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Episode #50: How Automation Helped LPL Financial Grow Into The Largest Independent Broker Dealer In The US – LPL Financial’s Dwayne White

October 2, 2020    Episodes

Episode #50:  How Automation Helped LPL Financial Grow Into The Largest Independent Broker Dealer In The US

In today’s episode of Ayehu’s podcast, we interview Dwayne White, Vice President of Technology Automation at LPL Financial Services

Some of you were introduced to automation in school, or at work, or perhaps even by a family member or friend.  Our guest on this episode began his automation journey in the US Marine Corps.  Corporal Dwayne White’s first automation project involved “digitally transforming” a manual process done on a Xerox typewriter into a far more efficient solution done on a PC. From there, he progressed through successive levels of technical & executive responsibility, until reaching his current position as VP of Technology Automation at LPL Financial Services. 

As the largest independent broker dealer in the country supporting nearly 17,000 financial advisors, technology plays an outsized role in LPL Financial’s success.  Dwayne was instrumental in leveraging automation to power LPL’s growth, both as a hands-on techie and as a manager.  He shares some key insights with us in this episode, and we learn how automation mitigates risk for LPL Financial, the specific kinds of processes LPL automates, and why you shouldn’t look at automation as a replacement for your staff. 



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 Dwayne White, Vice President of Technology Automation at LPL Financial Services. For those not familiar, LPL Financial is considered to be the largest independent broker dealer in the US, with nearly 17,000 financial advisors and $762 billion in advisory and brokerage assets under management, as of June 2020. Dwayne is a hands-on IT operations executive in charge of technology infrastructure automation. He’s also worked a lot with L1 and L2 NOC engineers, overseeing their efforts in a never ending pursuit of reducing incident MTTR. Automation has played a big role in Dwayne’s success at LPL Financial, and since he brings a unique dual perspective, with both first-hand and managerial experience in automating various IT processes, we wanted to bring him onto the podcast and see what we could learn. Disclosure: LPL Financial is a customer of Ayehu, the company sponsoring this podcast.

Dwayne, welcome to Intelligent Automation Radio.

Dwayne White: Thank you, Guy. It’s a pleasure to be here today. I always enjoy listening to the Automation Radio podcast.

Guy Nadivi: We appreciate that, thank you. So Dwayne, you started out at LPL Financial as a developer, and 20 years later, you’re Vice President. What were some of the bigger IT challenges you overcame during those two decades while the company was growing as rapidly as it did?

Dwayne White: Well, for me, it was both a personal, and I guess you can say, IT challenge. On a personal nature, for me, early on it was deciding in my career if I wanted to be a techie, or did I want to be a developer, did I want to be a manager? And for me, I wanted to be a manager. And what that meant to me is it meant I can go ahead and mentor and train new staff, and have a voice with my managers, my leadership. Outside of that, early on still in the back at LPL. We were a small company, and as a small company, we had our issues, our challenges, and some of those having to deal with how we managed incidents. Back in that time, our pagers would go off, we would jump on a phone call, everyone would talk over themselves. It was just organized chaos. Now, that seemed to work for us at the time, but like everything else, we knew we can do better. And what better meant for us is we started looking at ITIL. ITIL basically is a framework that people used for instituting IT business processes. And once we started moving down the ITIL model and we started maturing our processes, things got a lot better for us. It was a good thing to do. Outside of that, was learning how to adopt to our change and transformation. Most people aren’t comfortable with it. I’m not comfortable with it sometimes. And usually, when change is implemented and transformation is implemented, sometimes it’s done well, sometimes it’s done poorly, and when it’s done poorly it’s mainly due to lack of communication out to the teams. What we found is that our teams, they want to be involved. They want to know what change is coming down the pipe. They want to have a voice in that change. As an example, if you were to come in on a Monday morning and tell your team that instead of working Monday through Friday, they’re now going to work Tuesday through Saturday, they wouldn’t be too keen on that change. But if you involve them in the process, communicate to them the need, not only for business, but for themselves, we can start getting their buy-in on it. We found that actually works a lot better for us.

Guy Nadivi: So what were some of the bigger reasons you decided to look into automation at LPL Financial?

Dwayne White: Well, for us, my boss actually got me down the path of looking at it, and he had concerns about how we were delivering our services. And services can be defined as how we processed our service request tickets, how we responded to incidents, how we communicated. And bringing automation into it just seemed like a natural fit for us. So, back in 2015, that’s when we started looking at the various tools, the different processes, we dealt with Gartner, started looking at some of their Magic Quadrant work, and we started moving forward. So, for example, one of the inconsistencies that brought us forward would be if you had a ticket assigned to somebody, and let’s say it had to do with the Windows server, a disk problem. You can assign that to three different admins and you’ll get three different results. One person has one way of cleaning up disk space, the other person has another. So we needed consistency in that. Automation? That was the clear path. It does one thing. You tell it what to do, it does it, and it repeats. The nice thing with automation, just like a disk space problem, is you learn as your applications grow and capacity changes. You change the script. You change the automation to adapt to it. The other part of it was risk. No one’s perfect, but with automation you can reduce the even element of risk. Even elements could be missed alerts due to outages. Staff’s not always at their desk watching their ticket queues 24×7. Or a slow response time to an incident. Again, you’re counting on your staff to be sitting at their desk, glued to their ticket queues, or waiting for their phone to ring. With automation, it’s there, it’s live. It’s 24×7 and it’s waiting to be called upon. It was a natural fit for us. I’m glad we did it.

Guy Nadivi: Okay. Now, you mentioned the need for uniformity and consistency, and it’s well known that financial services firms have very rigorous regulatory requirements to comply with also. Given that reality, how challenging was it to persuade management that automation was worth a try?

Dwayne White: It’s true. I mean, we’ve got a whole bunch of regulations. It’s interesting, we learn more and more each day as our government changes them, or FINRA or the SEC. There’s always something new to adapt and change to. But at a high level, when you look at the financial industry, its regulations are there to protect our consumers, prevent fraud, and limit risk. And the risk limiting is mainly what can that financial institution do to investor’s money? So, looking at risk, that was probably one of the big selling points. So, as we approached our architectural review board, I basically highlighted basically how automation can help lower the risk, as previously mentioned, as well as the rewards, such as consistent delivery of service, improving mean time to restore service improved SLAs, satisfactions. I mean, the list can go on if you can put the case properly. And basically, with the help and guidance of the review board, we were able to adopt it and we’re now moving in the right direction.

Guy Nadivi: Dwayne, I think it would be very interesting for the listeners if you could talk a bit about the platforms that you’re performing automation upon in your environment.

Dwayne White: So, platforms, integrations, an example would be Active Directory. So we currently have automations that deal with self-services to modify Active Directory to find user accounts. We revoke user accounts. We add users to various security groups. And we can schedule the automations. We have hooks that are tied into Microsoft Exchange, we’re hooked into the file shares, we’re doing work with ServiceNow. With ServiceNow, basically, we use that as the catalyst to monitor the ITSM queues, to pull back service requests and incidents that we can respond to with automation, as well as you’ve also got to look at your automations you’re creating as not being dealt with. So, for example, if you have an automation that is going to reach out and do something with Active Directory, what happens if your Active Directory controller is not working? You need to put in some error checking and then detect the error and then go ahead and create an incident for someone else to look at it. So that’s how we go ahead and create incidents with ServiceNow. We also hooked into Microsoft SQL servers, we’re doing access provisioning, space consumption and alerting. We do work with Windows servers, we take incidents, we call them “level zero triaging”, as well as we’ve got scheduled service restarts. We’ve also got automations that are tied into third party web services. With that we do REST APIs, data extraction and reporting, as well as we create incidents off of those. What we’re working on now, and hopefully over the next few months is the integration packs for AWS. So we’re starting to hook into the Cloud and see what we can automate out there. We’re going to start working on SharePoint here soon. Also, let’s see, Oracle database access provisioning. And it’s interesting, in talking about the regulatory stuff above, when we first got the platform, our regulatory team came to us with some automation suggestions, and we got those implemented for them. So it was nice to have that as one of our first automations. We’re happy.

Guy Nadivi: Okay. Clearly you’re automating and attempting to automate lots of different processes. So how do you define success once you’ve automated a process?

Dwayne White: Success, we actually try and get the success defined before we automate. And what we do is we basically engage with the teams. So an example, if someone comes to our team and says, “Hey, I got this widget and I need this widget and process automated.” So what we do is we look at the number of requests that would come in, that’s being done manually. We’d take a look at the triggers that would trigger the workload, and the time that it would take to complete the request manually. And what is the current SLA for the request and/or work incident, what’s the mean time to resolve it? Outside of that, we also look at the effort we put into the automation versus a manual task. So, for example, if the manual task, right now it takes an hour, but you’re only doing it three times a month, maybe that’s something we’ll keep in place. That’d be a manual process because it’s the development effort to design the automation might be longer than that. So, for example, recently we did a thing with Active Directory, a simple automation to add somebody to a security group. Our current statistics have basically shown us that the manual process had averaged about 1.5 days for the team to actually do the work. And that’s with the ticket coming in, somebody approving the ticket, and then, over the next one and a half days, somebody actually doing the work outside of their normal daily routine. We found out we were averaging about 265 of those requests a month, but once the team actually got the ticket and did the work on it, it actually only took about five minutes. So, doing the math, and this goes back to the success part, the manual process was 265 tickets, five minutes each; basically we were spending about 22 hours a month on that one ticket item in a manual process. Also, you’ve got to remember, it took one and a half days for them to finally get this ticket done. Now, you throw in some automation with it, you get to take the same 265 tickets, instead of being five minutes, it’s now done in 30 seconds, and we’re only spending 2.2 hours of automation time on it. So we just freed up 22 man hours. And the other nice cherry on the top is, if you remember, it took one and a half days for the manual process to finally open and close. With automation, we’re talking 30 seconds, because we’re constantly polling our ITSM tools for the next ticket. So now you have a clear, consistent, repeatable process that your customers will see, and it’s a win/win.

Guy Nadivi: Okay. So now I’m a bit curious; do you ever get more formal by calculating the ROI of automating a particular process? And if so, other than time-savings, what kind of metrics are most relevant for you?

Dwayne White: So for us, I present my management, I try to at least monthly, to know how our team is performing. And part of that is showing the automations that we took over and what the manual process was keyed up at as far as SLAs and time to resolve for incidents … I’m sorry, mean time to resolve for incidents. And I’ll put together a nice little dashboard showing them the savings done with it, as well as any failures within our automation, which is very, very limited. But it’s a nice dashboard that shows them the KPIs that they want to look at.

Guy Nadivi: Dwayne, with all the processes you’ve automated, I’m curious if there’s any particular one that stands out as the most successful IT business process you’ve automated?

Dwayne White: So I would say the most successful one that we’ve automated … oh, let’s see. So we have about 43 automations right now. Of those, most successful, I would probably have to say it’s probably the employee offboarding automation. What makes it successful is that one’s actually looked at from a internal audit perspective. So for an example, when an employee decides to move on or is terminated, whatever the case may be, once the effective date comes in, we have two business days to get them terminated and off-board properly out of our systems. So what was different about this is they can actually put the ticket in a couple of weeks in advance. So, for example, if a guy wanted to move on from Ayehu, he would tender his resignation and they would go ahead and submit the termination paperwork, but it wouldn’t be effective until let’s say two weeks down the road. So for us, it was trying to pull in and design the automation to where when the ticket was put into the system and it had all the approvals, how not to process it until the actual effective date. So that one did stump us for a while, but we did work through that one finally, and we’ve got it in place and it has been running successful right now for probably about four or five months. And the nice thing is we’re able to use that as a framework for other automations that had similar characteristics with it. If you look at what we had to do with our employee offboarding, it would take a system admin 30 minutes to go through and touch upon the different areas that they had to remove accounts from, or pull them out of different security groups or distribution lists. Now, automation does it in two minutes, and it does it within the 2-day SLA, the second the effective date happens at, let’s say this Friday at 5:00 PM, automation is kicking off. So we don’t have to worry about, “Uh oh, you were working over the weekend,” or, “You didn’t have to work over the weekend to make sure you kept your SLA.” And it’s kept our internal audit team happy, Infosec’s been pleased, and haven’t had any issues. So.

Guy Nadivi: Dwayne, you were in the Marines for nearly six years, but not in an IT capacity. First off, I’m sure I speak on behalf of all of our listeners when I say thank you for your service. Secondly, I’m curious to hear how did being a Marine prepare you for a career in IT operations?

Dwayne White: Yeah, let’s see. And thank you, it was my pleasure. I actually enjoyed the service. Actually I joined when I was in high school. So they had a program back then called a delayed entry program; you could join in your senior year, and upon graduation, you can go ahead and jump into the Marine Corps. So that’s what I did. I had a nice two week summer vacation. And this was … oh, let’s see, back in 1984. So I served in the Marines from ’84 to 1990. And Marines, there’s different jobs in the Marine Corps. So I was assigned to a helicopter squadron and my role was an aviation ordinance technician. Normally you’d think that sounds like fun, and it was, but as an aviation ordinance technician, a lot of people think, “Oh, cool, you get to play with bombs and missiles and things like that.” And there’s not many things to automate, it’s a lot of manual work, it’s heavy lifting. But what people don’t think about, and sometimes they forget, is our government and the military, they love their paperwork. And the paperwork has to deal with maintenance on the aircraft, personnel changes, scheduling, you name it. There was a ton of paperwork that was being done. And we didn’t really have a computer back then, but we had a nice typewriter, a beautiful … probably, if I think about it, maybe a Xerox typewriter. And that’s how I learned how to type. That plus high school. But from there, I went ahead and took a course at a local community college. I was stationed out in Jacksonville, North Carolina. And the class I took was around data processing because I thought that would be a good fit because I got tired of trying to type on the typewriter and make everyone happy, because my penmanship’s not the best in the world. And after graduating from the community college, I was able to come back to my shop, convince our Master Sergeant that, “Hey, we really need to get a computer because I can help us with all this typewriter stuff by taking it from a typewriter and putting it into a computer and then producing the same paperwork, the same forms, changing what we needed to change.” And I got that implemented. It took a little while, a lot of hit and misses, but it soon started working for us. And that’s how I got going with the automation. Outside of that, I’m in the Marine Corps, it’s great. I mean, how they prepared me, like everything else, it’s how they train you. It’s the discipline, it’s the operational efficiency of the Marine Corps. If we wouldn’t be efficient, we wouldn’t be disciplined. That’s it, pretty much, in a nutshell.

Guy Nadivi: Dwayne, 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?

Dwayne White: I would probably tell them that they need to invest into a dedicated automation team. What I mean by that, it’s not going to be someone’s part time job, it’s not going to be an afterthought, it’s truly a team dedicated to automation. And once you have that in place, you get them involved with your projects. You get them involved early on, because they’re going to bring a skillset that they haven’t seen before, because there’s still a lot of IT companies who are used to manual processes. If you look at a lot of the data center operations or batch operations, you’ve got these operators glued to your computer monitors, and all they’re doing is staring at it and waiting for something to happen. Or maybe they have a task list that they have to go through at nighttime to make sure the batch processes are running properly. Those are opportunities for automations, and you’re not going to see those unless you have a dedicated team who’s out looking for them. The other thing, and I tell this to my team and the teams that I work with when I’m trying to get them to bring me more ideas for automation, is do not look at automation as a means to replace your staff. That shouldn’t be your first thoughts, thinking that you could save a few dollars. You need to look at it as an opportunity to give back to your staff time. As we mentioned earlier, that one automation, it went from 22 hours down to two hours. There’s 20 hours of time back to your staff for them to focus now on your manager’s next big project, or give them time to invest back into their training through their career development. It’s a win. You can’t go wrong.

Guy Nadivi: Great advice from a hands on practitioner. All right, looks like that’s all the time we have for on this episode of Intelligent Automation Radio. Dwayne, our listeners have told us they want to hear more firsthand insights from automation practitioners like yourself, and you’ve definitely delivered that to our audience today. Thank you very much for coming onto the show. Dwayne White: Oh, thank you. Have a good day.

Guy Nadivi: Dwayne White, Vice President of Technology Automation at LPL Financial Services.

Thank you for listening everyone. And remember, don’t hesitate, automate.



Dwayne White

Vice President of Technology Automation at LPL Financial Services

Dwayne White has been with LPL Financial almost 20 years and a Developer for almost 30 years.  LPL Financial is the largest independent broker/dealer in the country supporting nearly 17,000 financial advisors.  While at LPL Financial, Dwayne has held various roles:  Software Developer, Incident Management, Problem Management, Data Center Operations, Service Delivery Management, NOC Operations and he has managed diverse teams to include Database Admin’s & Developers, Network Engineers, Developers, Windows Operations & Engineering, Unix Operations & Engineering, Active Directory, Exchange Engineers & NOC Engineers. 

Dwayne’s current role with LPL Financial is Vice-President Technology Automation.  In his new role, he and his team focus on delivering Infrastructure as Code & IT Process Automations focused on Service Delivery and Incident triage.  Dwayne is a strong believer that Technology Teams need to embrace Automation as a tool for their arsenal as part of their Digital Transformation and let them know Automation is not a threat to their job.  Let the automation handle the day-to-day grunt work and allow your teams to focus on the company’s larger efforts & priorities.  The end result will be a happy customer & client. 

Dwayne can be reached at: 

LinkedIn:         https://www.linkedin.com/in/dwaynewhite/ 

Email:              Dwayne.White@lpl.com 

Quotes

“ITIL basically is a framework that people used for instituting IT business processes. And once we started moving down the ITIL model and we started maturing our processes, things got a lot better for us. It was a good thing to do.” 

“…usually, when change is implemented and transformation is implemented, sometimes it's done well, sometimes it's done poorly, and when it's done poorly it's mainly due to lack of communication out to the teams. What we found is that our teams, they want to be involved. They want to know what change is coming down the pipe. They want to have a voice in that change.” 

"…I tell this to my team and the teams that I work with when I'm trying to get them to bring me more ideas for automation, is do not look at automation as a means to replace your staff." 

About Ayehu

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

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Links

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

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Disclaimer Note

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

Episode #48: How Microsoft Will Change The World (Again) Via Automation – Microsoft’s Charles Lamanna

September 16, 2020    Episodes

Episode #48:  How Microsoft Will Change The World (Again) Via Automation

In today’s episode of Ayehu’s podcast, we interview Charles Lamanna – Corporate Vice President, Low Code Application Platform at Microsoft

“To me, Microsoft is about empowerment… we are the original democratizing force, putting a PC in every home and every desk.” That quote by CEO Satya Nadella, of course, reflects the ubiquity achieved by the Windows operating system. His company’s feat of democratization however, is just prologue to the coming revolution Microsoft foresees in automation. An upheaval expected to be so disruptive to the status quo, it will empower the information worker masses to finally overthrow the oppressive yoke of robotic tasks smothering their productivity.  With newfound freedom to unleash their ingenuity, they’ll not only enrich their own lives, but add greater value to the organizations employing them. 

The Microsoft executive charged with redressing the imbalance between toil & talent plaguing white collar wage earners is Charles Lamanna.  As Corporate Vice President, Low Code Application Platform, his portfolio of responsibility encompasses all the critical assets needed to bring Microsoft’s lofty vision to life.  In this wide-ranging discussion, we get first-hand insight from a senior executive on the vital role automation plays in the software giant’s Cloud-First, Mobile-First strategy.  Along the way we’ll also learn why the shifting ratio of repetition to creativity within a given task will determine which automation type it’s best suited for; the automation skills one should master to position themselves for success in the future; and what the single biggest disruptor for automation will be over the next few years. 



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 Charles Lamanna, Corporate Vice President, Low Code Application Platform at Microsoft. Now, there are many products at Microsoft that Charles is responsible for which I’m sure our audience members are very familiar with, including the Dynamics 365 platform, Power Apps, Power Automate, Power Virtual Agent, AI Builder, and the Common Data Service products. And as everybody in IT knows, Microsoft almost always becomes a major player in any market they enter. The automation and AI markets which we focus on, are unlikely to be exceptions to that. So given the strategic automation and AI assets Microsoft has entrusted Charles with overseeing, he’s someone we absolutely had to have on this podcast. And we’re thrilled, he’s taken time out of his very busy schedule to join us today. Charles, welcome to Intelligent Automation Radio.

Charles Lamanna: Thank you for having me on the show today, Guy. I’m super excited to get into the thick of automation with you. I know I’ve been a listener recently, so really excited to get into the dialogue.

Guy Nadivi: So let’s start with that, Charles, please tell us a bit about your role at Microsoft and the types of automation you’re focused on.

Charles Lamanna: Sure thing. So as you mentioned, I’m the Corporate Vice President of Low Code Platforms at Microsoft. So I’m on the R&D side, engineering and product management, lead those teams related to the Power Platform and Dynamics 365. The most relevant products that I oversee when it comes to automation and AI is Power Automate, which is our robotic process automation offering at Microsoft. Power Virtual Agent, which is our low code chatbot experience, and AI Builder, which is our low code AI and machine learning tool for business users and business developers. And those three things really together combine to create what we call our automation platform.

Guy Nadivi: So earlier this year, Microsoft made a big splash in the automation market by acquiring Softomotive, an automation vendor with 9,000 global customers. And that capped off a sequence of high-profile transactions in the automation space, which made it clear this is going to be a market of intense focus for some very significant players. Charles, how does Microsoft’s automation fit into its Cloud-First, Mobile-First strategy?

Charles Lamanna: That’s a great question. The first thing I’d say is that we’re super and incredibly excited about the Softomotive acquisition within Microsoft. We think it really is a great compliment to Power Automate, Power Virtual Agent, AI Builder. To really kind of map back what we were thinking around Softomotive in our general automation strategy, I do want to spend a second just talking about the overall automation vision at Microsoft, because that I think helps paint a really good picture for it. When we talk about that vision, there’s really four main pillars to it. The first one is that automation is more than just UI Automation. One of the big trends recently in automation technology has been robotic process automation or RPA. But RPA historically is incredibly centered and focused on UI Automation and more specifically Windows-based automation. And it’s our view that that UI Automation is necessary, but insufficient to really enable interesting automation scenarios and really transform every aspect of every company in every country around the world. So things like API connectivity or API-based automation or AI capabilities like natural language understanding or NLU or a whole bunch of other exciting AI technologies, those are also key ingredients. So just being more than UI Automation is really important. The second is being cloud first. We think there’s I’d say a legacy of automation being very PC-centric, very on-premise centric, and there’s some real potential to reimagine what automation looks like in a cloud native, cloud first way. So that’s really important to our vision. Number three is that automation has to be generated and supported by AI. Has to be enabled by AI capabilities in terms of identifying what can be automated and the best way to automate it. As well as when those bots run, use AI to go make them better over time. And last but not least, by far my favorite aspect of our vision is low code. And this permeates really a lot of work we’re doing at Microsoft these days. But low code is a whole idea that you want to make it so anybody and everybody can be a developer, can build bots, can contribute to the automation revolution. That’s not just constrained to a small group of experts or developers. So those are the four aspects more than UI Automation, cloud first, generated & supported by AI, and low code. But getting back to the Softomotive acquisition, the WinAutomation desktop app was really in our view the leading low code RPA tool out there, has a huge fan base, very frequently adopted virally and by business users. So people just going to a .com, downloading it, and starting to automate. Additionally, WinAutomation was built in such a way as well as with the new open source Robin programming language for easy accessibility into the cloud. So it can very easily integrate with a cloud provider. So that combination of that low code desktop application, as well as the cloud integration and cloud readiness made Softomotive a great fit for the Power Automate vision and the Power Automate offering, and therefore a really great fit for the broader and mobile centric cloud first approach that Microsoft is taking these days.

Guy Nadivi: Interesting strategy. So there are many professionals today Charles, that can be categorized as information workers and maybe eventually some of them will also become app developers in the sense that you were talking about. How do you envision automation changing the jobs of information workers, and which roles or positions do you think will be the most difficult to automate?

Charles Lamanna: Yeah, I would say, we think that automation will be an important part of really any modern information worker job in the future. But the importance and the criticality will be a spectrum from say, somewhat impactful to very impactful, but really all information workers will feel that impact, will feel the responsibilities change and evolve over the next five years or so. And a major reason for that is the advancements in artificial intelligence to understand unstructured content like voice, video, text, as well as the fact that basically all the information worker’s job is captured digitally, is running on a PC or on a mobile device or mirrored in the cloud. So you can really start to enhance and automate almost any profession. However, I’d say that this transformation isn’t, I’d say all or nothing. There’s actually two really different ways that we look at what automation will do. The first is what I would call human assisted automation. And the second is autonomous automation. When we talk about human assisted automation, the idea is it’s all about helping a human do their job better, be faster, reclaim time, spend more energy on creativity and high value, high cognitive tasks. Less on doing data movement or simple rote activities. And autonomous automation is automation happens in the background. Does things without interacting with the human, pulling work off a queue or responding to events. And there are two fairly different approaches in terms of how automation can impact an information worker. And we think that some jobs will be heavily impacted by autonomous automation while others will be impacted primarily by the human assisted automation. And the difference between the two is really going to depend on how much repetition and how much creativity happens as part of the job. There’s more repetition and less creativity, there’s going to be more autonomous automation. If there’s less repetition and more creation, there’s going to be more human assisted automation. And that human assistant automation can sometimes be really subtle. If you imagine, in Outlook these days there’s suggested responses to emails, right? That’s automation. That helps me respond to emails more quickly, things like that. So we’re really going to see this permeation of applications, whether they’re integrated with the standard SaaS apps, standard OS’s or custom bespoke automation built for a company, we’re really going to see an emergence across both those front, the human assisted and autonomous-based automation.

Guy Nadivi: Okay. Let’s expand a bit on what you said and assume that automation will be part of the role for all or most information workers in the future. If I’m a college graduate entering the IT job market, or a seasoned IT professional looking to change specialties and interested in automation either way, what skills should I focus on acquiring to accelerate my career?

Charles Lamanna: Yeah, the first thing I’d say is automation is a fairly broad ecosystem. So if you want to be part of the automation revolution in terms of contribute to building out these different automations within the enterprise, you have to I think go to a few different places. The first one I would say is UI Automation, RPA is a really key aspect of it. And that’s because there’s a whole lot of systems which can only be reached via UI Automation. Like I said earlier, it’s necessary but insufficient, but you definitely want to go out and get familiar with RPA tools and UI-based automation. The second thing is get a good view of APIs, and what enterprise application integration looks like, whether that’s APIs or event-driven architecture, because that’s the more future-looking way that automation will be built and created in the enterprise. And having a good view of service-oriented architecture, microservice, API catalog, event catalog, things like that will be very useful. The third is interesting because I’d say it’s not really related to technology at all. And that’s understanding business processes and designing business processes. Because automation is all about improving a business process. So knowing the language, the terminology, and the aspects you want to optimize when it comes to business process engineering is a really great tool. The fourth thing would be just a standard software development life cycle. If we go look at what it looks like to build out these automations, there is a design phase, there’s a planning phase, there’s development, there’s deployment. And the automation tools out there are compressing these cycles to be just hours or days long as opposed to weeks or months. But you still should know that cycle because that’s important to be successful in the enterprise. And the fifth, which I would say is the extra credit, but it’s going to really separate the good from great is going to be AI and ML understanding. And you don’t have to be a deep learning expert, doing super 40 megawatt AI model training like GPT-3 or something. We should feel comfortable around the … At least the high level concepts of machine learning. So things like reinforcement learning or transfer learning, which are going to be really important in the future when it comes to building durable, reusable, high value automation, at least from Microsoft’s perspective. So those are kind of the five things. Four, I’d say standard, and one, a little bit extra credit that would be important to really be successful in the IT space when it comes to building automation and the enterprise.

Guy Nadivi: Let’s talk about one form of durable automation that you’re referencing. In the form of AI-driven assistance or bots, which are growing in prevalence for a lot of customer-facing applications. Gartner believes there are as many as 1,500 chatbot vendors worldwide. And I quote, “The majority of these conversational platform vendors offer very simple platforms using modified open source components to deliver simple question and answer chatbots.” Now I think it’s safe to assume the market doesn’t need 1,500 vendors in this space and an inevitable shakeout is coming. Charles, what kinds of things do you think will differentiate the survivors in this market space from the vendors who will fall by the wayside?

Charles Lamanna: Yeah, I think like any kind of technology market, as it becomes more mainstream, you start to see more consolidation and all-in-one offerings start to emerge as opposed to lots of little point solutions. And folks that know me well, I love my numbered lists. So I’d say there’s probably four different aspects that will really define what chatbots in the future will look like, that at least map into our strategy at Microsoft. The first is omni-channel, and what we mean by that is a chatbot that only works in a web-based chat experience is going to be insufficient in the future. You’re going to need to support I’d say WhatsApp, SMS, Facebook, voice, things like Alexa. There’s really going to be a need to support all kinds of different form factors to be successful. And you need to abstract away those channels from the bot authors and bot developers. So the ability to go reach into tons of different channels will be absolutely essential. The second is really being deeply, deeply AI-enabled. Chatbots are probably one of the best places where we see amazing return on advanced AI right now. Things like reinforcement learning, where you actually improve the control flow in your chatbots based on experiments and the results, and improve your models basically for matching entities are intense. For the bots that have used that for our technology at Microsoft, that significantly improves the success rate of sessions. And that’s pretty sophisticated AI capabilities. The third is really integrating with broader business processes, because what we see is no bot is an island, right? No man is an island, no bot’s an Island. No bot just exists on its own. It has to integrate with other systems in the enterprise to take actions, to fulfill returns, to help a customer purchase something. That requires integrating with other workflow systems, other databases, and really kind of running the end to end workflow. So really that integration to a broader ecosystem is going to be key. And the fourth one, the last one I think is not always super obvious, but it’s the ability that go hand off to a human, to work with a human, to have a chatbot and humans work side by side. And this, the reality is that there is no general artificial intelligence. There is no chatbot that you can run that can answer any question of a customer with anything. So any chatbot will always run against its limit – the limit of its abilities. And in those cases, you can’t churn the customer out or push them to a dead end, or say “We’ll call you back.” Instead, you need a seamless amnesia-free handoff to a human agent that can continue the conversation and grind it out. And what we’re finding is that this is what allows the usage of chatbots as a main line dependency in mission critical enterprise defining business processes, because you can cover the 75% with the chatbot and then you can cover the 25% with the human. And this is a great example of that human assisted bot versus human assisted automation I was talking about earlier. And one of the great examples of this at Microsoft internally, we have a chatbot which we use for our support experiences at support.microsoft.com. There’s over a million support cases that run through it every month. And the chatbots and human agents work hand in hand to address the needs of our customers. This produced, when we rolled it out, demonstrably, better customer satisfaction. We improve the customer experience and at a much lower cost. So that last one we think is going to be key. And if you do just a chatbot and don’t have a story for human agents behind the scenes, you’re really going to be leaving a bunch of use cases on the table. Because when a customer runs up against those dead ends, they’re going to go bail on the chatbot entirely. So I think those are the four main things that we really think are going to be defining for the space over the next few years and therefore be defining for the vendors in the space over the next few years.

Guy Nadivi: Speaking of humans, when you talk with your customers, what are they telling you are some of the biggest challenges they’re experiencing in deploying automation within their organization?

Charles Lamanna: Yeah, I’d say the biggest thing we hear really with everybody is finding the right skills, finding employees and experts with the right skills. And when I talk about skills, it’s not just related to the technology. It’s also about how do you understand the problem, how do you understand business process engineering. How do you understand the business needs, where automation will provide value. And that combination of being able to understand the business process, understand the business needs, in addition to understanding the automation technology, whether it’s RPA, AI, or DPA – that combination is really what we see a lot of organizations struggle with, and things like creating automation centers of excellence or doing internal skilling and training programs. The combination of those things is really what customers are trying to do today to go respond to this challenge. I mean, there’s probably a tale that’s been around for quite some time for disruptive or interesting technologies, which is just that change management skilling and mapping into the business need is what’s really slowing down adoption in most cases. So I’d say having a good strategy for skilling and training is a really important aspect for a lot of the customers that we work with to go make them be successful with the technology that they have.

Guy Nadivi: We’re hearing more and more about process mining and other AI-based discovery platforms being deployed as part of digital transformations. Charles, how do you think these tools are impacting adoption rates for automation?

Charles Lamanna: They’re accelerating them. Massively accelerating them. And I think process mining and the AI discovery capabilities is probably the most interesting thing that we’re watching at Microsoft when it comes to automation over the next couple of years. And the reason is because it’s still early days today, of course, but these tools help you very quickly identify processes that are ripe for automation. And even more interestingly is they actually help with the calculation of the ROI for an automation project. And this really is the dream of most IT transformation projects. Before you invest in building out the bots, before you invest in building out the AI, you can quantitatively analyze your workforce, understand where there’s inefficiencies, and then project the actual efficiency gains and customer experience gains once you roll out automation. And once you have this kind of closed loop of mine the processes that are happening, identify the upside, address the automation need, then confirm that you saw the results you expected. This is going to create a very virtuous cycle of building bot after bot, after bot, after bot, that will really start to change the landscape in IT and for information workers. So we think this is really going to help just accelerate it, but it all goes back to just helping understand the economics, understanding the ROI, and understanding whether or not you were successful with a IT or automation project. It all goes back to those basic principles which every IT manager is always worried about. It makes that be much less of a guessing game. And if I were to make a comparison, it reminds me of the shift in marketing, from broadcast marketing, where it’s very hard to understand the impact of a marketing campaign, because you didn’t know how many people actually went to go purchase something as a result of a commercial or something in a newspaper. When you went to digital marketing, for the first time you could know for every ad, how many people actually purchased the good that you were advertising, because you have tracking and things like that. That is – and that actually drove a ton more adoption, a ton more digitalization of advertising. We think a similar phenomenon is going to occur because you are going to be able to go track from ideation of an automation project, to the ROI of the automation project end to end. So that is what I would say is the acceleration we’re seeing and the why, and how we really imagine it shifting over the next couple of years, going forward.

Guy Nadivi: Some organizations have really embraced automation, at least partially because they understand the ROI potential you just spoke about, and they’ve made it a core part of their IT operations. Other organizations have more of a wait and see attitude. Regardless of where an enterprise falls on the automation maturity spectrum, what do you think are the key factors they should consider when formulating their automation strategy?

Charles Lamanna: I’d say the most important thing to consider is that any automation project or automation transformation, is recognizing that it’s going to help your business processes go faster and be more efficient where it doesn’t inherently reimagine or transform your business process. And the reality is that automation is just like any other tool in the tool chain in IT. Whether it’s like cloud or mobile machine learning, event driven architecture, things like that. It’s going to help accelerate and reimagine your business process, but it’s not something you can really adopt in a vacuum and it’s not going to solve all of your problems. You frequently need to go look at the business process that you actually want to automate to make sure that you’re reimagining it, updating it, making it more modern in the process, because if all you do is automate every process exactly as it is, you may get some gains, but you’re really not going to be transformational. And that’s kind of a … Just one of the most important things that we really work through in terms of being successful with your automation strategy. And whenever I talk about this with customers, it always reminds me of a great quote from a football coach, Lou Holtz. He had a quote which was something like, “You’d rather have a slow guy moving in the right direction than a fast guy moving in the wrong direction.” Automation is kind of like that in that if you roll out automation for the wrong project, you’re just going to have the wrong business process go a heck of a lot faster in the wrong direction. So you really want to make sure you’re building your automation, you’re reimagining the business processes along the overall strategy and direction of the company, which maximizes for your business, as opposed to just taking what’s already there and making it go faster.

Guy Nadivi: There’s a variation on that Lou Holtz quote that I personally love, which is, “To err is human, but to truly screw up requires a computer.”

Charles Lamanna: Yes, too true.

Guy Nadivi: Charles, you’re certainly in a position to know. So I’d love to hear what 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.

Charles Lamanna: So I can only answer this in one way and with one thing. I’m a little bit biased about what I work on, but I have to say the single biggest disruptor for automation is going to be the low code development of automation. And the main reason we see this being the case is because of, I’d say four big shifts, four big changes that are happening in IT development today. The first is a workforce shift. 35% of the workforce today are millennials or 75% of the workforce will be millennials by 2025. This audience has incredibly high expectations for modern digital experiences at work. And they aren’t the folks that like to copy-paste data between 17 different systems or in green screen terminal applications and things like that. They really want modern, not rote, creative and innovative experiences at work. So the workforce is shifting. The second thing is because of the shift in workforce and because of these expectations and in general push. And that every company everywhere is that there’s a huge surge in demand and the need to digitally support and enable your employees. We can see this in really unprecedented demand in terms of the acceleration of digital projects. We project over the next five years, there’ll be as many digital solutions built in the enterprise as were built over the last 40 years. Just huge, huge demand. So a new workforce with high expectations and huge demand. But there’s a third problem, which is an incredible, a staggering shortage of professional developers and coders. In the United States alone, we’re going to be short a million developers over the next decade. There just aren’t enough developers out there to go solve and address this growing demand. And then to kind of top it all off is a fourth thing, with COVID-19 the associated recession, which we’re calling the great lockdown, we’re going to be in a period of time where IT is going to need to do more with less, or do more with your existing resources and your existing technology. So all of these things are kind of mixing together right now. These four things. And what we’re seeing is that low code is really going to be, I think, emergent as a result of these changes. Because low code automation technology, which make it possible for everyone to be an automation specialist, a business user, an IT professional, or a coder can all start to automate tasks is what low code is all about. This completely changes the calculus of automation projects, completely solves the problem that I’ve talked about throughout the discussion of, do you understand the business need as well as the automation need? It actually makes, so the people who understand the business need in the business can solve the automation problems with these low code automation tools. And this starts to change just what the IT landscape looks like, drives more collaboration between business users and IT, and the end result is a heck of a lot more automation being built in a fairly short period of time. So really over the next one to three years, we see that low code is going to be one of the most disruptive forces and in particular, low code automation tools, which have visual authoring environments, visual debugging environments, as well as easy to understand concepts and management configuration is going to be one of the most disruptive aspects. And that really is the heart of our thesis at Microsoft of where automation is heading over the next three years.

Guy Nadivi: I think you’re absolutely right about low code because the history of technology is that it gets easier to use over time, which democratizes its abilities for the masses. So history would seem to agree with you. Charles, 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 moving forward with automation.

Charles Lamanna: This may be obvious to some of your listeners, but I’ll repeat it because it bears repeating. Which would be the best time to start building out your automation strategy and getting serious about automation for all functions of your company was probably three years ago. The second best time is now as the saying goes. And just the reason is that the return on the ROI on projects in the automation space really is phenomenal. There’s a huge amount of digital processes that have been accumulated over the last two decades that are just waiting to be enhanced and improved through automation. You can improve the employee experience, make your employees happier, keep them working at high cognitive high value tasks. You can improve customer experience, solve the customer’s problems faster and more efficiently than ever before. And you can do all of this with relatively minimal budget, but large outsize return. These things all just make it easy and straightforward to go build the case, to go build … To create an automation strategy, and to go chart what automation is going to need over the next few years. So if anything, I would just say now is the time to really make sure that you’re getting serious, that you’re looking at how automation can reach all parts of your company. And I think just speed and moving quickly is going to be key because as we go look out over the next couple of years, which are going to be a little bit challenging, macro economically speaking, automation is going to be key to being efficient, being lean, and building a great customer experience during those times. So I will say, move, move fast, move now, if you haven’t already, when it comes to automation, that would be the biggest takeaway.

Guy Nadivi: I think that’s very prudent advice because if you don’t, your competitors certainly will.

Charles Lamanna: Absolutely.

Guy Nadivi: All right. Looks like that’s all the time we have for on this episode of Intelligent Automation Radio. Charles, it’s been fantastic having you here today and learning about your perspective on the automation and AI space. I think everyone is going to keep a keen eye on what you and your team at Microsoft will be doing to shape the future of this market and continue moving it forward. Thank you very much for joining us.

Charles Lamanna: And thank you for having me, Guy.

Guy Nadivi: Charles Lamanna, Corporate Vice President, Low Code Application Platform at Microsoft. Thank you for listening everyone. And remember don’t hesitate, automate.



Charles Lamanna

Corporate Vice President, Low Code Application Platform at Microsoft.

Charles leads the Engineering teams for the Low Code Application Platform (LCAP) in the Business Applications Group at Microsoft. The LCAP team includes the Dynamics 365 platform, Power Apps, Power Automate, Power Virtual Agent, AI Builder and the Common Data Service products.  

Under his leadership, the Dynamics 365 service moved to Azure and evolved into a fully managed SaaS–on a single version, with regular updates. The Dynamics 365 platform is now one of the largest fully Azure hosted SaaS products in the world, deployed to over 30 datacenters and supporting the entire Dynamics 365 business. 

Before that, Charles worked in Azure for 4 years, leading the engineering teams that created Azure Resource Manager, Azure Autoscale, Azure Logic Apps, Azure Activity Logs and several other management related capabilities. Before Azure, Charles founded MetricsHub, one of the first offerings for public cloud cost management and service health monitoring. MetricsHub was acquired by Microsoft in 2013. 

Charles can be reached at: 

LinkedIn:                https://www.linkedin.com/in/charleslamanna/ 

Twitter:                  @clamanna  

Try it out:               Power Automate 

Quotes

“…RPA historically is incredibly centered and focused on UI Automation and more specifically Windows-based automation. And it's our view that that UI Automation is necessary, but insufficient to really enable interesting automation scenarios and really transform every aspect of every company in every country around the world.” 

“We think there's I'd say a legacy of automation being very PC-centric, very on-premise centric, and there's some real potential to reimagine what automation looks like in a cloud native, cloud first way. So that's really important to our vision.” 

"…low code is a whole idea that you want to make it so anybody and everybody can be a developer, can build bots, can contribute to the automation revolution." 

“…we think that automation will be an important part of really any modern information worker job in the future. But the importance and the criticality will be a spectrum from say, somewhat impactful to very impactful, but really all information workers will feel that impact, will feel the responsibilities change and evolve over the next five years or so.” 

“I think process mining and the AI discovery capabilities is probably the most interesting thing that we're watching at Microsoft when it comes to automation over the next couple of years. And the reason is because it's still early days today, of course, but these tools help you very quickly identify processes that are ripe for automation. And even more interestingly is they actually help with the calculation of the ROI for an automation project. And this really is the dream of most IT transformation projects.” 

“35% of the workforce today are millennials or 75% of the workforce will be millennials by 2025. This audience has incredibly high expectations for modern digital experiences at work. And they aren't the folks that like to copy-paste data between 17 different systems or in green screen terminal applications and things like that. They really want modern, not rote, creative and innovative experiences at work. So the workforce is shifting.” 

“…there's a huge surge in demand and the need to digitally support and enable your employees. We can see this in really unprecedented demand in terms of the acceleration of digital projects. We project over the next five years, there'll be as many digital solutions built in the enterprise as were built over the last 40 years. Just huge, huge demand.” 

“…the best time to start building out your automation strategy and getting serious about automation for all functions of your company was probably three years ago. The second best time is now as the saying goes. And just the reason is that the return on the ROI on projects in the automation space really is phenomenal. There's a huge amount of digital processes that have been accumulated over the last two decades that are just waiting to be enhanced and improved through automation. You can improve the employee experience, make your employees happier, keep them working at high cognitive high value tasks. You can improve customer experience, solve the customer's problems faster and more efficiently than ever before. And you can do all of this with relatively minimal budget, but large outsize return.” 

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Links

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

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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 #46: Why Chatbots Are Critical For Tapping Into The Most Lucrative Demographics – Gupshup’s Beerud Sheth

September 2, 2020    Episodes

Episode #46: Why Chatbots Are Critical For Tapping Into The Most Lucrative Demographics

In today’s episode of Ayehu’s podcast, we interview Beerud Sheth – Co-Founder and CEO of Gupshup

The Millennial generation is still retail’s most coveted demographic, but Generation Z isn’t far behind.  Both cohorts grew up as “digital natives” with computers, game consoles, and mobile phones.  It’s no surprise then that being online is second nature to them, and increasingly, chatbots is where Millennials & Generation Z can be found interacting online with retailers & other businesses.  Conventional marketing wisdom has long dictated that you have to meet your customers where they are.  Our guest on this episode argues that means chatbots are where marketers should go. 

As Co-Founder and CEO of Gupshup, Beerud Sheth knows quite a bit about chatbots.  His bot-building platform is already being used by over 30,000 businesses worldwide, and was selected by Amazon as one of two preferred bot builders for their .bot registry services. With bots increasingly automating many tasks & activities currently done manually, Beerud also has interesting insights on how they may disrupt the labor market, another topic he’s well-versed in having previously co-founded eLance which kick-started the gig economy. Beerud shares his vision with us about the opportunities that lie ahead, and the steps businesses must take to maximize their return from automating this growing customer touchpoint. 



Guy Nadivi: Welcome, everyone. My name is Guy Nadivi. I’m the host of Intelligent Automation Radio.

Our guest on today’s episode is Beerud Sheth, Co-Founder and CEO of Gupshup, an advanced bot-building platform used by over 30,000 businesses worldwide, and which handles over 4 billion messages per month. Prior to Gupshup, Beerud was one of the co-founders of Elance, which many listeners will remember was a pioneering online platform for freelance workers that really helped to kickstart the global gig economy. Those accomplishments alone give Beerud a unique perspective on how digital transformation will impact the future of work, two topics of immense importance on this podcast. We’ve asked Beerud to join us today and help us peek over the horizon a bit to better understand what that future might look like. Beerud, welcome to Intelligent Automation Radio.

Beerud Sheth: Thanks, Guy. Thanks for having me here.

Guy Nadivi: In 2019, Business Insider estimated the worldwide chatbot market as worth a bit more than two and a half billion dollars, but they forecasted that by 2024, it will approach $10 billion. That’s a compound annual growth rate of over 29% a year. We are, of course, now in the middle of a global pandemic, and so, Beerud, I’m curious, how do you think the COVID-19 crisis will affect this growth rate? Beerud Sheth:Oh, I think it’s certainly going to accelerate it. In many at least technical areas, we’ve seen decades of progress compressed into these three months, with a rapid adoption of, let’s say, work from home and telecommuting and remote meetings and so on. I think the same will apply to the chatbot market as well. It is accelerating the interest in developing bots and implementing them and so on for a variety of reasons. One is people are more conscious of social distancing and not getting into physical contact and so on. Once you get into remote customer support situations, whether it’s a human agent or an automated chatbot providing the responses, it matters less. It’s different when you’re face to face at a desk, but once it’s remote, it’s a lot easier to automate. So customer support is certainly one of those big areas. Also, there’s this massive shift to online commerce from offline. Suddenly retailers and shopping assistants and transactions, ordering pain, a lot of that is moving online, which again is rife for automation through chatbots. That’s happening across many, many different aspects, but as we move more and more into a tech & virtual economy, most of those interactions can be automated, can be enabled to a conversational chatbot. So I see it increasing dramatically.

Guy Nadivi: You mentioned customer support. It turns out that customer service and the IT help desk seem to be the two most popular use cases for chatbots right now. Beerud, what other functional areas of the enterprise do you envision will experience growth in chatbot usage?

Beerud Sheth: The way I think about it is, for a business, literally every customer touchpoint is going to get transformed with conversational experiences through chatbots. If you think about it, the entire customer life cycle, businesses, it starts with marketing on the front end, and then sales and transactions in the middle, and then support at the end of that customer life cycle. Across all of those touchpoints, you will see a greater adoption of chatbots. Let’s take the example where a customer is looking for products. If you had a chatbot that can educate, that can explain … I think Sephora had a chatbot where you can look for different colors and different shades of cosmetics long before the buying decision is made. Or you have complex products. If you’re buying insurance, if you’re buying health care services or large complex products, you want to look at review, want to look at products, look at options and so on. It makes it … So that’s the whole front end of the buying cycle, the marketing part of it, or even sending deals and offers and coupons and engaging with that. That’s on the marketing side. Then when you come to sales, the actual transaction, the merchandising, the purchasing, the shopping cart, the checkout and so on. Then even the support long after that, in case there are problems, returns and so on. I think every customer touchpoint really is going to get transformed. Today, if you think about it, most businesses have websites and apps. You really have to think of chatbots as the latest reincarnation of websites and apps. Because consumers, especially millennials, the younger ones, they prefer the messaging … They’re using mobile devices. On the small screen, messaging is used far more heavily than either browsers or apps. So businesses will have to meet consumers on their turf, on their terms. You have to meet customers where they are. If they prefer the chat and conversational experiences, then clearly businesses will have to interact in the same way. Everything from browsing to window shopping to ordering food and items and so on. You can see a version of this future if you look at WeChat in China. Everything there, a lot of it happens through the messaging app where you can interact with, not just businesses, but even every vending machine or every billboard or a restaurant table. You just arrived at a restaurant. You want to order food at that table. You can just do that through conversational experiences. In their case, it’s mini programs. But that’s the idea. Just through the messaging app, it becomes a super app that allows you to do virtually everything. I think businesses will have to transform their digital touchpoints into chatbot.

Guy Nadivi: Gartner believes there are as many as 1,500 chatbot vendors worldwide, and that “The majority of these conversational platform vendors offer very simple platforms using modified open source components to deliver simple question and answer chatbots.” I think it’s safe to assume the market doesn’t need 1,500 chatbot vendors, & there’s an inevitable shakeout coming. Beerud, even though we’re still fairly early in the conversational AI era, what kinds of things do you think will differentiate the survivors from the chatbot vendors who will fall by the wayside?

Beerud Sheth: I’m a little more optimistic about the future for chatbot vendors. There are different elements. Of course, some vendors provide platforms, and the number of platforms will be few. But a lot of other vendors provide services, and there there’s limitless potential. The analogy I like is think of it as website development or app development. There are numerous, perhaps thousands or more, dev development agencies, app development agencies, and so on, or even, let’s say, social media marketing agency and such. Those provide very custom solutions to brands. So if we say that virtually every business and brand will need to build conversational chatbots, and not just one, but multiple ones across different use cases, then there is a need for lots and lots of agencies and chatbot vendors to provide these services. To survive, what the vendor should do is get deeper into the business workflow. If somebody specializes in banking chatbots, and even within that it could be retail banking, or banking in the US versus in Europe versus in Brazil. There may be differences in each of these cases. The workflows can get fairly deep, fairly complex. There will be a need, because all these organizations are going to need to build these chatbots. So I think there is room. The key is, like in any business, you have to figure it out your core competency, your unique differentiation, something that you can offer that somebody else can’t replicate. If you do that, then I think there’s enormous room for growth, but I think we’ll need lots of … If you’re going to have millions of bots, you are going to need thousands of vendors providing some of these services. The caveat is, I think, some of the underlying platforms will be fewer and will get standardized on a smaller set. There, again, it depends on the comprehensive nature of the capabilities, the breadth and depth of the platform, how many things it can provide, what it integrates into and so on. That’s what the platforms have to watch out for.

Guy Nadivi: Interesting point. Beerud, there are some concerns about biases, intentional or otherwise, creeping into the AI that powers things like chatbots. In order to root out bias, do you think that AI algorithms should be audited in the same way financial statements are for publicly traded firms?

Beerud Sheth: I think it’s a little early to institute audits. It’s important to think about it certainly. There’s no doubt. Well, let’s start at the beginning. Yes. The AI is trained based on existing documents, which are created by humans. Therefore human biases may be inherited by these AI models which just learned from these documents. The academic community is working on fixing these biases, on quantifying and measuring these biases. There’s been a lot of progress on that already. The awareness keeps increasing as well, given the social injustice movements going on. I think there’s certainly a greater awareness in the community around that. So firstly, the community is self-motivated to fix these long before the software gets into production. Nonetheless, there may be biases, ones that we may not be aware of or conscious of today. I think that’s been one of the human failings, that a lot of unconscious bias creeps in, things that we think okay today may not be okay years from now and so on. Certainly AI software is improving. The community is working on fixing these biases. Then as we go further, we need to make sure that businesses deploying AI use it in ethical ways. We need to hold them accountable if they don’t. So certainly there is room for some oversight, some audit, some policing of AI, not just of the AI models as well as the applications. Basically what’s inside the model and what they are applied for, both of those need to be … There needs to be some governance mechanisms around this. There’s no question. It’s just that it’s still a little early in the development of these things. I think we should let innovation flourish, but in parallel, there are a lot of conversations going on about how to use it, what to use it for. There are valid concerns around the surveillance state, around privacy, in addition to the biases and equal treatment and so on. So yeah, I think both those will have to progress in parallel, even as innovation gallops on. We need to move quickly to figure out how to monitor it. I think it will. I’m optimistic. I think the AI community is already familiar, both with its capabilities, as well as shortcomings, are already working on fixing many of the known issues. I think it’ll evolve over time, but yeah, I think we should be thinking about governance mechanisms.

Guy Nadivi: Your company, Gupshup, is one of two preferred bot builders that Amazon chose for their .bot registry services. Can you please tell us about that relationship and how you’re enabling the bot building market?

Beerud Sheth: Sure. Amazon happens to own the .bot top level domain. It’s like .com but .bot. I think it’s a wonderful domain name for a whole variety of bots that want to create a unified identity, that can use it for marketing purposes and so on. Those of us that were around in the late 90s remember how critical the .com domain names were in the development of the early Internet, and being able to create a memorable marketing identity to drive the adoption of websites at that time. In a similar way, as more and more bots are proliferating, each bot has a unique or a different identity on the appropriate channel. On Facebook messenger, it could be some name. On WhatsApp, it’s a phone number. On SMS or RCS, it could be different kinds of identities. It makes it very challenging. If a business wants to tell a user to come find its bot, there’s no single central location where it can direct it, because there are different … the identity’s fragmented. That’s where the .bot domain name comes in. It could provide that single central identity, which could then redirect the user to the appropriate bot on the appropriate channel. It can make it easier to identify bots, to market your own bots, to drive traffic and so on. So I think that’s the … In addition to identity, there could be additional services that could be provided right there around perhaps authentication, verification, and other services as well. That’s a shared vision that Amazon has and we have too. We want to make it easier for bot developers to get discovered, to drive traffic, market themselves, because I think it’s good for the overall chatbot ecosystem. We’ve been engaged in conversations with Amazon for a long time. I think ultimately when they went live with it, they selected Gupshup as one of the key platforms. What it means is really any bot developer on Gupshup can very quickly and easily, I mean, literally check the box and get a .bot domain name. It could be shopping.bot or travel.bot and so on. They can easily get those domain names. It’s seamlessly integrated. That makes it easier. So we’re excited about the partnership. I think it’s good for the ecosystem, and it will drive greater adoption and standardization in the bot ecosystem.

Guy Nadivi: Beerud, before your foray into conversational AI and chatbots, you helped launch the gig economy by founding Elance, which eventually merged with oDesk to become Upwork, which today is the largest freelancer marketplace in the world. Do you think that one day we’ll see a similar marketplace for task-specific bots that organizations and even individuals can hire on a per hour or per project basis?

Beerud Sheth: That’s certainly conceivable isn’t it? In fact, for all you know it may already be happening and it’s just not visible. It is entirely possible that some freelancers might already be deploying bots to automate their tasks and activities. That may very well be happening. At that point, what does it even mean to have a per hour billing, because bots operate on a different timescale? Per project, of course, makes sense. So yeah, I think that’s exactly what’s happening. Once you automate tasks that were previously done solely by humans, it blurs this boundary between a human delivered task versus a chatbot delivered task. Or it could be a hybrid task, part human, part bot. Over time, that distinction may disappear altogether, as in the customer may not know, or may not even care, so long as the deliverable is done. Upwork often describes itself as a talent cloud, which is you get access to, just like you have the computing cloud and the storage cloud, I think of it as a talent cloud, where with one click, you can get access to loads of talent. It’s just that talent gets redefined as not just humans, but also automated AI programs delivering these things. So I think we’re in for some very interesting times as this evolves. I think it just opens up a whole lot of possibilities. It’ll be very interesting to see how it develops.

Guy Nadivi: Beerud, 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 conversational AI at their enterprise?

Beerud Sheth: Well, the one piece of advice would be to get started on this journey. It’s a long journey for multiple reasons. AI itself is developing. AI is not always accurate, but the accuracy rates are improving very dramatically. It behaves differently in different domains. There’s a lot of trial and error and testing that has to be done. But it is critical that executives get started on this journey, and take small incremental steps towards creating conversational experiences, enabling chatbots, leveraging AI to enable this. Because the cost of not doing something will far outstrip the cost of doing something. If you do something, and if it fails or if there’s some mishaps, I think the learning experiences, that will help you get there faster. We’ve seen these sort of transitions before as well. In the mid 90s, there was a time where a lot of marketing executives would say, “Well, why do I need a website? I already have a phone number. I have this offline retail presence. Nobody’s visiting us on our website.” Very quickly, it switched over to you were fired if you didn’t have a website, if you didn’t have a digital strategy and so on. Then it was the same thing with mobile experiences about a decade ago, with people needing to create apps and such. I think we are, yet again, at a similar point, where we are going to go from, “Why do I need a chatbot or conversational interfaces?” to it’s going to become the critical, the primary way in which consumers interact with brands. Anyway, I think the opportunity is huge. Yes, there are certain challenges in getting it right, but it’s critical to get started on the journey and get started now.

Guy Nadivi: Great perspective. All right. Looks like that’s all the time we have for on this episode of Intelligent Automation Radio. Beerud, it is a real honor to speak with someone whose previous work with Elance positively impacted so many people around the world, and whose current project with Gupshup has the potential for an even greater impact. Thank you for joining us today. It’s been great having you on the show.

Beerud Sheth: Guy, thanks for having me.

Guy Nadivi: Beerud Sheth, co-founder and CEO of Gupshup, an advanced bot-building platform, and previously one of the co-founders of Elance, known better today as Upwork. Thank you for listening, everyone and remember, don’t hesitate, automate.



Beerud Sheth

Co-Founder and CEO of Gupshup

Beerud Sheth is the cofounder and CEO of Gupshup, the world's leading platform for cloud messaging and conversational experiences. It is used by over 30K+ developers and handles over 4.5 billion messages per month. He previously founded and led Elance (now Upwork, a publicly listed company), the pioneer of online freelancing and the gig economy. Prior to founding Elance, he worked in the financial services industry – modeling, structuring, and trading fixed income securities and derivatives at Merrill Lynch and Citicorp Securities. His graduate research, at the MIT Media Lab, involved developing autonomous learning agents for personalized news filtering. Beerud earned an M.S. in Computer Science from MIT & a B.Tech. in Computer Science from IIT Bombay, where he was awarded the Institute Silver Medal. 

Beerud can be reached at: 

LinkedIn:                https://www.linkedin.com/in/beerud/ 

Beerud’s blog:       https://blog.gupshup.io/ 

Quotes

“Suddenly retailers and shopping assistants and transactions, ordering pain, a lot of that is moving online, which again is rife for automation through chatbots.” 

“The way I think about it is, for a business, literally every customer touchpoint is going to get transformed with conversational experiences through chatbots.” 

"Today, if you think about it, most businesses have websites and apps. You really have to think of chatbots as the latest reincarnation of websites and apps." 

“So if we say that virtually every business and brand will need to build conversational chatbots, and not just one, but multiple ones across different use cases, then there is a need for lots and lots of agencies and chatbot vendors to provide these services.” 

“…as more and more bots are proliferating, each bot has a unique or a different identity on the appropriate channel. On Facebook messenger, it could be some name. On WhatsApp, it's a phone number. On SMS or RCS, it could be different kinds of identities. It makes it very challenging.” 

“It is entirely possible that some freelancers might already be deploying bots to automate their tasks and activities. That may very well be happening. At that point, what does it even mean to have a per hour billing, because bots operate on a different timescale? Per project, of course, makes sense.” 

“Once you automate tasks that were previously done solely by humans, it blurs this boundary between a human delivered task versus a chatbot delivered task. Or it could be a hybrid task, part human, part bot. Over time, that distinction may disappear altogether, as in the customer may not know, or may not even care, so long as the deliverable is done.” 

About Ayehu

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Links

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

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Disclaimer Note

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

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