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Courtesy of Abbyy's Reginald J. Twigg, Ph.D. and Richard Rabin, below is a transcript of his speaking session on 'You’ve Automated to Survive COVID-19, But What Now? Transforming the Messy Processes that Serve Users' to Build a Thriving Enterprise that took place at Digital Process Automation Live.
You’ve Automated to Survive COVID-19, But What Now? Transforming the Messy Processes that Serve Users
COVID-19 forced mass adoption of Digital Transformation technologies, mainly to keep businesses running when the workforce, customers and partners at once became virtual and relied on whatever automation was readily available. Now, a year into this new paradigm of work, we’ve learned that merely automating a process is not digital transformation; rather, processes must be re-imagined as experience management – especially those processes around employee and customer service.
This session highlights:
Be sure to join this insightful session, and walk away with answers you need.
Welcome, Ratchet, twig, and Richard Robbing, from Abby, who are here to kick us off this morning. So Reggie and Richard, great to have you if I was excited about having you with us today. I'm gonna start with an introduction with Richard here.
Richard is the Product Marketing Manager for Process Intelligence. Abby.
He works closely with Global Enterprise to help them better understand and optimize their business process workflows, bottlenecks, and how to select initiatives that will be most business value with intelligent automation and, most important how they will impact overall operational excellence. Richard, great to have you with us.
And we also have ratchet twig here, coming from Salt Lake City, Utah. With over two decades of experience in enterprise software in artificial intelligence, doctor Reginald twig is an expert in automating document processing applications with digital approaches. Abby, he oversees the application of digital transformation, and intelligent document processing solutions, to Enterprise markets and clients, in industries such as financial services, insurance, transportation and logistics, and cross industry, functional areas, like Finance and Accounting, Reggie, what a pleasure to have you with us. Thank you for taking the time to share your expertise of our global audience today.
And, I will go ahead and start sharing my screen here.
1:49OK, so, I will, I will go ahead and get started. I'm having a few technical difficulties, which just means that things may move a little slowly, but I I hope to be able to keep time.
So, with that, A little bit of background.
Let's go ahead and get started on the presentation.
And today's topic is both broad and narrowly focused in, in a couple of ways that and that will become clear through the course of the presentation. And what I want to talk about today is what is happening with digital transformation because of covert 19 and how covert radically changed the way we work, the way we do business. But I also want to talk about some areas of digital transformation that became friction points in, in our efforts to digitize and more specifically to.
Gear, our businesses, to working remotely, both being remote from our fellow employees and being remote from our, our end-users and our customers.
So, let me get down to see if I can get my cursor to work. There we go.
So, today, we will, we will be covering a couple of different topics. The first of which is understanding what digital transformation actually is. Now, a lot of digital transformation. It's one of those topics that is so big that it can mean just about anything. So, the purpose of this, this, for the first part of the agenda is to narrow the scope to talk specifically about how digital transformation as practically applied in businesses. And, secondly, I want to talk about one of the particular challenges that organizations face. Again, and again, when they attempt to digitize their process and we will talk about what it means to digitize your process. And specifically, the one of the major challenges, though, that we see in digitizing processes is how those processes handled on 10, and by content.
I mean that, that unstructured information, that organizations use to make decisions every day, every minute, and their business processes, And those can include things such as messages and documents, And how do those, the, those forms of unstructured content fit into the flow of your business process, how do you automate that, and how do you make decisions on it?
This particular kind of information can pose some unique challenges. And, for a digital transformation initiative, these are challenges that many organizations are taking head on, but are still having some problems in the way that they're bringing them, and making them work, and, and, we will be talking about that.
Third, I want to give a little bit of background on artificial intelligence. And, in the specific role that artificial intelligence plays, in what we can describe as content enabled processes. Finally, we'll wrap up with a new look at process, And that is how we understand our processes, discover, monitor, create alerts on those processes, not only based upon the simple things that we've learned how to do, such as workflow, and, and, and, and an exception handling. But, more importantly, that messy part of process, which is the human interaction with the process. And the elements of content that flow throughout the process, that humans actually have to interpret and make decisions on.
My cursor got a little bit fast on me. So let me just jump back.
Are our first topic today is understanding the new automation way and how it redefined work in and in specifically how kogod redefine how work gets done. Now, we're more than a year into the covert, the covert crisis, and many of the changes that it brought about, and how we do business, how we interact with our employees, and how we get work done, have become completely normalized. And it's fair to say that the normalization of these practices will continue even after we come out of the pandemic.
So, let's talk about what digital transformation means. In everyday life, we see digital transformation all around us. And as we have moved from, though, from a workplace environment to the home work environment, we've seen this every day and the way that, that we just get on with our lives, but back to the days when we could travel, and hopefully, those days are returning. So, we learned a lot about, ride, share, share applications. So, for example, a good, a good example of digital transformation is, is rideshare applications.
So, when, when you, when we would travel, we would fly to an airport?
We would go from an airport, either to our business meeting, or to our hotel, or some other destination, and how often do you pull up your phone and, and do a ride, share like Uber or Lyft or whatever your regional provider is?
And the interesting thing is, that experience is such that, you know, as soon as you book the ride, you know who your driver is going to be. What kind of car you will be driving and what route you'll be taking. Approximately, how long it's going to take, and exactly what it's going to cost you.
Back in the days when we use taxi. We had none of that kind of certainty in the way that we experienced derived from one place or another. And because of the how ubiquitous Rideshare apps have become, they create a certain amount of fear and anxiety. If you take your traditional, you take a traditional taxi.
And, um, and, and, and that is an example of how digital transformation has changed our everyday experience.
And what the, what digital transformation is really about is targeting points and points of friction in our experience, and using intelligent technology to remove them.
Such that many of the, the applications, we see today, that are good instances of digital transformation. Whether it's streaming media, whether it's visual math, whether it's getting a ride, or whether it's the way that we actually purchase, and consume music and other media forms.
Those, those apps have really not created any particularly new technologies for getting the job done. But what they've done is they brought them together and created applications for those technologies that fundamentally change the experience we have between ourselves and the business that that we are engaging.
So with that extended definition I want to talk about the compelling event that that we have seen and that is the digital tsunami. The culvert pandemic has forced a paradigm shift in the way we connect technology and automation to customer and user experience.
And specifically, we have seen very clearly, up until the point of, about a year and a half ago, when we were adopting digital transformation initiatives in our organizations, automating a part of customer experience. figuring out a part of a process to change, adopting, robotic process automation to, to handle a lot of the everyday task automation, now that we need.
Largely, those digital initiatives were in the early stages of adoption going into 2020 last year.
But the covert event and forcing us to work from home has has, has put the accelerator on these initiatives, such that we have seen, according to analysts, such as Forrester, we've seen the mass adoption of digital technologies as a way of doing business. And in fact, one of the populations that up until then had been the most resistant population to adopting digital approaches to doing business. And that would be the baby boomers during the pandemic, became the fastest adopters of digital transformation approaches to doing business. Whereas, normally, they would go to the bank in person to take out money or to do a transaction. We, when forced to do it online quickly, those users realized that this type of experience, which is just conducting day-to-day business, is best handled through automation. And as a result of that, according to Forrester, we saw an overwhelming overnight mass adoption of digital technologies among this population.
So what did covert do? It created a moment of clarity for digital transformation initiatives.
First of all, if force mass adoption of digital transformation initiatives and organizations had to put, put their foot on the accelerator on those digital programs to make them work, in a time, when we were, when we had to work socially distance. And when we had to work from home and in isolation, we had to rely on virtualization a lot more to conduct business.
We had to rely on automation to get a lot of the Back Office tasks done for us and coven for us, the Mass, The Mass integration of digital initiatives into the way that we do work.
And it's forced us at the same time to re-imagine the automation process, assisting customers and employees and the way that they get things done.
And that re-imagining has as come in, in the form of rethinking how the processes work, and how we can use digital technologies to work with them. An important element of digital transformation is that it was already moving toward a paradigm of replacing a lot of person to person interaction in business transactions with person to device interactions so that the virtual experience would become highly, highly, highly personalized. And what cov it forced us to do is to realize that, we have to do that now.
And it forced the mass adoption of these approaches. In the way that we do business. And it forced the mass acceptance of these, these digital person, to device interactions as the basis of conducting business, and how our processes actually get run to support them.
But a year into Kelvin, we facing, we are facing the phenomenon of covert fatigue. Which has been widely identified from analysts, such as such as Gartner, or Forrester, and other and other industry leaders who've talked about the way that we've become fatigued in the in the way that we're doing work in isolation.
And specifically, analysts have pointed to the problem that the major driver of covert fatigue is actually the technology we're using to try to stay connected.
For example, how often did we actually use video conferencing apps such as soon be leading into the pandemic, not nearly as much as we rely on them today. And we have completely changed our behavior to offer ourselves up on, up on camera. And to put ourselves under surveillance as a way of doing business, because we're no longer face-to-face and an office. We're no longer face-to-face doing business. So we have substituted virtual interactions for face-to-face interactions. And the net effect of that is it has been to cause extreme burnout among users, And what that has created for users is a growing, impatience for the way that a lot of technology works.
The number of clicks, the number of screens, the number of steps it takes to get through things, those are direct causes that the burnout and the feet fatigue that we're seeing among our user population.
Finally, calvet burnout will force us to re-imagine business from customer experience into the process at no time before, before, have digital and niche initiatives actually. Given this much attention to experience. Because we're dealing with a mass population of burned out users and customers. We have to think about experience and put this the put experience at the center of how we digitize and how we automate our processes and our interactions.
So, now, let's move on to one of the special challenges that digital transformation initiatives run into, and that is specifically the content enabled process.
And as we jump into this topic, it's, it's important to understand that not all processes are created equal.
In enterprise software applications, where I've been for most of my career process is something that, virtually any enterprise application is concerned with.
And, we have seen the mass adoption of a business process automation, for the past four. Decades. First. In the form of ERP as, as mass adoption. But, then customer relationship management, supply chain, management, buying, management, content, management.
All of these three letter acronyms for these massive waves of automation, and bringing in system rubber records systems, of record have all been about automating the way that we conduct business, and automating certain business processes.
But for the most part, those applications, and those systems of record, have run on data, specifically, relational data, and our, we have built a world of business automation that is data driven.
But here's the problem, so many of our business processes, and so many of our decisions are based upon actually using documents and other sources of content that knowledge workers actually have to read, understand, and make decisions on.
And while these documents are a source of data to run process automation systems, there also is the need to understand the information, put that information in context, and buy it by contexts. That may put it in the context of the user's experience, the user's specialized skill, the user's knowledge, in that particular area of the business, in order to make decisions. And so, our processes, largely, have been automated when it comes to having good data and good data sources. But when it comes to something such as content and documents, those forms of automation, and tend to break, and we approach documents and unstructured content as a workaround, to, to the best practices that we've tried to implement in our organization, and other ways.
So, the important thing here, is to know how people, in the process use the content before automating it. And many organizations have begun to wake up to that fact, that content driven processes don't work exactly the same way, that data driven processes work. So, you need a different approach to be able to use them.
So, where is the friction in business today?
Gartner pointed out about 25 years ago, and it still is the case that, of all the information we deal with in an organization and in business, about 80% of that information is, is, is unstructured information.
Only about 20% of it is structured, and organizations have done a phenomenal job of automating data driven processes.
But, when you think about it, about 20% of the total process in an organization is actually fully automated, whereas the rest, whereas the rest of it, it is still not automated. And polls of executives have found that many, many executives believe that about 5% to 20% of their business processes have actually been automated. The rest are not because it involves dealing with with a lot of information that is not in clean data form.
So, today, we face the problem of content and the knowledge worker running into each other. And so, working in isolation with the tools that have been available at the time that we entered the pandemic and trying to deal with the overload of information that's in documents. All kinds of documents, if you're in banking, it's onboarding customers, and all the documents you need to onboard the customer. If you're an insurance and your phi, and you're managing claims, it's the claims documents at the trailing documents that are part of a train that are part of a claim that you have to settle.
And you typically have to read these documents individually And oftentimes this is what we refer to as swivel chair automation, where the claims worker in an insurance and then in an insurance management environment has to bring up the claim, Bring up the first Notice of Loss document.
Look at the information on one screen swivel over to the other screen where the, where the data systems are, key and the data and then move it on.
And then, oftentimes, that image gets archived, fairly late, in the process.
So these processes largely have remained and have remained unchanged during the course of the pandemic.
So, let's turn now to an approach to helping to solve this problem, And that's, that's the use of artificial intelligence.
Artificial intelligence has been around for a number of years, and it probably made its biggest, popular introduction. When IBM Watson won three back to back episodes against the all-time Jeopardy Champions back in 20 11. Which now has 10 years ago. But then, we've seen the mass adoption of other forms of artificial intelligence, such as the use of smartphones, voice activated commands, et cetera. But, what I want to talk today about today is a specific area of artificial intelligence.
As it relates to how we can automate those difficult to automate business processes, specifically those processes that use content, and, and on which humans, rely on content to make decisions for their customers.
So, why artificial intelligence, or why AI, and why now? Well, we've seen movies promise it for, for the past 50 or 60 years, everything from 2001 to Terminator and Terminator. As this dystopian future is all about when we create artificial intelligence. That is so sophisticated that it become sentient and begins to thank for itself.
And, and that's that's the reality that we were given in the media.
It has been postulated by many theorists that the media reflect the reality we live in, which is true to a certain extent, but it's also been shown that the media forecast, that the, the reality, that, that we're about to experience. And there was an interesting documentary on this point that I saw years ago called Star Trek Tech, which looked at a lot of the things that happened on the bridge and in other places in the starship enterprise. And, oddly enough, 30, 40 years later. Those are the technologies that we started to use.
And it's, it's a good case of how fiction has influenced the reality and set expectations for it.
So some of the fundamentals of artificial intelligence, or AI, have been around for years, those include concepts such as natural language processing or NLP. And I'll talk about that more in depth in a moment.
Machine learning assisted training, neural networks, that is, computer systems that are starting to think more and more like the way humans think.
And those systems and those applications are focused on understanding content, specifically documents, corporate records, messages, e-mails, all those unstructured, free form forms of information that that flow ended out of the business process all the time.
And what are the approaches that artificial intelligence has pioneered for this particular kind of processing of content, and, and pulling data, and verifying data from the content is a concept known as named entity recognition, and extraction.
So, in the old days of traditional OCR, we had the ability to read a document, extract fields of documents, and then, and then create some applications, write some code, that would tie all of those fields together. But, now, the technology has become a lot more intelligent. And it has the ability to look for a business entity and a document. For example, if you're a bank onboarding a customer, the customer is the entity you're looking for, And that customer is defined as the relationship among a number of different data fields and data entities. And it's looking for that relationship composing it. And doing it on the fly in real-time, That is what defines named entity recognition. And that was a major advancement, and where optical character recognition technology has been boosted by artificial intelligence to give us what we call intelligent document processing.
And in the process, AI has become more personalized. It's become personalized in anticipating how we use language and how we get things done on your smart phone.
How often do you do you rely on and more often than that curse, you're auto correct for the way it's changing the words you're using? Because it's trying to learn how you use those words and anticipate the next move to make it easier. And it doesn't work very well.
But we see examples of this kind of artificial intelligence in everyday, everyday reality. That include the time when Watson on Jeopardy, it includes Alexa. When we can go around the house and say, Alexa, turn on music order bror more toner, or what do, what are some good ideas for dinner, or we can get Siri to text ourselves to get to the point.
We can use photos, we can cluster by person, we can, we can extract information on the photo exactly when that photo was taken, the place it was taken, and some other associations can be automatically created with it.
So, the rise of assistant bots is the next step in digital transformation and AI enabled automation.
And we're seeing the growth of virtual agents and chatbots. How often do you make a customer service call for any reason now, where you're going through an automated system? and, you might be using chat to interact with, with your vendor, or your bank, or your, your insurance company. You're using chat and you're talking to a chatbot. So, we've already seen the adoption of these but, we're also seeing the adoption of smart objects and environments, physical, embodiment and also the growth of natural language processing. Which is still, though, it has been around for quite, for quite a number of years, is still in the early stages of adoption. Specifically, as it's used to manage documents, it's interesting to note how many processes are actually manual paper based processes when it comes to documents.
For example, in corporate accounting and finance, which is a business function that every organization has, every supply chain, as level research pointed out in October of last year, that 65% of invoices and payment related documents come in via mail, or via e-mail, and are printed out in order to do the data entry. Imagine that 65% of the documents that run a core area of business are still manually handled.
So even though we have the ability to automate tasks, and automate the processes that are tied to them, the processes for handling documents and content are still based upon a manual: document processing paradigm.
one where you're opening up a document, information man.
So you may have automated other parts of your process, but if you, but many organizations, have not fully automated their paper based processes. And that's the next frontier.
So lately, we have heard about the concept of the digital workforce. And there are many different definitions of it.
If, if you hear presentations, or if you hear discussions around robotic process automation RPA, you're 10, tending to think that that digital workforce is the same thing as as an RPA bot. And it is not. There are different classes of digital labor, and they are evolving towards smarter, more intelligent ways of doing, doing work, and getting work done.
And those include the application of rules, moving to the processing of unstructured data and other information, And then finally, bringing in machine learning and neural networks to make our system smarter.
And one of the critical capabilities in the digital workforce, which brings together artificial intelligence, forms of task automation, such with RPA, process mining, and other insights to create what's literally a digital assistant for the knowledge worker.
We see one of the critical capabilities is using AI to crack the code on unstructured text. For example, some of the most difficult documents deal with contracts, commercial leases, liability, regulatory filings. We now have the ability to automate using named entity recognition and artificial intelligence.
And nowhere is this more important business than in businesses that handle a lot of documents.
This is a real example of a mayor, of a major organization who literally dealt with millions of pages of documents, and how do they get through all those documents, how do they handle those records When, when having that information can mean the difference between business running and not running.
So, the volume of documents can be staggering for any organization. We need to find a way to automate them.
And I'll close with this final self satisfaction section that looks at how processes and humans, how processes interact with humans and content to make decisions.
Some predictions that have been made, digital intelligence is a key to successful transformation and it starts with process. According to Gartner, by 2024, organizations will lower operating costs by 30%.
By combining hyper automation technologies. With redesigned operational processes, McKenzie points out the enterprises that do the best at automation will take time to consider how they redesign their processes. Already, there's a relationship being noted here between automating and process.
So, automation is not simply about automating a process.
It is about redesigning your process, to make it work with the automation capabilities we now have. Forrester talks about optimum automation, bringing together machine learning and AI, to make your automation processes smarter, and to think more like humans.
And, again, the key to automation here is not necessarily replacing humans, but making your knowledge workers, those key humans, who make decisions for on behalf, and on behalf of customers every day, making those knowledge workers smarter, by using technology to become the assistance, that help them with the task of organizing, making sense out of, and making decisions on, on the content that they deal with.
At the core of automation, as processes, and you can't understand processes, if you don't have the right intelligence tools, for understanding, specifically the content and the knowledge work, When we meet with customers who are outlining their processes, the whiteboard, as you see here, is a classic way of outlining how a process works.
But very quickly, the, the hard written flow of tasks and workflow and exceptions.
Meet some problems and that is, as you see here, the sticky notes.
And the sticky notes contain different exceptions and more often than not in a process, those sticky notes involve a particular kind of decision and a particular piece of content, in, for example, processing a mortgage or a loan, you need proof of identity. You need proof of residence, proof of income and proof of employment, and where do those documents come into the process? Well, they can come in anywhere, and they create exceptions.
So, when many organizations attempt to discover and understand the processes, they use a lot of, of arrows, and lines, and sticky notes moving all around, because each one of those little sticky notes, each one of those documents, each one of those decisions, creates an exception that disrupts the process. And it's normal flow. And so, we have to use technology to be able to bridge that gap between that easily managed, easily automated processes, and those parts that are not.
So, the digital intelligence approach that, that, that we're seeing emerge, brings together process awareness, which includes process discovery, analysis, optimization, as well as ongoing monitoring, and alerting on how that process is performing against your KPIs against, against your other performance metrics.
But, increasingly, that process awareness is starting to look at, not only the data, but using the data, and the, the logs of activity to discover the human actions. What does taking place and the human actions, and the content dimension of that.
And, that brings in the content transformation element of digital automation and intelligent approaches to doing it. It allows us to capture the content as it enters the business process, not late in the business process not as a workaround to the business process, but as it enters the organism at process as a key point of decision.
So, digital intelligence really complements and extends the capabilities of the digital workforce that organizations are building to automate knowledge work, and to help automate knowledge work being more effective.
And digital intelligence is helping to enable both process awareness and content awareness for the purposes of transformation.
And I'll close with this quote from, From technology writer, Dan Newman, who wrote, in Forbes about a year ago, that there is a key difference between optimization of process and transformation of process.
As organizations seek to transform process, to deliver best or better, better customer experiences, there, they have to rethink how the process works. Not just add automation to it, any any points out if you're pursuing tech adoption for the company's benefit? to save time, improve processes, avoid those day-to-day side, Time sucks. Like, returning the same e-mails over again, over and over again, are looking for that invoice, the process, or sorting through your sales lead.
You're likely only optimizing an existing process, You're not transforming the process. So, optimizing an existing process can only give you incremental improvement in that process, but being able to transform it radically to rethink that process, from the standpoint of what the approaches to automation, what your intelligence is able to show for you, that is how organizations, smarter organizations, are transforming their process.
And it's all about bringing together people and experience, process intelligence, and content transformation.
So, that, the last frontier of automation, which is expert knowledge workers: with, with lots of experience, using that experience to make the best decisions for customers, Bringing technology, and automation together digitally, in ways that enable those knowledge workers to be effective.
And that is creating processes and automating processes for those workers, will help us post, cov it, to make automation work in ways that it has never worked before.
That is fantastic, graduates! Thank you so much for that.
We, we have lots of questions coming in, so I'm going to optimize or maximize our time together here. I'm gonna ask you ready to click the button that says stop showing screen so that we can the audience can see us and the bigger screen still not perfect And I'm gonna invite Richard back with us to Richard come on back because you're going to provide some insights our audience as well. I'm gonna, I'm, there are lots of different themes that have emerged here in terms of questions.
And I'm gonna start with something that sets sets the stage for a lot of organizations. And I think you did a marvelous job of pointing that out.
Then in the world of advanced technologies, a lot of organizations are still dealing with very basic processes and paper based processes.
And, uh, And the And the idea of automation has been around for a long, time, but, it has not become a reality for them.
So, the question is, with all the advances that we have seen across industries, what would be the best approach, when it comes to adoption of new technologies for business value creation?
What would be the, the, the first few steps, if you will, that organizations that have not done automation, at scale, yet, should take, choose, to do, to create the automation systems them that create the most value for their organizations. Or some of the best practices, if you will, to get started on the right foot.
Reggie, I'd be happy to give a first take on that, and then you can add to it. I would think that the first thing, that organizations need to do, is to understand their existing state. You need to understand your process, and understand where the friction is, so that you can, before you do any kind of automation, you want to have an idea of where you want to go with that. Not just repeating what's already there. But understanding where the problems are, and what things can be done better as you're doing your automation. Reggie.
I would add to that that process discovery is an essential first step.
And it's like, I can't help think about the 12 step analogy.
The first step in, in changing your life is recognizing you have a problem and and that has been borne out in inexperience in in the evidence that I've seen.
Organizations that have adopted different forms of automation. For example, RPA.
one of the things that they say over and over again, that perhaps the single most important factor in getting the return on investment, is actually doing process discovery.
And in automating document driven processes, those those same organizations have actually quantified it, and said about 90%, the return on investment they've had for a document automation or content automation process.
Our project is actually been in discovering the processes, and realizing, number one, what they can automate, and how to automate it. Number two, what processes just don't work?
And, number three, where does the process, and where does that, that particular behavior need to change, in order for this automation to work?
And it's regulatory for organizations doing that discovery, and doing it across the, the organization.
But, most importantly, it's not simply discovering the workflow.
And event elites do Event B, et cetera. Because the data now give us the ability to see more, and that is how humans interact with the process. What is the time on task that people spend, and what kind of activity are they doing?
Are they spending a lot of their time chasing down a data field, for example, like finding a customer number, even though, you know, they're able to see it in the document. Simple things like that.
People can spend a lot of time on it. Their processes are broken.
Though, those insights are terrific from both of you.
It's very common that people who work of tech knowledge, present technology, solution to problems, because, you know, when you're only, when your only tool is a hammer, everything looks like a nail, right? And in the book, but you'll show the depth of expertise and experience, that you have to note that it's much deeper than that.
And thank you for sharing that with our global audience.
So, absolutely, you know, understanding what, which ones are your critical processes? And then understanding how they deliver value to two stakeholders is critical and a non-trivial step.
Let's assume that organizations have done a decent job at identifying those now.
And now we are ready to start automating them. We let, we went through and we streamline them. We eliminate non value added activities. We reduce non value add activities and are ready to automate.
Question, now, becomes is that people can get overwhelmed by the, just the number, the sheer number of technologies available nowadays, right. I mean, do I do RPA or process mining, or implement an LP? And you can get into enterprise architecture type of approaches.
Is there some sort of mapping, if you will, on, on how you approach automation, in the, in the best, possible way. Once you decide you're going to automate, what are some technologies that are ready for prime time right now? Versus a bit of a hype that may exist around some of the technologies?
So I'll, Again, I'll take a first crack at it.
Then I think that, we've talked about process mining, which allows you to get a view as to what your your overall environment looks like.
The issue with that, is it process mining is somewhat limited, in that it only really works well with processes that are very standardized and repeatable.
You hear us refer to process intelligence.
This is really just an extension of process mining that replaces the the reliance on a schema diagram showing you a picture of your operations with more Numerical Analysis, and as such.
It works with all processes, regardless of whether they're ad hoc with, with almost no standard path, and every path is different. So once you have this ability to overall view what's happening within your environment, and get down to the nitty gritty details of the numeric of where things are taking long, where there are problems, you then have the ability to also define behaviors, and see how these process behaviors relate to the results you're getting. Once you have this view in the process, That's when you have an understanding of what other technologies you need. Whether you're talking about being a part of a platform, so that you've got content intelligence as a part of this.
Whether you're talking about using RPA, two of the areas that clearly are important to use along with your automation process, you have an understanding of how to leverage these areas.
So for instance, RPA is something that gets discussed a lot, but you need the ability to not just choose what processes to automate. But to be able to understand what is the value of automation. Not just in automating a given task, but the overall larger process. How much of that task automation really help you to monitor the process, too.
Use predictive analytics to be able to determine when a developing situation might lead to a problem and deal with it before it's a problem. And take action. It's sometimes referred to as a control plane, a a set of technologies sitting outside of your various systems of record, and users that can watch over this and to, and take corrective action as necessary.
While this is still ongoing, Reggie, I would just add a few things to that.
Is that once you understand your process and have identified the friction points, and typically, the friction points occur with when, when humans are in the process by necessity.
Because processes are designed two as tools to help humans be more effective. Especially in so many of the industries who will be presenting and interacting in this conference.
Banking, insurance, health, care, and those organizations that rely on experience, when experienced, humans have to make decisions, based upon certain kinds of information.
Typically, the process is not what as well designed for that.
And they approach us to automation, can be deployed for enabling that robotic process automation RPA can be used to automate assistant tasks, like reading an e-mail, an M by a box, to look for this particular kind of document, and then routed or do some verification.
But, that also needs to work in conjunction with artificial intelligence, that actually reads the document, and understands it, and then, can make help, can automate the decision making, of the, those, the information, that, that is revealed from those documents.
All of that is now possible.
That is fantastic. We are out of time right now. But, I have a quite one quick ask from you. I mean, what, you, both, and the whole team at Abbey, are doing, in advancing the implementation of Smart Technologies, the real create value is outstanding. For our audience. Those of us who want to learn more about the Abbey journey and what you're doing, what is the best way for us to connect with you and follow along what you're working on.
Well, there, we do have some follow up resources that, that we will be distributing after after this presentation. Of course there, abby dot com provides a host of resources. Not only understanding who we are, what we do, but also what our customers are doing and how our customers are solving these problems every day.
That is excellent. And I want to remind our audience that if you look under the handouts portion of the goto Webinar interface, you have handouts that you can download right now to get additional information. But for now, Reggie and Richard, thank you so much for sharing your expertise for a global audience today. We're all better off as a result of that.
Ladies and gentlemen, that was Reginald a twig and Richard Robin from Abby sharing their expertise on the journey of digital transformation and the use of smart technologies to create value in our, in our businesses. Now, we're going to take a break. And, at the top of the hour, we're going to bring another cross industry expert, Kevin ..., who is the Enterprise Customer Success leader for Sigma view, is going to be here with us. And he's going to talk about how to drive efficiency and customer excellence on your business transformation journey. Again, with, in his role as ..., He works across multiple industries, around the world, scene, all.
That's happening with respect to best practices for efficiency and customer excellence on the transformation journeys of clients, in them, in with very distinct business models. So we look forward to learn, from, from his expertise at the top of the hour. And again, a reminder for you that you can download additional resources under the hands our Hands Out portion of the goto Webinar interface. You can also check out undermining shows up here is on LinkedIn. And you can ask additional questions, You can interact with our speakers. You can interact with myself. And you see the posting under my name on LinkedIn, for digital process automation live. So, for now, we'll take a break, and I will see you back at the top of the hour. Thank you.
Reginald J. Twigg, Ph.D.,
Director of Product Marketing, Digital Enterprise,
With over two decades of experience in Enterprise Software, Reginald Twigg is an expert in automating document processing applications with artificial intelligence technologies. At ABBYY, he is instrumental in bringing Digital Intelligence and Intelligent Document Processing innovations to enterprise markets, with a particular expertise in the financial services and insurance sector.
Prior to joining ABBYY, he spent a decade in senior product marketing roles at IBM, where he introduced the first revenue-generating applications for Cognitive Computing approach to analytics and launched advanced Artificial Intelligence offerings for Enterprise Content Management. He holds a Bachelor of Arts degree from the University of Southern California and a Ph.D. in Speech Communication and Rhetoric from the University of Utah.
Product Marketing Manager, Process Intelligence,
Richard Rabin is the Product Marketing Manager for Process Intelligence at ABBYY, a Digital Intelligence company. He works closely with global enterprises to help them better understand and optimize their business process workflows, bottlenecks, and how to select the initiatives that will yield the most business value with intelligent automation, and how they will impact overall operational excellence.
Richard has a remarkable academic background in Computer and Information Science and AI and has more than 35 years of software engineering expertise. He previously worked as a Senior Solutions Consultant at Appian, where he led sales of Appian’s digital transformation platform primarily in the pharma and financial services industries. Before that, he led his own consultant business, where he provided services for Kofax Insight in the areas of business intelligence, process intelligence, and behavior-based analytics.
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