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Courtesy of Blueprism's Jon walden & Bruce Mazza &, Ernst & Young, LLP's James Matcher below is a transcript of his speaking session on 'Leveraging Hyper-automation to Transform Operations & Create Competitive Advantage' to Build a Thriving Enterprise that took place at RPA & Intelligent Automation Live.
Leveraging Hyper-automation to Transform Operations & Create Competitive Advantage
Join Blue Prism and EY at The Largest Premier Gathering of RPA & IA Industry Leaders & Senior-Executives where we will be sharing key solutions to current & future RPA challenges.
In a business environment that is rapidly changing, automation at scale is quickly becoming the new normal. Gartner predicts that industry adoption of Intelligent Automation (IA) will reach 85% in some form by 2022, and hyper-automation (rapid automation using a combination of automation tools) will be at the core of these automation efforts.
Hyperautomation is transforming every aspect of organizational function from finance, tax, HR and IT to supply chain, regulatory compliance and customer care. World class, best in breed organizations are now combining robotic, intelligent, and autonomous systems into their everyday working practices – widening the scope of potential tasks and processes that can be automated every single day.
Join Leaders from Blue Prism and EY for a panel discussion centered on how hyper-automation is transforming operations and helping create new opportunities for growth.
We will share:
Now, further ado, Let's welcome our first set of speakers, who are going to share their wisdom with us.
They're going to be talking about leveraging hyper automation to transform operations and create competitive advantage, and I'm talking to, I'm bringing in three amazing leaders in the industry to share their expertise with us. Thank you for being with us, John James, Bruce, Quick introduction, each one of them, John Walls, and he currently serves as the Chief technical officer Americus for Blue Prism.
He joined, John is a solutions-focused executive with more than 30 years of success across a wide variety of industries. You're in great hands when you're listening to John, because he has the theory. And it has a lot of practice over a long period of time. What makes these things successful? Joining John, you'll have Bruce ..., who is the VP of Blue prisms, Global Technology Alliances Program Tap. He's responsible for realizing intelligent automation by combining the best in class capabilities of their partners. Bruce also has over 22 years of experience in technology and solution roles.
And last, but certainly not least, we have James Match or with us, and Jane leads ... into intelligent automation practice in the United States, and he has over 20 years of consulting experience in the digital enablement domain. He specializes in designing and implementing scale, these automation programs, driving strategic value extraction for a large, multinational organizations, John, James, and Bruce, what a privilege to have with us. Thank you for sharing your wisdom and expertise with us in our global audience today.
Thank you so much for having us, given the fact that we just did introductions, I'm not going to spend a whole lot of time, because he said these sessions are short. There's one of my other two presenters, are. The folks can just verify that we can see my screen?
Fantastic, Just wanted to make sure on that regard.
I'm gonna go ahead and go through a real brief agenda of what we're going to accomplish for today. I want to spend just a minute or two doing that, Then I'm going to hand it over to James James, as was stated, it's from E Y.
It has all sorts of expertise in this deploying Blue Prism and all sorts of different clients, and that's that perspective. Beyond that, I'm going to come back.
one of the things that's important is really how Blue Prism can enable whatever automation, we're going to Bruce describe what that means in a real-world environment. A little bit more. Beyond that, give chance for James to say a few more items, and then we're gonna go ahead and talk about how we can help in general, or how we have helped.
More Importantly, with that being said, know, RPA is one of those very interesting elements.
And I use this quote a number of times with regards to defining terms, and I think it's important because I was part of the I Tripoli element that spent better, part of a year, trying to define RPA, separating it from all the hype that existed. Separating it from RGA versus RPA, those types of elements. And when you look at it, it really deals with the aspect of application, probably more than anything else.
And that application revolves and resides in what you as an organization want to accomplish. Automation has been around for a long time, a number of different ways, but it's really a question of now how we do it, within the bounds of your existing systems of record.
Now, the how you do it is really kind of an interesting element. Because, we're here, talking about intelligent automation. You know, maybe some people consider that RPA on steroids, whatever the case may be.
The interesting part is, there been a number of studies that have looked at how people are finding intelligence, what they're looking at in general.
And last year, when they did the study, about 58% of the respondents said they were doing AI in some way, shape, or form.
It actually went down this year and cut down to 50%.
The really key element here, though, is the fact that greater than 50% of those organizations have now started to really acknowledge that they had to have KPIs associated with it.
Because it wasn't just a matter of having machine learning, and AI, and those types of things in place. It was really that they had to apply in some way, shape, or form.
And the most interesting study, which is a series of other studies to me, was that over 80% of people, when they were defining, when they actually drilled into what those terms meant, we're really only talking about OCR, and AI and intelligent automation can mean so many different things. So many different people. I really think it's kind of important, in general, that you do think about what it is you're trying to accomplish, and, more importantly, define the, not only terms, but to find what you want to accomplish with that.
Now, that being said, as I said, it was just going to take a minute or two.
He wasn't a long standing partner with with Blue Prism.
What I'd really like to do is introduce James here and give James a chance to tell you, from his perspective, what he has told clients, in general, when they start talking about this, this idea of hyper automation, what it ends up leading to them.
John, thank you very much. And welcome, everybody, today.
So when we talk about a lot of automation, is trying to get their appliance challenge, always challenged on a database, cost, growth, breast content, these challenges for every single day to be able to rethink the business. Where am I in the future? Work myself back to where I am today, and how do I delta?
Fundamentally, what you'll find is that this will end up starting to change them an impact on four major areas.
In the process itself, amongst the people, the underlying data that they provide and consume and manage on a daily basis.
In the IT landscape, quite an interesting look at the IT landscape, that's across all three layers.
That systems of record your piece, the Navy applications, notice the digital technologies, but it's in the digital technology space. Where the greatest opportunity for change and involvement and enhancement currently resides.
And it's in this space. I think the organization is starting to grapple appreciate if there is an opportunity for us to be able to do things, not just differently, but do different things in its entirety.
Let me start looking at the constructs of Apple information. Was kinda said, well, what are the pillars? What are the things that kind of make it all come together? Fundamentally, the R three.
So in order to say you have automation, you've got to be enterprise wide.
Although, there's been a lot of focus around key areas and functional domains, like finance, some of the back office functions.
True hype automation allows us to create this capability at an enterprise level, the front office, the middle office, and back office, and there's certainly opportunities, although, being different across that full landscape and spectrum.
The second area around that is the constructs of multi threaded technologies.
I'll touch on a bit more later, but you'll see, historically, often, the technologies, whether it's RPA, OCR, some of the AI cognitive capabilities, have always being discreetly applied to a process.
Hyp automation brings these multiple faded technologies together in an integrated way that allows us to be able to achieve so much more.
And the third tenet around that is execution and speed.
How do you do all of these things? Enterprise wide multi threaded technologies SP?
It's the ability to be able to go at scale, create volumes, in, create a digital workforce that's changing organization, to sit alongside your human workforce at a cadence, an acceleration that hit a tree is not known in the classic IT world.
And as you start bringing these things together, what You thought that you end up with a hot automation engine.
This is a little bit different from that, And Louis, It also is three genres and trends around this thing.
So first is, you know, automation, one is heavily focused around task automation, pipe automation.
Start coming out is when we start talking about automation to Windsor, process transformation, the ability to re-invent that process.
And it is a precursor to ultimately we will go to the future, which is Automation three, which will revolve around process re-invention, on the basis of AI centric technologies that allow us to re-imagine those processes in its entirety.
What you'll see as we move to hop automation, you move from cost optimization and efficiencies, which are automation, one, to broad spectrum value realization. So how do we end up generating revenue in the front office, driving operational and risk, mitigation, agendas in the middle office, cost optimization in the back office, et cetera, et cetera.
Ultimately, today, we have stakeholder re-invention. three points here.
So the ability to bring these three things together, fundamentally biotype automation.
I should go to that, John.
Just because we would hop automation, doesn't just mean that it happens overnight.
I'm very intrigued to kind of pass back to kind of ask, how does Blue Prism enabled hyper automation in a practical sense?
To be able to allow organizations started achieving this progressive trend as we have today.
No, that's it.
That's a really good question from that perspective.
And I think you hit on it some, when you were talking about looking at a process. You know, very often, we think in terms of IT, in terms of the process, people in technology and RPA is really interesting space because it fits smack dab in the middle of that. There's, there's not, if you put it entirely in technology and IT, it tends to get lost. And people think of a lot of coding in that orientation. If you put it entirely in business, on every, on every desktop, it tends to be grow out of control, and there's no real governance from that perspective.
It has to be considered across all the realms when you begin to look at intelligent automation and the things that it can do, And there was actually a question of how do you keep intelligent or the intelligence side of things from producing bias.
And I think it's really important to recognize that intelligent automation and RPA in general is not just, um, it cannot just be applied as a technology.
It is, and I very often refer to as the unification of different types of workforce, you know, we've been very good over the years.
Doing it, moving things off, shore, we've been doing really exciting, different people, different roles.
What we now need to do, is, we need to recognize that AI, ML, RPA, is just another workforce. Which is why Blue Prism doesn't necessarily refer to as bots, but we refer to it as a digital workforce.
Because you've gotta consider, what is the ratio that you have with regards to people and digital And the backend systems of record that you have, There may be some processes where a majority of that can go to a digital workforce.
The thing you have to be aware of when you look at the idea of bias introduction is that you still have You're not You're one of the big pundit. Some of the big pundits often say, The sky is falling. We're going to lose all our jobs.
It really has not been the case from what We've seen, What we ended up seeing is, We end up seeing this digital workforce taking some of the work, actually returning ours back to business.
But then, you, you have to manage them, and you have to unify them with your people, because those people are the ultimate, um, verification of work that's been accomplished as well as any bias or any confidence factors, Because it all comes down to trust. When you're dealing with AI and ML, that trust and confidence is a critical component. And that's why people are still have to unify with this large workforce, that it allows you to accomplish what you need to.
Now, from Blue prism's perspective, we look at it from the idea that everything is connected, and we really begin to focus on, from a business user, being able to discover processes, being able to help you, design them, and then being able to deliver them in the production environment, usually through what we call a center of excellence, All of these things are critical.
When we look at discovering, we offer a number of capabilities that really help people find these things. We we actually just released over eight products this past year, one of which is an idea called Capture, which helps people document their processes. I am still amazed and change. Maybe you can give me a head not. Do you still find that a lot of organizations don't even know what their real processes are or how they're being accomplished?
It is always amazes me for some reason that I continue to be surprised by it but it is a standard that I see nonetheless.
So, these things really help people, not only discover, but document them from that perspective.
When we talk about designing, you know, we have an interface that is really designed for to be business driven, and, then IT gover, the idea of doing this, with very little code, if you had to have code, we embed it a little bit deeper in. Usually, those types of objects are created through a center of excellence, or somebody who understands it.
But, most of our business users never see any code in any way, shape, or form.
They design it in a very visual fashion, sort of like diagramming, a process flow, and that's really, what we're talking about here, is we're talking about processes, you're talking about accomplishing work, and that work has to be done through a process.
And that's one of the important tidbits that I've made on a lot of other sessions is that, recognize, and this gets back to the previous question, any AI and ML needs to be applied in terms of a business process, or it's really just a science experiment.
And, those are great!
Those help you learn, but they don't necessarily provide value to the business, And that's really important to segment, and I think, this leads into, to what you mentioned with regards to, you know, phase one, phase two, phase three, which we at Blue Prism call waves.
It's that idea, that, as you get to this idea of literally looking at your processes, sometimes you could redesign them.
Sometimes you have to go from a zero based design orientation, and really start over and refocus on, but it allows you to go from that.
People, process, and technology, too, What I like to really talk about being, you know, the business purpose, the workflow that's going to support it, and then the workforce that's going to accomplish it.
And when you start talking about that workforce element, then you're really talking about how do you deliver it?
Know, Blue Prism has has been expanded in the last couple of years to include things that really bring together the unification of human, a digital workers, so that answers your question about trust or something. Digital worker doesn't understand, it can escalate it back up to the human. It's that idea that, in general, you need to be able to manage this workforce, not just let it run on every desktop. Let it run ***** nilly. But you need to manage it, because you were gonna have to govern it. You're gonna have to print, and especially with nowadays, with all appliances, of, either to the California Protection, or the European Union, whatever the case may be, You gotta pay true documentation and governance as to what's happening here. And Blue Prism, really designs, provides you a complete circle across the board for that, you know, just as a little little background, just so that you're familiar. This is what Blue Prism designs and delivers.
This, however, as I mentioned before, is really about the digital worker.
The process may have to be augmented through some very important parts and pieces, and those parts and pieces are what I want to actually bring Bruce in here.
Because when we start talking about AI and ML, Blue Prism is not going to be so arrogant, is to say.
we will tell you which type of AI and ML UV, because it's really in that, as I mentioned before, in that understanding what your business purposes and what that workflow is that you're going to have to decide.
Maybe I need a CR, maybe ID, translation, whatever the case may be, it's, that's what you have to do.
Bruce, what I'd like to do is have you talk about how we accomplish that a little bit more effectively across the board.
Yeah. Thank you so much, John and James.
It's a pleasure to be here with the audience and the global audience around the world, in this critical topic of process transformation and re-invention.
That James and John.
It highlighted Blue Prism is very focused on providing a rich set of capabilities to meet exactly what James talked about for achieving this hyper automation.
Enterprise wide capabilities, multi threaded technologies, at execution at speed, and one of the things we're very focused on is providing a broad range of technology partnerships. These are the organizations and software that you invest in across your enterprise, whether it's large CRM platforms, ERP platforms, or the new up and coming AI and ML capabilities that are out of the market.
And a broad domain of capabilities.
We have a program that we run that is very focused on providing pre integrated cognitive technologies that are tested, are available, and are available, too, bring into that process, framework that John just went through, in a no code manner.
And the reason why we do that is all about that execution, that's speed, and that's enterprise wide.
And that really relates back to these three waves of automation that John and James talked about.
So, we'll kind of go through just briefly, and share with you just some insights into what we're seeing for the market and trends in each of these areas and capabilities, and just extending on what John said around discovery, design and deliver.
This is very much focused on the concept around automating the automation life cycle.
So as your teams that are in the domain of this center of excellence, to perfect, how automation is done, perfecting that automation life cycle.
So that it is in fact, also more automated itself is one of the key things that we're driving.
And we want to provide you, all the insights from how you mine your current process.
How do you assess? what the best processes to build?
Then speed to build and test And ultimately manage and govern. As John said in a secure way that integrates in this digital workforce in your enterprise.
And there are many different tools out there, and Blue prism's architecture is designed and it extensible way that you can actually build these capabilities to market leading tools at a very highly integrated fashion.
So these are some of the technology partnerships that we work with in the industry and you'll see some names there.
For example, Abby, Timeline, Fortress site cue slowness those are some of the leading vendors and mine and assess around process discovery. That we integrate those capabilities to further complement how you actually discover processes and bring them in.
We have capabilities to automate the test cycle, so that, when you're testing these processes, that they're against best practices and security practices, and then even extending that management and government of a platform.
How would you do that across all your tools in the enterprise? Where you're looking at process transformation capabilities like me, and raga manager, very much designed around that?
So, your plugin this into a large digital transformation effort, and it is recognized that this is one of the core capabilities that Prism offers, but you have a lot of other considerations, whether they're BPM tools, whether they're OCR tools, and how do you orchestrate them together, enterprise wide.
The other thing that's very key now is, and this really drive us into this process optimization side, and how you drive transformation, is investing in these cognitive capabilities.
Know, a lot of the discussion has been about, how do you leverage machine vision. So OCR, intelligent document processing, and bring that into workflows, and very much, that's widely adopted down into many of our clients.
But now we see this extending into this wider range of capabilities that are multi threaded.
It's being able to take your digital workforce, and tie it into your security platforms, around identity, communication, and management.
All of your ERP and CRM systems, your human capital management systems, and extending tools like iPads, in with RPA, then we really get into those cognitive capabilities.
Those triangles that you see on the top, this is injecting in machine learning, AI, business analytics, natural language processing, and understanding.
And all of these kinds of capabilities really start to move from the back office to the front office in terms of this process transformation and the value to the enterprise.
So, as we start to look at that, again, our job is to make this relevant and integrated into the common tools you use in the industry, for each one of these things, And there's a lot of logos on here, this is just a sampling of the partners that we have.
But the key point is, we want to provide you choice. We want to provide you best in class. Of how you integrate these technologies together.
I'm just gonna highlight one example, and then I'll do it on the next slide here, too.
Is this idea of making processes, more cognitive, is very much a reality now.
So, some of the partnerships that we have in the Areas of AI and ML have powerful engines for data science, data, manipulation, and understanding trends inside of your enterprise.
Now, what you want to do is actually not just link in humans in the loop that are touching those data points and data scientists, but actually leverage those engines in real time, so that if you have to make a decision that is based on critical learnings, critical data analytics, maybe it's how you process your month end of books.
Maybe it's your it's critical supply chain and adapting in real-time their supply chain to learnings that come from these cognitive engines.
Now you can tie these capabilities together so that we actually don't just put a human in the loop if we actually put this machine learning or AI capability in the loop of a process and a continuous process. So that's very much a reality. Now our clients around the world are now leveraging these technologies to get to that process transformation work.
And ultimately when we go up the stack and go to this for process re-invention, it's very domain specific.
This is where U Y and Blue Prism work very.
I believe in hand with you as clients to look at this process re-invention.
What is your industry? What is best in class, what are zero based design ideas, that can drive true transformation and re-invention inside of each of your domains?
And for example, one of the things that we see very often happening movements push to the front office, leveraging these technologies in your customer experience transition.
We have a lot of clients together that are looking at context centered transformation, and this is the idea of leveraging automation to improve and speed customer interactions in the front office.
There are some very key breakthroughs around not only doing things like reducing the time it takes to resolve customer problems, but also transform it transforming those into for digital processes that really re-imagine and propel customer service to the next level.
So that's really where we get into this true process, re-invention. And leveraging these technologies. So, James, back to you, I'd love to just share a little bit more again, as a, as a close partner Blue.
Prism, can you tell us a little bit more about how you actually describe and work with clients around hyper automation, back to you.
Thanks, Bruce, And I always get excited when I go through an angle, that broad spectrum, or blueprint that has to offer. Because although there is a clear science and an ability to be able to leverage technology.
Well, when we look at Hop Automation is quite important for us that we understand that you need to drive some changes at a sort of strategic level as well.
I'm just trying to get the slides to progress. Yeah.
There you go, Thanks, John. And so, we're not looking at the technology summing up play. It's really important for us to look at the, some tenants, apart automation, several strategic views and perspectives. That you really need to make sure that you don't forget or focus on in order to be able to execute a hot automation program. And, I'm going to touch on a few of these now very briefly.
So, the first one, in my mind, is the ability to be able to remain true to the tenants of Hoppe Automation.
So, the first one of that would be, you gotta be able to maintain your agility.
The principles of early automation around speed, dynamicism, and this must be true when you go to high automation programs, that as they get bigger and more complex, if they start becoming more cumbersome, slow to implement, they lose the principles of what they're trying to do upfront.
Second principle, you need to make sure that you maintain within that being there, is get your engineering and technology and integration solid.
Your functional structures are reflective of your technical structures. Now, I'll kinda take you through now. What I mean by that.
So, the first thing around that one, is the ability for us to be able to say, Well in the past, Hawk Automation has always been something that started with RPA.
And, what we ended up seeing within this construct? Sorry, John.
I think we, for some reason, I'm not getting my slots to progress.
You should have access, try one more time.
Cool, we'll give it another.
We'll see if it's actually going, Hey, you guys having happen there.
So, the first one is, always started with RPA, and price automation was the basis of what we wanted to do. And many organizations and triggered, I said, great. We then created the functional architecture. We created strategy definitions, pipeline management, model risk, and control. In order for us to be able to more deeply present and shape of that process automation capability, That's not sufficient.
Next element you need to be able to do is make sure that as you start expanding the technical landscape that has happened, as well. So, we start seeing the advent of these technologies like business process management. We alluded to earlier, Andreas ...
talked about processes mining and oscillators them integrate that, that, becomes relevant to understand that procedural side of the House.
On the data centric side, we start seeing advancement there, as well, advanced analytics, the continent stack, and AI, machine learning stuff, coming into place, with the OCR, computer vision classification.
And as we start bringing this in, place, the necessity grass denialists to get a whole spectrum of integration to be able to layer and integrate both the data and the procedural activities becomes imperative.
Then underpinning all of these things is the ability to understand the data pipeline. How does it fit together? How does that work together?
As you can imagine, although you might add different technologies into the environment, you're setting should, the functional side of the house, top off the circle matures and evolves as well, you, John alluded earlier on, around risk. And control around. How do we end up dealing with bias data? Privacy issues around that. AI is a data centric use, cases, will change from, when it was just a pure RPI play, your models more mature.
The way you define use cases becomes more complex.
Says, instead, right upfront, the ability to say, as we add different technologies, balance it with the functional expansion, as well. Mature, your ability to identify engaged process becomes absolutely pivotal.
And remember, the background is both high code and low code versions of all these technologies. Working out when to apply them becomes very effective.
Use low code where it makes sense, Use high code where it's relevant, and be able to be able to work it out on a day-to-day basis, enables you to truly, truly move the agenda forward at speed.
That's what I'm going to talk around, is the ability to have value centric use cases and develop with the focus of transformation.
As these use cases become more complex and bigger.
The identification of saying what carries a tool called RPA.
And now I'm going to go ahead and pull all of the stuff that can automate and try and justify it's existence afterwards, has gone.
Organizations have to start off, what am I trying to achieve?
What is the value creation I'm trying to obtain? And therefore, what are the technologies that I need to bring to bear that will happen?
Let me give an example, let's let's take a single price, slightly to cash.
In order for us to truly transform those processes effectively, you can either do a complete rip and replace, which is powerful, but very few organizations are able to completely redesign a process. In one instance, budget, challenges, change fatigue, the rationalization of what people are trying to do. How do we transform our perform indirect?
The way you want to go about it is identifying what are those key domain metrics at al thinkable throughout this process and be able to inject the critical ones that if we move them by 30, 40 50 per cent fundamentally change how this crisis it's performed.
And then, from that point of value, work out, what is the combination of technologies and techniques required in order to be able to realize that value shift?
Add to the desired requirement, and then start targeting these systemically one off the other across that end to end life cycle.
This ability to be able to transform the thing allows us to get their ability to really extract the value and organizations to measure it effectively off event.
Not treating a spot, organic benefit is helpful.
when you do it by orchestration so carefully orchestrated the timing and the sequencing of these transformations, it becomes very, very important, because that's how, over time, the true value realization that you're trying to achieve comes to the fold.
It attracts the funding and everything else you require.
Last, tentative, hop automation, which is so important, is for us to be able to understand how do you maintain a balance between the process and technology.
This becomes quite important, because from experience, we see organizations generally pass in 1 of 2 journeys along the way.
They started out with RPA and analytics is the base, then either move to progress in 1 of 2 paths.
First one, would be, obviously, a diverse technology execution.
So, they've moved from process optimization and base RPA to intelligent automation, if add additional technology lies to the stack, virtual agent, Intelligence machine learning.
And they've created almost a structural. If I create these platforms, they shall come talk methodology.
Which is great, but often they've not been enough focused on the process themselves.
The alternative is some organizations have gone from price optimization, business transformation, The primary focus has been the process itself, to deploy BPM approach is wanting to deeply understand how these processes come together, but they have not been able to truly realize the value, because they have not got enough of net new technology, and to be able to truly leverage this.
We've become really powerful, and the objective is, is we start combining both these together.
So the ability to add additional technologies into your stack, and coupled with a deeper understanding of your process, and transform the environment very, very quickly with these new technologies.
As Bruce alluded to earlier, the ability to bring technology partners into play, through the Blue Prism platform, allows you to be able to do both of these things simultaneously, that the ability to take that second step.
It's truly how organizations now will change the way going forward.
So, as we start seeing with these things, John, it's always kinda thing, is, as I mentioned, the methodology is solid.
But how does Blue Prism truly allow and support and engage a hype automation agenda, more effectively? what are the practices that you guys adopt in order to make this really come to life?
You know, it's interesting because, I've seen you give this presentation once or twice, and I'm actually going to cheat here just a little bit and go back to your slide you mentioned, with regards to that separation of functional functional versus technical and development.
And this is some of what I discussed earlier, when, I talked about that idea, that, no, you have to, you have to focus on these things from a business driven orientation.
But the IT or technical has to be involved.
And one of the reasons why Blue Prism customers have been so successful at scale is really, we recognize this early on, that idea of managing this workforce was really critical to us. And so we introduced very early on a thing called the robotic operator model.
This framework really takes that into consideration, takes that separation, and gives it the amount of focus, and the amount of consideration that it really needs.
Because, if you don't really have, know, Ben Franklin said, If you plan to fail, if you fail to plan, you're planning to fail.
That orientation of having vision knowing on what you want to do this, takes it from being, you know, especially in the intelligence phase, takes it from being a, a science project, to really giving it the business purpose from that perspective.
You've gotta have good organization that can, can support that, both from the business, as well as the technical side. And you've got to be able to govern these things, and I'm not gonna go all the way around.
The circle is really the critical element here, is that you have to, and you can only, and you've got to this as, well, when you talked about applying those KPIs appropriately, you have to understand what it is you're going to do, how you're going to measure it, and then how you can deliver it.
And that's especially important when you're dealing with with the business side to a great extent.
The technical side, you know, is another element, and we've actually introduced what we call it digital exchange to make that a lot easier for customers. Because we recognize that a lot of business users may not get the support that they need, and they may have to access systems that maybe they don't have all the time to do, develop what we call the Lego building blocks of an object.
And so the D X is really an app store that allows you to find these and other people who have put in there or find them that Blue Prism and put out there or find them that partners have put up and they exist everything from creating connectors to different systems to full Fledge processes and automations and redesigned automations to make companies more effective.
Now, all of this so far, it's been, you know, three guys ...
writing to you to a great extent, And this is really about the application. And so what I want to do is, before we begin to enter the questions, I want to give you, sort of both a vision as to what can be accomplished. as well. As sort of just some points is what this has been able to do if you take this seriously. And you come at it with an approach that is really looking at it from transformation perspective, rather than just a task automation perspective.
I decided, imagine this, James, I decided to pick on E Y first.
You know, all the rhetoric that we've done is all great and good, but I want people to understand here that E Y has not only been great partner to Blue Prism, but they've been a great partner to their customers, and they've also been a Great Blue Prism customer.
Don't know if that came out quite the way I wanted it to be.
Hopefully you get the idea.
And if you look at this, you know, you begin to understand and recognize that you folks have over 2000, you know, RPA instances in place. You know, I love that. one went down to the bottom more than 22 million hours saved in all the different process improvements. And I actually had to grab this from a screen print. You folks were kind enough to do a session during our Blue Prism world.
And this happened to be finding, and when I was prepping for this, this is not the only use case, though.
You know, if you look at a particular use case, and this is one that you folks actually helped implement, you know, you're looking at the ability to really reduce the work that humans have to do.
And it's not just the work that humans have to do.
Think about this from a customer centric perspective. And I'm just gonna focus on one little, little item there in the center, 80% reduction, in average call handling types. That's great from a business side, but let's look at that from the customer side.
You were able to help customers that much more quickly, and that's one of the things that we see very often, cross borders, is that benefit. It's not just two.
The companies that are implementing implementing intelligent automation. It's also to the customers that they're servicing in so many different ways.
You know, if I continue this, we can end up looking at, you know, internally, Coca Cola has given us, you know, this idea that they've saved or 16 hours per day.
16 hours back to the business per day, That one is not important, It's important to me is, I want to talk about the last point here.
Do you actually implemented within the bounds of HR, and I'm gonna try and hit a couple of different industries, and couple different functional areas here, They actually implement an EHR, were they were doing a 10% compliance orientation. Initially because of digital workers, They've now been able to move to 100% compliance, and that gets really critically affect governance piece I talked about earlier.
Someplace like Walgreens, this one's also a little bit nature orientation.
But it gets really well to that last box about elevating the employee experience. This is not necessarily about eliminating workers in any way, shape, or form.
It's about allowing workers to do what they should be doing, or what they were trained to do, were, went to school, to do, or what they find enjoyment in this, compared to acting as an automaton between systems of record.
And, then, finally, I'll give you 1 last 1 here, from that perspective, and that is the idea that, No, you mentioned just a little while, a few moments ago, James.
The idea of, And I'm gonna use my term tonight in terms of being captured. Well, into the idea of where do you pay for this, how do you how do you justify cost, justify this?
And I think this is a really good one because in No, Hershey's ended up being able to, once they put some processes in place, able to gain or recognize seven point four million dollars in inventory.
So, this is inventory that would either have to be off shelf because it was too old, or just wasn't getting where it needed to be.
They put that number on there, and that's really, when you begin to look at those types of numbers. And this is not an unusual number by any stretch.
That's really what's driving this whole ideal. It's, it's, it's great that, we have resiliency. And after the year, we've had it would be recognized as you need resiliency.
But it's also being driven by the pure value that we're delivering.
Now, with that, I want to end up giving you some next steps from that perspective, and then we'll go ahead and go to questions. You know you can certainly pull a free trial down from Blue Prism. ... has been great with their time today and I want to thank James significantly for it. They actually do these wonderful things called Value Engineering sessions, and I want to make sure you're aware of those, if you're looking and you are a Blue Prism customer. You've looked at Blue Prism before, recognize the digital exchanges there, and then we also have all of our contact information along the bottom.
Now, I'm gonna take just a minute, and I'm gonna go ahead and go over to the question and answers, can see if there's questions that we have not have not hit.
John, thank you very much there. There are lots of questions here.
I'm gonna go through a number of them that we have time for. So very great participation front of the audience. First of all, thank you for the presentation.
Very comprehensive view covered lot of important concepts here. So I have one begs the question, just just situate some of the maybe less experienced in the audience. Just surprised article perspective, when did RPA became a thing, that it became a commercial product and you started deploying RPA.
So I mentioned before that I was part of the I triple E, automation itself has been around for a long time, RPA.
No, Blue Prism is actually giving credit with sort of standardizing on that term, intelligent automation has certainly been a revision of it.
We started as a company in 2001.
Our first product was actually released Barclays, in about 2005 or so, but I want to say it really started hitting things around 2012 or so.
That's when it really started to take off considerably.
Which is quite a long time, it's, I think the most people don't realize that even a commercial scale, it's not new, It has been around for nearly a decade, as you just pointed out.
My first experience, sexual acts as an executive leader for Neu and Gas Company and, and that was 20 15. And specifically with Blue Prism in automotive finance processes. And the lot has happened since then of course, what is the state of the technology? Should they, in terms of its ease of use, ease of implementation, and maybe a little bit about it, smart capabilities?
Well, I think the ease of use and ease of implementation has definitely changed a lot over those, those years, you know, I mentioned that we've, we've released eight different elements is here, really focused at making it much easier from that perspective. We've always focused on enabling the business user.
We introduced DX probably about 2 or 3 years ago. Because we recognize Bruce helped me, we started with probably about 4 or 5 people on the D X four, or five items. And we have now, how many out on the DX, how many different assets?
Yeah, we're approaching 2000 assets and those are downloadable, no code, drag and drop capabilities to integrate your platform.
So, significant time savings and ease of use, that's now achievable with, with capabilities like John's talking about here.
And it continues to accelerate as well.
Outstanding. And this one is for James, James, From your experience on, on the enterprise wide implementations, what percentages you see of organizations. Right.
now, they're looking at AI, ML, hyper automation as foreign enterprises wide perspective, versus a local, a local implementation. And then the and then the follow up on that is that I think there are a bit of a rhetorical question. There's probably more local than enterprise wide. And that, does that create our sub optimization throughout the enterprise and, what does your perspective between, you know, start small and scaly and having an enterprise wide deployment?
Yeah. So a few things, one I'll touch on was growing equations in reverse.
It's very important for most organizations.
And advice has always been, even if you're not doing it today, design for enterprise wide because you will get eventually.
We see too many organizations don't do that. So they'll start grappling with the immediacy of what they're doing now.
And I suddenly get a year later, realized that the basic credit is not big enough support where they're going.
So they start all over again and ended up going through these multiple iterations of re-invention organizations that sort of plan for the future and then say how do I not execute systemically? January the acceleration, that value extraction is much faster.
Coming to the distinction between low code versus high co, enterprise wide capability, you need them both.
They target very specific agendas, one very centric around task automation, so general upliftment of everybody's capability. Think about how much I will change every day when Excel became something we all could use every single day.
Low code automation is enabling it in a similar vein.
But to the same point, just like, Excel can never become an ERP, neither can some low code technology service the full capability to the clients will want to do.
So you need to have a bimodal environment at function nice effectively.
In terms of percentages, high class, organizational ****, the recent survey, 79% of executives, says that they will increase or accelerate the adoption of AI capabilities.
That's very critical, is that AI is implemented and executed in the process through automation capability.
Automation is the delivery mechanism, a practical scenario right now. It's almost like saying, if I want to take the vaccine wapping about my cheek does. No good. I need some delivery mechanism, get into my body. Automation is exactly that, So this ability to put these two together is critical.
So, as we see, the adoption of AI and some of the cognitive capabilities come to bear, there'll be an acceleration and enhancement of the automation capacity to deliver it into the premises.
Excellent. We are out of time here, but here, I'm going to push another one, I'm gonna push another one because this is a very important topic for our audience and it's worthwhile. If you can keep it as a short answer.
And I know this is a tough one.
The expectation is that we're going, you know, the RPA capabilities is something akin to maybe knowing Microsoft, Excel used to be with someone graduates from college, you expect that. They know Microsoft Excel type of thing, and the RPA has become ubiquitous to that level, and in a lot of the people in our audience and the industry.
The question is, what is your advice for the people in our audience today who are trying to upskill, are trying to come come up, come up to speed on RPA capabilities, around your resources, Any suggestions that you would have for them to pursue those skillsets?
Just a comment and I'll come back to John. John is a plethora.
So there are a plethora of opportunities organized for people individually is on the way of an injury. But, my advice is always to get close the major vendors. And the players like, like, Blue Prism, have access to and direction on how to be able to build up that knowledge base. Not just in the technologies, but the application and approaches that you require as well. John, You can probably expand a little part of it.
I was going to say, you are correct, all of the major vendors have universities and training skills out there to a great extent, but the one biggest thing I would say is, don't forget the soft skills. You know, we talked about processes and understanding the processes. This is not just a technology that you apply or that you learn. You have to understand the business purpose of the process as much in order to really apply it well.
Gentlemen, thank you so much for sharing your wisdom and expertise. We've had tremendous interaction and engagement here, many who follow your journey here on ... and your specific leadership. So thank you so much for sharing that expertise with our global audience today.
It was our pleasure. Thank you very much.
Ladies and gentlemen, those are industry leaders who are on the field implementing the solutions and cross industry organizations, so terrific to have them with us. And we are going to be taking a break now. And at the top of the hour, we're going to be switching gears. So, we've talked about the technology side of things. Let's shift into the human side of things a little bit.
How do professionals across multiple organizations feel and adapt to, this changes, are happening very rapidly in our society and workplace? How can we best leverage technology?
How can we overcome fears that we may have? And, how can we, how can we strengthen our culture to have this great collaborations between technology and humans, in implementing solutions that create value for our enterprise and for our society? So, at the top of the hour, we're going to be bringing a leader in this area, hits Martin Lanford, who is the director of customer support operations for B C L C. And Martin is going to be talking about motivating and engaging teens in achieving operational excellence while staying focus on what really matters to them. So I will be closing this session, right now, if you have a popup to rate the session, you can do that. And I will see you back at the top of the hour with Martin Lampman. Thank you.
Jon Walden currently serves as the CTO – Americas for Blue Prism Software. Jon is a solutions-focused Executive with more than 30 years of success across a wide variety of industries. Leveraging extensive experience in technology he has been a valuable advisor for organizations seeking guidance in aligning the business with growth initiatives. With deep roots in diverse technologies focusing recently on RPA and Automation, Jon Walden thrives on helping to solve challenging and complex business problems faced by organizations.
VP, Global Technology Alliances Program (TAP),
Bruce Mazza is the VP of Blue Prism’s Global Technology Alliances Program (TAP), responsible for realizing Intelligent Automation by combining the best-in-class capabilities of our partners with Blue Prism’s leading RPA platform. Bruce has over 22 years of experience in leading alliances, sales, product management, product marketing and solutions development.
Americas Intelligent Automation Leader,
Ernst & Young, LLP.
James leads the Intelligent Automation practice in the US and is the Global RPA leader for the Mining & Metals sector. With over 20 years consulting experience in the digital enablement domain, he specializes in designing and implementing scaled digital automation programs driving strategic value extraction for large multinational enterprises. Drawing from a broad based technology experience in data analytics, advanced automation, cognitive technologies and process redesign he has led numerous large scale programs across Africa, Middle East, Europe and US. In his spare time he enjoys spending time with the family in the outdoors and is an avid mountain-biker.
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