Posts

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.

GET STARTED WITH AYEHU INTELLIGENT AUTOMATION & ORCHESTRATION  PLATFORM:

News

Ayehu NG Trial is Now Available
SRI International and Ayehu Team Up on Artificial Intelligence Innovation to Deliver Enterprise Intelligent Process Automation
Ayehu Launches Global Partner Program to Support Increasing Demand for Intelligent Automation
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
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

Follow us on social media

Twitter: twitter.com/ayehu_eyeshare

LinkedIn: linkedin.com/company/ayehu-software-technologies-ltd-/

Facebook: facebook.com/ayehu

YouTube: https://www.youtube.com/user/ayehusoftware

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 #58: What works? A Senior Partner from Bain articulates the keys to automation success – Bain & Company’s Michael Heric

February 1, 2021    Episodes

Episode #58: What works? A Senior Partner from Bain articulates the keys to automation success

In today’s episode of Ayehu’s podcast, we interview Michael Heric, Senior Partner at Bain & Company. 

Bain & Company, one of the world’s three largest strategy consulting firms, has been at the forefront of digital transformation for many years now.  Leading global organizations retain Bain’s services both to keep pace with technology advances, as well as gain competitive advantage in their markets.  It’s not a bad place to be employed either, as evidenced by Glassdoor ranking Bain #1 on their list of Best Places to Work (four times!).  No wonder then that Bain attracts the best, both customers and employees, which in turn leads to some of the best insights available on the state of automation. 

We take a peek inside this prestigious firm by interviewing Michael Heric, Senior Partner at Bain & Company, and the executive in charge of their Automation Center of Excellence.  In his 20 years at Bain, Michael’s seen a lot, and he shares with us why automation is increasingly sitting outside of IT’s jurisdiction; how Bain took a disappointing automation program that yielded only a few million dollars in savings to one generating savings of over a hundred million dollars a year; and why it’s unlikely there will ever be a single platform delivering all of an organization’s automation needs.  



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 Michael Heric, Senior Partner at Bain & Company, and the man who runs Bain’s automation center of excellence. We’ve been wanting to have the leader of a high-profile center of excellence on the show for some time now, and it’s a real treat for us to have Michael Heric from Bain, which as many of our listeners know, is one of the prestigious big three management strategy consulting firms. So the automation best practices they’ve developed are based on engagement with a diverse collection of some of the world’s biggest firms and have broad applicability for our audience. Michael, welcome to Intelligent Automation Radio. Michael Heric: Great to be here, Guy. Thanks for having me.

Guy Nadivi: Michael, can you please share with us a bit about what path you took that led you to Bain and the field of automation?

Michael Heric: Sure. Thanks again, Guy. I’ve been in Bain’s Technology and Cloud Services practice for about 20 years, working with providers across the ecosystem. In the last five years, I’ve become more involved on the customer side, helping companies use technology to transform their support functions, such as finance, HR, and other functions. And now I lead this capability for Bain, and automation has been an important part of this work. And that’s what really led me to start and now lead Bain’s automation capabilities, including our automation center of excellence that helps clients in their automation journeys across the full life cycle.

Guy, I’ve also had just an interest and a passion for disruptive technologies for a long time. And automation, as you know, is one of those. For example, in the late 2000’s, I was just very interested in cloud computing and helped the firm develop our point of view and capabilities in this area. Back then, the market capitalization of the top five public cloud companies was only about $14 billion, for example. And today the top five public companies have a market cap over $600 billion, which is more than a 40 times increase in the value over the past decade, with infrastructure as a service and software as a service individually now topping $100 billion in revenue each. It’s not clear to me if all these new automation technologies will be as disruptive, as fast, and as profoundly as cloud, but many people think so, and it certainly has the potential. And so that’s why this is just an area that I’m very excited about.

Guy Nadivi: Just about every automation vendor advocates for organizations to create an automation center of excellence as part of their digital transformation initiative. However, EMA Research reported that only 7% have done so, despite there being some good evidence that COE’s play a major role in an organization’s automation success. Michael, you run Bain’s automation COE. Why do you think COE’s haven’t proliferated as widely as they should?

Michael Heric: That’s a great question, Guy. Automation has been around a long time, as you and many of your listeners know. The IT department has historically been the center of excellence for automation for companies. IT has been automating business processes for decades. So in a sense, this is nothing new. We’re really now in the next chapter, in which new technologies, whether that’s RPA, intelligent automation using machine learning or natural language, low code-no code, or many others are opening up new possibilities for automation and offering the promise to create more business value with faster payback periods than ever before. And in our experience, the most successful companies deploying automation often have a center of excellence. And I think you’re going to see those statistics improve pretty dramatically here over time. And we at Bain are actually seeing this as well. But one thing that I would say is that success requires so much more than a high performing center of excellence. We at Bain, we have a framework and a methodology that includes seven elements of a successful automation program, and certainly having a center of excellence or having some governance around your automation program is absolutely vital. But we believe a successful automation program really starts with strong senior sponsorship from business and IT leaders and bold automation goals, and it requires including not just the COE, but how you’re thinking about governing automation, whether that’s a centralized, federated, or a decentralized model, and it includes other elements, from a healthy intake and pipeline development process to the right delivery and partners, to change management, to the right incentives, and of course, value realization. So we see COE’s as only a small part of the journey here, Guy.

Guy Nadivi: I’m curious, Michael, when the center of excellence you run at Bain evaluates a process to be automated, is there a minimum ROI you need to justify automating that process?

Michael Heric: We typically want to see 20 to 40% savings, but it varies by process, as you might expect. Ideally, we also want to see other sources of value beyond cost savings, whether that may be improved customer experience, reduced cycle time, lower error rates, greater resiliency. We want to see other benefits. There is absolutely, in our experience an experience curve when it comes to automation, and I’m sure many of your listeners feel the same way as well. Just recently, and this is outside of the studies that you have here, we recently completed a new automation survey that found on average, companies only save about 12% of costs on their automation projects. And I realize that’s quite low, but when you look at the more experienced automation users, they’re four times more likely to actually achieve greater than 20% cost savings. So while there’s a great deal of frustration, even disillusionment at times in the market with some of these automation tools and whether these savings are real, what we do find is those that have more experience, that stick with it and learn from past experiences can often break through and achieve pretty meaningful savings.

Guy Nadivi: You alluded to a survey, which of course earlier this year, Bain conducted a survey of nearly 800 executives worldwide, which yielded a wealth of insights about where many major enterprises stand vis-a-vis automation and other digitally transforming technologies. Some of the findings concerned execution barriers, which persist in hindering organizations from realizing the full value automation can deliver. For example, you reported that 44% of respondents said their automation projects have not delivered the expected savings. Your prescription for addressing this was to advise enterprises to “ground automation in the customer’s experience”. Michael, do you think that makes improved customer experience a more important metric than return on investment when evaluating automation?

Michael Heric: I’m not sure they are mutually exclusive. I think they’re quite related. From our experience, the trap that many companies unfortunately fall into is the following, and let me paint this picture. Some companies buy a handful of RPA licenses, as an example. They assign a junior project manager to run around the organization, pushing people in the business to find tasks to automate. Once those tasks are automated, business leaders can’t find the savings in their P&L, programs stall out. So we see this movie playing sort of over and over again. Our view is that automation is ultimately about business process transformation. And business process transformation should start, and the outcomes should be measured by, improvements in the customer experience. A customer could be the end customer or the customer could be an internal business stakeholder, like HR, serving managers and employees. When automation, in our belief, is grounded in and is one of several ways to achieve a broader business process transformation, we believe automation is likely to be more embraced and gain more traction and organization. And that’s why we focus so much on the customer experience, because we think that’s how you get the return on investment.

Guy Nadivi: Michael, an article you published earlier this year, entitled “Intelligent Automation: Getting Employees to Embrace the Bots”, highlighted an interesting finding from your survey of those 800 executives. When asked to rank the three most important benefits achieved by implementing new automation technologies, the number one result was freeing up staff to do higher value work. Now this is very interesting, because the thought of encroaching automation has created a bit of anxiety for people and even triggered some resistance from employees fearing job loss or radical changes to their job. That’s a condition we refer to on this podcast as robophobia. Michael, do you think the prospect of doing higher value work and therefore becoming even more valuable to an organization will be enough to mitigate people’s robophobia?

Michael Heric: Guy, I think it helps, but automation success requires much more. As I mentioned before, automation is about business transformation. It’s a change program, and most people fear change, regardless of the form it takes. We often tell our clients at Bain that organizations don’t change behavior, people do. Organizations have to find ways to inspire people to want to change, to want to adopt automation. I mean, just take the impact of the pandemic. There’s been a lot written and more importantly observed in the marketplace on the impact of the pandemic on accelerating automation. And we at Bain, we believe this as well. The pandemic has challenged longstanding beliefs, how people and business processes work, and the role that remote work or automation can have. This is inspiring companies to change and to adopt automation more. And let’s hope this energy around automation sticks as we recover from the pandemic. So in our work, we encourage our clients to really understand the long-term impact on their people from automation and to communicate honestly with employees about the impact of automation, that there will be job loss or permanent change to jobs. So robophobia is in fact real. But most importantly, we try to encourage our clients to develop talent strategies and plans on how to address this head-on. You might’ve seen, for example in the press, how Amazon is doing this by investing about $700 million in retraining people whose jobs have been lost due to the impact of automation. And I realize all of this sounds simple. However, in this recent survey that you quoted and that we just wrapped up, we found only 10% of companies felt the organization’s leadership and HR department were highly prepared to respond to the automation workforce challenges. So tons of focus around technology, how do we find the right use cases and so forth, just less time and focus on dealing with these issues around robophobia and really thinking about this as a change program.

Guy Nadivi: In another recent article you published entitled “A New Dawn for Automation”, you talk about how companies that invested in automation before the pandemic have weathered the crisis much better than those that have not. As a result, business resilience has emerged as a priority for many executives. Given the growing strategic importance of automation to an enterprise’s resilience and competitiveness, is it time for the automation function to be unbundled from IT, so that automation can become its own department reporting directly to the CEO via a Chief Automation Officer?

Michael Heric: Great question, Guy. Our view is that successful automation programs are business-led, IT-supported. Many of your listeners, I realize, are IT executives, and IT plays a critical role, regardless of where automation reports, whether that’s a consistent control framework, a manageable number of software and implementation partners, helping with delivery, knowledge management, sharing of best practices. These are just a few of the ways that IT can add value. But our view is that automation ultimately is not worth doing unless there’s real business value attached. So let’s take, for example, cost savings in RPA. IT can build a bot, but only the business can capture the savings from the automation and ensure that value flows through to the P&L. So it’s hard to predict how many CEOs will be open to yet another direct report, like a Chief Automation Officer, but who knows? As we know, the CIO role has only been around since the mid-1980s, and for most companies, it’s now unthinkable that a company would not have the CIO role. We do see automation increasingly sitting outside of the IT department for the reasons that I mentioned, as well as the Chief Automation role. Don’t know if it’s going to report to the CEO, but I think it’s going to be a critical role. And our view is maybe even the term Chief Automation Officer might not be the right one, because we believe ultimately, it’s about business transformation, rather than finding things to automate or tasks to automate. And that’s why we are increasingly seeing business transformation officers or chief transformation officers, where automation might sit under them.

Guy Nadivi: Michael, can you please share with us some of the outcomes from processes Bain has automated that you’ve been involved with?

Michael Heric: Sure. A good example would be a healthcare company that I recently worked with. So let me just set some of the context here for your listeners here. This company had an automation program for several years that was struggling to get results. After several years of having a dedicated automation COE, they had only achieved a few million dollars in cost savings and other financial benefits. I’m sure many have seen this movie before. They brought in a new Chief Automation Officer that we worked with. Now, while automation was clearly a top corporate priority and the potential was clear, the first step to really jumpstart the program was to build a healthier pipeline of opportunities working more effectively with the business. And so what we did was we started with a series of workshops in various business areas, and the goal of these workshops was not only to fill the automation pipeline with viable opportunities, but more importantly to start creating more pull rather than push for automation in the organization. Historically, this had been a major root cause of struggling to scale the program, namely enough collaboration with the business. We didn’t merely measure the results of these workshops by the number, the value of the automation opportunities identified, but also by things like what we call NPS, net promoter score, which I’m sure many of you have heard in say a consumer context, and how many people would actually volunteer to become automation ambassadors coming out of these workshops. So from that, of course, building a healthy pipeline is great, but as your listeners know, we want to take these opportunities into production to achieve the value. So we first prioritize the opportunities that could create a broad range of business value, not just head count savings. So a good example of this was an automation to reduce errors in claims processing to reduce overpayments and recovery fees. Reducing simply a fraction of these overpayments through automation created millions of dollars in savings, not just FTE savings. And then finally, a critical part of this work was supporting the new Chief Automation Officer in rebuilding his automation processes, methodologies, and tools, from intake to value realization. And this was absolutely essential, Guy, to building an automation program that could scale. And the net results of all this work went from saving a few million dollars a year, as I mentioned earlier, to one poised to achieve savings and other financial benefits north of a hundred million dollars this year. So I’m particularly proud of this healthcare example, of really driving value sort of end to end. Not just finding great things to automate, but really transforming the program from end to end, Guy Nadivi: Michael, 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 anyway. Based on the unique perspective available to you at Bain, what do you envision will be some of the biggest disruptions we’ll see in the next one to three years with respect to automation?

Michael Heric: Great question, Guy. It’s going to be really interesting to see the next few years. I think there’s some disruptions that I think many are expecting. So for example, RPA moving from on-prem to cloud. I would point to a couple major disruptions. I would say first, the continued democratization of automation, and then the second, the continued convergence of automation technologies. So let me take the first one first on democratizing automation. As you know, there’s always been citizen developers. I remember in the early 1990s, building macros in Excel to automate work, but it was hard work, let me tell you, as a college student. As automation tools become easier and you see the adoption of low-code and no-code development platforms, I believe that citizen developers will become much more empowered than ever before. And so you’re going to see automation absolutely permeating across the enterprise. I think the second one is this continued convergence of automation technologies. I’m skeptical we’re going to live in a world where there’s just one integrated automation platform that does it all. So companies can go there and it’s going to do everything you could possibly imagine, but I certainly believe that there’s too much fragmentation, and at times overlapping technologies out there. We also see that automation often works best when several of these technologies actually work together, such as we’re seeing now with more forms of intelligent automation. So I see a world with much less fragmentation, where these disparate technologies start to work more effectively together. So I don’t think we’re going to have one single platform, but I definitely see much more consolidation and convergence around the entire automation technology. And I think we’re poised to see a pretty dramatic sort of shake out or consolidation over the next two to three years.

Guy Nadivi: I think I agree with you. There has been such a proliferation of automation vendors, and especially chat bot vendors over the last few years that a shakeout is inevitable. Michael, 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 automation at their organization?

Michael Heric: I would say keep the faith and don’t give up. Succeeding at automation requires so much more than great technology or hands on keyboards, as I would say. For many companies out there, they’re very, very focused on let’s make sure we pick the right process, pick the right automation technology, and everything else will sort of work out. But as we know, automation is tough and it requires, as I mentioned before, an effective change program. It’s a business process transformation, and it takes a long time to get these things done. I think for many of your listeners out there, they’ve probably seen many cycles. If you think about software as a service, as we all know, they were application service providers a long time ago. There was a huge shakeout in that industry, and now we see what’s happened with software as a service. So these things take time. And so our view is keep the faith and don’t give up and keep pushing forward. And ultimately, at the end of the day, we believe the results will come through automation.

Guy Nadivi: All right. Looks like that’s all the time we have for on this episode of Intelligent Automation Radio. Michael, there’s a reason why so many Fortune 500 CEOs hire Bain for advice, and what you’ve shared with us today demonstrates the depths of insight available from senior Bain executives, like yourself. I’m sure our audience learned quite a bit from our discussion. Thank you for coming onto the podcast.

Michael Heric: Thanks, Guy. Appreciate your time.

Guy Nadivi: Michael Heric, Senior Partner at Bain & Company. Thank you for listening everyone, and remember, don’t hesitate, automate.



Michael Heric

Senior Partner at Bain & Company

Michael is a senior partner in Bain’s Technology and Cloud Services practice and leads Bain’s automation capabilities globally.  He brings more than 20 years of experience working with both leading providers across the technology ecosystem and customers deploying technology solutions to improve the effectiveness and efficiency of their business processes.  As the leader of Bain’s Automation Center of Excellence, Michael supports clients in their automation journeys to achieve more value faster.  Bain supports the full range of automation technologies, whether that may be scripting, workflow automation, Robotic Process Automation (RPA), low code/no code development, cognitive / AI-based automation, and many more. 

Michael works with business and technical teams to set bold automation goals, redesign their business processes to embed automaton, identify the right automation opportunities, build the multi-year roadmap, conduct pilots, and support full scale deployments.  Most importantly, he helps put in place the right capabilities, governance (including CoE’s), and change management to achieve automation goals and ensure that the business value is achieved and sustained over time. 

Michael can be reached at: 

Website: https://www.bain.com/our-team/michael-heric/

Quotes

“…in our experience, the most successful companies deploying automation often have a center of excellence.” 

“…when you look at the more experienced automation users, they're four times more likely to actually achieve greater than 20% cost savings. So while there's a great deal of frustration, even disillusionment at times in the market with some of these automation tools and whether these savings are real, what we do find is those that have more experience, that stick with it and learn from past experiences can often break through and achieve pretty meaningful savings." 

“Our view is that automation is ultimately about business process transformation. And business process transformation should start, and the outcomes should be measured by, improvements in the customer experience.” 

“…automation is about business transformation. It's a change program, and most people fear change, regardless of the form it takes. We often tell our clients at Bain that organizations don't change behavior, people do. Organizations have to find ways to inspire people to want to change, to want to adopt automation.” 

“The pandemic has challenged longstanding beliefs, how people and business processes work, and the role that remote work or automation can have. This is inspiring companies to change and to adopt automation more.” 

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.

GET STARTED WITH AYEHU INTELLIGENT AUTOMATION & ORCHESTRATION  PLATFORM:

News

Ayehu NG Trial is Now Available
SRI International and Ayehu Team Up on Artificial Intelligence Innovation to Deliver Enterprise Intelligent Process Automation
Ayehu Launches Global Partner Program to Support Increasing Demand for Intelligent Automation
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
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?

Follow us on social media

Twitter: twitter.com/ayehu_eyeshare

LinkedIn: linkedin.com/company/ayehu-software-technologies-ltd-/

Facebook: facebook.com/ayehu

YouTube: https://www.youtube.com/user/ayehusoftware

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

Automation Has Long history. What’s Next?

Automation Has Long history. What’s Next?

The concepts of automation and artificial intelligence are not nearly as new as many believe they are. In fact, humans have been tapping into machines and technology for more than a century. Today, of course, AI and automation are deeply ingrained in our day to day lives, from automatic doors in retail to virtual support agents in the home and workplace.

If we’ve learned anything over the past several decades, however, it’s that this technology does not remain the same for long. Advancements in cognitive capabilities will continue to accelerate the adoption of intelligent automation at a breakneck pace, bringing about new and exciting events and opportunities. Here’s what’s in store in the not-so-distant future.

Increasing Maturity

IT leaders have long faced mounting pressures to remain a step ahead in terms of technology and output. This demand has been multiplied exponentially since the start of the pandemic, which has brought about a dramatic and often sudden shift in priorities. Rather than planning for the long-term, IT decision-makers are now realizing the criticality of agility.

As we move forward and begin adapting to what will likely become the “new normal,” look for greater reliance on intelligent automation as a solution that not only minimizes costs, but also provides the support needed to weather any storm – global health crises included.

New Skills

The age-old argument of robots taking over human roles and making people obsolete in the workplace may finally be put to rest as organizations recognize the value of the human/AI collaboration.

Will some jobs be replaced by automation? Undoubtedly. But the proliferation of intelligent automation will likely create more jobs than it destroys. The key to survival will be the development of new skills. Organizations can establish a strong position in the future of work by investing in the reskilling of existing personnel. This will also minimize the skills gap over the long-term.

Automation at Scale

As organizations continue the process of rebuilding following the pandemic, most will not be able to rely solely on hiring more people to get back up and running. In fact, many are facing the difficult decision to make severe budgetary cuts, including those relating to human resources.

Automation can bridge this divide, enabling businesses to rapidly recover without having to increase expenditure. It will also deliver the speed, accuracy and scale that enterprises will require in order to remain profitable over the coming months and years.

Rise of Low-Code/No-Code Automation

Perhaps the biggest development on the automation front in the near future will be the widespread adoption of no-code or at least low-code solutions.

This straightforward, easy-to-use yet highly advanced AI technology will allow organizations to get up and running with automation in a fraction of the time it would normally take (e.g. hours vs. weeks or months).

Additionally, because the use of low-code/no-code automation does not require the oversight of highly skilled developers, businesses can save money without sacrificing performance.

If history has taught us anything, it’s that change is always on the horizon. The future of automation is bright and exciting. Don’t get left behind! Get started with our no-code solution today and put the power of intelligent automation to work for your organization! Click here to claim your free, fully functioning 30-day trial.

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.

GET STARTED WITH AYEHU INTELLIGENT AUTOMATION & ORCHESTRATION  PLATFORM:

News

Ayehu NG Trial is Now Available
SRI International and Ayehu Team Up on Artificial Intelligence Innovation to Deliver Enterprise Intelligent Process Automation
Ayehu Launches Global Partner Program to Support Increasing Demand for Intelligent Automation
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

Follow us on social media

Twitter: twitter.com/ayehu_eyeshare

LinkedIn: linkedin.com/company/ayehu-software-technologies-ltd-/

Facebook: facebook.com/ayehu

YouTube: https://www.youtube.com/user/ayehusoftware

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 #53: Why End User Experience May Be A Better Measure Of Automation Success Than ROI – GAVS Technologies’ Balaji Uppili

November 16, 2020    Episodes

Episode #53: Why End User Experience May Be A Better Measure Of Automation Success Than ROI

In today’s episode of Ayehu’s podcast, we interview Balaji Uppili, Chief Customer Success Officer for GAVS Technologies. 

Wikipedia defines Customer success as “…the business method ensuring customers achieve success, their desired outcomes while using your product or service.”  If automation is your product/service, what are the keys to ensuring it succeeds for your internal and/or external customers? When digital transformation projects have a documented failure rate as high as 84%, how should you approach implementation of automation to be part of the 16% that succeed? 

For answers we turn to Balaji Uppili, Chief Customer Success Officer at GAVS Technologies, one of the leading global IT service providers for midsize enterprises.  As the man tasked with assuring GAVS clients get the desired outcomes they demand, he’s developed critical insights on how to increase their odds of success.  He shares some of his accumulated wisdom with us, including why cost reduction shouldn’t be your most important measurement of success. 



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 Balaji Uppili, Chief Customer Success Officer for GAVS Technologies. For those of you unfamiliar, GAVS is a global IT services provider focused on AI-led managed services and digital transformation. AI and digital transformation of course are two of the primary topics we focus on at this podcast. And as Chief Customer Success officer for a global MSP providing those two services, we’re very interested in hearing from Balaji what the keys are to successful implementations in those disciplines. Balaji, welcome to Intelligent Automation radio.

Balaji Uppili: Hi Guy. Very good morning. Hi. Good to talk to you.

Guy Nadivi: Balaji, please tell us how you ended up in your current role as Chief Customer Success Officer for GAVS Technologies.

Balaji Uppili: Very well. Thank you. This is my 10th year at GAVS Technologies. We started off as a global delivery officer, and then when we realized that delivery is to deliver towards an SOW or a contract or a predefined SLA, we felt we need to go way beyond that and deliver to the outcomes which the customer wants, deliver to the roadmap and aspirations which they want. And hence, we felt delivering to the success of the customer is far more important to deliver this project successfully. And that’s why we represented as customer success. And we think we made the right choice because we are now able to measure and live up to a larger set of expectations and value to the customer than just delivering to a project. And that’s how I ended up as a Chief Customer Success Officer at GAVS.

Guy Nadivi: As Chief Customer Success Officer, I’m curious, how does GAVS Technologies define success when it comes to automation projects.

Balaji Uppili: Success actually respective of automation or otherwise, is extremely critical for the long-term relationship and connect, and more so in current days when automation has become the central need for all of our customers. We define success by understanding that individual who’s playing the key role with us from the customer organization and customer itself. When we get to interact with them, we identify and understand their larger business goals, capture those. We identify, understand what are the larger aspirations and expectations way beyond what the initiative we are working on and capturing those, measuring those, and being transparent with them as to how we are embarking on that journey is what defines success. And that’s what we actually take pride in doing at GAVS.

Guy Nadivi: I imagine that one aspect of customer success for automation projects involves user adoption, especially when it might lead to a change and a given user’s role, and this can lead to a type of anxiety we refer to as robophobia. Balaji, how does GAVS help organizations overcome their staff’s robophobia?

Balaji Uppili: Very good question, Guy. Customers actually want automation in normal circumstances, but when it comes to individuals, they feel that automation could actually replace them. They feel that their jobs may be going away. The entire change management, which is very critical, is to actually emphasize that automation actually augments human beings. Automation is not a replacement. So when we actually bring in an element of process change or technology change, we are very fast to adopt because that actually helps us. That actually makes us better. But when it comes to automation, it is felt as a replacement. The best way to address this is to actually let automation solve their mundane regular problems first, before embarking on complex ones. So involving the customer, having them participate in the journey of automation, and having them in the central part of defining what the automation can derive is actually key to success. And when they participate, their anxiety levels actually go away and probably they’re actually faster in embracing it. So the change management is extremely critical when it comes to automation.

Guy Nadivi: Balaji, can you talk about some of the more interesting and successful automation projects that you and GAVS have delivered for customers?

Balaji Uppili: Sure. For one of the largest public relations firm in the US, when we embarked on automation, it was felt that it is actually an exercise of reducing manpower, and to reduce costs for gas so that we can actually execute it using automation. But later we realized when we actually started introducing automation step by step, and we actually achieved about 40% and above automation over a period of 18 months, we then realized that the customer is actually delivering higher user experience. When the whole conversation turned from a labor arbitrage or a peek in production conversation to higher user experience, then their ability to embrace it actually improved to the extent that the CSAT went from anywhere from two to 2.5, to close it to 4.5, one a five scale, and they were able to bring a lot more value to the end user in defining what is user experience, in defining what can be the way the end users can actually have a very frictionless environment. So that’s one big customer engagement I would talk about. And quickly, the second customer engagement we’ve talked about is a very large aircraft manufacturer company in the world. They wanted to carry out a large digital transformation and towards that, they were doing a lot of manual activity in orchestration in trying to lift and move the data from as is environment to a target environment. When we brought in automation, they felt that they could focus on much larger business process re-engineering, rather than just focus on the day-to-day or heavy lifting of the applications and services from on-prem to the cloud. These are two examples, which I can relate to in the last 12 to 18 months, which has significantly brought value to our customers, Guy.

Guy Nadivi: Hearing you talk about these projects, Balaji, I’m curious when GAVS evaluates a customer process for automation, is there a minimum ROI you need to see in order to recommend automating that process to your customer?

Balaji Uppili: It does. I mean, at the end of the day, automation is felt as an overhead initially to automate the manual steps before starting to use it. But in most cases, we have found that the business case is written not for an initial investment, but over a period of time, how the benefit actually accrues. So if you plan out the automation initiative with regards to cost, with regards to availability of intellectual capital, and more importantly, with regards to enhancing end-user experience upfront these, three automatically fund the automation initiative. These are critical because cost alone is not a measure of automation. Frictionless execution, end user experience are also equally or better in terms of how automation can define the way enterprise operates. So driving these upfront, and capturing these, automatically provides a very useful ROI case for any automation.

Guy Nadivi: So speaking of ROI, is there a single metric other than ROI that best captures the effectiveness of the kind of automation you deploy for organizations?

Balaji Uppili: Very well. Good question, Guy. The biggest beneficiary beyond even costs is actually end-user experience. I take a small example, in one of the largest consumer goods customers, the CIO actually wanted us to bring in as much automation so that he’s proactive to his business. He is proactive to how his end users are able to react. The more we provided him information and were proactive, his ability to be accepted as a technology leader within his business organization was far higher than before. So the end user experience is probably a lot more valuable parameter than even costs as part of an ROI. Every time end-user is able to get that particular activity out without difficulty, absolutely frictionless, and offer very higher quality, automation speaks for itself. I think end user experience and frictionless operations are probably much higher in the scale when compared to ROI in such automation, Guy.

Guy Nadivi: Interesting. Balaji, GAVS touts itself as a global IT services provider focused on AI-led managed services and digital transformation. Now digital transformation projects have a notoriously high failure rate, as high as 84%, according to some. Balaji, for the remaining 16% of digital transformation projects that succeed, what factors did they share in common?

Balaji Uppili: It’s very simple. Automation or digital transformation cannot be done in isolation. It has to be done in an extremely collaborative manner. I mean, to date GAVS has been successful in every digital transformation initiative. When we involve the key stakeholders at the customer, including the people who are going to be using the target state platform early on, it actually makes a big difference. Digital transformation is not about moving everything to the cloud. Digital transformation is not about automating everything. Digital transformation is changing the way of life. Digital transformation is making our customers to do the same thing in a much better fashion. It could be automation, it could be cloud, it could be analytics, it could be mobility. So having the key stakeholders of the customer participate early on in the planning process and in the transformation process is key. And second one is showing quick wins and demonstrating through pilots and proof of concepts earlier on, makes the customer to participate even better. Those are, I feel, are genuine key considerations for success of the digital transformation. And that’s what actually GAVS has taken pride in because we have created something called as a migration office template for digital transformation. And that is actually helping customers to participate in a very collaborative manner and see the benefits of it from day one.

Guy Nadivi: At the time of this podcast’s recording we’re in the middle of a worldwide healthcare crisis due to COVID-19. Balaji, how is COVID-19 affecting global IT services providers like GAVS Technologies when it comes to providing IT services to enterprise clients?

Balaji Uppili: I wouldn’t be doing justice if I say it did not. So it definitely has impacted the way people relate to others. The way people are collaborating. It’s all being done remotely. So more and more, when we start looking at this new normal of working remotely, collaborating remotely, ability to deliver value remotely, I think automation plays even more, a larger role. The reason why I say that is automation doesn’t necessarily mean it’s a script running to be able to drive some work done. Automation is identifying certain elements or certain processes within an enterprise, which could have either been avoided manually, or could be done much differently, and then figuring out how to do it differently. So we have a principle. We say that if in case you want to do something second time, why do it through a human? Why not automate it through a bot? Now, if I use that, it actually applies even better for remote collaboration and remote working. Wherever we feel that we can actually use the remote workforce to do much more higher value, pass it on to them to do it, and bring in these automation scripts and bots, to be able to do the day-to-day stuff in a human and remote manner. So the actual remote working, while it has changed the culture while it has changed the working patterns, has actually lent itself very well for automation. And we are seeing a lot more customers wanting to automate, wanting to look at digital transformation during these times.

Guy Nadivi: So with that in mind, what has been the pandemic’s effect on enterprise decisions about implementing automation, AI, and other digital transformation initiatives?

Balaji Uppili: It’s actually gone up. While they were cautious in the early days, what has happened is now the customers want to do remote collaboration. They want even more better frictionless applications or business process, because they now don’t have the touch and feel of the customer themselves in helping them out. That is one aspect. The second aspect is cost. The cost optimization has become significant. People are wanting to reduce costs because of the uncertain times. That automatically means that automation is an answer to some of that. And lastly, because it is remote collaboration, newer techniques of Agile, newer techniques of execution are happening, which automatically lends itself to automation. I think the new norm is actually going to drive digital transformation and automation in a much better way without impacting lives of people, because I think cost and user experience are automatic increased expectations in this new norm

Guy Nadivi: Balaji 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 automation successfully at their enterprise?

Balaji Uppili: Don’t just work towards an ROI which has costs as the primary driver. Bring in end user experience, involve the various stakeholders who are going to contribute to the end user experience. Bring in a cultural change in the way you would like to execute, bring in elements of digital transformation, elements of things which can be eliminated like a waste elimination, or use the Lean Six Sigma principles to arrive at some of that. Don’t just consider this as a cost optimization exercise, but consider it more as a transformative exercise, consider it as an enhancing end-user experience and making your enterprise frictionless, which means you have to have a larger participation of your enterprise stakeholders in this initiative. Doing it in isolation, and only as cost will probably not help you achieve some of those good results which come out when you think of automation and digital transformation

Guy Nadivi: Making your enterprise frictionless, I think is some great insight. All right, looks like that’s all the time we have for on this episode of Intelligent Automation Radio. Balaji, you are the first Chief Customer Success officer we’ve ever had on the podcast, and I think you’ve really enlightened our audience about the importance of customer success for the advanced technologies many enterprises are adopting as part of their digital transformation initiatives. Thank you very much for coming on the show.

Balaji Uppili: Thank you Guy. It was my pleasure and we look forward to more and more of such conversations, but please keep in mind, automation is the new norm, digital transformation is the new norm. Don’t get scared, embrace it. It will give you lots and lots of benefits and make people’s lives better. Thank you very much Guy for the opportunity. Good luck. Have a great day.

Guy Nadivi: Balaji Uppili, Chief Customer Success Officer for GAVS Technologies. Thank you for listening everyone. And remember don’t hesitate, automate.



Balaji Uppili

Chief Customer Success Officer for GAVS Technologies.

Balaji has over 28 years of experience in the IT industry, across application value management, digital transformation, managed services in infrastructure and applications, BPO and Strategic Operations handling P&L, global Delivery, Operations and customer success management across multiple verticals which includes Healthcare, Information Services, Retail & Hospitality, Media & Publishing, Manufacturing & Logistics, and Consumer goods. Balaji has played various roles across geographies viz., USA, Continental Europe, and Asia Pacific, through his previous stints at Patni Computers, L&T Infotech, Cognizant Technology Solutions, and Virtusa Software Solution Limited. 

Balaji’s enthusiasm, energy and customer focus are a rare gift, and he plays a key role in bringing new clients into GAVS.  Balaji heads the Delivery and passionately works on Customer success delight.  He says work is worship for him, and enjoys watching cricket, listening to classical music and visiting temples. 

Balaji can be reached at: 

Website:        https://www.gavstech.com/service/sqa/  

Email:             inquiry@gavstech.com  

Quotes

“Customers actually want automation in normal circumstances, but when it comes to individuals, they feel that automation could actually replace them. They feel that their jobs may be going away. The entire change management, which is very critical, is to actually emphasize that automation actually augments human beings. Automation is not a replacement.” 

“Digital transformation is not about moving everything to the cloud. Digital transformation is not about automating everything. Digital transformation is changing the way of life.” 

"People are wanting to reduce costs because of the uncertain times. That automatically means that automation is an answer to some of that." 

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.

GET STARTED WITH AYEHU INTELLIGENT AUTOMATION & ORCHESTRATION  PLATFORM:

News

Ayehu NG Trial is Now Available
SRI International and Ayehu Team Up on Artificial Intelligence Innovation to Deliver Enterprise Intelligent Process Automation
Ayehu Launches Global Partner Program to Support Increasing Demand for Intelligent Automation
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

Follow us on social media

Twitter: twitter.com/ayehu_eyeshare

LinkedIn: linkedin.com/company/ayehu-software-technologies-ltd-/

Facebook: facebook.com/ayehu

YouTube: https://www.youtube.com/user/ayehusoftware

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 #52: Chatbots Aren’t Human, So Don’t Expect People To Pretend They Are – Charli.ai’s Kevin Collins

November 2, 2020    Episodes

Episode #52:  Chatbots Aren’t Human, So Don’t Expect People To Pretend They Are

In today’s episode of Ayehu’s podcast, we interview Kevin Collins, CEO & Founder of Charli.ai. 

Is conversational AI all it’s cracked up to be, or is hype eclipsing hope when it comes to deliverables?  Has the gap between expectations and reality grown so wide that disappointment is inevitable, both for end-users and enterprise decision-makers?  Or have the majority of chatbot vendors simply been targeting the wrong use cases, inadvertently leading their customers to insurmountable dead ends? 

One man with a clear-eyed vision of the market opportunity uncluttered by misconceptions about the technology’s potential is Kevin Collins, Founder & CEO of Charli.ai.  Following GE Digital’s acquisition of his IoT company Bit Stew, Kevin set out to build a personal AI Chief-of-Staff front-ended by a chatbot.  With Charli.ai recently emerging from stealth mode, Kevin joins us on the podcast to explain why despite expert predictions falling short about conversational AI’s advances he’s still enthusiastic about the technology; why front-end conversational interactions must never exceed back-end automation capabilities; and how CIO’s should approach conversational AI implementations. 



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 Kevin Collins, CEO of Charli.ai, which recently emerged from stealth mode to provide intelligent automation for everyday tasks in the digital workplace. Kevin and his partner, Alex Clark, previously co-founded and built a software company that was eventually acquired by GE Digital. Charli.ai then became their next project, which they began for the very personal reason that they were tired of doing their own administrative tasks, and what they plan to deliver to the marketplace is a tool that leverages automation, AI, machine learning, and chat to handle that administrivia, and as a bonus, requires zero coding or any technical skills to use or configure. That’s intriguing. So, we’ve asked Kevin Collins to come out of stealth mode himself and join us on the podcast to discuss Charli.ai and the overall state of the conversational AI market. Kevin, welcome to intelligent automation radio.

Kevin Collins: Oh, hi, Guy. Thank you for having me on the radio.

Guy Nadivi: Kevin, please tell us a bit about your background and what led you to launch Charli.ai, which I’ve read has been touted as a conversational AI chief of staff.

Kevin Collins: Yes. That’s a good description of where we want Charli to go. My background has been 30 years in the high-tech sector, and I think as you mentioned, Alex and I had started a company called Bit Stew that eventually got sold to GE Digital back in 2016. Bit Stew had a lot of AI on how we were doing integration. That AI capability is what I fell in love with and it’s something I wanted to bring into the world of Charli to really get rid of a lot of the pain that I go through on a day-to-day basis of just doing the administration work.

Guy Nadivi: Kevin, in 2019, Business Insider estimated the worldwide chatbot market is worth a bit more than $2.5 billion, but they forecasted that, by 2024, it will approach $10 billion. That’s a compound annual growth rate of over 29% a year. How do you think the COVID-19 crisis will affect this growth rate?

Kevin Collins: That’s a good question, and COVID-19 has impacted quite a bit from what we have seen just in the past few months alone. It’s created a lot of uncertainty in the market. It’s an area where we believe that uncertainty will continue at least for the near-term future and something that we at Charli are trying to navigate. But I do believe that COVID-19 will have a positive impact on that growth rate. If you’re looking at people’s attitudes to working from home, the remote work, that’s putting more pressure on software companies to automate. Automation is going to come with heavy AI involvement. It’s also going to come with an easier interface that people are looking forward to work with their software. Instead of being in the office where they’ve got more tolerance for the enterprise way of doing work, they’re going to want simpler ways of working with their software, and this is where I believe that chatbot innovation is going to come from and where that investment into chatbot technologies, especially when you’re looking at the enterprise and the corporate world.

Guy Nadivi: Okay. Now, speaking of chatbots, according to Gartner, there are 1,500 chatbot providers currently. Inevitably, there is going to be a shakeout that will cause that population to decrease precipitously, I believe. At the TechExit.io Conference earlier this year, you and Hans Knapp of Yaletown Partners had a discussion about creating barriers of entry for competitors as one strategy to preserve your market position. What barriers to entry can Charli.ai erect to defend itself against 1,500 others competing in the same market?

Kevin Collins: I completely agree. I believe that entire market for chatbots is ripe for consolidation. There’s far too many of the technologies that are out there. There’s also a massive amount of hype that’s gone into the chatbot area and people are now realizing the reality of chatbots will only take you so far. They’re really, for us, a channel into the intelligence within the systems we have. If I look at Charli’s approach to chatbots, we want the chatbot to be an input into Charli, but we need Charli to automate all of those administration functions that need to happen, and the automation needs far more intelligence than just a chatbot. We use the chatbot for that natural language processing, but we don’t use the chatbot for natural language understanding and how to translate that understanding into action, and that’s where the real intelligence on Charli is. So, we’re building defensible technology into how we automate those tasks for that chief of staff function that you mentioned earlier, and that requires heavy lifting from an AI perspective. Far more than what we would see just on the chatbot, which needs to be natural language processing. We really have to do natural language understanding and translation of that. So, two questions there. Will the chatbots consolidate? Definitely. I believe there’s far too much out there and it’s a natural consolidation. For us on the defensible side of it, it’s more than just a chatbot. It’s now understanding and translating that into action.

Guy Nadivi: Sticking with Gartner, in 2017 they predicted that “By 2020, 40% of all mobile interactions will be via virtual assistance.” Virtual assistance, of course, being a type of smart chatbot. Clearly, we’ve fallen short of that forecast. So, let me ask you, when do you predict we’ll reach peak app as it were, and start transitioning to conversational AI as the predominant user interface going forward?

Kevin Collins: Definitely have fallen short. I think the reason for that is a reality check. This is hard. It’s really hard. There’s a combination of not just that conversational ability. There’s also translating that into the action as I mentioned previously. And then you also have to have a conversation which is a behavior change for a lot of people. I think the virtual assistants that we see today are simple one task. You ask it to do something. It’s very simple. You spoon-feed it. You get the task done. But for a human to have a full conversation with their computer is a lot different and a lot harder. It’s easy to tackle low-lying fruit opportunities around customer support. Walking a user through a particular scenario and then manually following up with it at the end. It’s a completely different challenge to have a human converse with a computer and that computer to completely automate what the human wants to do and have a full-on interaction. I believe that we’re going to take some pretty key baby steps on really having the human converse with the computer in order to get an action done rather than get onto full conversational, which is going to take many years for that to happen.

Guy Nadivi: You mentioned low-lying fruit. So, let me ask you in broad terms, what are some of the lowest hanging fruit best suited for conversational AI applications within an organization?

Kevin Collins: Some of the ones that we’ve seen today that I think are perfect for it are the customer service, the customer support. Even if I look at it for me personally, I much prefer to chat through my support issue, really to understand the frequently asked questions and answers or to walk me through getting a refund on a purchase I had made. The flow for that is fairly predictable, and I would prefer to chat with a computer over chatting with a person to get that done. That is low lying opportunity for people to address, and it does take a big burden off of corporates and enterprises that have to invest heavily into their customer support.

Other areas that we see are prime opportunities for this are areas that Charli is targeting as well, and that’s the administration side. We’re finding people spending 20% to 50% of their day just on the minutiae of administration, and that’s distracting them from a lot of the work that they have to get done that’s a real value. We can spend a lot of time on automating that and having a chatbot in front of that. So, the conversational ability to really instruct the computer to get administration done is another low-lying fruit opportunity. One that we certainly want to jump on.

Guy Nadivi: Now, there are some concerns about biases, intentional or otherwise, creeping into the AI that powers things like chatbots. In order to root out bias, Harvard Business School published an article not too long ago, calling for the auditing of algorithms, the same way companies are required to issue audited financial statements. Kevin, do you think AI algorithms should be audited in the same way financial statements are for publicly traded firms?

Kevin Collins: Very interesting question. When I hear audit and I hear regulations, the hair stands up on the back of my neck right away. I think that’s just a natural reaction. As CEO of companies, I understand the need for regulation. I definitely understand the need for audit. It’s a bit of a balance between the innovation you want to see and then getting into that regulatory red tape. Biases are very real, and biases get introduced by the data scientists that put the models together. It gets introduced by the training data that’s going into these models, and those biases are very real, similar to the biases you might have in an organization just dealing with people, and you have to ensure that diversity gets introduced into your data science and into your AI. It’s one of the key areas that we love about the AI that we’re innovating at Charli because we have to test, and we have to test out the biases, and testing becomes an automated routine for how the AI needs to get deployed because we want to always act on the best interest of our users and our audience. That means that that needs diversity in the training sets. It needs diversity in the models. When you’re getting into auditing of the algorithms, I feel it’s far more important for the auditors to look at how these models are tested and continuously tested and implemented in order to avoid the introduction of bias, rather than just auditing of the algorithms. I don’t think that’s a fair approach. I believe it’s far better to continuously test these models as they’re operating and they’re being trained.

Guy Nadivi: Given the current state-of-the-art, what do you think are some of the most unrealistic expectations currently plaguing the field of conversational AI?

Kevin Collins: I believe the biggest AI missed expectation that we’re seeing is that the users, from a behavior perspective, don’t want to converse with their computer. That’s a big one, and that was a big highlight for me recently is watching how the users want to interact with their computer, either on their mobile device or through their laptop and desktop. Conversational interaction with a computer or a piece of software just became unnatural. Humans are expecting the computer to behave like a human, and we’re nowhere close to that today. There’s a lot of nuances on how human beings interact and how they ask for items. There’s a lot of expectation that the computer is completely automated behind the scenes. So, natural language processing that conversational is really just the front end. Then, there’s a missed expectation of this translating it into intents and having it fully automated by the computer. It’s just not there. That automation can’t match what the user expectation is, so when you get into conversing, there’s a lot of edge cases. There’s a lot of failure scenarios, and we end up spending a lot of time addressing the failure scenarios, the error conditions. We also try to spend a lot of time in putting up guard rails to guide the user conversation. What we’ve had to do is take a step back from just understanding conversational AI to maybe the user just wants to make a request and then wants some clarification on that, rather than having a conversation, and it’s avoiding the unrealistic expectations that we’re seeing. We don’t have the cognitive ability in AI to match what the consumers and the users are looking for today.

Guy Nadivi: Speaking of expectations, in technology, to paraphrase the economist, Rüdiger Dornbusch, things take longer to happen than you think they will, but then they happen faster than you thought they could. Kevin, what are some of your predictions for conversational AI over the next three to five years?

Kevin Collins: Things do certainly take longer to happen than you think it will. So, looking forward, I get impatient and it certainly can take a longer time than what I’m anticipating. But hindsight is, “Oh, that actually went pretty quick.” And that’s just, I believe, human nature. It is going to take longer to get conversational AI where we need it to be. If I look at what we have to invest time on is I think stepping back from just a full-on conversation with an AI to this request-response to clarification elements that can happen just with language understanding.

I believe the other area that we have to get into with the innovation that needs to happen over conversational AI is the automation to support the conversations or the interaction, and that automation is where I believe in the next three to five years the innovation is going to be. It’s going to be on no-code solutions. It’s going to be on the ability to have these models trained such that the user gets more out of the conversation through the automation, rather than having to get frustrated. We need to get the automation matching what the natural language processing can do, and that requires more than just the scripting and the coding that happens today. So, a lot more around this no-code capability, a lot more around the continuous training of the models and tweaking of the models to match the expectation.

Guy Nadivi: Interesting. Last year, there was an article in MIT Technology Review about Artificial General Intelligence or AGI. In that piece, the author, Karen Hao, who’s been on our podcast, wrote, “There are two prevailing technical theories about what it will take to reach AGI. In one, all the necessary techniques already exist. It’s just a matter of figuring out how to scale and assemble them. In the other, there needs to be an entirely new paradigm. Deep learning, the current dominant technique in AI, won’t be enough.” Kevin, what do you and your team at Charli.ai think it will take to achieve AGI?

Kevin Collins: Really pertinent question today. This one has come up a number of times, especially now that Charli is very focused on the AI technology that we’re doing. Our belief is that AGI is a long ways off. We’ll see in the various studies, and it can be anywhere from 10 to 40 to 50 years, depending on who you ask. I do believe it’s a 20-, 30-year journey before we see the massive innovation that’s needed for an AGI. But the other side of us goes, “Who cares?” There’s a lot of brilliant technology in the AI world today, and that’s what needs to be leveraged. If we’re looking at it from a corporate and an enterprise perspective, AGI is coming at some point with new algorithms but the reality of what we have today is brilliant. We’ve got deep learning, we’ve got machine learning, and I believe that the paradigm shift that we do need is more around the scale and the assembly. We’re completely missing that in the world of AI. You have to be able to scale your AI, not just to perform, but it has to scale from the perspective of models have to work for the individual, as well as the corporation, as well as an industry. You have to scale that because you have to apply context, and context awareness is one of the keys that we needed within Charli. How do we achieve context awareness at scale? The other part of it becomes assembly, and assembly of the models is a critical challenge. This is why I believe it’s the paradigm shift of scale and assembly because you need to bring context and you need to bring continuous learning and continuous testing of those models. You also have to assemble those models because the decision-making isn’t just a machine learning algorithm. The decision-making becomes a collaboration of various models to take in various inputs and to resolve conflicts in order to take action. This is why I believe that paradigm shift is all about scale and assembly. That’s what we need. Regardless of new models and methods that may come, scale and assembly is still a massive problem that needs to be solved today.

Guy Nadivi: Kevin, for the CEOs, 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 introducing new technology that leverages conversational AI and, in particular, what change management considerations do you think they should keep in mind?

Kevin Collins: Fantastic question. We’ve actually had the benefit of comparing and contrasting various enterprise organizations that we work with to see how to introduce this into it and what the success or failure rate has been. I would say there’s a high failure rate if you’re expecting too much around the conversational UX and that you can go and converse on any number of things simply because your automation on the backend cannot match the user expectations on the conversation. I think the biggest advice that CIOs need to take away from this is that you need to go in this eyes wide open and tailor the chatbot experience or that conversational input to what you can automate on the back, and make sure that you’re keeping the user interaction with your software guided. But the other big thing around that is that I do believe that this conversational AI element is where the future is going. We want software to work with the user far better than what it is today. We don’t want the user to have to learn the software. We want the software to learn about the user. So, there has to be a big innovation and a big investment into the conversational AI, but take these baby steps. Make sure that you are allowing the user to interact with the computer and interact in a way that you can automate, and you’re not frustrated. You don’t want to go down to say, “I’m just going to do conversational AI and put in a chatbot.” There’s a significant investment into scripting how the user flow needs to go. Similar to how you had to build up the UX or the user experience with your web-based interface, you’re going to have to invest into how you guide the user on their conversational flows, and that is an area of innovation that CIOs really need to look at.

Guy Nadivi: All right. Well, it looks like that’s all the time we have for on this episode of Intelligent Automation Radio. Kevin, thank you very much for joining us today and sharing your thoughts about the current state of conversational AI. We’ve really enjoyed having you as a guest.

Kevin Collins: Well, thanks, Guy. I really appreciate it. These have been fantastic questions. Obviously, one where we’re pretty excited about, but I’d love to follow up if there’s any follow-on questions from folks.

Guy Nadivi: All right. Kevin Collins, CEO of Charli.ai. Be on the lookout for them as they get closer to general release. Thank you for listening, everyone. And remember, don’t hesitate, automate.



Kevin Collins

CEO & Founder of Charli.ai.

Kevin is founder and CEO of Charli AI, a startup focused on helping busy workers get more life back in their work-life balance. As a serial entrepreneur and technology company founder, Kevin has experienced the explosion of productivity software and the tools we use to work, yet productivity is declining and people are more stressed than ever. Enter Charli, a novel conversational AI that eliminates productivity killers from your workday. Part workflow automation, organization wizard, and search engine - Charli simplifies some of your most time-consuming tasks. 

Kevin brings more than 30 years of experience in architecting and designing software, both as a start-up entrepreneur and as a corporate executive. Kevin has extensive knowledge about artificial intelligence and machine learning. Before founding Charli, Kevin was CEO and Co-Founder at Bit Stew Systems, a data intelligence platform, which was acquired by GE Digital for its AI and ML capabilities in 2016. Prior to his time in Silicon Valley, Kevin worked in the high-tech networking and security field, and led technology firms specializing in cryptography, public key infrastructures and high-performance and scalable networks. As a second time founder, Kevin is passionate about sharing his expertise in building successful startups. 

Kevin can be reached at: 

Website:          www.charli.ai 

Twitter:           @charliai 

Newsletter:    https://charliai.substack.com/p/hey-were-new-here 

LinkedIn:        https://www.linkedin.com/company/charliai/ 

Facebook:      https://www.facebook.com/charliai 

Quotes

“I believe that entire market for chatbots is ripe for consolidation. There's far too many of the technologies that are out there. There's also a massive amount of hype that's gone into the chatbot area and people are now realizing the reality of chatbots will only take you so far.”

“It's a completely different challenge to have a human converse with a computer and that computer to completely automate what the human wants to do and have a full-on interaction.”

"We're finding people spending 20% to 50% of their day just on the minutiae of administration, and that's distracting them from a lot of the work that they have to get done that's a real value. We can spend a lot of time on automating that and having a chatbot in front of that. So, the conversational ability to really instruct the computer to get administration done is another low-lying fruit opportunity. One that we certainly want to jump on." 

“When you're getting into auditing of the algorithms, I feel it's far more important for the auditors to look at how these models are tested and continuously tested and implemented in order to avoid the introduction of bias, rather than just auditing of the algorithms.”

“I believe the biggest AI missed expectation that we're seeing is that the users, from a behavior perspective, don't want to converse with their computer. That's a big one, and that was a big highlight for me recently is watching how the users want to interact with their computer, either on their mobile device or through their laptop and desktop. Conversational interaction with a computer or a piece of software just became unnatural. Humans are expecting the computer to behave like a human, and we're nowhere close to that today.”

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.

GET STARTED WITH AYEHU INTELLIGENT AUTOMATION & ORCHESTRATION  PLATFORM:

News

Ayehu NG Trial is Now Available
SRI International and Ayehu Team Up on Artificial Intelligence Innovation to Deliver Enterprise Intelligent Process Automation
Ayehu Launches Global Partner Program to Support Increasing Demand for Intelligent Automation
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

Follow us on social media

Twitter: twitter.com/ayehu_eyeshare

LinkedIn: linkedin.com/company/ayehu-software-technologies-ltd-/

Facebook: facebook.com/ayehu

YouTube: https://www.youtube.com/user/ayehusoftware

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