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Episode #60: Why Lasting Automation Success and Competitive Advantage Require Process Excellence – FireStart’s Robert Hutter

March 1, 2021    Episodes

Episode #60:  Why Lasting Automation Success and Competitive Advantage Require Process Excellence

In today’s episode of Ayehu’s podcast, we interview Robert Hutter, Founder and CEO of FireStart. 

“If you can’t describe what you are doing as a process, you don’t know what you’re doing.” That quote was coined by William Edwards Deming, the famous 20th-century management consultant, who viewed process excellence as a sine qua non to performance excellence.  When it comes to digital transformation, process excellence is very much foundational to automation excellence.  Yet surprisingly, many organizations can’t fully describe what they’re doing as a process, suggesting that Deming was more prescient than many realize.

One man on a mission to bring process excellence to the mid-size market is Robert Hutter, Founder and CEO of FireStart. His firm focuses on human-centric process modeling, documentation, and enterprise workflow automation, resulting in holistic digital transformation.  We chat with Robert to learn how enterprise workflow automation differs from robotic process automation, the natural limitations facing citizen developers, and why you should value process as the most relevant asset in your company. 



Guy Nadivi: Welcome everyone! My name is Guy Nadivi and I’m the host of Intelligent Automation Radio. Our guest on today’s episode is Robert Hutter, Founder and CEO of FireStart. FireStart, for those not familiar, focuses on process modeling, documentation, and enterprise workflow automation in the mid-size market. This sort of holistic approach to automation is something we haven’t really dived into yet on the podcast and we don’t get a chance to talk much about the mid-sized market either, which is expected to be booming for automation. So having Robert on gives us a chance to kill two birds with one stone and hopefully learn some new things about both of these areas. Robert, welcome to Intelligent Automation Radio.

Robert Hutter: Hello everyone. Thanks for the invite.

Guy Nadivi: Robert, can you please share with us a bit about the path you took that led you to launch FireStart, and how you came up with that name?

Robert Hutter: Yeah, sure. So I originally started FireStart back in 2008, together with a colleague of mine. And from my professional background, I’m a software engineer, so I started software engineering and started building applications in the markets. And whenever we came across customer problems and we tried to fix them in the applications we were building, the process was always a very key element of the architecture and the fulfillment of the requirements in the end. But it always was a very hard topic to tackle. And since I was always a big fan of a model-driven approach and how to tackle problems and we have a fast track to building solutions, that was kind of the core idea why we started FireStart, to really have a platform that on the one hand can help you keep the governance on your process development on the business side, but makes it a lot easier in the translation to the automation and the IT architecture involvement. And with that in mind, how did we come up with the name? So we wanted to have something with emotional attachment and fire is a very emotional element that everybody knows, and usually has a very positive attitude towards, and it also has a little destructive element in it, which at some point you need, because very often you have to tear down old-fashioned mindsets and silos in order to let new processes and agility grow. And that’s also a major part in the name. And the third part, it’s like the “Start” is like, we want to get in production quickly. So it’s not about beating around the bush with the process, but the process is a core element, but you want to deliver results in a very fast fashion. And that’s like getting up to speed very quickly that also reflects in the name.

Guy Nadivi: So process architecture and governance are big parts of what you do at FireStart. Why are those such important elements in building a lasting automation strategy?

Robert Hutter: In general, whenever you want to build something, you should have a plan before you start building. Just like as an example, if you want to build a house you’re not starting right away building it and then see where you end up, but you would want to have a decent plan before you start building that gives you an idea how it looks, that gives you an idea how expensive it will be, or will it fall apart? And that’s a major element in efficiency on delivering the right results because if you have a plan before you start building it, you also have a better expectation about the results. And then once you have a plan, you can repeat the process. You can build multiple houses on the same plan that you have initially designed, and then it’s worth spending more time on the plan, so the better the execution, you can just get better and better and faster and faster. And this is why very often have the feeling that when you don’t have a proper process governance and process strategy in place, you very often end up in dead ends and you are kind of reinventing the wheel each time and you have nothing you can build upon. And processes are very heavily dependent on usually, so they’re not living side-by-side. But you build processes on top of other processes and therefore, you also need to manage the governance and translation between process changes, which is very essential if you want to make business process automation a part of your digitalization strategy. And it’s about all the segregation of duties. So you might have somebody doing the design, you have somebody else doing the cost calculations. You have somebody else doing the actual building the house. So process architecture is also about having segregation of duties, but that at the end of the day, everybody can collaborate on working together as a team, creating the results. And this is also what process management and workflow automation, it’s about getting people together so that they actively can work as a team in the whole engineering process.

Guy Nadivi: So you’re talking about a process-first approach, which of course makes a lot of sense, but I’m curious, what other approaches have you seen in the market?

Robert Hutter: Well, in my opinion, process is pretty much the most critical asset that you should start, where you want to build a design upon. And from the other approaches I’ve frequently seen in the last years, either they are very application-centric, let’s put it that way. So usually you start trying to squeeze an architecture into one application. And you always start with the boundaries of your application in your process design, which is…since a process is mostly a natural element that lives beyond a single department or beyond a single application, a very bad approach, because it already constrains you in the way, the creativity you can imagine about how this process could look and feel in the end. Another approach is very, let’s say data-centric or document form-centric, where everything is around the document that you’re processing and that is like the key artifact that you’re managing in the process. But then it’s very often hard to imagine parts of the process where it’s just about communication, where it’s just about collaboration, where not a single document is involved at all. And so I would always try to also start with a people-centric approach because when you do process design and you do automation, it’s mostly about making the day-to-day work of people easier to complete and to accomplish and to get satisfied in the work they do. And so I would really enforce a people-centric approach and start with the process design first, like a process-first approach and then on the second-hand, talk about data integration, talk about application design. But the process should be the core asset to start in the architecture and design.

Guy Nadivi: We’re hearing more and more about process mining and other AI-based discovery platforms being deployed as part of digital transformations. Robert, what role do you foresee process mining will play in enterprise workflow automation.

Robert Hutter: It’s definitely a topic that is very much picking up and it’s just like a technology that you can use to answer a very simple question, which is what is the current status in my day-to-day business, with the processes that we already have in place and that we already run on specific applications? And as easy as that question might sound, hardly any company is really familiar with what’s really going on in their applications. And either you bring in a lot of external consultancy or you have internal development teams that start analyzing to find out what the status quo is. And that, of course, takes a lot of time and is also very resource intense and costly, just to find out what’s going on in my processes. And process mining at the heart, is technology that can really shorten the time from, to understand what the current status quo of your processes is and to really raise the full visibility on the processes. And not like the PowerPoint. Nice to have visibility, but really like the brutal hard day-to-day facts about which variations you have in place, you never imagined that they could be in place. And it’s just like a good starting point to get the full truth of your process, so that you actually find in a quicker and more efficient way, where to tackle the problems. So you might find some variations of the process that you don’t want to have because they would violate maybe data privacy rights. And then you can start working with RPA and workflows to get rid of this unguided processes and bring in more structured and guided processes in place, so that at the end of the day, from the many thousand variations you might have, you can come down to the dozens of design variations that you want proactively establish at your company. And process mining just makes the fast ramp up for this first discovery phase – what’s going on in my process world today.

Guy Nadivi: Now, speaking of RPA, what is the difference between enterprise workflow automation and robotic process automation?

Robert Hutter: Yeah, it’s a term that very often gets mixed up in the market from my experience and they sound similar, but they’re heavily different topics, in order what problem do we tackle with them? So when we talk about enterprise workflow automation, we come from a organization or company perspective. And the goal here is to create process standards where all the applications and users are aligned to the corporate guidelines, so that the process runs as smooth and efficient as possible and also fulfills the enterprise requirements. The product process automation starts from the end user to tackle automation problems from a personnel perspective. So you would want to… Robert is always doing the same repeating tasks, so we try to build a software robot that can help Robert doing his job better. But it works in this scope from a individual perspective and it usually also works in the governance of the individual user. So I’m personally responsible for building the robot, for maintaining the robot, for phasing out the robot, if not needed anymore. So it’s in my personal governance. If we talk about enterprise workflows, the whole governance is a lot more difficult and complex because you need to have multilayer architecture. You need to have staging in place. You need to deal with data access and security. So you might end up in a conflict because the company wants to have standardized processes, and the user would maybe want to have highly individual requirements fulfilled with his robots. So in a ideal world, these should originally work hand-to-hand together and so that you can have the individual flavor and the enterprise standards combined in one automation strategy. And think of it like if you compare Excel sheets with SQL server. The one is like holding the governance on the corporate data, making the access available for the users, but it’s one single point of truth, where people can go and pick up the data in a governed and maintained way. Excel sheets, at the other hand, I would like to have my personal calculations and work with the standardized data, but with my personal pie charts that I just like, and nobody else. So I can change the Excel look and feel in my personal flavor, but I would work with the corporate data and standards that the SQL server provides me. And this is how enterprise workflow and RPA should be seen as technologies that just fulfill different requirements that automation needs.

Guy Nadivi: Robert, there’s a lot of talk these days about low-code/no-code automation and the rise of citizen developers as a result. When will orchestration tools be simple enough to use, that they’ve democratized automation for the masses?

Robert Hutter: Yeah. The markets, as you said, there’s like heavy code, low-code/no-code, as a way how to approach our technology problems or application engineering problems. Of course, heavy code is not the way to go because this is where we come from. It’s complex. It causes a lot of maintenance and a lot of costs on top. On the other hand, the other extreme, no-code is very much hitting the roof too quickly, when tackle more complex process problems. So ideally the way we want to tackle problems is a low-code approach, which applies to the 80/20 rule. So let’s say 80% of the engineering you can do with involving business users in certain parts of the process and just doing like the last mile, the last 20% for specific more complex parts of the process, where you actually need to go to a coding level. But in that combination, you have both scopes on how to tackle a problem in a meaningful resource usage, to engineer the solutions that you want to have. And I would definitely see low-code as the future because like the citizen developer approach, with the end goal, every citizen developer can do automations and application engineering on his own. I wouldn’t see that this should be the goal to reach because we already came from excellent macros and you know where we ended up with that one, and you see like the similar risk here, that it’s at the end of the day about engagement, that different stakeholders can do different parts of the engineering process. But at the end of the day, it’s for a citizen user, I would say. And the more understanding a citizen user has from the engineering process, the better he can be involved in the whole requirements, engineering, and testing, and roll out of the solutions. But it’s not necessarily that I see as the big goal that these users should be the one engineering the process. Maybe as an example, if you pick a manufacturing customer. So there are professionals coming into assembling a production line from electricity, from manufacture, putting the right pieces of the machinery together, with the goal that the workers then working in the process are perfectly aligned with every step to do in the process. And the same applies to process engineering. You need to have engineers, you need to have architectures, that know their profession in order to make the whole design right and that everything fits perfect. But it’s a profession and you need to bring professionals into the process because you don’t want to have the workers, every worker building his own assembly line, so that he needs to have all the knowledge because he will not be able to have all the knowledge to do that. And this is the way how I would see it.

Guy Nadivi: Getting back to enterprise workflow automation. Can you share results from one or two of the more interesting enterprise workflow automation projects you’ve worked on?

Robert Hutter: Yeah, sure. So we had really a lot of different customers and errors in the last two years, ranging from big corporates to really small businesses, applying BPM and workflow automation. Maybe one from the larger enterprise cooperates. We had a really successful project at a very large retail company with about 30,000 people worldwide, where they really had the need of applying a unified workflow strategy along the company, so that people are really harmonized in the way they are engaging in processes and just be more efficient in the way they work it. And it was actually a pretty cool project. We, from zero to production, had about two weeks to really roll out the first workflows for about 500 users involved. And there was literally no announcement, no training involved. And once we kicked off the project, the first two projects, which were about, I think one of the cases was HR onboarding, they had around 200 onboardings a month that they needed to schedule. And on the other hand, the second use case was the contract management with their suppliers because they have about 4,000 suppliers, where they need to do regular updates on the contracts they have. And these were the two use cases we rolled out. And the funny thing was like, after the rollout, the customer turned completely radio silent for about two months. So we had no feedback about how it’s working, what is the feedback? And then after two months, I got the call from the project manager that was leading the project. And I just approached him, saying, “Hey, how’s it going? What is the feedback?” And then he paused. And the first thing he told me was like, “Oh, it’s so cool. It’s so cool. I have to tell you.” And this was really just a very good memory because it really, the whole emotion spread out of him and you really could see the emotional attachment to the solutions we have built. And it really rolled out like clockwork. And they already had, after the first two months about another 20 projects in the pipeline that came from the business users with a lot of problems. They haven’t really figured out how to tackle them. But with that approach they really had a complete different way of thinking and how they tackle now, other problems. And we doubled the speeds of the processes within the first two months. The engineering effort was a fraction of multiple of 10, versus the heavy code approach they used to have. So they used to code everything on top of SAP, which was the core ERP backbone system. And now with the more agile process driven approach and FireStart, they virtually brought down the efforts and speed with a multiple of 10, which is pretty huge. And over time they rolled out, I think now, they are at 100 plus projects they executed on our platform. And they are a super happy customer for us for many years. And this was really very cool to see how our core technology and principles could be applied so successful on such a huge organization. On the other hand, we had a small customer in Switzerland, which is the Funk Insurance Group. They are managing a lot of processes regarding insurance management for the clients. And their biggest pain point was always that they were super dependent on the vendors with every little process change. They always had to go to the vendor and kind of begging for a change. And it was super expensive for every little process step that they turned. They would get an invoice with a couple of thousand euros for the adaption of the process. And that was kind of what was really frustrating for them. And then they got in touch with FireStart, installed the platform. Then they didn’t really know for one or two months how to tackle it because they had no experience. And then they called us. “Okay, we will lock ourselves up for a week. We will even change the building and we will do nothing else, then work our knowledge in FireStart and align our internal users on this newer way, to approach.” And after that one week, they were 100% up to speed, to do every process development and change completely on their own. Not with us involved, not with a partner involved. They kind of really got the freedom back to be 100% in the driver’s seat of their own process engineering. And this is also like a feeling, if you’re always dependent on whatever, it kind of frustrates you because you always have to, the feeling that you need to go back for something. And that’s especially the frustration that you mostly see in the business side, that IT resources are limited and there’s a lot of lost in translation effect and that causes a lot of frustration on both sides. And it’s really cool to see this freeing up the process and getting my freedom back and my process design was implemented on a small customer that literally had no IT experts, or software engineering experts in the team. It was mostly driven by the organization development department. And that was another thing, like really cool project, at the other end, on typical customer sizes that we address.

Guy Nadivi: Cool stuff. Given your experience with enterprise workflow automation, what do you think are going to be some of the biggest disruptions we’ll see in the next one to three years, with respect to automation, AI, and other digitally transforming technologies?

Robert Hutter: Yeah, of course, AI is currently the big thing in the market, since the technology is evolving that much and really at a incredible speed, which is amazing. And it will kind of freely enable a lot of predictability in the engineering. So if you think about predictable outcomes, predictable resource allocations for a specific process. So the better you can predict a certain future state, the better you can start now aligning towards it with your process adaptions. And I think in that regard, AI will play a massive role in how much predictability you will get into your process design. And on the other hand, data, the amount of data sets available is also massively exploding. You see a lot of data platforms popping up that really can provide your data as a service. And that again, in combination with AI, super powerful. And as we already discussed process mining. I would see process mining as a key technology in that space, helping in the translation from the raw data to the more intelligent process insights, that you can then again take as a starting point for initiating enterprise workflows, initiating robots to do the right job in the right timing and getting the state of predictability, is key in that regard. And I think a third thing that I would see in the future is in general, the way how you approach process design. Because from the history, it was mostly somebody who knows the process, designed the process, in order that other people can use it and run the process. And I think it’s always like the adaption always comes from the design part. So always the process manager has to be involved to adapt the process. And with that technologies, I think that will also be more self-aligning and kind of self-adapting, so that the process designer will start building the process design on top of just watching people doing the work. And with people adapting the work, it will have an implication on the process design and the change that will help in the background. So I think it will really reward the whole way, like learning by doing and by people changing their behavior, it will also change the process design in the backbone and therefore be a lot more self-adapting to changing to new requirements in the market.

Guy Nadivi: Robert for the CIOs, CTOs and other IT executives listening in, what is the one big must have piece of advice you’d like them to take away from our discussion, with regards to implementing enterprise workflow automation at their organization?

Robert Hutter: The first piece of advice would be that whatever you do, start with the people in process first approach, because this is like the foundation to bring out successful outcomes of whatever you do. Then second advice would be don’t shoot for this. Like everybody should be able to fully do automations because it’s like there are professionals that should build the architecture, bring in automations and there are business users or citizen users that should consume the solutions with the least complexity. And this is the way to go. Remember that enterprise workflow automation and robotic process automation are at the end engineering disciplines. So you should also tackle the problem like you would tackle any other engineering problem, thinking about architecture, thinking about abstraction, thinking about reusability and thinking about the overall strategy behind it. And really value the process. It’s the most relevant asset in your company. It what separates you from other competitors and peers in the market and it’s the most relevant asset that will define the success or failure of your organization. And coming to a famous quote from Charles Darwin, “It’s not the strongest, the most intelligent ones that will survive. It’s the ones that are most adaptable to change.”

Guy Nadivi: Wise words. Always good to end on a note about evolution, which is very applicable to our field. Looks like that’s all the time we have for on this episode of Intelligent Automation Radio. Robert, it’s great hearing about an automation company focused on the mid-size market because it not only reflects the growing reach of automation, but also the growing opportunity for companies such as yours, with a unique solution. I think that bodes well for everyone and I thank you very much for sharing your insights with us on the podcast today.

Robert Hutter: Thanks a lot for the invite. It was a pleasure.

Guy Nadivi: Robert Hutter, Founder and CEO of FireStart. Thank you for listening everyone and remember, don’t hesitate, automate.



Robert Hutter

Founder and CEO of FireStart 

Robert Hutter is founder and CEO of FireStart, one of the leading software vendors for Business Process Management and Enterprise Workflow Automation. After graduation with a Masters Degree in Software Engineering, he worked in the banking industry as an application development and enterprise software architect before founding FireStart. Today, Robert is supporting process digitalization and transformation programs with the FireStart iBPMS platform at customers like Swarovski, KTM, and LENZE, helping to connect the dots between people, process and technology.   

Robert can be reached at: 

LinkedIn: https://www.linkedin.com/in/robert-hutter-78413b19/ 

Email: r.hutter@firestart.com 

Website: www.firestart.com 

About FireStart: https://youtu.be/jcyG9c5dMos 

Quotes

“…when you don't have a proper process governance and process strategy in place, you very often end up in dead ends and you are kind of reinventing the wheel each time and you have nothing you can build upon.” 

“So process architecture is also about having segregation of duties, but that at the end of the day, everybody can collaborate on working together as a team, creating the results. And this is also what process management and workflow automation, it's about getting people together so that they actively can work as a team in the whole engineering process." 

“…ideally the way we want to tackle problems is a low-code approach, which applies to the 80/20 rule. So let's say 80% of the engineering you can do with involving business users in certain parts of the process and just doing like the last mile, the last 20% for specific more complex parts of the process, where you actually need to go to a coding level.” 

“Remember that enterprise workflow automation and robotic process automation are at the end engineering disciplines. So you should also tackle the problem like you would tackle any other engineering problem, thinking about architecture, thinking about abstraction, thinking about reusability and thinking about the overall strategy behind it.” 

About Ayehu

Ayehu’s IT automation and orchestration platform powered by AI is a force multiplier for IT and security operations, helping enterprises save time on manual and repetitive tasks, accelerate mean time to resolution, and maintain greater control over IT infrastructure. Trusted by hundreds of major enterprises and leading technology solution and service partners, Ayehu supports thousands of automated processes across the globe.

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Links

Episode #1: Automation and the Future of Work
Episode #2: Applying Agility to an Entire Enterprise
Episode #3: Enabling Positive Disruption with AI, Automation and the Future of Work
Episode #4: How to Manage the Increasingly Complicated Nature of IT Operations
Episode #5: Why your organization should aim to become a Digital Master (DTI) report
Episode #6: Insights from IBM: Digital Workforce and a Software-Based Labor Model
Episode #7: Developments Influencing the Automation Standards of the Future
Episode #8: A Critical Analysis of AI’s Future Potential & Current Breakthroughs
Episode #9: How Automation and AI are Disrupting Healthcare Information Technology
Episode #10: Key Findings From Researching the AI Market & How They Impact IT
Episode #11: Key Metrics that Justify Automation Projects & Win Budget Approvals
Episode #12: How Cognitive Digital Twins May Soon Impact Everything
Episode #13: The Gold Rush Being Created By Conversational AI
Episode #14: How Automation Can Reduce the Risks of Cyber Security Threats
Episode #15: Leveraging Predictive Analytics to Transform IT from Reactive to Proactive
Episode #16: How the Coming Tsunami of AI & Automation Will Impact Every Aspect of Enterprise Operations
Episode #17: Back to the Future of AI & Machine Learning
Episode #18: Implementing Automation From A Small Company Perspective
Episode #19: Why Embracing Consumerization is Key To Delivering Enterprise-Scale Automation
Episode #20: Applying Ancient Greek Wisdom to 21st Century Emerging Technologies
Episode #21: Powering Up Energy & Utilities Providers’ Digital Transformation with Intelligent Automation & Ai
Episode #22: A Prominent VC’s Advice for AI & Automation Entrepreneurs
Episode #23: How Automation Digitally Transformed British Law Enforcement
Episode #24: Should Enterprises Use AI & Machine Learning Just Because They Can?
Episode #25: Why Being A Better Human Is The Best Skill to Have in the Age of AI & Automation
Episode #26: How To Run A Successful Digital Transformation
Episode #27: Why Enterprises Should Have A Chief Automation Officer
Episode #28: How AIOps Tames Systems Complexity & Overcomes Talent Shortages
Episode #29: How Applying Darwin’s Theories To Ai Could Give Enterprises The Ultimate Competitive Advantage
Episode #30: How AIOps Will Hasten The Digital Transformation Of Data Centers
Episode #31: Could Implementing New Learning Models Be Key To Sustaining Competitive Advantages Generated By Digital Transformation?
Episode #32: How To Upscale Automation, And Leave Your Competition Behind
Episode #33: How To Upscale Automation, And Leave Your Competition Behind
Episode #34: What Large Enterprises Can Learn From Automation In SMB’s
Episode #35: The Critical Steps You Must Take To Avoid The High Failure Rates Endemic To Digital Transformation
Episode #36: Why Baking Ethics Into An AI Project Isn't Just Good Practice, It's Good Business
Episode #37: From Witnessing Poland’s Transformation After Communism’s Collapse To Leading Digital Transformation For Global Enterprises
Episode #38: Why Mastering Automation Will Determine Which MSPs Succeed Or Disappear
Episode #39: Accelerating Enterprise Digital Transformation Could Be IT’s Best Response To The Coronavirus Pandemic
Episode #40: Key Insights Gained From Overseeing 1,200 Automation Projects That Saved Over $250 Million
Episode #41: How A Healthcare Organization Confronted COVID-19 With Automation & AI
Episode #42: Why Chatbot Conversation Architects Might Be The Unheralded Heroes Of Digital Transformation
Episode #43: How Automation, AI, & Other Technologies Are Advancing Post-Modern Enterprises In The Lands Of The Midnight Sun
Episode #44: Sifting Facts From Hype About Actual AIOps Capabilities Today & Future Potential Tomorrow
Episode #45: Why Focusing On Trust Is Key To Delivering Successful AI
Episode #46: Why Chatbots Are Critical For Tapping Into The Most Lucrative Demographics
Episode #47: Telling It Like It Is: A 7-Time Silicon Valley CIO Explains How IT’s Role Will Radically Change Over The Next Decade
Episode #48: How Microsoft Will Change The World (Again) Via Automation
Episode #49: How One Man’s Automation Journey Took Him From Accidental CIO To Unconventional VC
Episode #50: How Automation Helped LPL Financial Grow Into The Largest Independent Broker Dealer In The US
Episode #51: Why Cognitive Architecture Might Be An Early Glimpse Of A Future With Artificial General Intelligence
Episode #52: Chatbots Aren’t Human, So Don’t Expect People To Pretend They Are
Episode #53: Why End User Experience May Be A Better Measure Of Automation Success Than ROI
Episode #54: How Digital Dexterity Will Generate Competitive Advantage For Agile Enterprises
Episode #55: Is It Time To Start Hiring Digital Coworkers So Human Staff Can Spend More Time With Customers?
Episode #56: How Intelligent Automation Will Empower People, Transform Organizations, & Improve Our World
Episode #57: Can The World’s Largest ITSM Vendor Innovate Fast Enough To Maintain Its Meteoric Growth?
Episode #58: What Works? A Senior Partner From Bain Articulates The Keys To Automation Success
Episode #59: Why 2021 Is The Year Organizations Will Start Widely Trusting AI

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Disclaimer Note

Neither the Intelligent Automation Radio Podcast, Ayehu, nor the guest interviewed on the podcast are making any recommendations as to investing in this or any other automation technology. The information in this podcast is for informational and entertainment purposes only. Please do you own due diligence and consult with a professional adviser before making any investment

Episode #55: Is It Time To Start Hiring Digital Coworkers So Human Staff Can Spend More Time With Customers? – Roots Automation’s Chaz Perera

December 15, 2020    Episodes

Episode #55: Is It Time To Start Hiring Digital Coworkers So Human Staff Can Spend More Time With Customers?

In today’s episode of Ayehu’s podcast, we interview Chaz Perera, Co-Founder & CEO of Roots Automation.

Bots.  They’re everywhere, proliferating fast, and evolving their capabilities.  Most of us are familiar with them in the form of chatbots, crawlers, and of course RPA bots, but what about an emerging class of autonomous software programs called Digital Coworkers?  They’re not just next.  They’re now, and are already impacting the future of work in verticals such as the insurance industry. 

To learn more about Digital Coworkers and how they’ll interact with their human colleagues, we talk with Chaz Perera of Roots Automation.  As the former Chief Transformation Officer of AIG (America’s 4th largest insurer by assets, as of 2019), he sought a better way to deploy robotic automation in enterprise operations.  Chaz explains to us why Digital Coworkers succeeded where other bots failed.  Along the way we’ll learn what the magic number is of automatable processes organizations need to have in order to justify establishing their own Center of Excellence, why a bot’s greatest value might be freeing up staff so they can spend more time with customers, and what a future with Digital Coworkers might look like. 



Guy Nadivi: Welcome, everyone. My name is Guy Nadivi, and I’m the host of Intelligent Automation Radio. Our guest on today’s episode is Chaz Perera, Co-Founder and CEO of Roots Automation, which claims to have the world’s first self-learning, zero integration Digital Coworker bots. There’s lots of debate about whether automation in the form of bots will replace more people or augment more people, and that’s one of the subjects we want to hear about directly from an expert. So we’ve invited Chaz to join us today and share his thoughts with our audience. Chaz, welcome to Intelligent Automation Radio.

Chaz Perera: Hi, Guy. Thanks for inviting me on. I’m excited to share what I’ve been learning over these last few years in the automation space, and yeah, hopefully your listeners will take a few bits and bites from it, and help them improve their businesses.

Guy Nadivi: Well, fantastic. I think the first thing, Chaz, that everybody would like to know is what was the path that led you to start Roots Automation and your focus on Digital Coworkers?

Chaz Perera: Sure. I, at one time was the Chief Transformation Officer of AIG, a large multi-national insurance company. We were, at the time, we had been leveraging RPA technologies for roughly five years. It struck me as odd that we were spending, in our case then, many millions of dollars running an RPA program, and we were sort of challenged to get to value. I started to ask people, my peers at other companies how they were sort of dealing with that challenge, and I was coming across the same sort of problems, which is that the traditional RPA deployment methods, which really mean you need to spend a lot of money on a variety of different skill sets, you need to spend a lot of money on different technologies, and you need to spend a lot of time, typically many months, building a bot, and that is different from what RPA technologies typically promise, which is speed, and short time to value, and so I wanted to come up with a different way to deploy bots in a working environment. The second thing that struck me and the reason that we are focused so much on Digital Coworkers, as opposed to just bots, is at one time, I also ran shared services for the company. I noticed that when we were running shared services, often, people here in the U.S. or the U.K., for example, would often complain that the folks in the Philippines or in India, wherever our shared services entities may have been didn’t understand the business. They weren’t helpful, and so people would rather just keep the work onshore and do it themselves. I noticed that when we started to introduce bots into the operating environment, people had the same responses that the bots weren’t doing the job properly. They weren’t as complete as they needed to be, et cetera, and so it struck me that we needed to create bots that had more human-like qualities that, where humans could feel almost a fellowship between themselves and bots. Otherwise companies would be making huge investments in robotic technologies, automation technologies, but not getting value from them because people were essentially opting out of leveraging these technologies.

Guy Nadivi: Now, you just mentioned shared services, so I want to ask about an article you recently posted about the importance of standardization for automating processes. Before automating a process, in addition to it being standardized, it’s also a well-accepted best practice that it should be optimized, as well as thoroughly documented, so I’m curious, Chaz, what percentage of business processes are you seeing that are standardized, optimized, and documented before you begin to deploy your automation?

Chaz Perera: It’s a really good question, Guy. I think the reality is when you start to talk to a prospective customer, you find more often than not, and by more often, I mean, 70, 80% of the time, their processes are not well-documented. Their processes aren’t optimized. Their processes may be standardized in their mind, but not necessarily the way we, in the world of sort of process improvement, think of what a standard process looks like. All that being said, one of the things that we see at Roots Automation, and this is the advantage of sitting outside of a company and seeing the business processes of lots of similar companies, what we find is that the processes at one company are often similar to the same process at another company. A very simple example would be the accounts payable process within a finance team at one insurance company, is often very similar to the accounts payable process at another insurance carrier. In fact, what we’re finding is that for those back office processes, the similarities amongst those processes are closer to 80%, so what we end up doing is thinking about that remaining 20% and how we can build our Digital Coworkers in such a way that that 20% becomes something you can configure as opposed to having to always build from scratch. Similarly, as we move into the front office of insurance or the middle office of insurance, so underwriting and claims, we find similar things that the underwriting processes have a lot of commonality, insurance company to insurance company. The claims processes similarly have a lot of commonality, insurance company to insurance company. I suppose a long-winded answer to your question, even though these companies may not have standardized processes in their mind or they may not have documented these processes to the degree that we would like, we see enough of these processes to be able to say that there is standardization, there is commonality amongst the processes that we can leverage and take advantage of.

Guy Nadivi: In another recent article you posted about automation and return on investment, you touched upon the topic of automation centers of excellence, which generally speaking, are highly recommended for enterprises as part of their automation journey. However, you state that, “Statistically speaking, only about 4% of COEs deliver a positive ROI.” Is everyone wrong then about the need for centers of excellence, or is there a better path to take in order for them to successfully deliver an appropriate return on investment?

Chaz Perera: It’s a really good question. I would say there is no one size fits all. I think if you are a very large enterprise, having an automation COE makes a ton of sense, because you want to standardize on a certain subset of technologies. You want to be able to take advantage of the scale, that leveraging those same technologies will bring you, but if you’re a medium-sized company or a smaller business, the requirements around talent, the requirements around the technologies you need to bring forward are so vast that a COE is not an affordable exercise for most companies. Just to give a very simple example, if you want a bot to be much more human-like, and you think about how processes often begin today, they often start with an email, you need to think about Natural Language Processing, and so you need to bring some AI, machine learning expertise to the table. How many companies have people with NLP as a specialty, and maybe you need to now start to think about OCR as well, because sometimes you need to actually digitize these documents before you can run them through your NLP, and that OCR expertise and the computer vision that’s required to get OCR to work at a very high degree of accuracy is very expensive, and so that’s why I say the COE model doesn’t make sense, unless you’re a large enterprise. Excuse me, what I would add to just provide additional color, some of the largest enterprises in the world don’t need to have a singular COE. They could afford to have COEs by function as long as those COEs are operating as a federation, where the sharing, the learning, leveraging the same technologies so you can take advantage of your scale is still sort of core to that federated model. For everyone else, the best bet is to partner with a third-party advisory house like EY or KPMG to consider systems integrators, or look for a company like Roots Automation, which provides Digital Coworkers as a service, where you physically don’t have to worry about anything other than, “Here’s my business process. Can I leverage one of your bots to run it?”

The last thing I’d say, Guy, on that particular topic, what we found in our research is that the magic number for needing to have your own COE is if you believe you can automate 35 processes at your company, then it makes sense for you to have a COE because you can get to break even on that investment over the course of a few, short years.

Guy Nadivi: Very interesting. I’ve never heard that specific number. Chaz, you write a lot of really good articles, and in another of your recently published ones, you talk about the importance of enterprises upskilling their employees. That’s actually a topic we’ve spoken about quite a bit on this podcast. Let’s say I’m one of those employees, and let’s also assume that I want to acquire the skills needed to ride this growing automation wave that’s digitally transforming everything. Regardless of whether my organization pays for my upskilling or I have to pay for it myself, what are the top skills I should acquire to take advantage of job opportunities in automation?

Chaz Perera: I think it is wise for everyone, regardless of the industry they work in to try to learn to code in some language. There’s a mindset, a way of thinking through logic that coding brings forward, and I think that’s important. If you’ve never coded before, learn to code in some language, and it doesn’t have to be deep understanding of it, but just understanding the basics. If you want to be in the world of automation and more specifically in the world of RPA, it makes a ton of sense to try to learn using one of the base, more common RPA platforms like a UiPath, or a Blue Prism, or an Automation Anywhere. I believe all the RPA software providers out there for the most part, at least, provide a community edition or some sort of free edition that you can use to learn. Then, I would say that, thinking about my answer to an earlier question, Guy, around machine learning, and specifically computer vision and NLP, I’m not saying you need to become a data scientist, but I do think it’s important you understand what the art and the science of data science actually is, so that you can speak to it with some level of understanding so that when you are sitting with a data scientist and trying to solve some of these complex problems, you’re able to work off of a single dictionary, and you’re not sort of two or three steps behind. I’ll quickly add one more thing that sort of comes to mind, Guy. In the world of automation, it’s really important to remember there are humans at the end of every single transaction, and so change management has to be a skill that we all have. Automation technologies should be scary. They’re not intended to be scary, but the way you can make them scary is by not being transparent, by not talking about how these technologies can really help to improve the experience for customers, help to advance business objectives. If you introduce this stuff without a little bit of fanfare, without the right change management, that’s when people start to worry about their jobs, and so I would say also focus heavily on change management.

Guy Nadivi: Okay, so let’s talk about the humans in those automation transactions. Your company, Roots Automation specializes in Digital Coworkers, and yet, that’s a term I imagine might create some anxiety in people, and perhaps even trigger some resistance from employees fearing job loss, or radical changes to their job. On this podcast, we refer to that kind of resistance as robophobia, and it’s been known to create friction for enterprises deploying automation. Chaz, what would you say to someone experiencing robophobia at the thought of working alongside a Digital Coworker?

Chaz Perera: We were very careful when we thought about what Roots Automation’s product would be and how we would offer it to the world. The reason we chose the term, Digital Coworker, the emphasis on “Co”, is because we wanted people to recognize that our bots are not simply there to take over their work. Our bots are there to be one, an extension of their team, two, to essentially step in and do the types of work that people typically don’t enjoy doing, don’t get much satisfaction from, and by being able to engage in that more mundane and rote work are, you as a team member of this Digital Coworker, you should now have the ability to engage with customers, to work on projects, to do things that we all hope will create more value for the company than more of the transactional work that bots or Digital Coworkers are just great at. All that being said, transparency is really important, and so when we are talking to customers about implementing one of our Digital Coworkers, we think it’s really important that they talk about where these coworkers fit in on the team, the types of work that the Digital Coworkers are going to be doing, the types of work that the humans will now start to do. Fundamentally, in our platform, Guy, you talked about how we provide this self-learning bot. We don’t pretend as though our bots on day one will be able to do all the work that a human does today, and we also expect that they will be imperfect in that exercise, and so what we encourage is an interactivity between humans and bots, and in our product, that means that as the bots come across things they’re not sure about. If they’ve come across data that they’re not sure about or data that’s missing, or they can’t triangulate data, what they will do is they’ll stop, and they’ll actually ask one of their teammates, the human on the team, a set of questions. Through that interactivity, the bots are starting to learn. What we found is that our customer’s employees, the people that are teammates to these Digital Coworkers, really enjoy that experience. What it’s allowed us to do is to dial down very naturally some of that fear, some of that trepidation that people have had.

When our Digital Coworkers are introduced in one part of an organization and people start to get excited and start to feel like these bots are really part of a team, they naturally start to talk to other parts of the organization about the experiences they’re having, the excitement they’re having, and it helps to, again, dial down some of those fears, and so nothing is better than one employee talking to another to say, “Hey, it’s not what you think it is.”

Guy Nadivi: Chaz, can you share with us some of the outcomes, and particularly the ones that created that excitement from Digital Coworker deployments you’ve overseen?

Chaz Perera: Yeah, absolutely. Typically, what we are able to do for our customer, because we provide these pre-trained Digital Coworkers, what we’re able to provide is a coworker that’s ready to work in a customer’s environment typically between three to six weeks. Because of their ability to learn and engage, they get to productivity quite quickly, and as a result, our customers are seeing a break-even on that investment in as little as five months. If you extrapolate the benefit, because one of our Digital Coworkers is as effective as four to eight people at a company or four to eight people on a team, what we’re seeing is our Digital Coworkers will get a company to about a 250% ROI over the course of a five-year cost benefit analysis. What’s also interesting, Guy, what we’re seeing that’s less to do with the financials and much more to do with the feeling on the ground at a company, our customer’s employees really do endear themselves to our bots. They give them names, they give them personalities, they talk about them as though they’re real people. In fact, we regularly get emails from customers saying, “Hey, any chance Roxy could do this? Any chance Claire could do that?” That is probably the best indicator of success, that we know we can make the CFO happy by getting them to the financial value, but making sure that the line staff and the line managers are just as excited is really what we’re striving to do.

Guy Nadivi: Personalization is very interesting. Chaz, given some of the radical changes to the way people have worked since the start of the COVID-19 pandemic, what role do you envision Digital Coworkers can play going forward?

Chaz Perera: I hope that because of the pandemic, companies recognize how critical their human workers are to keeping customers apprised of what’s happening at the company, keeping customers highly engaged, keeping people loyal to brands and how important employees are to solving those substantive problems that customers often have. And so really, I hope that Digital Coworkers are enabling that by continuing to leverage these bots to not just handle your low complexity and mundane tasks, but because in the world of intelligent automation bots are starting to learn that they can move beyond the more rote tasks that companies often use RPA to do, and start to move towards the tasks that are slightly less sort of defined and structured, because then, you really can free your people to focus almost entirely on engaging with your customer, having conversations with them. Ultimately, that’s the thing that will allow you to build your brand and keep customers on your books in perpetuity.

Guy Nadivi: Chaz, as you know, the pace of innovation in our field can leave your head spinning, given some of the advances in automation, AI, and other digitally transforming technologies, but I’ll ask you this question anyways. What do you envision will be some of the biggest disruptions we’ll see in the next one to three years with respect to Digital Coworkers?

Chaz Perera: I think a couple things. The first, in the context of process mining, I think a lot of the process mining technology we have today is very good at developing a solution designed to document, providing you with that process map, but I imagine that over the next few years, we will be able to go from an exercise in process mining to an actual working bot, this concept of no code actually occurring in the world of bots, and so that would be a huge leap in terms of getting to value quickly, simplifying the exercise of developing and maintaining what are quite complex technologies. I think that would be a fantastic shift in something I do see coming. The second thing would be GPT-3, starting to get bots to not just be able to converse more naturally, but read more naturally. That will allow these bots, as I was sort of talking to earlier, start to move beyond the more mundane, rote, standardized tasks, and start to move into those tasks that require more and more judgment. Then lastly, and this is something we pride ourselves on at Roots, when we talk about Digital Coworkers, we want our coworkers to have very human-like qualities, and so today, our bots learn, our bots communicate, and they can do that on Slack, they can do that on email, whatever it might be, and our bots have this ability to sort of anticipate things. In our parlance, two examples of that might be that our bots, Guy, might recognize that you have your cup of coffee at 9:15 every morning, so that’s not a good time to bother you, come ask me questions at 10:00 instead because you’re more likely to provide a good answer. That’s an example of how we see bots being more human-like. What I hope to see over the next few years is that bots, our Digital Coworkers start to anticipate more. Imagine a Digital Coworker participating in your daily huddle, listening in on the conversation, hearing that the manager who’s leading that team saying things like, “These are the 10 things that are going to be the priority for the day.” “Everything else comes second,” and the Digital Coworkers actively reprioritizing work as a result of what it’s hearing. That’s how we get to a more cohesive office environment that has this happy balance between humans and Digital Coworkers, and certainly that’s what we’re striving for.

Guy Nadivi: Intriguing. Chaz, for the CIOs, CTOs and other IT executives listening in, what is the one big must-have piece of advice you’d like them to take away from our discussion with regards to implementing Digital Coworkers at their organization?

Chaz Perera: It’s interesting, I’ve heard a lot of IT leaders at companies of all sizes talk about agile, and that being the way they deploy technology quickly and create value quickly, but what’s often missing in those conversations are business people, so the IT part of the organization has adopted agile, is trying to move fast, but they’re not doing as good a job educating their business counterparts about how they need to operate, they need to contribute, how they need to learn in this agile-operating environment. You can’t have a true agile environment unless all parties are at the table with an equal understanding and an equal ability to contribute, so I would say that is something, thematically speaking, I see often that some people are left behind in that conversation. Then, the other thing I’d sort of throw out there, bots don’t fail gracefully, and so I would encourage IT leaders across an organization to think long and hard about the interactivity layer that needs to exist between humans and bots so that you don’t leave a human stranded. The thing that, going back to that original question, Guy, you asked about, “Why Roots Automation?,” one of the things that absolutely drove me nuts about the deployments of robotics at AIG, we would give our business users an Excel spreadsheet at the end of the day that said, “Here are all the things the bots did. Here are all the things the bots couldn’t do.” “For whatever reason, you need to pick it up.” That is not a great user experience. That is not a great customer experience, and so I would say spend time thinking about that interactivity layer and how you can create a better human experience for people that now have to work with bots.

Guy Nadivi: Setting realistic expectations, always a good idea. All right. Looks like that’s all the time we have for on this episode of Intelligent Automation Radio. Chaz, we love having automation innovators on the show, and it was great hearing your thoughts about the innovative role Digital Coworkers will play in the future of work. Thank you so much for coming onto the podcast.

Chaz Perera: Guy, it was a pleasure, and again, thank you for the opportunity to share my two cents at least with your audience.

Guy Nadivi: Chaz Perera, Co-Founder and CEO of Roots Automation. Thank you for listening, everyone, and remember, don’t hesitate, automate.



Chaz Perera

Co-Founder & CEO of Roots Automation

Chaz builds AI-powered, fully-functional digital coworkers that empower business owners to intelligently automate any process, leaving the time and resources of their human team to focus on strategic tasks they’re passionate about. As a result, businesses experience a 400-800% ROI and have happier, more productive team members.  

As a senior executive with 15 years of global operating experience leading successful transformation across multiple global businesses and functions, Chaz leverages data science, behavioral science, robotics, and AI technologies to build products, drive profitable growth, and reduce operating costs. He has a proven track record of building and leading high performing teams of up to 7,000 with a diverse range of skills, capabilities, cultures, and geographies. Chaz is recognized for his ability to develop and execute a strategic vision with sustained change, while being an agile leader with strong influencing skills who drives change with stakeholders from front-line teams to the board. 

Chaz can be reached at: 

Email: chaz@rootsautomation.com 

Phone:(973)713-3585 

Quotes

“I think the reality is when you start to talk to a prospective customer, you find more often than not, and by more often, I mean, 70, 80% of the time, their processes are not well-documented. Their processes aren't optimized. Their processes may be standardized in their mind, but not necessarily the way we, in the world of sort of process improvement, think of what a standard process looks like.” 

“…if you want a bot to be much more human-like, and you think about how processes often begin today, they often start with an email, you need to think about Natural Language Processing, and so you need to bring some AI, machine learning expertise to the table." 

“In the world of automation, it's really important to remember there are humans at the end of every single transaction, and so change management has to be a skill that we all have.” 

“…transparency is really important, and so when we are talking to customers about implementing one of our Digital Coworkers, we think it's really important that they talk about where these coworkers fit in on the team, the types of work that the Digital Coworkers are going to be doing, the types of work that the humans will now start to do.” 

“…bots don't fail gracefully, and so I would encourage IT leaders across an organization to think long and hard about the interactivity layer that needs to exist between humans and bots so that you don't leave a human stranded.” 

About Ayehu

Ayehu’s IT automation and orchestration platform powered by AI is a force multiplier for IT and security operations, helping enterprises save time on manual and repetitive tasks, accelerate mean time to resolution, and maintain greater control over IT infrastructure. Trusted by hundreds of major enterprises and leading technology solution and service partners, Ayehu supports thousands of automated processes across the globe.

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News

Ayehu NG Trial is Now Available
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Ayehu wins Stevie award in 2018 international Business Award
Ayehu Automation Academy is Now Available

Links

Episode #1: Automation and the Future of Work
Episode #2: Applying Agility to an Entire Enterprise
Episode #3: Enabling Positive Disruption with AI, Automation and the Future of Work
Episode #4: How to Manage the Increasingly Complicated Nature of IT Operations
Episode #5: Why your organization should aim to become a Digital Master (DTI) report
Episode #6: Insights from IBM: Digital Workforce and a Software-Based Labor Model
Episode #7: Developments Influencing the Automation Standards of the Future
Episode #8: A Critical Analysis of AI’s Future Potential & Current Breakthroughs
Episode #9: How Automation and AI are Disrupting Healthcare Information Technology
Episode #10: Key Findings From Researching the AI Market & How They Impact IT
Episode #11: Key Metrics that Justify Automation Projects & Win Budget Approvals
Episode #12: How Cognitive Digital Twins May Soon Impact Everything
Episode #13: The Gold Rush Being Created By Conversational AI
Episode #14: How Automation Can Reduce the Risks of Cyber Security Threats
Episode #15: Leveraging Predictive Analytics to Transform IT from Reactive to Proactive
Episode #16: How the Coming Tsunami of AI & Automation Will Impact Every Aspect of Enterprise Operations
Episode #17: Back to the Future of AI & Machine Learning
Episode #18: Implementing Automation From A Small Company Perspective
Episode #19: Why Embracing Consumerization is Key To Delivering Enterprise-Scale Automation
Episode #20: Applying Ancient Greek Wisdom to 21st Century Emerging Technologies
Episode #21: Powering Up Energy & Utilities Providers’ Digital Transformation with Intelligent Automation & Ai
Episode #22: A Prominent VC’s Advice for AI & Automation Entrepreneurs
Episode #23: How Automation Digitally Transformed British Law Enforcement
Episode #24: Should Enterprises Use AI & Machine Learning Just Because They Can?
Episode #25: Why Being A Better Human Is The Best Skill to Have in the Age of AI & Automation
Episode #26: How To Run A Successful Digital Transformation
Episode #27: Why Enterprises Should Have A Chief Automation Officer
Episode #28: How AIOps Tames Systems Complexity & Overcomes Talent Shortages
Episode #29: How Applying Darwin’s Theories To Ai Could Give Enterprises The Ultimate Competitive Advantage
Episode #30: How AIOps Will Hasten The Digital Transformation Of Data Centers
Episode #31: Could Implementing New Learning Models Be Key To Sustaining Competitive Advantages Generated By Digital Transformation?
Episode #32: How To Upscale Automation, And Leave Your Competition Behind
Episode #33: How To Upscale Automation, And Leave Your Competition Behind
Episode #34: What Large Enterprises Can Learn From Automation In SMB’s
Episode #35: The Critical Steps You Must Take To Avoid The High Failure Rates Endemic To Digital Transformation
Episode #36: Why Baking Ethics Into An AI Project Isn't Just Good Practice, It's Good Business
Episode #37: From Witnessing Poland’s Transformation After Communism’s Collapse To Leading Digital Transformation For Global Enterprises
Episode #38: Why Mastering Automation Will Determine Which MSPs Succeed Or Disappear
Episode #39: Accelerating Enterprise Digital Transformation Could Be IT’s Best Response To The Coronavirus Pandemic
Episode #40: Key Insights Gained From Overseeing 1,200 Automation Projects That Saved Over $250 Million
Episode #41: How A Healthcare Organization Confronted COVID-19 With Automation & AI
Episode #42: Why Chatbot Conversation Architects Might Be The Unheralded Heroes Of Digital Transformation
Episode #43: How Automation, AI, & Other Technologies Are Advancing Post-Modern Enterprises In The Lands Of The Midnight Sun
Episode #44: Sifting Facts From Hype About Actual AIOps Capabilities Today & Future Potential Tomorrow
Episode #45: Why Focusing On Trust Is Key To Delivering Successful AI
Episode #46: Why Chatbots Are Critical For Tapping Into The Most Lucrative Demographics
Episode #47: Telling It Like It Is: A 7-Time Silicon Valley CIO Explains How IT’s Role Will Radically Change Over The Next Decade
Episode #48: How Microsoft Will Change The World (Again) Via Automation
Episode #49: How One Man’s Automation Journey Took Him From Accidental CIO To Unconventional VC
Episode #50: How Automation Helped LPL Financial Grow Into The Largest Independent Broker Dealer In The US
Episode #51: Why Cognitive Architecture Might Be An Early Glimpse Of A Future With Artificial General Intelligence
Episode #52: Chatbots Aren’t Human, So Don’t Expect People To Pretend They Are
Episode #53: Why End User Experience May Be A Better Measure Of Automation Success Than ROI
Episode #54: How Digital Dexterity Will Generate Competitive Advantage For Agile Enterprises

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Disclaimer Note

Neither the Intelligent Automation Radio Podcast, Ayehu, nor the guest interviewed on the podcast are making any recommendations as to investing in this or any other automation technology. The information in this podcast is for informational and entertainment purposes only. Please do you own due diligence and consult with a professional adviser before making any investment

Robotic vs. Intelligent Automation – What’s the Difference?

Robotic vs. Intelligent Automation – What’s the Difference?The development and widespread adoption of robotic process automation (RPA) technology has changed how organizations approach their business operations, particularly in terms of streamlining and scaling business processes. Given this innovation, a question that naturally arises is what does the future hold for RPA? The answer to that question is intelligent automation.

What is RPA?

In simplest of terms, RPA is an application of technology that enables people to configure computer software – or robots – to process transactions, manipulate data, trigger responses and communicate with other digital applications, programs and systems. Deloitte defines RPA as “a way to automate repetitive and often rules-based processes.”

The concept of RPA really began to gain traction during the early 2000s when, at the time, businesses had been relying on basic automation executed through software commands which followed scripted processes to perform tasks within single IT applications. RPA technology brought this to the next level by scripting tasks across several applications, enabling companies with complex infrastructures to also extract value from automation.

Ultimately, RPA tools are best suited for tasks, processes and workflows that have repeatable, predictable interactions with other IT applications.

What is Intelligent Automation?

The natural progression between robotic and intelligent automation has occurred over the past decade or so, and has further expanded the benefits of automation by introducing machine learning and artificial intelligence into the mix.

Unlike RPA, which is designed to automate routine, repetitive tasks, intelligent automation provides the capability to automate non-routine tasks. Furthermore, intelligent automation can tackle processes that require judgment, intuition, creativity, persuasion and problem-solving – all skills that previously required human input and intervention. It is, essentially, a cognitive technology that features human-like capabilities.

When combined with RPA technology, the resulting solution can enable organizations to harness the power of automation to streamline both routine and highly complex processes and workflows, creating an intelligent, self-driving enterprise.

Getting Started with Intelligent Automation

Whether you’re looking to simply dip your toe in or are eager to dive headfirst into intelligent automation, there’s a strategy that should be followed. Perhaps Deloitte outlined it best in their recommended five-step process, shown in the infographic below.

 

Deloitte Infographic - Getting Started with Intelligent Automation

 

Without question, intelligent automation will become an even more integral component of future business models. As a result, organizations across the globe are shifting their focus to intelligent automation solutions that can support both their current as well as their future needs and provide competitive advantage in a growing market.

The best way to get started with intelligent automation is to experience it in action. Click here to schedule your live demo of our Next Generation IT Automation, powered by AI – and don’t forget to grab your FREE copy of our latest eBook below.

Free eBook! Get Your Own Copy Today

Ayehu Partners with Kryon Systems to Integrate Robotic Workforce and IT Automation

Ayehu Software Technologies and Kryon Systems are pleased to announce a partnership which will couple the back-end IT operations strength of Ayehu and the comprehensive robotic process automation services of Kryon. With this new partnership, Kryon Systems, a leader in Robotic Process Automation (RPA), and Ayehu, an IT automation and orchestration platform, will offer enterprise users a complete automation solution including the full range of RPA services for business applications, and the automated back-end IT operations capabilities, providing workforces with tools to not only increase efficiency, but allow them to remain focused on tasks which require more individualized attention.

The rapid growth taking place in the RPA industry demonstrates the important role automation will play in growing and sustaining enterprises in an increasingly competitive market. Offering a package of RPA and IT automation services which can be deployed quickly, the partnership provides a unique range of highly specialized capabilities not otherwise available on the market, including the first-of-its-kind Hybrid Automation Solution offered by Kryon Systems, which allows the human workforce to interact effortlessly and seamlessly with the virtual one.

Ayehu’s platform, which allows IT departments to orchestrate and automate a wide range of manual and time consuming IT operations tasks, which enables rapid issue resolution and significant increases in IT process efficiencies, has already been utilized by enterprises worldwide.

Kryon Systems’ Leo platform uses visual recognition and deep-learning technologies to record and execute processes running on any application and across multiple applications without requiring integration. By allowing enterprises to offload processes to an “in house” robotic workforce, saving substantial amounts of resources, employees can be freed from repetitive and time consuming tasks.

By partnering, Kryon and Ayehu are bringing the full potential of RPA and automation services to all aspects of an enterprises operations, increasing productivity and profitability.

“There is no question that RPA as well as other advanced solutions are changing the nature of the workplace as it becomes more digitalized. Yet often the complexities that come along with the added IT work can make handling the transition and implementation of these new systems a nightmare,” said Harel Tayeb, CEO of Kryon Systems. “By streamlining not only the business processes, but the back-end IT ones as well, enterprises can maximize the benefit of embracing digitalization without the headache.”

“Our partnership with Kryon is a natural complement for our IT process automation solution, as it extends the benefits of automation and machine learning across the enterprise,” said Ron Lozinsky, Director of Partnerships and Alliances at Ayehu. “For customers seeking to expand on the benefits of automated technology with access to top of the line RPA solutions, this combined solution opens up the opportunity to create a significantly more efficient and profitable enterprise.”

About Ayehu

Named by Gartner as a Cool Vendor, Ayehu’s IT automation and orchestration platform is a force multiplier for IT and security operations, helping enterprises save time on manual and repetitive tasks, accelerate mean time to resolution, and maintain greater control over IT infrastructure. Trusted by major enterprises and leading technology solution and service partners, Ayehu supports thousands of automated processes across the globe. For more information, please visit www.ayehu.com and the company blog. Follow Ayehu on Twitter and LinkedIn.

About Kryon Systems

Kryon Systems’ intelligent robotic process automation platform amplifies the power of RPA, using patented visual and deep learning technologies to improve operational performance. To this end, Kryon’s flagship Leo platform supports both virtual and human workforces alike, facilitating the efficient and accurate execution of business processes on any enterprise application. The Leo platform can be leveraged for unattended (RPA) and attended (desktop) automation, as well as hybrid automation (where there is interaction between the virtual and human workforce), providing a greater return on automation investments. Numerous Fortune 500 organizations benefit from considerable cost savings, improved efficiencies, and near-zero error rates by using Kryon’s intelligent RPA platform. Learn more about Kryon Systems and its products at kryonsystems.com.

The Role of Robotic Process Automation in Big Data Analytics

Without a doubt, we are living in an age when information is always available at our fingertips. Sometimes it seems as though we are practically drowning in the data that’s available to us. In fact, according to IBM, there are some 2.5 quintillion bytes of data created every single day, and an estimated 90% of all the data in the world today was created in the last two years alone. And while much of this “Big Data” may seem irrelevant to you, organizations around the world are taking it very seriously. So much so that many are now employing the use of robotic process automation to help harness, analyze and leverage it.

The Role of Robotic Process Automation in Big Data AnalyticsWhat’s the connection? Well, for starters, using robots to automate business processes can simultaneously result in the retrieval of all kinds of information about how those particular processes are carried out. In this sense, robotic process automation is much more informative than even the best human analyst could ever be. In addition to extracting data, robots can also record everything and pull it together to become much more useful to key decision makers, helping to discover bottlenecks and other problems and identify opportunities where processes could be better optimized.

Data analytics can transform an astronomical amount of information into patterns that are logical and easy to understand. In fact, it’s pretty commonplace for advanced analytics to be built right into many of the software products that are on the market today (Google Analytics, anyone?). Robotic process automation solutions are similar in that they are capable of gathering data and reporting analytics for any given time duration.

You can use RPA to gain insight into any of the following (just as a few examples):

  • Total number of completed transactions
  • Average time each transaction (or workflow) takes
  • Number of business and/or application exceptions generated
  • Estimated time until task/process/workflow completion

Ultimately for Big Data to be useful, it must be properly vetted, thoroughly analyzed and appropriately organized into something that makes sense to someone who doesn’t necessarily have a background in advanced analytics. Delivering this valuable end result is another key benefit that robotic process automation has to offer. So now, not only can robotic process automation help create a more efficient, productive work environment, but it can also help identify problems and opportunities for improvement.

Could your business benefit from using robotic process automation, for Big Data or any of the countless other advantages it affords? Why not find out today for free? Download your own copy of Ayehu automation platform and start experiencing for yourself how powerful the right RPA solution can truly be.





eBook: 10 time consuming tasks you should automate




Reducing Complaints with Robotic Process Automation

Reducing Complaints with Robotic Process AutomationCould robots help you reduce the amount of complaints for your operation? The answer is yes. Well, robotic process automation, that is. By implementing RPA within your organization, you can dramatically reduce the number of human errors that occur from manual processes while also improving the speed with which you are able to deliver service. Fewer errors and faster results mean end users and customers alike will be more satisfied. Let’s take a look at exactly how this all works.

Firstly, robotic technology delivers productivity levels that are multiple times greater than that of human workers. When’s the last time your IT team was able to work round the clock without ever taking a single break? In fact, the only time RPA is inoperable is during system down-time, which is typically planned for and scheduled in advance. Using robots to complete most back-office processing tasks alone can result in an improvement of efficiency levels of upwards of 90%.

In addition to creating a more efficient, productive work environment, robotic process automation also provides a much greater degree of flexibility and scalability. Most businesses experience certain peak times during which the workload and subsequent demand on human workers fluctuates up. Previously when this occurred, organizations were faced with the limited options of asking existing employees to work more or hiring additional workers to compensate for the increased need. Robots have revolutionized how these peaks and valleys are handled, allowing businesses to scale up or down at the veritable click of a button.

Because robotic process automation technology facilitates greater productivity and efficiency and delivers the ability to seamlessly adapt to changing workload demands, it naturally helps to reduce many of the costs associated with the traditional non-automated workplace. Furthermore, by shifting many of the highly repetitive, mundane tasks from humans to robots, morale and employee satisfaction subsequently improves as well. Talented personnel is freed up to focus their skills and attention on other, more worthwhile and fulfilling activities, which benefits employees as well as the company as a whole.

Regardless of which industry or sector your organization happens to operate, without question robotic process automation could deliver a whole host of benefits, not limited to the ones listed above. The better your company operates within, the greater degree of satisfaction you will achieve, both internally as well as with your customers. Happier employees and clients mean fewer incoming complaints, which is music to the ears of almost any executive.

If you haven’t yet begun reaping the benefits of RPA for your company, the time to do so is now. Download a free 30 day trial of eyeShare today to get started and experience for yourself how powerful having an army of robots at your disposal truly can be.





eBook: 10 time consuming tasks you should automate