May 1, 2020 Episodes
Episode #40: Key Insights Gained From Overseeing 1,200 Automation Projects That Saved Over $250 Million
In today’s episode of Ayehu’s podcast we interview Danilo McGarry – Global Head of Automation for Alter Domus.
Every moonshot needs a rocket. For many enterprises around the world, digital transformation is their moonshot, and automation + artificial intelligence is their rocket. In order for those digital transformations to achieve mission objectives though, enterprises must scale up their automation & AI deployments. When they do, the results can be out-of-this-world. But why do some automation & AI initiatives deliver such extraordinary returns while others fail to launch? Why do others manage lifting off, but fail to break free from the gravitational bonds of corporate inertia?
For answers to these & other questions, we turn to Danilo McGarry, Global Head of Automation at Alter Domus. Danilo’s track record of producing outsized results with automation and AI at his current & prior roles might be unprecedented. He shares his valuable insights with us, including the surprisingly aggressive minimum ROI you should aim for in year one of your automation projects, the specific steps to take to overcome internal robophobia about automation & AI, and why proof of concept projects are a waste of money.
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 Danilo McGarry, Global Head of Automation for Alter Domus, a global financial services firm based out of Luxembourg with $750 billion under its administration. Danilo is also a member of the European AI Alliance as well as a thought leader and keynote speaker on automation and artificial intelligence, and as someone leading efforts in those realms for a large worldwide organization, he has a unique perspective on automation and AI’s transformational power. That’s very relevant to other enterprises moving forward with their own initiatives.
Guy Nadivi: So we’ve asked Danilo to join us today to share his insights and perhaps inspire our audience with some ideas on how to leverage automation and AI to drive competitive advantage for their own organizations. Danilo, welcome to Intelligent Automation Radio.
Danilo McGarry: Thank you Guy. I’m really looking forward to our session.
Guy Nadivi: Danilo, you’ve run some very big automation programs and started some AI programs from scratch. Can you share some details about some of these with our audience, especially the ones you’ve been involved with, which had particularly impactful results?
Danilo McGarry: Sure. I’ve been in automation now for about 15 years. It has been a heck of a ride, a roller coaster. In the past couple of years, I have been one of the leaders in running the automation program at United Health Group. For those that don’t know United Health Group is the world’s biggest healthcare company. Its aim is to have roughly 500,000 employees by 2023. It makes over $200 billion in revenues per year.
Danilo McGarry: It was UIPath’s biggest client with over 1,000 robots, which was under my team. So that was… That is until today, the biggest automation program that I’m aware of. So it was a very interesting program to be part of, had a significant infrastructure in place, a significant budget as well. It was really making a significant stride in terms of transforming healthcare to the way we know it today. It’s going to really impact the world.
Danilo McGarry: One of the other programs that I used to run as well is I used to be head of AI & Machine Learning at Citi Group. Then, again for those who don’t know, Citi Group is the 13th largest financial institution in the world with around 150,000 employees. Just an interesting fact, it’s responsible for roughly 70% of America’s FX transactions on a daily basis. So should Citi Group ever go down, it would really make a huge dent in the US economy.
Danilo McGarry: That program was particularly interesting as well. I was asked to start the artificial intelligence program from scratch with a team of two or three people in the beginning, and that scaled to become one of the, if not the most successful, artificial intelligence programs in the financial services world. Won many prizes. A lot of the advisory houses named it as #1 AI program in the financial industry. It was a great honor to be part of that. That was a really interesting journey.
Danilo McGarry: Just as a kind of stat in my lifetime doing bots in the last 10 years, I’ve overseen over 1,200 robots in the making that went to production. I keep tabs on how they’re doing still with my ex-colleagues, and a total savings that those bots have made until today is roughly $250 million. These are big numbers and I think CIOs, CTOs, CEOs should really pay attention to those numbers because those numbers are coming from three or four institutions only. It’s very interesting.
Danilo McGarry: In terms of a particular case study, there are many out of that 1,200, but one that really hit home run for me, that really had a huge impact was one at one of the financial services companies I was in. In every bank, there is a payments and receivables team. They’re generally a middle- or back-office team. For those who are part of the financial services world, they’ve probably heard of the term “trioptima”, which is looking at offsetting payments and receivables for the same counterparties so that you don’t make… You make the least amount of transactions in order to net out payments.
Danilo McGarry: This team is very busy. If you go to Bulge Bracket Bank, one of the largest banks in the world, they’re making millions of payments a day to the tune of tens or hundreds of billions of dollars a day. It’s serious business. It’s very intense. It’s very stressful. The teams that were doing this, they were really in bad shape. They’d been under massive, massive stress for the last number of years. Turnover rates were extremely high. People would last roughly six months to a year maximum. There was no continuity, and it was very hard to retain staff, and it was very manual. People bringing up Excel sheets, receiving emails from counterparties demanding payments, and trying to offset and doing these reconciliations very manually using Excel.
Danilo McGarry: Now I was tasked with automating that process and I can say it was a very hard task, first because of getting everybody’s attention when everybody was very short for time, but we got around to it. We got the business analyst working away and understanding the process very well. We got the automation done for it in phases, but in the end, the bottom line of it was that we managed to save around $18 to $20 million in reserves that the bank kept setting up every day just in case it didn’t make the right payments. That unleashed roughly $18 to $20 million in reserves back to the bank that could be used for other activities, which as you know, can be a very lucrative thing instead of just holding up money in case you’ve got your processes wrong.
Danilo McGarry: The biggest part of this, which I thought was mostly impactful was the transformation in the teams itself. People were behaving in a very obscure way. They weren’t behaving like a team. They were very aggressive towards each other and after the automation was in place, they were getting some help and it was automating roughly 30%, 40% of the process in all. It was amazing the transformation that the teams went through. The retention times went up. People were staying for two years plus. People started having team events and they started behaving like humans again. That got people also talking to clients more. Rather than just talking through emails, they were having more phone calls. That really improved the relationship of that bank with its other counterparties that it would make and receive payments from.
Danilo McGarry: It really… In the end, if I could take away anything out of it, which was really impactful was that it really helped people become more human. It’s a bit of an oxymoron. How can automation, how can robots help humans become more human? But that’s really the result of it. I’ve always heard one of the founders of automation, Kai Fu Lee, who was the ex-head of Google for Asia, who’s now got his own venture capitalist firm investing in AI. He always said and predicted that automation would make people more human. I never quite understood it until that use case came about and I saw it in my own eyes.
Guy Nadivi: Interesting. It reminds me of the statement, I wish I could remember who quoted it, who coined it, but it’s something about automation can take the robot out of the human and it sounds like that’s what you’re referring to really.
Danilo McGarry: Exactly.
Guy Nadivi: Danilo, your title is Global Head of Automation, which is the type of title I think we’re likely to see at more and more companies as automation continues becoming more crucial to enterprise operations. Tell us why should organizations have a Global Head of Automation and what are the most important benefits one provides?
Danilo McGarry: I totally agree. I see other titles as well, similar to mine, Chief AI Officer, Chief Innovation Officer, and it’s really because of the size of the market. If you look at the World Economic Forum, which is one of the leading NGOs, they’ve coined AI and automation to be the fourth industrial revolution that we’re in right now. If you think of the words ‘industrial revolution’, that’s quite major. That’s quite transformational. There’s only been three others since the beginning of time. This is the fourth one and it is to do with AI and automation.
Danilo McGarry: That already gives you a good indication that this is important and that companies, governments should be really paying attention to this. If you look at stats from leading advisory companies like PWC, McKinsey, they’re all estimating that AI and automation is going to bring roughly anything between $9 to $15.7 trillion in terms of economic growth by 2030. These are huge numbers. We’re not talking billions, we’re talking trillions and it’s double digits.
Danilo McGarry: Given that there is so much out there for companies to grab, so many savings for them to make, new opportunities, new revenue streams that they could be generating. This has really brought the attention of CEOs, CTOs, CIOs, because they’ve had to create these positions in order to go after those market opportunities.
Danilo McGarry: Just in my career and some things I’ve achieved as well and I’ve seen others achieve, almost any company, roughly 30% of any company can be automated. That’s quite a huge chunk of a company. Let’s say a company has an operating expenditure of roughly a hundred million dollars a year. That’s a $30 million save every year. That’s very significant. Given all of that, given the tremendous opportunities in the market, the size of the market, and the fact that it really gives you a significant competitive advantage, most companies have had no choice but to take this seriously and create positions and create teams in order to grab a piece of that pie.
Guy Nadivi: Okay. Now just to follow up on taking it seriously, on a recent podcast, you stated that automation and AI have become, excuse me, top five objectives over the last two years among blue chip companies. So what do you think are the likely outcomes for enterprises that don’t prioritize automation and AI that highly and don’t take it seriously?
Danilo McGarry: It really boils down to what we mentioned earlier, which is allowing humans to be humans. Right? Since the beginning of industrial revolutions, when companies like Ford came out, Rockefeller was about, we’ve been trying to make humans into robots, produce faster, putting in conveyor belt situations, but really we’re not built for that. Biologically, physiologically it just doesn’t work.
Danilo McGarry: Let’s say you had a company who had 30% of its tasks being performed by robots and another company who didn’t have any robots. Who do you think is going to have a better competitive advantage? Yeah, obviously the one with the robots. Robot doesn’t sleep, doesn’t take coffee breaks, doesn’t smoke, doesn’t have maternity/paternity leave. It can work 24/7 tirelessly and without fail and the accuracy of robots, when the process has been automated correctly, is just so much higher than the human. There’s just no competition. Especially if the process is very high frequency and relatively low to medium complexity.
Danilo McGarry: It’s really just about being able to stay relevant in the market, being able to compete with your peers, bot versus human. That’s just plain and simple. The other thing as well, that’s why it’s come to light, especially now during this COVID-19 situation is companies that had robots during this BCP mode that everybody’s in, business continuity planning, they’re doing a lot better than companies that didn’t have robots. Companies who had to send their workers home to work from home, they’re all scavenging trying to get their RSA tokens working, trying to get the hardware working, trying to log in. Citrix isn’t working, but behind the scenes the robots are working fine because they’re installed in the service.
Danilo McGarry: That’s just another example of how bots can, for certain items, can give you a significant advantage. Especially now, the situation that we’re in and the difficulty people are having from working from home, that’s really driven home the bot versus human arguments. So all of that really gives a company a huge USP, a huge competitive advantage. It’s just not something of a surprise why it’s really gone to the top five objectives of most companies, especially blue chips.
Guy Nadivi: Okay. Now you just mentioned a bunch of processes and I’m curious, Danilo, when you evaluate a process to be automated, is there a minimum ROI you need to justify automating it?
Danilo McGarry: A lot of companies, a lot of automation leads, they look at ROI differently to people who are not experienced in automation. As a typical base level, I would really go after opportunities who have a 4x return on investment in year one and that’s really because of something called “dropouts”. So on day one when you receive your idea to automate, you have the SMEs, the subject matter experts, telling you about it, they’re super excited, they want to get it automated, but when you go through that journey and you start automating something, you come across barriers. You come across systems who are not easy to work with, legacy systems. You come across broken processes which aren’t ready to automate, or there are certain regulatory barriers in place, audit barriers in place.
Danilo McGarry: There are dropouts, there are things that you have to put aside. You don’t often get to automate something end to end. So if you have that cushion of 40% or 4x and some dropouts happen, then you might get 20% return on investment year one out of it. So it’s a good cushion to have.
Guy Nadivi: As a Global Head of Automation, I imagine you look at automation and AI projects just a little bit differently than others in particular when it comes to scaling up to an enterprise-wide basis, like for some of the very large organizations you’ve mentioned earlier. What have you found to be the biggest challenges in scaling up automation and AI projects?
Danilo McGarry: I often explain this and some people do get quite angry at me. So the issues that I’ve come across, none of them are technical. With the tremendous vendors and people that exist today, there’s almost nothing that you can’t automate and there’s so much to automate that there’s no point crying about the things that you can’t. It’s not a technical challenge, it’s more of a human challenge and there’s lots of them, but I’ll talk about one challenge in particular and it’s to do with the chicken and egg conundrum of buy-in.
Danilo McGarry: When an automation program is about to start in the company, everyone is scared to sponsor it from a senior level. That’s because they see it as high risk. They maybe don’t know too much about it, they hear some horror stories in the market, but as soon as you start having some success and your automation team starts returning some great ROI back to the company, then everybody is grappling on top of each other trying to be the sponsor of that program. It’s always very interesting to see, the lack of interest in the beginning and as you pick up pace, how many people you know want to be your new boss. That conundrum… That kind of politics, it happens in almost every company and it’s just very interesting to see and it can pose a real challenge. It can pose a lot of issues with clarity of direction, clarity of strategy. If it wasn’t the case, companies could really save a lot of time and money.
Guy Nadivi: Fear is one of the challenges with people and “robophobia” is the term that we use to describe people’s fear of automation, particularly as it pertains to the impact it might have on the nature of their job or even their employment. How have you addressed and overcome robophobia with some of the automation and AI projects you’ve been involved with?
Danilo McGarry: It really boils down to the approach. I’ve been in situations where I’ve seen companies trying to implement automation or AI in a very covert way, kind of Area 51 need-to-know basis and that’s really what puts people on edge. You can’t perform automation without the good advice and the good process of the people doing it. It has to be an inclusive program. There has to be open communication. People have to see that it’s one of the top objectives of the company, it’s the direction that the company’s going in and if that’s made clear, then people can prepare in advance. They can start educating themselves. They can start going on training courses. They can start re-skilling so they can stay relevant in the new working environment they’re in today.
Danilo McGarry: When you give people that opportunity and when you give them that backing and that support, it really puts people at ease. They buy into the idea a lot quicker. They help instead of trying to be a hindrance and especially if you go even a step further and you empower those people, you make them be an integral part of an automation program as a deliverer, as they help the automation team, bring them to light, bring those new skills that they’ve learned and apply it to the next automation project, give them something else to do, something that gives them a career development path choice. When you combine all these things together, it’s really a way of tackling robophobia. It really helps eliminate all of that and it turns the company all in the same direction and gets all your ducks lined in a row.
Guy Nadivi: Okay. Now, speaking of the new working environment, you published an article on Medium in the summer of 2019 outlining your prediction on organizational setup changes from the year 2030 onwards, and in that article you stated, “In general, working from home will become the absolute norm with flexible working as a given.”
Guy Nadivi: Well Danilo, your prediction may have been much more prescient than anyone realized given the massive numbers of people who’ve been encouraged or ordered to work from home due to the coronavirus epidemic, and many are speculating that the current quarantine many are under will drive exactly the shift that you predicted. I’m curious, how does automation and AI help make a work from home paradigm not only sustainable, but possibly something of a competitive advantage for organizations?
Danilo McGarry: Well, some people joke, they call me “Mystic Dan”. So good to see that prediction came to light, unfortunately for something that has hurt the economy. To be honest with you, I think with what’s happened with the coronavirus situation, the revenue projections of most companies for this year is going to go down and the pressure is going to be on EBITDA, is going to be on trying to stay profitable and when you do that, you’ve got to cut costs.
Danilo McGarry: When you look at one of the highest costs that any company has, it’s to do with physical working space, the square footage cost of having an employee in an office. If you look at expensive cities like Tokyo, London, New York, et cetera, that can be very, very high. So I think there might be a big push for working from home just simply because of the reason of trying to cut costs. I think having people working from home, having robots, working with humans, aiding and giving them some support to get through volumes and backlogs like it’s happening now during this BCP mode everybody’s in, it’s opened everybody’s eyes that bots and humans can work together if they’re in the office or not. Projects can be carried out whether people are in the office or not.
Danilo McGarry: Given the pressures to cut costs, given the enlightenment that companies have had, that working from home is almost as effective or even if not more effective than being in an office, I think all of that’s going to create a transformational change in the way that we work going forward, and I hope it sticks because given the way that our societies are built and the way companies are integrated into our personal lives, there really is no need to be in an office all the time. Let’s see what happens, but I think it’s really going to stick and I think the new norm is going to be working from home.
Guy Nadivi: Danilo, for the CIOs, CTOs and other IT executives listening in perhaps from their home office today, 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 and AI at their enterprises?
Danilo McGarry: If I was to give CIOs, CTOs a big piece of advice in automation and AI, it would be to really integrate this into your company’s strategic roadmap from day one. A lot of companies go through POCs first and they try to understand it a little bit more, but look around you. Automation is prevalent. AI is in almost everything that you do in your daily lives. If you’re in transport, the way you ordered the cabs is using AI. You go into an airport, you go up escalators, even escalators are automated now. When you look around you, automation is happening. Proofs of concepts, in my opinion, unless it’s for something very, very tricky and very particular, it is a waste of time. It’s a waste of money. Don’t be scared to integrate this as one of your top objectives. Look at the size of the market. Look what everybody else is saying, what everybody else is doing. It’s the direction everybody should be going in.
Danilo McGarry: Really it’s to do with integrating it with your strategic roadmap. If you do that from day one and you involve people, you empower people to go after it with you, you are going to save so much time and so much money for your company that it’s going to make a huge difference to where you are in that league table in comparison to your competitors.
Guy Nadivi: Great advice from somebody with a significant track record of success in automation. All right. Looks like that’s all the time we have for on this episode of Intelligent Automation Radio. Danilo, it’s great having a Global Head of Automation on the show because I think it reflects the increasing importance that organizations are putting on automation, and given what you’ve shared with us about some of the work you’ve done, I think we’ll be seeing more and more that those in charge of their enterprise’s automation and AI efforts continue being elevated to more strategic roles within their organizations. Thank you very much for coming on the show today and sharing your insights with us.
Danilo McGarry: Thank you, Guy. It’s been a huge pleasure.
Guy Nadivi: Danilo McGarry, Global Head of Automation for Alter Domus, a global financial services firm based out of Luxembourg. Thank you for listening everyone and remember, don’t hesitate, automate.
Global Head of Automation for Alter Domus.
Danilo McGarry is the current Global Head of Automation at Alter Domus (a market leading fund services company, part of the Permira Private Equity Group). Previously he led Artificial intelligence & Machine Learning at CitiGroup (3rd largest US bank, 17th largest Financial institution globally) that was recognised as being the leading AI program in the financial services industry. Danilo was also part of the world's largest Automation program that is part of UnitedHealth Group (#5 on the Fortune 500 and world's biggest healthcare provider). He is also part of the European Union Commission AI Alliance and has had his work and thoughts published in prominent publications such as The Times Newspaper, InfoMoney Bloomberg, and other leading journals. Danilo is coined as a thought leader in the topics of Automation, AI, and Innovation being a frequent keynote speaker in some of the world's largest conferences in this space. In his 15 year career in this space he has overseen over 1,200 automation projects that to date have delivered circa $250 million in savings.
Danilo can be reached at:
“I've always heard one of the founders of automation, Kai Fu Lee, who was the ex-head of Google for Asia, who's now got his own venture capitalist firm investing in AI. He always said and predicted that automation would make people more human. I never quite understood it until that use case came about and I saw it in my own eyes.”
“If you look at the World Economic Forum, which is one of the leading NGOs, they've coined AI and automation to be the fourth industrial revolution that we're in right now. If you think of the words ‘industrial revolution’, that's quite major. That's quite transformational. There's only been three others since the beginning of time. This is the fourth one and it is to do with AI and automation.”
"If you look at stats from leading advisory companies like PWC, McKinsey, they're all estimating that AI and automation is going to bring roughly anything between $9 to $15.7 trillion in terms of economic growth by 2030. These are huge numbers. We're not talking billions, we're talking trillions and it's double digits."
“Just in my career and some things I've achieved as well and I've seen others achieve, almost any company, roughly 30% of any company can be automated.”
“With the tremendous vendors and people that exist today, there's almost nothing that you can't automate and there's so much to automate that there's no point crying about the things that you can't.”
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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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
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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
The Center of Excellence (CoE) for Automation has become a very hot topic these days, moving from distributed organizations that each own several tools and scripting to one vertical center that provides automation solutions across the enterprise.
In response to this growing demand, Ayehu has established an Automation Academy that will help enterprises to transition and build their own CoE, training people to become Automation Specialists / Engineers. This will allow organizations to better prepare for the future (when machines will do almost everything) and help drive efficiencies via automation with a stronger emphasis on innovation.
Building your own CoE for Automation isn’t necessarily as complicated as you may think. In fact, it can be accomplished by implementing just a few strategic steps. Here’s how.
Step 1: Evaluate and Adopt Automation
The first step in the process of establishing a CoE for Automation is to gain adequate understanding of the various challenges, opportunities and benefits of automation. During this process, project management teams may choose to identify certain “quick wins” that can be automated fast and result in immediate return on investment.
Step 2: Define, Document and Set Up the CoE
Having gained a strong understanding of the challenges surrounding adoption of automation as well as the tremendous, quantifiable opportunities it presents, the next step is actually establishing your Center of Excellence for Automation. This involves selecting the appropriate core team members as well as evangelists who will assist in spreading awareness and advocate for the benefits of automation.
Keep in mind that the ideal core team for a CoE demonstrates a broad spectrum of skill sets. For instance, you’ll need someone who can assess the impact and document the processes, someone who can handle the implementation and integration process and someone else who can monitor and test the automation.
Step 3: Establish Systems and Infrastructure
Your CoE for Automation will only be as effective as the technological foundation upon which it is built. Making wise choices upfront about the systems and infrastructure you establish will set the stage for rapid growth and also help to prevent potential issues from occurring down the road. Invest in enterprise-class automation and architecture that includes robust features. Create and document best practices with a focus on automated processes that are consistent, efficient, accurate and auditable.
Step 4: Train, Educate and Reskill
While automation will inevitably eliminate some jobs, there are opportunities to train and reskill people for new, next generation roles, such as Automation Engineers. Reskilling and redeploying back to work will ultimately create higher value for the organization, its clients and for the employees themselves. Look for training options that are specific to CoE development, like Ayehu Automation Academy.
Step 5: Sustain and Scale
Once your CoE is officially established, the next phase should involve aligning the automation strategy with the strategic objectives of the organization. This typically involves scaling the approach to make it broader. For instance, while the initial goal of automation might have been to reduce costs, the scope should eventually evolve to include such larger goals as creating stronger customer loyalty or driving greater agility.
The entire CoE needs to work on firming a matured process so it can become agile enough to respond to demand and maximize efficiency. This process should have a definition of how the organization should approach the CoE, how the CoE should evaluate and prioritize these requests, how it should develop its internal design to production processes, etc.
Finally, the core CoE team should specifically include analysts who can continuously identify automation opportunities, translate business needs to IT processes, determine potential ROI and create the logic steps necessary for the automation engineers to build and implement the processes. Remember – a CoE isn’t stagnant. It’s something that must change, evolve and improve as time goes by.
Step 6: Incorporate Automation into the Culture of the Enterprise
Ultimately, automation should become a complement of continuous process improvement for the entire organization. The last step of building a CoE for Automation involves changing the overall business mindset to embrace the opportunity automation presents to change and improve how it operates.
Creating the CoE without making a cultural change in the organization simply will not work. The organization (the people) must change their behavior and think about automation as opportunity to live better, to focus on more important things and be freed up for innovation. Embracing automation will allow the CoE to become relevant to an organization that wants to change and automate as much as possible.
Keep in mind that this phase can take a good deal of time to complete. You’ll know you’ve achieved success once automation becomes embedded in every department and function throughout the enterprise.
Step 7: Market the CoE
Once the CoE for Automation is successfully established and the necessary cultural shift has been set in motion, it’s time to start promoting the CoE to outside to end clients. Any client-facing employee should be prepared to sell the innovation and success stories of automation. This will create demand generation and fulfillment and help the organization achieve maximum competitive advantage.
This is clearly a high-level overview of the CoE process, but it should at least provide a framework upon which to build. If you’re considering making a move in this direction, we encourage you to take advantage of our resources and expertise by allowing us to assist you with developing and establishing your Center of Excellence.
Why go it alone when you can rely on a team of experts who can help you every step of the way? To learn more or get started, contact Ayehu today.
Over the past few years, Gartner has made some pretty bold predictions surrounding artificial intelligence and automation technology. These include such projections as the generation of $2.9 trillion in business value, the recovery of 6.2 billion hours of worker productivity and the creation of some 2.3million new jobs. All of this is expected to take place over the next couple of years, if not sooner.
Whatever you believe about AI, one thing’s for sure – it’s not going away any time soon.In fact, all signs indicate that the not-so-distant future will look a lot different from what we are used to today, with machines performing not only the physical work of humans, but also the thinking, planning, strategizing and decision-making as well.
At Ayehu, we’re always trying to stay a step ahead of the curve in terms of technology and its capabilities. Such was the purpose of our recent panel discussion entitled The New Wave of Hybrid AI in the Automation Era, during which we sat down with several AI and automation thought leaders, including:
- Brian Boeggeman, Chief Revenue Officer, Ayehu
- Manish Kothari, President, Ventures, SRI International
- Andrew Brill, VP Engineering & Cloud Services, RPA/IA, Change Healthcare
- Ross Tisnovsky, Head of Americas, Digital 20/20, McKinsey New Ventures
We asked these experts to take a look back at some of the emerging trends observed and experienced in 2018 and offer a glimpse into the future. We also asked each of our esteemed panelists to go out on a limb and make a bold prediction for 2019.
Here’s a little taste of what we uncovered.
Evolution in IT Operations
One of the first topics touched upon by our own Brian Boeggeman centered on the creation of automation centers of excellence (COE) and the automation engineers that are driving adoption and proliferation of automation within the enterprise.
“We saw a trend taking place this year where there’s a lot of focus put on the creation on these centers of excellence to really drive automation,” said Brian. “Automation is clearly seen as a business imperative and a clear necessity in order to orient the next phase of enterprise operations, where efficiencies can be uncovered and realized across the business.”
He continued, “Those automation engineers effectively become the change agents within the organizations to drive that cultural change within the enterprise. As we engage with many of our customers, we’re continuing to see that as a high focus for them actually making investments to build out these COEs to push across the entire organization and enterprise as a whole.”
Brian also talked about the acceleration and creation of new services through automation and AI, pointing out that automation has emerged as a key strategy to achieve the delicate balance between innovation and operational excellence.
Download the on-demand recording to learn how to unleash new capabilities of human capital as well as what trend Brian believes will forever change the service levels and operating capabilities of organizations.
How AI and ML are Impacting the Adoption of Automation in the Enterprise
Next, we turned the floor over to Manish Kothari, who has been involved with artificial intelligence and machine learning since the 70s. Manish opened his statement by pointing how critical data is to extracting the full value of AI.
“I think we’re starting to see a very big transformation take place across all sectors from agriculture, to consumer, and especially in IT where the need is arguably one of the highest,” Manish commented.
He went on to say: “If you are at the IT infrastructure side, you are, actually for one of the first times, really in a position to become an enabler rather an impediment to innovation.”
Manish also shared his insight on what enterprise managers who have never dealt with AI should know before deploying it and how he envisions the roles of managers changing once AI begins to get a foothold.
Find out everything that Manish had to say here.
Top Reasons Organizations Should Automate IT Operations
The next topic on the agenda was turned over to Andrew Brill of Change Healthcare, who was asked to share his thoughts on the top reasons for automating ITOps.
He was quick to point out that while the initial reasons typically revolve around cost savings and efficiency, some really exciting things can begin to happen,particularly in terms of an organization’s ability to remain compliant and consistent in its operating practices. Automation essentially becomes a force multiplier, saving users time and skyrocketing productivity and facilitating innovation.
“When we transform our staff who were doing the more robotic functions and eliminate that from their daily work, it allows them to start thinking about how we advance the organization, how we build better engineered solutions, how we work with partners that add the most value,” Andrew points out.
“Their brains are more actively working on the things that solve business problems as opposed to the functional tasks and work that perhaps we’ve had them do over the past ten years.”
Check out the playback to hear more and learn what Andrew believes are the biggest benefits of automation.
The Impact of AI on Digital Transformation
The discussion then turned to Ross Tisnovsky of McKinsey who was asked what kind of impact he believed technologies such as intelligent automation and AI having on IT digital transformation efforts in the enterprise.
In his response, Ross shared how he approaches the adoption of new technology. In particular, he highlighted the main things that users want from IT which, in his opinion, include:
- A workspace for collaboration and enhanced productivity
- Improved decision-making
- Support for business innovation
- High efficiency at a minimal cost
According to Ross, the solution to these needs requires a hybrid of AI, automation and human decision making.
“Automation works on both sides of the picture and so does the artificial intelligence. In other words, it’s likely to become part of anything we do on the business side today.”
Watch the on-demand discussion to discover the Ross’ most intriguing thoughts on hybrid AI from his real-world experience.
Key Insights and Future Outlook
During the final portion of the panel discussion, the experts weighed in on such points as:
- The role of humans in automation adoption
- Biggest challenges to automating IT operations
- Skills needed to automate effectively
- Critical KPIs/success metrics to focus on at different stages of the IT digital transformation journey
- What enterprise IT leadership should be doing right now to start preparing for the changes to come
- Bold predictions for AI in 2019 (and beyond)
Don’t miss out on what was certainly one of the timeliest and most informative panel discussions we’ve ever had the pleasure of hosting. Tune in to the full recording today!
There’s much talk about the so-called skills gap in the cybersecurity realm, particularly as it pertains to a lack of qualified staff. What isn’t mentioned quite so often is the fact that because those who are skilled enough to handle the daunting task of enterprise security are in such high demand, the essentially hold all the cards. For IT leaders, it’s not just about attracting the best talent. It’s about keeping them on for the long haul. Given the competitive landscape, this is no easy task. The one ace you can hold in your pocket, however, is automation.
A recent survey revealed that almost half of today’s cybersecurity professionals receive contact from a recruiter or another party regarding a job opening. Those who hold the title of Chief Information Security Officer (CISO) receive five or more such solicitations each and every week. Even more concerning? The same survey indicated that 44% of security professionals are satisfied in their current job. 15% said they aren’t satisfied at all.
This means that if you’ve got even a few employees who are currently unhappy and a plethora of recruiters knocking down their doors on a regular basis, it’s pretty easy to understand why retention in the cybersecurity sector is one of the biggest challenges organizations face today.
Thankfully, you have the ability to turn things around. It starts with providing your IT team with the tools and technologies they need to do their jobs better and more efficiently – in particular, leveraging automation to streamline manual processes like incident response.
Consider for a moment that 92 percent of organizations field 500 or more cyber alerts each and every day. That adds up to around 15,000 alerts per month. This volume of incoming incidents, coupled with inevitable false positives, can easily lead to alert fatigue, especially considering that the average cybersecurity analyst is only capable of accurately handling around ten alerts per day. In other words, without the right tools, your IT team is drowning and you’re probably going to lose them as a result.
To improve employee satisfaction and retention, IT leaders must take the initiative to automate the many manual, tedious tasks and workflows currently bogging down cybersecurity analysts. This significantly lightens the workload while allowing skilled security professionals to apply their expertise to more strategic projects and perform more interesting and meaningful work. These things can dramatically improve morale and satisfaction, which will make it easier for you to keep your best employees.
With the right cybersecurity orchestration and automation platform, your IT analysts could focus on such initiatives as:
- Proactive threat management. While automation handles incidents that have already occurred, your IT pros can spend their time hunting down potential threats and preparing for them in advance. Being proactive rather than reactive is better for the employee as well as for the organization as a whole.
- Optimize processes and policies. By eliminating the need for manual incident management, security professionals can work on improving existing policies and developing best practices.
- Perform routine system and process audits. With the free time automation affords, your IT team can work on reviewing and analyzing other tools, systems, applications and programs that are currently in use and make necessary changes to improve operations.
- Conduct risk assessments. Automated incident response provides the IT team with the ability to go back to basics, identifying and addressing vulnerabilities and closing any existing gaps in policies and processes.
When it comes to running the most secure, efficient and effective enterprise, retaining top cybersecurity talent is key. The tips and tools listed above should help you keep your IT team happier, more productive and on-board for the long haul so that when recruiters come calling, your employees will gladly send them packing.
To try our next-generation cybersecurity orchestration and automation platform for yourself, simply click here.
Shifting human work to machine is nothing new, nor is it something so vastly complex that it’s reserved only for the likes of multi-billion dollar operations. One needs only take notice at the interactions of their everyday life to realize how much artificial intelligence has become an integral part of our society. In fact, if you’ve ever used the self-checkout at your local grocery store or deposited a check at the ATM, you’ve leveraged automation technology.
So, what does this mean in terms of business? Specifically, how does automation impact the modern workplace? From a strictly benefits standpoint, automation is revolutionizing the way work is performed and providing advantages to organizations of every size and across every industry. Not only can AI boost productivity and eliminate human error, but it can also dramatically cut costs and provide the key to competitive advantage.
From a personnel perspective, automation is not necessarily something that will replace entire occupations, but rather the tool needed to streamline and improve workflow for human employees. Management must therefore focus on redefining roles and processes so that the two – automation technology and human workers – can complement one another.
To gain a deeper understanding of the role automation can and ultimately will play in the workplace of tomorrow, let’s take a look at three fundamentals of function below.
Automated Human Activities
Much of the conversation around workplace automation centers on the automation of simple, mundane and “codeable” tasks and workflows. While this is certainly a significant benefit, particularly in the field of IT, advances in artificial intelligence and machine learning technology have virtually blown the doors off this concept. In one study conducted by McKinsey & Company, nearly half (45 percent) of all work activities could be automated using already demonstrated technology.
In fact, in many cases, automation technology is already capable of matching, or even exceeding, the median level of human performance. This includes such intuitive activities as planning, coordinating and decision-making tasks.
Evolution of Roles and Processes
Very few occupations could be completely automated. More than half, on the other hand, could potentially see a significant portion of their daily duties and activities automated. What this means is that although artificial intelligence is not yet capable of replacing humans entirely, automation will most certainly begin to – at least to some degree – change the vast majority of occupations. To accommodate these changes, a redefinition of roles and subsequent adaptation of businesses process will be necessary.
Thankfully, this is actually good news for many because while automation may eliminate some of a human worker’s task load, it will simultaneously free them up to focus their skills and intellect elsewhere. In other words, job descriptions and their duties will inevitably evolve. At the same time, however, new and innovative job opportunities as they relate to managing AI will begin to emerge.
A More Universal Impact
Logic dictates that the lower-wage, less skill-based jobs will be the first to be displaced by automation. In reality, particularly due to the incredible advances in AI technology and machine learning, it’s becoming clear that even those who hold high-level, high-wage occupations will not be immune to the impacts of automation. In fact, to some degree, there may actually be a fundamental shift.
Take, for instance, the role of a corporate CEO. A big part of his or her job duties – and one of the reasons for his or her hefty salary – is the ability to analyze data and make critical business decisions. Trends indicate that a good portion of this level job could be automated using intuitive technology, including analysis, reporting and decision making. As such, the high value placed on such a senior level position may begin to wane.
Conversely, those who hold jobs in certain fields such as home health aides, maintenance workers and landscapers – fields that have tasks that cannot easily be automated – may actually be viewed as more valuable in the future, and therefore paid more handsomely for their skills.
Ultimately, time will tell just how much of an impact advanced automation, machine learning and artificial intelligence technology will have on the future of work. One thing is for certain, though. Its adoption is inevitable. The best way to prepare your organization is to stay a step ahead by embracing the tools that are currently available to you.
If you’d like to give our intuitive automation and orchestration platform a try in your own company, simply click here and download your free trial.
Over the past decade or so, the buzz surrounding robotic process automation has continued to grow increasingly louder. Along with greater awareness, however, there have also been a number of myths, misconceptions and outright untruths being perpetuated which have led to many otherwise savvy professionals feeling leery about adopting this innovative technology. As a result, organizations across the globe are missing out on the many incredible benefits that RPA has to offer. That being said, we’ve identified 5 of the most common misunderstandings and the real truths behind each of them.
RPA will replace humans.
One of the biggest misconceptions about RPA is that it will eliminate the need for human workers altogether. This thought process has bred fear and caused a great degree of resistance, particularly among those in the IT field. In reality, RPA is meant to complement human workers and make their jobs easier and more efficient. Will that mean some jobs will be replaced by robots? Sure. But for the most part, adoption of this technology will ultimately create new and better opportunities for people to pursue.
You can automate everything with RPA.
On the other end of the spectrum, many early adopters of robotic process automation falsely believed that 100% of the workload within their organizations could be seamlessly transitioned from human to machine. While it’s true that some companies have been able to automate up to 80% of their processes, there will almost always be at least some areas where human resources are still necessary (further supporting the previous point). For best results, RPA should be implemented in small increments, testing, modifying and slowly increasing, thereby optimizing the technology to its fullest capabilities.
RPA is only for IT.
Small to mid-sized companies often forego adoption of automation because they believe it’s only ideal for larger firms with dedicated IT departments. In truth, RPA can be applied to almost any repetitive, manual task, workflow or business process – regardless of whether it’s housed under the umbrella of IT or not. Additionally, the right RPA product should be affordable, quick and easy to implement without requiring a great deal of technical know-how. In other words, perfect for businesses of any size or industry.
All RPA solutions are the same.
This is, perhaps, one of the biggest misconceptions surrounding RPA, or automation in general. While the basic concept is consistent across the board, the tools themselves are often vastly different, as are the companies that develop and market them. It’s also important to point out that more bells and whistles an RPA tool has doesn’t necessarily make it better. It’s all about what fits best with your needs. That said, when evaluating robotic process automation solutions the key things to look for include: ease of use, time to deployment, cost of ownership, scalability, ROI and support after the sale.
RPA is a passing fad.
Last, but not least, many have resisted jumping on the RPA bandwagon because they simply don’t believe it’ll still be around in the relatively near future. After all, how many other technologies have come and gone over the past several decades? The reality of this lies in the growing demand for companies in every industry to find ways to minimize costs, maximize efficiency levels and remain competitive. RPA is the ideal solution to each of these objectives, which indicates that it’s a technology that’s here to stay and will only continue to improve as time marches on.
Are you guilty of believing one or more of these myths about robotic process automation? Ready to shake off those misconceptions and experience for yourself just how beneficial this technology can be for the success of your organization?
Get started now by downloading a free trial of eyeShare.
Many organizations place disaster recovery on the back burner because they consider it to be too big of an expense. Why allocate money toward “what if” scenarios when those funds can be put toward more immediate business needs, like sales and marketing? The problem is, treating cyber security incident response and disaster recovery as an afterthought or unnecessary luxury in an attempt to save money may very well end up costing your company a lot more than you may realize. In fact, some research indicates that upwards of 25% of businesses that close due to unforeseen events never reopen.
Even a temporary downtime can be incredibly costly, with average hourly losses ranging from $50,000 up to millions of dollars. Shifting perspective from expense to investment by identifying ROI can improve how disaster recovery is viewed and increase adoption, which means a safer, more secure business operation.
First and foremost, you can’t calculate the value of having a solid cyber security incident response and disaster recovery strategy until you first understand what a loss could potentially cost. Specifically, by determining what costs and losses are acceptable, you can then begin to establish acceptable recovery parameters. This will include a Recovery Time Objective (RTO) as well as a Recovery Point Objective (RPO).
Your defined RTO should indicate the maximum amount of downtime your organization is willing to tolerate. Your RPO should help gauge how much data your business can comfortably afford to lose, measured in seconds, minutes, hours and/or days. Typically a different RTO and RPO values will be set for each system or business process, based on importance. For instance, you would likely set higher objectives for systems for which downtime would likely have the lowest business impact, such as email servers, versus mission-critical systems that directly impact revenue.
Assigning priorities to each proposed scenario can be handled using a “cold” versus “hot” scale, with higher RTO and RPO scenarios requiring a cold solution and those will lower tolerances requiring hot capabilities. For example, systems that can withstand a downtime of 24 hours or more without making a significant impact would be categorized as cold while systems with an RTO of 15 minutes or less would require a much more urgent – or hot – response.
The final step in the process is to officially calculate the expected ROI considering the following factors:
- Unprotected downtime (amount of time required to restore operations without a formal disaster recovery plan in place)
- Protected downtime (amount of time to recovery with a DR solution in place)
- Hourly revenue (amount of annual revenue divided by the total number of working hours in a year)
By multiplying both downtime scenarios by the hourly revenue you can determine the potential loss associated with each. The difference between the two represents the loss that can be avoided by implementing a documented disaster recovery strategy.
From there, the formula for calculating the overall ROI of DR is as follows:
ROI = (Avoided loss – cost of disaster recovery solution/disaster recovery solution cost x 100%)
It’s important to point out that given today’s digital landscape, the risks associated with potential online security breaches and the subsequent downtime they can cause should play an integral role in the overall disaster recovery policy. Specifically, implementing a strong cyber security incident response plan that features automation as a central tool for monitoring, evaluating and addressing incoming incidents can help avoid potential losses that a successful breach can result in. This can and should also be considered when calculating ROI.
IT professionals who recognize the importance of cyber security incident response and a strong, established disaster recovery strategy can make a case for their cause by presenting the proposed ROI to key decision makers. By selling the value of such a strategy and positioning it as it rightfully should be – an investment rather than an expense – the chances of getting the financial backing needed will greatly increase.
To learn more about how you can beef up your company’s safety and security and limit costly potential downtime, give us a call today at 1-800-652-5601 or click here to request a free product demo.
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Ayehu’s codeless Intelligent Automation and Orchestration platform uses a drag-and-drop visual workflow designer to automate IT tasks in minutes.This saves 95% of the time spent remediating incidents, delivers a 35% cost reduction on repetitive manual tasks and cuts MTTR incidents by more than 50%.
Our 220+ Enterprise customers, including large MSPs such as Cognizant, Capgemini, and Accenture, are using Ayehu’s platform for its digital labor, increasing their operational efficiency by sending robots to work.
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