understanding what's going on what challenges and pains people are facing in their day to day, and then understanding how best we might be able to address those pains.

So I'm very happy to be here and share some of that insight that I've gathered, and also the insight that, you know, Solar's has gathered over time.

Jumping right into the agenda. So, first, we're going to start off with a little bit of background, current state of affairs, and banking, specifically from the digital transformation side, that kind of background. Then, we're gonna get into some of the challenges that we see, and that's particularly around the process friction. What things are slowing down processes within businesses that are leading to these challenges that are causing us, not to achieve the outcomes that we want to see. Then, we're going to talk a little bit about the methodology that's the lowness users, to understand these problems and react to them, and really improve the business in a meaningful way, and, again, that's really a discussion about the methodology itself, not really discussion about technology at that point.

And then, last, we're going to talk about a customer success story with a Bank that implemented this methodology and talk about some of the results that they were able to achieve and get a little bit of insight into how they were able to do that Finally, ending up with a little bit of Q&A, so go ahead, I'm kicking it off here.

So, one of the trends that we've seen, particularly in the last decade, is that companies are spending billions on digitizing processes within enterprise software. I mean, they're spending a, an incredible amount, and bringing in new technology to help this digitization, digitalization, moment movement, and we see this quote from Gartner here, where digitalization is rapidly changing, how organizations create value and how they compete. And the idea of bringing in technology is not necessarily new. If we look at this timeline on the bottom, we can see that, over time, We've, we've adapted technology solutions, you know, things aren't done on pen and paper anymore, and even though sometimes systems can be outdated, and it definitely, there are legacy systems. It's still exist and operate in a lot of financial institutions. There is this this, this trend where we have been investing in technology.

But I think now more than ever, we've really got into a point where we're kind of at this critical mass, this critical threshold of what that really means and really embodying the idea of using data to run to run businesses.

I mean, I think one of the, one of the reasons for this is that there's all these new challenger financial institutions, and you know, we hear words like disruption being thrown around and things like digital native.

and I want to take a second to just pick that apart and understand, like, why that's important. So I think again, this move to Cloud, which has really only been embraced and maybe the last 10 years. And particularly in financial services because it's so regulated like privacy is of the utmost importance, unlike some other industries. But it is starting to be embraced, particularly over the last decade.

But the reason that these challenger banks are popping up is, it's about the customer experience at the end of the day.

I think that, that's, people are realizing that you're win, or lose on the customer experience, and these companies aren't going digital native just for technology sake, right? Or just, for transformation, say, it's really about the business outcomes at the end of the day, and I think the critical one, in this case, is really the customer experience. You know, a little personal anecdote here. So I'm refinancing on my house. You know, a lot of people are doing that right now, because of the record was. Because a coven and I went with a new fintech company. They've only been in the business for four years. Everything was automated. It was super easy to go online, upload the documentation I needed. My people reaching out to me at exactly the right time, telling me what they needed. So the entire process was seamless. And when I went for my original mortgage, was actually like an older local bank and it was a lot of pen and paper, and their hours for weird. It wasn't 24 7. I had to either have a bank account with them to pay for my mortgage or Handoff. I check in person.

So, like, know, Again, it's not technology for technology sake, it's really about the customer experience that people are focusing on and that's why all of this money is being spent on digitizing these organizations.

Just, you know, there's some statistics here. They, again, coming from Garner that the average company has 508 enterprise applications, which is a crazy amount. Maybe too much. Depending, if you have some redundancy there, there's a $431 billion total spend on enterprise software. And two out of three CEOs are saying the digital strategy is a top priority. So the good news is, for the Transformation Office, we had the attention. There is definitely money and effort being directed at this cause. And I think, now more than ever, you know, I hate to say this, because of what what's Happening with coven, but Efficiency is so key. Now, you really need to make these processes fluid and make sure that there isn't a lot of ways. And so I think it's forcing the issue even more than we're seeing here.

But the challenge that we're seeing is that those processes still aren't delivering the expected results. And I mean, this also is not something particularly new. This has been the case, I thinks it, since we've had technology entering the scene, the Gartner says, the digital transformation projects are over budget and behind schedule.

And I think if you look at some of the KPIs, the world's best run companies, you can see this. And these are all, again, related to that customer experience, being a driving factor, but it takes 20 days on average for customer onboarding. The Net Promoter Score is 25, which, for those of you that aren't familiar, it's loosely it measure customer satisfaction autoscale -100 to 100. So, that's, you know, there's still a lot of potential there. And only 668% of customers actually come back for more for additional product or service. So, these are, and this is in the world's best run companies, so these numbers can obviously be improved. And if it's not, one of the world's best run companies, you know, they could potentially, even be a little bit lower.

So, there's this gap right here, right, We're spending all this money, on Enterprise, Software and digitalization, but we're not seeing the results that we expect in the in our in our outcomes and in this case, particularly customer experience.

And so, what's impacting those metrics, right? So, we talked a little bit about the technology, we talked a little bit about the outcomes. But what are the processes that underpin those outcomes? And they're all across the banking value chain. We see for service centers, basically here, four centers of operation, governance, risk compliance, customer operations, and finance and administration.

And you can see that within each of those different sections, there's so many different processes that go into making the financial services institution operate smoothly, and so many different KPIs that we're measuring, and tracking, or should be measuring and tracking to understand how we're performing.

So, it's not a And this adds some complexity, right? Because it's not a one stop shop, It's not just one application that we need to be worrying about. If you want to deliver truly a better customer experience, you can see that there's a ton of different processes involved. Anything from bringing them on as the lead for, when they're handling an application to, When you're onboarding them, to, managing a portfolio. So, the customer, service, there's all these different touch points, right, that we need to master. So this is the, when we're talking about processes, this is really what we're thinking of, to ground the conversation.

And if we look at some of those processes and in this case, we're looking at just credit application and KYC as an as an example, we can see that where some of that friction comes from.

And some of that comes from all of these disjoint applications and technologies that we have within the company. You know, various different systems that are being used. In addition to, like, IT systems, you know, legacy systems. or, like a ServiceNow, or even like Workday, you know, Blue Prism, you have some automation solutions. In addition to that, there's also all of the desktop tools that are being used, so things like Excel, an e-mail when people are taking notes. So, those are all part of these processes as, well. It's, it's, it's not entirely digital.

But, between those two things, between the actions that people are taking, on their desktop, and the actions that are happening in these core banking systems, in these onboarding systems, and these other source systems are legacy systems.

We do have an IT footprint. We have a trail of exactly what's happening.

So we can see exactly, We realized. So we see, you know, start an outcomes here. Like, for instance, in credit application, the application is created. And the ultimate detriment is that there's some leakage there. And, you know, it gets lost, maybe gets lost with a credit check or something like that. And by the time you figure it out, the customer has already gone somewhere else. Or with the KYC process is initiated and you eventually get it done. But it takes too much time, right, and it violates your SLAs.

The beauty of having all this information is we can tell what went wrong. I mean, the challenge here is that it is fragmented, and it is complex. But the beauty is that there's this IT footprint, We can see exactly what's happening in this, in these systems. We can see how long it's doing to take specific activities. We can see the root causes that are causing these ultimate outcomes to happen.

And so, that's one of the benefits of having all of this information. And sometimes these processes are intermingled right? in this. In this case, for credit application. KYC is also a part of that credit application process, so sometimes they're disjointed, And that can be handled separately, And sometimes they're together, and they can have a knock on effect in other parts of the business.

And I think the way that you know that you have friction within your business is if you experience, if you are experiencing any of these symptoms. And the first one is, if you don't know how your processes really run, if you don't have insight.

So, I think everybody is probably familiar, at some point in their career, particularly if you're in the transformation office, You have this experience where you're sitting down, maybe you hire some consultants, maybe you try it internally first. But you get a bunch of people in the room, and you say, OK, how does this actually work? What are people actually doing? And if you ask to, people, you're gonna get five different opinions, right? You might do some white boarding exercises, put some sticky notes up on a board. But the reality is that oftentimes, people don't have the full story. Or they have a through no fault of their own, a biased understanding of how that process is really functioning. So, what you need is to be able to see how this process is really run and the road. And to do that, you need to be able to pull that information from the source systems, and like that activity that the different employees are going through in order to paint an objective picture.

So, that's the first. And another one is you don't know where the friction is, and you don't know what the root causes are. So, all you see is these outcomes, you know, that you have low MPs. You know that you have a long onboarding time. It's not at your target and what's not at your benchmark, but you don't know what the real friction is. Maybe you have some ideas, but you don't know for sure. And there might be things that even if you think you know that you're dead, you're not aware of, that can still be uncovered. You know, hidden issues, if you will.

And, then the last one is, if you don't have the means to fix the friction. So, let's say you do understand the processes run. You do understand what the specific challenges are. You can objectively prove both of those things, but then, you still don't have a means to fix it. And, I think that this is, you, know, I, automation is a big one here as a means to fix some of this friction, but there's also some process re-engineering if you will. That in some cases, needs to take place in order to make this happen. But, in some cases, if you don't have the means to fix it, you know, That's another symptom of this, of this greater issue.

So, the way the Lowness views this from a method methodology standpoint, it's methodologies standpoint, is there's really 3 P 3 key pieces to understanding and improving those processes in a way specifically that approves of business outcomes. And the first pieces, knowing, again, that's really just understanding how your processes really run objectively, all the information from your source systems. All the information that people are sending e-mails and using Excel or whatever they're doing on their desktops. Getting all of that information.

And then doing a little bit of analysis to understand, OK, what are the actual pain points, right? And not only what are the pain points, but which pain points are the most important? It's important to prioritize. It's important to know which of these are going to really move the needle.

And I think, once you, once you have that understanding what you've done that analysis, and really painted that objective picture for yourself, the next thing is, you need to be able to sense that in real time. So if you know what's going on, but you can't intercept these problems, If you can't stop this friction as soon as it happens, then, you know, it only goes so far. Like, you need to be able to actually do something once you have that insight. So, sensing it is really important, right?

To understand, there's something that's happening in my process, right? Like, there's something, with this particular credit application, maybe it's missing some information, maybe it's coming from an area that we are working with a specific credit provider, that we know we've had challenges within the patch, right? It's saying we have certain information about this point in the process. We know that friction is going to occur, we've identified what the root cause of that specific friction is, and then be able to to come up basically with a solution for it.

And so I think, no, that's it. That's a really key point is, again, once you know something, you need to be able to do something with that knowledge.

And then the third piece is actually taking that action. And that usually comes in two forms. There's of course automation, but there's also bringing in people when, When, it makes sense.

You always you're always, always, always going to need people to make some sort of decisions, and I don't think that we're talking about No, I don't think we're talking about ordering automating away. jobs we're talking about automating away like remedial tasks and things that just very clearly should be automated very clear manual action. So that the employees and the associates can actually use their time for some higher level activities that make more sense to get more value add for the business.

And so those are kind of the three pieces. The methodology, I'm going to jump into this a little bit further.

So, the first piece, knowing how your systems, or how your processes really run across all the source systems, I think that some key things that you want to look out for when you're trying to understand how to do this are, you need real-time data collection. These processes are happening in real time.

You know, it's, it's not at the end of every day you have to get the what happened that day when?

For instance again when I in my mortgage store when I was, or just applying for my refinance, I uploaded some documents and 30 minutes later I was getting a response from the team saying thanks for uploading these documents. You know there's nothing else you need to you need to do right now know, that kind of reaction and that kind of customer experience can only happen if this is happening in real time. So, I think, no matter how you go about understanding how these processes run, right, no matter what kind of technology you're using to do this, you do need to make sure, I think it's very important that we do it in real time.

You also need to be able to visualize it, because that's the core of the analysis. You need to understand how those processes are running in real time to identify, again, what activities are problematic? What steps in the process are causing the most, the most pain?

And then, you need to be able to drill down in specific cases and understand, why didn't this work? Because only once you had that analysis, can you actually do something about it.

And I think that an important piece of this is really understanding the variation. So I think a lot of people are surprised.

Again, you have a standard. You know, you look at something like credit application, and on the surface, it's really not that complicated process. You know, somebody fills out a form day, they say how much they want to, they want to borrow. It comes in and you need to do a couple of checks to make sure that the person that you want to be doing business with. You need to make sure that the credit worthy, and it needs to go through the proper approvals, but really, that's not too complicated of a process. But when you, when you peel back the onion and you look a little bit deeper, you might start realizing that you're asking them for additional documentation that maybe you don't need. Or maybe they already provided the document that had information that you could have used.

Or, you know, something is getting stuck at a certain point, where maybe it's going through two approvals, and it only needed to go through one. So these things that you wouldn't expect to be challenges, because it's, it's not really something that makes sense. You'll start to see, when you look at all these different process variations.

The next piece is sensing.

So this is, again, sensing once, once you have an understanding of what those pains and challenges are, you need to be able to identify them as they come in. And then do that root cause analysis in an automated way, to understand, what are we going to do with this specific, in this case, application, right?

And we need to make sure that we are understanding which applications are going to most impact our outcomes.

So for something like a credit application, right? They're not all created equal. No, maybe if there's a particularly credit work, creditworthy individual that wants to borrow a large sum, this is something that you shouldn't necessarily get held up at. Any of these may be different process checkpoints that we see, and so we want to make sure that for those high priority applications, that we're treating them with the diligence. So they deserve And the expediency that?

They deserve I mean, I think some of the things that you wanna look for as part of this step is you want to be able to do that automated root cause analysis.

So, if you have to figure out for yourself, what's causing this application to go through slowly each time, well, now, it's just the tedious amount of work, You've almost duplicated the work for the applications. So you need to be able to understand in some sort of automated capacity, some sort of, you know, checklist, or something.

You know, some sort of system check or some sort of machine learning prediction model, that's something that's becoming more and more popular, particularly over the last I'd say five years, This has really gained a lot of traction to understand why this particular friction is occurring. And then, I think the last thing is you need to be able to package that business logic across all the systems, and you need to be able to also access home-grown systems. So particularly in banking, I'd say more so than any other industry that I've had experience in dealing with, there are a lot of legacy systems, home-grown systems. There's not a lot of off the shelf products, like you would see in a lot of other industries. So you need to be able to make sure that when you're doing this fencing, that you can do it with these systems that aren't exactly, you know, standard for lack of a better word.

Then, the last piece is action. And I think action with intelligent automation, and I think intelligent is the key word there, is important.

So again, you need to be doing taking action based on the outcomes and making sure that you're prioritizing appropriately for those tedious, menial manual work, things like just taking an application at a certain point, and handing it to the next person. That's something that could easily be automated. Or reaching out, and asking for some documents when they're missing. That's also something that could be an automated. Right. Making sure that, that the people that are involved in the process, are asking real questions in interacting with the customers in a meaningful way, right? Because that's more, that's a big part of the customer experience. But automating away and that tedious manual work.

And also that, um, part of this intelligent automation is making sure that the next, that there is a set of next best actions, that are also prioritized for decisions, and tasks that need to be made by an individual. That can't be automated away.

And I think that bringing this back to the title of the session, I think that this is a key piece because I think, And actually, I, I'm gonna go to the next slide to make this point, going back to this overall methodologies, and No *** Act, I think that the way that you tie the process improvements to the business outcomes is by having both this analytical and operational piece. In this case, it's kinda know an act. That's bridged by the sensing piece. Because what you need to be able to do is to either make sure that once you have this insight about the process, then either you can automate away the problem in some way. Or that you can bring the problem to the line of business. People, in a way that makes sense, That has all the context that it needs, that they need to make that decision and surface those options for those people. Because I think one of the challenges is that the transformation office, at least, that I've seen, is in working with Wanda business leaders.

It's always a matter of, no.

Yes, You want a business.

And this is not everywhere, but, but something that I have seen is that the line of business leaders agree with the transformation office and say, yes, we absolutely need to improve this, but we just don't have the time to take a step back and like, change the way we're doing this. You know, we're in go mode where there's no way that we can. So it's not that we don't want to change that simply, We just can't, we don't have the energy.

And so I think one of the key ways to actually move the needle is to bring the actions directly to the line of business teams and say, this is what we think you should do. This is, this is, this is why we think you should take this action, and so there's really no, it's not like for them. It's not like changing their day to day. It's not saying you need to necessarily wellness new piece of technology, or you need to do fundamentally different work in your day to day, It's just saying, Hey, we understand that. There's a list of things that you could be doing here. Are the things that are going to help the business, that are going to line up with your line of business targets in the most intelligent way. Here's all the information, you need to make the decisions. And here's what, we know, that, this is what's most important. And I think really just bringing that to the doorstep of the business is the key piece in, in moving forward, in, making it, making really impactful and successful change.

And so I'd like to, I think, with the, with the rest of my time here, talk about a customer story, that, they did just this. So CJD, they did, we, were working with them for a credit recovery process, and also credit granting. But I'm going to focus on credit recovery specifically.

And I think the quote from Joachim Here, was says it all He's saying that those recover agents that were using Selina started recovering and 70% less time than others.

And I think that the root, first of all, let's just think about that.

So you have credit that you're trying to recover for the bank, obviously. The more credit that you can recover. The more quickly, the more cash at the bank has on hand then to re-invest. So the business outcome here is pretty clear for credit recovery, It's, you know, get more money in house To say that you're able to get that money at how 70% faster or put another way that is, or, sorry, 70 and 70% less time put another way.

That's 3.5 times as quickly is a phenomenal business outcome, right in the way that they were able to do this is they really embodied this no sense act approach where, at first, they had, you know, the credit managers or the credit recovery managers had a good understanding, I guess Overall of how they're they're like what the, what the outstanding credit was, How burden their their Agents' work, but they didn't really understand the process and what was preventing that number from going up?

You know, like, again, really moving the needle? And for the agents, the analysts to work every day, They have a portfolio that they manage. But there wasn't any real prioritization as to how they were. They were going about the day to day. And, I mean, there definitely was, it wasn't like they were shooting in the dark, but it wasn't, I guess, based in the data of the process.

And so, it started off as a process by knowing, with just a couple of dashboards that they had built out, allowing them to understand kind of what the current outstanding activity was, and then transition to getting some recommended next best actions for specific steps to take during the credit recovery process that would lead to faster credit recovery.

And then it went to getting daily notifications in real time of activities that would impact the process. So, you know, someone just opened an account, but they're there, they have outstanding credit. So that's something that you want to investigate, or someone new has been added to your portfolio. So you need to start doing a deep dive dossier process for that for that individual.

And so it was, And this was a good lesson and agility and I know that there's a lot of people from the transformation office on the webinar lessening in. So, I think that they one of the best practices that they went through, which was a real lesson. And agility, you know.

They were able to basically get 200 people on board with this, new, this new way of or this enhanced way of working rather in three months, which is pretty quick, I'd say for any sort of change management three months is super quick, especially for 200 people. But what they did was they started out with a minimum viable product and kept the communication channels open. They started off with just the dashboard, you know, something really easy.

that could give them some information that they didn't have. They wouldn't have to go into their CRM every day and run a report. You know, it was just right there for them in the Dashboard. And they said, what else can we do? And then the business was like, well, this dashboard is great, but I don't exactly know what I need to do. Next, Like, you know, this is a good overview. But like, it's not very prescriptive, say, went back to the drawing board and said, OK, here's some prescriptive actions that you can take. And here's the prioritization. And here's why. And, you know, a lot of it was based around, if you don't do this, you're gonna violate the SLA. Or this is a particularly important account that you need to be focusing on, or something like that.

And I said, OK, well, this is, this action is great, but It's, it's not, it's not like up to the minute. So they went back to the drawing board and said, OK, as soon as we get some new information, as soon as information comes in, about someone opening up a new account, or you're getting a new account attitude or your portfolio, you're going to immediately be notified about that. And so just gradually over time, they took these users. They rolled it out to a bunch of users and interviewed the best performers and the people that weren't using it to get a good idea as to what people were enjoying, what people work with this new process and kept that communication channel open.

And, I think, just, again, understanding what you need to do and taking that next facts action. Bringing that to the doorstep of the credit recovery agents was really all of the difference here. It wasn't just knowing that these were particular pains, that this part this part of the credit recovery process was slower. It was identifying, and then, taking action on that in a way that could really move the needle here.

And again, you know, 3.5 times faster money coming back in the door, that's a huge, that's a huge number. 12% improved SLA adherence. Again, a huge change, and that's it. That's only after three months, I mean, that's only with 200 of their, of their agents.

So, I think that this is just like a, again, a really good story. A really good embodiment of the of this methodology of these principles for how to, for how to move the needle. for how to tau the technically tie, process changes, understanding what those process changes are, and then bringing that to the business to meaningfully impact business outcomes.

So, I think the last thing I'll say is just, I know we're about to jump into Q&A, but just everybody, thanks for listening. You know, don't go away again. We're about to go on QA, but thank you so much for listening, I know that, you know, everybody takes a lot of time and everybody's busy here. So I appreciate you having a chance to listen in, and I'd love to further the conversation. You know, we're going to jump into Q&A right now. But if there's any other questions you have, I'd be, I'd be happy to answer those offline as well. I, Again, I love talking to the industry to understand more. What's going on. So, thanks again for your time.

Terrific Max. So thank you for your presentation and we had the questions coming in during, during, during, during that, and I'm going to release some of those to you now. First one, comes from friend. Direct me, I think the ... is, if I remember correctly, is in Michigan, and Friend asks, is it really more of a personal question to you? What is the any specific training to learn how to improve operational processes, Tell us a little bit about your own personal experience, and any training that you have received on improving operational processes.

Yeah.

So I think, um, I won't go so far as to, I guess, recommend a specific course or a specific program. There's lots of organizations out there that do this, and I'm not here to say that one is any better than the others, but I will break it down into two pieces. I would say that there is more of a technical process improvement training, right? Where you understand from a system level, what the inefficiencies are, how to improve them, how to measure them, what system changes you need to make. And, I think, you know, there's plenty of tools out there to assist in that. You know, like, process, mining tools, or BI tools, or things like that, right? That help you understand, from a technical level, what's going on. And, make data driven decisions on how to improve the process. So, there's, that's one area. And then the other area is really the, the social project, management change management area, right, which is no.

And this happens at a couple of different levels, but it could be a training on how do you align if you're a leader, for instance, how do you align the incentive models in the company to match what you're actually trying to get out, right? Make sure that people are incentivized to be acting in a way that will actually change the process in a meaningful way, that will then change the business outcomes. So, I think it's because change management is difficult, right.

And I think that, that's kind of, one of the, one of the points of the presentation that I'm trying to make is, change management is definitely an important, it's super important piece, that you wind up the process teams with the line of business teams. And, I think part of that, you can do through technology. And through the methods that I described, but part of it is that social change. And so, there's plenty of best practice organizations out there for how to implement change management.

So, those are good.

Very good, very, that's, those are good insights, and that Max Antonio, were keizer, asks about, excuse me, to what extent and what you presented. The root cause analysis process is really automated. And you want, he asks you to elaborate a bit about the role of subject matter experts in the art and the root cause analysis process in order to find the true root cause. And the, and the how much of that is automated, How much of it is just through, you know, dialog and interactions.

Yep. And so, I think that the answer is, it depends, And I know that's not the answer you want, so I'll try to add some clarity here as to what it depends exactly means. But, I think it depends on what the technical maturity of the company is. Do you have the kind of software in place that can do that can assist in this analysis, right? Do you have machine learning models that can do accurate predictions and accurate analysis into what the root causes? Do you have some sort of knowledge, management solution that will let you understand which things impact which outcomes, right? And I think that, so that's one piece of it, right? And the more technically mature you are.

And, of course, you need to have the business that actually understands the value of those, and how they're used, right? Like meaningful technical maturity, then it can be legitimately can be more automated. And that's something that we've seen. That's something that we've helped customers know ourselves get out there and deploy. But then there are Of course, the role of the subject matter expert is going to go away. I guess I should have started with that, right? Like, subject matter expert needs to be there. They will have the insights.

They are going to, you know, even if you have one of these models, they're going to make the base set of assumptions for how to, how to set this up and really do the analysis.

So, I think, in some cases, it is more of a in that no step, right? Where you're doing the analysis. You're doing the process visualization. You're trying to understand the root cause. That can be a very manual and I say very manual.

But I mean, again, it's, it's visualized, it's easier. There's plenty of good technology out there that does this, nowadays.

The, it could be manual analysis, that then they take back and take specific actions, but it also could be automated where we say, you know, there's technology and says, we see this process. We understand it. We've been here before. We know that for this specific outcomes these are the root causes to look for and it's, you know, go go down.

Very good. Victorious Sabbath is asking about the interactions that you have maybe, even from your perspective as a provider but also for our clients from perspectives. The role of Lean and six Sigma on some of these deployments, you interact with, with folks who are Lean six Sigma practitioners and the companies that have that, that, the methodologies in place and how you interact with companies like that.

Yeah, absolutely. Absolutely. It's a great, actually. All three questions have been great, but this is also a great question. So, absolutely. I think that speaking from a slowness standpoint, for no, less specifically, we do deal with anybody on the transformation office side. So, Head of Transformation, and anybody in process excellence, anybody inline, Lean six, Sigma, any Center of Excellence, any process mastery, like any, any any sort of department like that, For sure. And I think that those are the people, really, that are doing this analysis, right?

There's this, this methodology is we're focusing on those people, right? Because oftentimes, we see the challenges with the Lean six Sigma people, these black belts.

Well, we know we've we've understood what's wrong with the process like, we figured it out. We know what the deviation is, like we can measure this very specifically, but now what do we do that with us? How do we, how do we convince the business, so that's part of what I was trying to articulate in the track is?

Yes, Like, yes, we'd get with those people, but like, you need to be able to take that insight and go back to the business, and we also work with line of business.

And I would say, the best operations that I've seen personally, both S one S and elsewhere, is when those two teams really do work together. And that can come in a variety of different forms. You know, we could, that interaction we can talk about, for, you know, another hour, but so we won't go there, but.

Yes, absolutely. You know, Antonio, or keys a follow-up on his question of a commentary on the quote on the answer, that you provided, that, his comment is, that machine learning models, typically give us correlation, but not causation, and the human element is still key to determine that, the real root cause. And the, and I assume, you know, you're highly aware of this, and then, then the, and that's why it's so important to get the subject matter experts working with the technology. And specifically, machine learning. To really understand if those correlations that come up are, are are happenstance, or if there are true causal effects that that's happening in the process, right.

Yes. And I think it's a great call out. And I, absolutely, Again, the role of a subject matter expert will never go away. I'm 100% confident of that.

And I think it is true that your machine learning model is only good, is the assumptions that are underpinning it. And so, I think that you do need to start off with a set of, like, known causes that you've identified are real root causes, perhaps during that. That no step that I'm talking about the methodology, where you've said, you know, we see in our process that we're requesting additional documents all the time, right? So this is clearly a point of friction.

This is clearly something we wanna look out for, and we know that if we're requesting additional documents, on average, it takes three days. And so, if we have an SLA and it gets pushed out by three days now, this is like, I'm sure to Antonio the. This is a gross oversimplification of the machine learning model. And I agree with you. This is more just business rules, but, you know, taken at the scale of the model, you're right. You you do need to have some knowledge underpinning it. And when it comes out, you should still validate it and check it for accuracy on an ongoing basis. But by and large, you are going to get an improvement, even if it is only a correlation at that point.

A known correlation, right? Like, like something that you've identified as a potential actual root cause for this, for this particular challenge?

Very well. Tell us a little bit about the technologies behind the methodology.

You have no sense, and you know, Sense, Act, methodology, and the curious about the technology behind it. You talked about, of course, machine learning. There's an implicit RPA kind of been through it as you talk about some solutions and the uneven the process of mining, and the end there seems to be a basic technological architecture behind what you do if you can talk a little bit more about that.

Yeah, absolutely. I think that this is a good question, and because we're a technology provider, I tried to stay away from this as much as possible in the, in the session itself.

I think that, again, if you go back to the methodology, and you look at, it comes in a couple of key areas. So, no, is effectively analytical applications, which, you know, anybody in the transformation office, I'm sure, knows what that means. And the, act pieces, really operational applications. Things that, like, take action in, assessing your day-to-day business, and then, you know, sensing could kind of be in the middle, maybe some, like, point solutions, like, do a little bit of both. But, if you look at the technology landscape, right?

Well, so, I'll start off by saying that, process, mining, technology encompasses all of these, And that is the kind of solution that so on. And that's kinda the last plug, I'll give about that, because that isn't what this is about.

But, if you look at the analytical line, there's all kinds of tools from process mining, to BI, to other kinds of analysis, to even things at the specific system level. Like a specific system might have some sort of analysis that you can leverage, right. There's all kinds of things, and you can understand what the challenges are with my system.

And then, for, like sensing, you can have, like, some specific line of business apps that are saying, hey, this, this, this applications coming in, do this, this, and this. In this order, and then send it to that person, right? And that could have a little bit of intelligence baked into it, right. So those like point, solutions could be kinda sensing, and then acting could be anything from, like, you know, BPM, where you're building applications to string together different systems. And, you know, forcing the automations to something like RPA, which is like desktop automation to API automation in the backend. And actually, directly go into the source system. So, there's all kinds of automation technologies as well, And, you know, process mining, kind of incorporates all three of those into one platform. And depending on what kind of other tool you have, they can incorporate more than one as well.

So there is a plethora of technology that can be used here, and I think that they should be used in conjunction rather than together. I think that there's a place for all of them.

Just saying, I think you might be muted.

Hmm.

I was, thank you. Have time for one more question here. And this one is just your observations on the field. Are there any change management best practices that you see out there, where we, where we have a better win rate on these implementations?

Yeah, I mean, obviously, communications. So, first and foremost, if the teams involved with this change from the people that are signing the contract to the people that are actually using any piece of technology that you're purchasing, If there's not alignment there, if one group is forcing it on another, then it's less likely to succeed. And I think that that's kind of obvious, but it's worth saying, because I feel like that is where a lot of it falls down as communication breakdowns in Charlotte.

But the second piece is, and I think that this is, this is something that you should focus on, no matter what technology you use. It needs to be focused on the business outcomes. I think if you can't demonstrate clear value for what the for the solution that you're implicated in implementing, whether that's, like, a manual process change, or a piece of technology you're implementing, If you can't say that as a result of this, we expect our customer, or customer satisfaction scores, to go up by two points, or you know whatever it is. Right. And you can't, you don't have a way of measuring what impact that change is going to have. Then it's unlikely to succeed, because it's not gonna have the buy in. But everybody's aligned, right. We say we're all going in this direction and we know what the outcome is and we know the changes, and we know how these things are related.

Then, it's very easy, because everybody's just saying did we do that or not? There's no, no, there's no conversation.

And those typically are the fastest and most successful implementations that we've seen.

Outstanding Mac's. So thank you so much for being here and sharing your expertise with us and the journey. And we really appreciate that.

Josie Thank you so much for having me. It was an honor to be here. I'm happy to be able to share this with everybody. And, again, if there were any questions we didn't get to, I'm happy to take those offline and continue the conversation. But thanks again, so much for being here. And thanks, everybody, for your time.

Thank you very much.

All right, ladies and gentlemen, this concludes this segment. And we're gonna wrap up with a fantastic session by Patrick Law and Cliff Torrone that will share with us the building of the workforce of the future to achieve excellence and some great way of wrapping up. They won and discussing on what that workforce may look like this workforce of the future, to achieve this enduring greatness and excellence. So, if, you, again, have any feedback on the session, you can, you can provide that as you close the session, that will be an option for you to prove to provide feedback. If you have additional questions for the speakers joining us on LinkedIn and ask questions right there, provide your comments about the about the sessions in general, and any follow up questions you may have, you can post there as well. And the speakers are pretty good at checking on that, and providing answers in the, in that forum. So, thank you, I'm gonna close this one segment, and we will open back up at the top of the hour. Thank you very much.