Episode #4: How to Manage the Increasingly Complicated Nature of IT Operations – Red Hat’s Alessandro Perilli

 

Oct 30, 2018    Episodes

 

 

Episode #4: How to Manage the Increasingly Complicated Nature of IT Operations

In today’s episode of Ayehu’s podcast we interview Alessandro Perilli, General Manager, Management Strategy at Red Hat

How can senior IT executives best deal with the increasingly complicated nature of managing IT operations?  The ever-growing demand for computing resources, the expanding complexity of computing environments, and the critical shortage of experienced talent are all seemingly conspiring to derail the C-Suite’s best laid strategic plans.

Alessandro spends a lot of time working on these issues as part of his role at Red Hat.  He believes that the proper alignment of automation, public cloud infrastructure, and shadow IT are the key to solving this 21st-century challenge.  Alessandro also has a unique recommendation for CIOs, CTOs, & CISOs on the #1 thing they should do to prepare their personnel for this rapidly shifting landscape.



Guy: Welcome everyone. We have another great guest for this edition of Intelligent Automation Radio. Joining us today is Alessandro Perilli, the general manager of Management Strategy for Red Hat, who are, of course, best known for the Linux distribution of the same name, but they do lots of other things too. Alessandro is focused on long term strategy for the company’s efforts in automation, artificial intelligence, and IT security among other things. All of these are topics this podcast is very focused on as well. He is a highly regarded expert on cloud management and virtualization, and is a frequent speaker at major industry events.

Alessandro, welcome to Intelligent Automation Radio.

Alessandro: Thank you. Thanks for having me. It’s a pleasure.

Guy: Your name really rolls off the tongue, and it’s fun to pronounce, so I may be saying it quite a few times today.

Alessandro: That’s fine. No problem.

Guy: Alessandro, before you became general manager of management strategy for Red Hat, you were a Gartner analyst in charge of cloud computing and automation for over three years. During that time, you no doubt had numerous conversations with high level IT executives from large enterprises around the world. Could you please share with the audience what you would tell organizations are the top 3 reasons they should consider automating their IT service, Cybersecurity, and DevOps operations?

Alessandro: When I was with Gartner, I started almost seven years ago, and that time was very different. The kind of environment that we are was quite a different situation compared to now. The public cloud computing was starting to emerge and now it’s a reality, well-established one, and so the kind of advice that I have for top executives in large enterprises at that time is kind of different than the one that I would have for them today. If this is a question for today, as I think it is, the answer is there is just one answer, which is you technically have no choice but to automate, to cope with the scale and complexity of very large environments that the environment that exists today.

I’m not talking just about public cloud environment. The facilitating large scale deployment or workloads because the infinite elasticity that they offer at the relatively cheap price, but also because even when you are on premises in private cloud infrastructure or in a hybrid cloud IT environment, you start to shift from traditional monolithic application architecture to more aggregated ones, and so you start to go for microservices architectures and cases supported by virtual machines, but then containers and then eventually [inaudible 00:02:51]. So even within the same single application, you start to have a lot of moving parts and there are a number of complexities that are related to provisioning those parts and then be sure that those parts are properly configured and updated and patched and retired and replaced and so on.

And then you need to multiply that single application architecture that has become so complex for all the other applications that you have in a public, or a hybrid cloud environment. To give a sense of the scale, that this is something that any CIO in a large enterprise knows already, the average size of an application portfolio in a large end user organization like the ones I used to consult for when I was in Gartner, is of over 1,000 applications. Now, this over 1,000 applications used to have a monolithic architecture with just three peers, right? The web frontend, the middleware, the backend services, the database, and that was it.

Now is that you move from those three tier architecture to seven, eight, 9, 10, 20 containers in a microservice architecture. There’s an explosion of components, and then there is the infinite scalability I mentioned before that forces the use of automation. There is no chance that a human operator, no matter how skilled, no matter how well paid, can possibly cope with that level of complexity. This is the number one, the only piece of advice that I feel it’s really necessarily [inaudible 00:04:39].

Guy: Yeah, that’s something that we talk about all the time here is that people don’t scale very well, and that’s why automation is really the only practical alternative to dealing with the complexity, the explosion in demand for computing resources, et cetera. What are the big challenges you see today in automating IT and Cybersecurity environments?

Alessandro: Cyber security is a very special, I would say, layer or corner of the whole IT organization and the computing stack. There are at least two major issues that I see today, and in my role, I talk to a lot of organizations about automating security. The number one is that if you look at the security ecosystem as it is today, you see that there is a massive, unprecedented amount of security solutions in the market, not just from established vendors, but also from startups that they merge in waves every year.

The amount of capital that is invested by venture capital firms into the security industry is reaching unprecedented peaks. We’re talking about almost four billion, according to the last research by CB Insights. This amount of capital to build new solutions corresponds to an enormous amount of spending on the end-user organization side. We’re talking about something close to $100 billion spend on security solutions. Now, I used to be in security when I was very young at the beginning of my career, almost 20 years ago. You would expect that since then, a lot of the problems that existed at that time has been solved, it’s been addressed, and are pretty much solved problem from an engineering standpoint, but actually, it’s not the case.

You would expect that the ecosystem would have consolidated compared to those times, and instead, no, the ecosystem has grown and grown and grown, and it’s exploding in size. You will lead to think that, “Okay, there is this explosion of vendors. This is the injection of capital. This is a massive amount of spending. These solutions are all for new problems that emerge as we got to deal with new technologies, but it’s not even the case. Quite the opposite.

The problems that we’re trying to solve with this new wave of solutions are always exactly the same that existed 20 years ago. There is an inherent inefficiency in the way the security industry is doing things, that it’s not being fixed by any of these new wave of startups that promise to disrupt the space. Quite the opposite. If you look at Gartner surveys or IBM surveys or all sorts of … [Silent 00:07:38] surveys, all sorts of companies, from all different corners of the IT industry, they all confirm that a chief information security officers are more and more concerned about their capability to secure, to protect the environment, to respond to attacks. This is getting worse. A lot of them complain that they don’t have enough security personnel to address this.

A lot of them lament that the intensity of the attack increased, and the time to respond to the attack increased as well. Why is all of this? There’s always a number of concurrent factors like in a very complicated situation, but I personally believe, and this is the first, of the two main problems that we have today in cybersecurity in terms of automation, is that when you look at the ecosystem, these vendors, the solutions don’t integrate with each other. They just don’t. They don’t talk to each other in any way.

Yes, there are minor connection, integrations between one or two solutions provided by the same vendor or there might be integration between two different vendors at the site to get to win a partnership before a limited amount of time because it’s a marketing effort, but that isn’t [inaudible 00:09:05] not universal integration like … And the standards that are being provided in the past didn’t have any market traction to the point and now we have a new wave of standards that are trying to solve the problem. This is a never ending cycle of attempting to solve the problem, which is clearly not working. This is number one problem. The biggest one problem is that even if you want to automate the security industry, those tools don’t integrate with each other. The solutions don’t integrate with each other. That is the first problem to solve.

The second problem is not technical, it’s not standards, it’s nothing to do with the industry per se, but it’s cultural. Security professionals, and I come from that world, so it’s a very familiar to me, they’re just very, very, against automation. There is a general mindset, that is we’re not gonna automate security because if things can be blocked, mission critical services and systems could be just stopped and somebody is gonna complain, and we don’t wanna get into the sort of liability responsibility and so on, which is insane. It will be like AWS, Amazon saying, “We don’t run automation with AWS. We prefer to do things by hand because we don’t trust automation.”

They will never reach the scale that they reach. But Amazon.com, in terms of warehouses, for example, for the Red Hat part of the business, and in terms, of course, of cloud computing. This is just untenable, so the mindset to the security professional has to change and has to evolve to accept and embrace the fact that at this scale, at this level of complexity, the only way is to automate the security layer just like all the others have been automated. Compute, storage, networking, all of them, security is the last one, and that has to change.

Guy: I think with the others, there were also some resistance at the outset but I think with security, there is a more pronounced problem and that is that according to various surveys and studies by 2021, there is gonna be somewhere around three and a half million unfilled positions in security, and you’ve just … In the next three years, less than three years, you’re simply not gonna find enough people to get trained on the complexities of security in that time period, so the only solution is to automate a lot of the work that those people need to do.

Alessandro: Absolutely, but even if we would have enough skilled personnel that is available to do those things, you will still not be able to cope with the speed. So far, I’ve been talking about scale and complexity, but there is a third element, a third dimension, that we’re getting into play very soon in the near future, which is the speed. What happens when artificial intelligence is used to drive these hacking attempts? These attacks. At what speed are the attacks and variations of the same attacks all around the world are executed if it’s an artificial intelligence that is driving that kind of effort? How a human, no matter if there are enough humans, but how a single human can cope with that speed? That is beyond the possibilities that any of us have, and so the only possibility here is that we go for automation, regardless of the personnel availability.

Guy: Yeah, that’s another thing that we tell people as well is that the attacks being launched against you are usually automated, so shouldn’t your defenses be as well?

Alessandro: Mm-hmm (affirmative), absolutely.

Guy: What do you feel then are the top skills a CIO or CTO or chief information security officer should encourage their staff to acquire in preparation for implementing automation in their environment?

Alessandro: There are at least a couple of aspects that are connected to each other. The first one is that in my experience at least, a lot of the security professionals, but also the traditional IT operation people, that might or might not be involved in security, don’t have a sense of operations at scale. I have a certain size of data center to deal with but it’s nothing even remotely close to the size of an AWS or an Azure or Google Cloud and even the smaller public cloud service providers.

A top skill to acquire for all these professionals is to start to understand how things change at scale. What does it mean to rethink an operational framework or a security framework at the scale that we are about to face or we’re facing already. That is number one.

The second aspect is that connected to this, is that I saw a lot of security professionals looking at automation as a very tactical tool, as a system that can in a very small pockets and limited fashion, try to be used to solve a minor task in the security analysis process. That is, I believe, limiting the possibilities that automation offers in security. My recommendation will be to shift in thinking from thinking security as a tactical tool and thinking more in terms of strategy. Automation, part of the security framework being used systematically and in a pervasive way throughout all the different operations that a security team performs during the day, could really make a difference in terms of the approach and the posture that the team has towards the discipline.

Guy: In kind of a related question to that, what’re your thoughts about general purpose automation platforms versus function specific automation platforms? Specifically for IT process automation, specifically for cybersecurity automation, specifically for DevOps?

Alessandro: This is a topic I’m extremely passionate about because I saw through two decades of career with Gartner, before Gartner, now after Gartner, I saw exactly what happens with customers, no matter how skilled they are, are put in front of general purpose automation tools or platform or frameworks, call it the way you want. What happens is that when these tools, and not just these tools by the way, any sort of IT tool kits that has general purpose capabilities suffers the same kind of issue in my experience, and it’s this.

When customers are put in front of those general purpose tools, and they come to the table with a very specific use case or two, three use cases in mind, and they’re being offered something that in theory will solve all those use cases because the general purpose nature of the platform is such that it can be adopted to solve different issues, but in practice this general purpose platform is not excellent at any of those use cases, and requires quite a lot of effort from the end user organization side in terms of crafting and adapting into the specific the business needs that they have with certain use case A, B, or C.

Customers struggle to see the immediate return on the investment, and the actual value of general purpose platform. They very much prefer, even if in theory it’s counterintuitive that when they ask logically what they prefer, of course they prefer a general purpose platform because they think that they can return on investment in a lot more use cases. There’s a bigger return, but in practice, they always go for point solutions. They tend to prefer point solution. This is the same kind of approach, if you think about it, that you would have in your home repair on a Sunday morning at home kind of routine.

If you’re doing some sort of home fix of any sort, you have two choices. You go for a Swiss Army knife, that is a general purpose toolset or you go for highly specialized tools that are more efficient to solving a problem. A hammer, a screwdriver, and so on. Why does it that humans always go for the specialized tool rather than just buy and use a single general purpose platform? The reason is that we tend to think in terms of what is the most efficient tool to get the job done? No matter if that fills the drawer and takes all the space and it costs probably 10 times more than a general purpose platform, we tend to go in that direction. I saw over and over and over in my career in IT, general purpose technologies and approaches failing over a long time for a lack of market traction for what I believe is this reason.

Guy: Touching upon the issue of the talent gap and the skills shortage, I wanna change gears a little bit and ask you about chat bots, which have become very popular lately as a new channel for IT organizations to deliver automated self-service. What do you think the future looks like for automated self-service versus the traditional way of delivering support via service desk?

Alessandro: This is an interesting question, and I have very strong opinion about chat bots in general, not necessarily popular opinions, but these are also two questions in one. One is the future of self-service provisioning and another one is what the chat bots, what kind of market opportunity is there for them? We saw an explosion in the industry regardless of automation, regardless of cyber security or IT operation in general chat bots had quite the momentum in the last few years, but then now we’re seeing a lot of companies that were offering these solutions just stopping it, so I think Facebook is one of them. There were a number of news in the market recently about the fact that chat bots didn’t create that kind of strong momentum as was initially expected.

What’s the reason for that? In my opinion, chat bots are just frontends. They’re not really solving the behind the scene problem, which is how do I automate a number of processes in the most efficient way, that it’s not complex. That it’s manageable. That it’s documented in a way that doesn’t require extraordinary amount of efforts in terms of integration & customization. They are frontends. They leverage artificial intelligence to do natural language processing, and they are in theory meant to simplify the interaction with the customer, but the problem is that the level of technology maturity that we have today is far, far, far away from what it’s supposed to be.

I am an Amazon Echo customer, and so I use Alexa all the time to do all sorts of tasks, and I’ve been doing for quite a few years, and I tried all the other assistants that exist on the market. I have to say that there is a massive gap between what the state-of-the-art solution are doing today in terms of natural language processing versus what is in our mind after watching series like Star Trek: The Next Generation, or movies like Her, for example. It is so far away. The chat bot per se is not yet going to give you that extra help that we hope it will in one day, in terms of simplifying the interaction with the automation layer for the provisioning of whatever we’re trying to provision. This is first part of the answer.

The second part of the answer is, “Okay, what is the future of self-service in provisioning the orchestration & all the other things?” I see, and I’ve been seeing this for quite a long time, a shift in terms of power, control, autonomy, that moves from central IT to line of business. The line of business are gaining more and more autonomy, control over the budget, selection of technologies that they want to use, and they tend to think in terms of, “Okay, how can I get as fast as possible to the business outcome I’m hoping to have?” Because they are measured by completely different metrics compared to the central IT. Central IT has a completely different mindset from line of business.

In this trend that I see accelerating and in part is fueled by this DevOps methodology kind of approach, a giant methodology, the capability for engineer to be completely independent, all of this is just accelerating this autonomy. The need for self-service is increasing, and it’s driven by, I would say a frustration of the line of business that being depending by the IT operation team for way too long. The IT operation team, the central IT has been too inefficient for way too long, and so there’s now there’s demand to let me do whatever I can in a fully automated way. When that is not delivered by central IT, what happens is that, and I saw this so many times in the last 10 years, then the line of business simply circumvents all the rules that exists in terms of compliance, in terms of security, and then just go and use public cloud service providers often in the form of software as a service to just get the job done as fast as possible.

I think that the future is gonna be completely automated in so many more ways than the ones we see today. I don’t know if the frontend for that automation will be chat bots, because I don’t see enough progress, but certainly we will have a way more automated future.

Guy: I think that Shadow IT, which is kind of a catch all term for what you just described, is definitely something that we’re seeing more and more of, and it’s been enabled by the public clouds like AWS, Azure, and Google Cloud. With that emerging trend and with the move towards an inevitable automation future, what is the one piece of advice you would give the CIOs, CTOs, CISOs considering whether or not to dive into automation?

Alessandro: Well, as I said in the beginning of this conversation, I don’t think that any of the persona have any choice. They’re forced to at least understand what does it mean to operate at scale, to do IT operations or to do security at scale. The professionals that report to them and need to develop that kind of awareness, if not the skills to just cope with the kind of speed that we see today in the market in the world. The one piece of advice is certainly to invest a lot in education. I am amazed, this is a small thing or it sounds so. I’m amazed by how many executives in very large enterprises never went to attend an Amazon Reinvent Conference, and they never saw in person what we’re talking about here.

A lot of people read about this in press articles or in news outlets but they don’t quite understand or develop the awareness that is necessary. Training is for the executives in the underline is critical to understand there is no other option. This is one thing to focus on. I’m a big believer in education, so I believe that training is fundamental to progress in any kind of IT management or enterprise endeavor in a large organization. This is certainly one thing.

The other thing is, as I said before, to start considering automation, not as a tactical tool, that can kind of shave off some of the time that you spend in doing a number of tasks, but reconsider it completely as a strategic tool to drive IT operations. There is a reason why public cloud providers like AWS, that started from scratch, are getting so massive and so popular and so efficient. It can drive the cost down to the level that it is today. That reason is that they design from scratch, the entire IT architecture to be automated. That was first thing that was part of the design guidelines. The IT operations, but in general the central IT as an organization today, faces that sort of competition, faces the competition of public cloud service providers that offer a better service, a faster service, a more automated service to their own line of business compared to what is offered within the corporate boundaries.

We’re really talking about an existential risk today. For the CIO, for the CTO, for the Chief Information Security Officer, there is all of them are at risk of losing their audience, and the audience as well validates their presence in the enterprise because they simply cannot think in the same way a public service provider is thinking. The mindset has to change before anything else in terms of processes, in terms of technologies can change.

Guy: Alessandro, we’re running low on time but I can’t let you go without asking about the H+ project you’re the founder of. Can you please tell our audience a little bit about what that is and the kinds of things you’re working on?

Alessandro: Sure. First of all, I need to say that that is not in any way related to my work in Red Hat. It’s a side project. I’m very interested, and I’ve been studying a lot for years a number of different disciplines that are related to human body augmentation or human announcement technologies as the industry calls them, and they go from neural interfaces to bionic prosthetics to genetic engineering, precision medicine, nano robotics and so on and on and on. The reason why we’re patient about this thing I question from neuroscience and genetics and cognitive psychology, is that I believe that we are a fundamental point of change for the way humans process information today. The scale of information is so massive for us to process, and you can tell by just looking at how people are glued to their phone when you go on a tube, when you go on a train, when you just stepped at an office, and everybody is looking at the phone rather than talking to each other.

The amount of information that must be processed are so massive, and there is such a social pressure to be sure that this information is processed in the most efficient way, and so you’re hyperreactive to what the world is saying around you that there is no other way eventually, than the one to augment yourself. I strongly believe that just like traditional prosthetics that exist today in the world, including things like, very simple like contact lenses or pacemakers, and so on, as those things became the norm & are perfectly accepted from a societal perspective, so the augmentation in the sense of blending together technology with the biology to increase human capabilities, and process more information and being faster in making decisions and better in making decisions, computer system, if you want to send this play is gonna be a mandatory step for the humankind. I don’t see any possibility for the future, so I’m very interested in that, and I’m interested in understanding what startups are doing what in the space and what kind of new academic research comes out.

H+ is an open research initiative that basically collects in a completely open way so anybody can access completely free, can access to all the things that I collect in my free time that talks about all these different technologies. Basically, it’s a way to track how we’re going in terms of the next stage, what I believe will be our evolution.

Guy: That’s great. All those issues that you’re covering. They just prove that there’s no longer anything such as science fiction. It’s just science.

Alessandro: Absolutely.

Guy: All right. It looks like that’s all the time we have for today. Alessandro, I’ve really enjoyed our conversation, and thank you again for being our guest.

Alessandro: Likewise. It was great. Thank you.

Guy: Alessandro Perilli, General Manager of Management Strategy for Red Hat and founder of the H+ project. Thank you for listening everyone, and remember – don’t hesitate, automate.



Alessandro Perilli 

General Manager, Management Strategy at Red Hat

Alessandro Perilli leads management strategy at Red Hat, including company efforts in cloud management, automation, predictive analytics, and self-healing IT. Alessandro also develops the vision behind new management initiatives in multiple areas (artificial intelligence, IT security, etc.).

Prior to joining Red Hat, Alessandro was a Research Director at Gartner, leading the private cloud research program in Gartner’s Technical Professionals division. Alessandro also spent time consulting for large end-user organizations and cloud vendors, advising enterprises on how to develop a cloud adoption strategy and writing acclaimed research papers, including “Climbing the Cloud Orchestration Curve” and “Market Profile: Cloud Management Platforms”.

In 2014, Alessandro was listed in Business Insider’s Top 39 Most Important People in Cloud Computing. He has been a keynote speaker for 18 years in a row.

Alessandro started his career as a practitioner in cybersecurity, creating one of the first ethical hacking courses in the world, authoring a book, and speaking at dozens of conferences about attack methodologies used by the hacking community.

Today, Alessandro is also fully dedicated to studying human enhancement technologies like neural interfaces, augmented reality, biohacking, bionic prosthetics, genetic engineering, nanorobotics, and wearable technology. He tracks advancements in these disciplines through H+ (https://h.plus), an open research project that he launched in 2017. 

Alessandro can be found at:

E-Mail:               alessandro@alessandroperilli.com

Twitter:             @giano

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

Quotes

“…you technically have no choice but to automate, to cope with the scale and complexity of very large environments that…exists today.”

"What happens when artificial intelligence is used to drive these hacking attempts?"

“A top skill to acquire for all these professionals is to start to understand how things change at scale. What does it mean to rethink an operational framework or a security framework at the scale that we are about to face or we're facing already.”

“…and I've been seeing this for quite a long time, a shift in terms of power, control, autonomy, that moves from central IT to line of business. The line of business are gaining more and more autonomy, control over the budget, selection of technologies that they want to use, and they tend to think in terms of, "Okay, how can I get as fast as possible to the business outcome I'm hoping to have?"

“I think that the future is gonna be completely automated in so many more ways than the ones we see today.”

“There is a reason why public cloud providers like AWS, that started from scratch, are getting so massive and so popular and so efficient……That reason is that they design from scratch, the entire IT architecture to be automated.”

 

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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Episode #3: Enabling Positive Disruption with AI, Automation and the Future of Work – Symphony Ventures Ian Barkin


Oct 11, 2018    Episodes


Episode #3: Enabling Positive Disruption with AI, Automation and the Future of Work 

In today’s episode of Ayehu’s podcast we interview Ian Barkin , Co-Founder and Chief Strategy Officer of Symphony Ventures

“Disruptive Innovation”, a term coined in 1995 by Harvard scholar Clayton M. Christensen, can wreak havoc and displacement upon markets, organizations, and product lines. New technologies such as Cassette Tapes, CDs, and MP3 files, are examples of innovations which disrupted the music industry, upending the existing order. Many people are predicting that automation, artificial intelligence, and machine learning could generate the same chaos. However, Ian Barkin Chief Strategy Officer for Symphony Ventures, preaches a contrarian viewpoint of positive disruption to his clients.

In Ian’s view, existing infrastructures should not be replaced by innovations like AI, but rather melded together, creating a new digital operations reality. He’s found numerous instances where the “non-cashable” benefits alone from this approach outweigh the “cashable” ones, and often in unexpected ways. Ian talks with us about positive disruption, the “extra hour scenario”, and why we must reform our education practices starting at the pre-school level in order to prepare our youngest generation for a future of work which will rely much more on creativity than doing routine tasks.





Guy Nadivi: Welcome everyone. Our guest today on Intelligent Automation Radio is Ian Barkin. Ian is the Co-Founder and Chief Strategy Officer of Symphony Ventures which is a leading global consulting, implementation, and managed services firm specializing in automation and artificial intelligence, two topics we’re very keen on here. Ian’s focus at Symphony Ventures is to design digital operation strategies for clients implementing global transformation efforts centered around these technologies and we’re really delighted to have Ian with us today. Ian, welcome to Intelligent Automation Radio.

Ian Barkin: Thanks, Guy. Delighted to be here.

Guy Nadivi: Ian, as the Chief Strategy Officer for Symphony Ventures, you’ve described part of your job as enabling positive disruption for your clients with regards to AI, automation, the future of work etc. There’s a lot of buzz about these topics today so it could be very challenging to separate the wheat from the chaff. For CIOs, CTOs, other IT executives listening, what do you recommend should be their first step on the journey towards digitally transforming the organization?

Ian Barkin: That’s a great question. I often say that I spend a lot of my time story-telling but much of it trying to be pragmatic and really as you say separate wheat from chaff just because there’s a great deal of excitement and I do not argue that some of the promise of the future is exciting, but I spend a lot of my time working with the C-suite to understand the art of the possible and what’s enterprise grade today from a tool set perspective so that some of the more interesting and esoteric promises of machine learning and AI, while very much on the roadmap aren’t necessarily the technologies that will solve the problems that they have operationally today, and so I spend a lot of time with them on that.

And then even more importantly I spend a lot of time on just the foundation, on just basically the education and alignment and change management and stakeholder management and communication plans within an organization because you could have the best, shiniest, most capable technology in the world, but if the troops aren’t aligned and clear what the destination is, you’re not going to get there.

Guy Nadivi: Right. I read also that you tell your clients there are seven benefits to automation that Symphony Ventures identifies when working with them and that you categorize them as “cashable” or “non-cashable”. The cashable benefits are kind of obvious I think with regards to cost savings, but I think it would be very interesting for our audience if you talked about what the non-cashable benefits are, which you described as potentially orders of magnitude more impactful to an organization.

Ian Barkin: Certainly. This dates back really to the earliest days of our exploration with several different classes of automation tools, and obviously it’s because as you said the cashable components, and really to cut right to it, the concept of headcount reduction that allows you to take cost out of an organization. That often is what gets projects funded.

You need that in your ROI calculation and your business plan. But it’s very primary and so what we came across and in some of it was frankly a surprise and an exciting one at that, were the secondary and tertiary benefits and so as you say we’ve described them as cashable and non-cashable because impacts like better visibility into an enterprise’s operations often very complex operations.

Better ability to control and to comply in highly regulated industries where audit is often a concern, and one of the ones that I’m most excited about is just the class of experience benefits, and that can be experience for your customers or depending on the industry you’re in, your patients, your citizens. It can also be experience for your employees, for your partners.

And the benefits of those while harder to quantify often end up materializing themselves in bigger ways. Reduced churn, higher just general retention, word of mouth, higher net promoter scores, reduced likelihood of audit fees and compliance credits. And so those are the sorts of opportunities we make a point of emphasizing for two reasons. One just because we know that those cashable benefits still are going to be the ones that often get projects funded so we don’t want enterprises to forget about the other opportunities.

But also because we want to encourage enterprises to really baseline and understand what good is, set that vision for themselves and then chase it by leveraging the class of automation tools that does more than simply reduce initial primary costs out of their operation.

Guy Nadivi: You mentioned regulated industries a couple times there, and in particular, we run into that a lot with industries that have a very strict compliance regime that they have to adhere to. I’m curious which industries are you seeing that are being impacted most profoundly by the changes that automation and AI are delivering?

Ian Barkin: Right. I’d like to think it’s a little bit more interesting and creative than this, but often you find the industries that are well financed and that have a real imperative to change are the ones that adopt somewhat earlier. And so in our history, we’ve been lucky enough to develop a really robust portfolio of partners clients in financial services and in healthcare, and so we’ve got a lot of banking, financial service and insurance firms who use automation across the board.

This is horizontal and vertical applications of it. Everything from the horizontal HR, finance, and accounting processes to the more specific to their industries like anti-money laundering, know your customer, mortgage processing, and maintenance, et cetera. And then in healthcare as well, just the security around data, both patient data, and financial data is high, and yet the dynamics of the healthcare industry are such that that’s an industry that badly needs change, badly needs transformation and cost reduction. And so we’ve been lucky enough to work with a lot of organizations in that industry to help them understand how to better run their businesses and optimize their operations.

Guy Nadivi: So can you please provide us with an example of a project you’ve been involved with where automation, AI, etc. had a profound impact on cost reduction both cashable and non-cashable operation efficiency, and other critical metrics?

Ian Barkin: Yeah, my pleasure. The great benefit of having done this for a while is I’ve got a wealth of examples to choose from. I’ll pick one that I think really resonates broadly with the wide audience just because I imagine most people have been hired for a job and paid for a said job. There was one solution we did within an HR shared services operation. Just so happens it was for a very large healthcare organization.

But this HR shared services function that they had centralized had several different roles but one of them was around what they called work absence management, and it was the basic concept of at a certain point in your career, you’ll need to step away either for disability or for maternity or paternity leave or bonding or family medical leave.

There’s a long list of reasons, and when you do that in the United States, there’s a convention in which you get paid by multiple sources, effectively insurance in state, and you need to integrate that pay. And so they had a team that was handling and coordinating that. That pay integration. Ultimately as you, if you look under the hood and try to figure out the components and the complexities of the process, it’s actually a massively complex process for a few reasons. One, because this was a union shop, so all of these different employees belonged to different unions who have different negotiated fee structures and relationships and contracts. And then you have the different leave types. You have whether it’d be maternity or disability or any of the others. And then you also had job grade, job type, location, tenure, salary level that really was this multi-variate equation of parameters that needed to be calculated correctly, hopefully, to handle this pay integration.

Now the result of that was these processes took a while. They had service levels of often two weeks or slightly longer to complete a transaction for someone who was home on disability to make sure that their paycheck was integrated correctly and so that meant they had a team. The team was quite busy. It was doing a very complex role. It took quite a long time to train the people to do correctly, and retention is always a challenge in shared services environments.

And so there was inherent cost in friction and experience issues if the pay was either calculated slowly or incorrectly, etc. So that’s the backdrop. And so the solution that we helped this enterprise deploy was one in which we automated a lion’s share of that process because while it was a very complex process, it was still just a lot of rules. That multi-variate equation was still an equation, it was rules.

And so the outcome was a few fold. One that the pay, the time it took to transact went from two weeks down to approximately two hours which is extraordinary in and of itself. And then there’s all these secondary, tertiary benefits I referred to. If it takes not two weeks but two hours to get your paycheck. If you’re home on disability, you’re not sitting there waiting, wondering where your paycheck is, or wondering if it’s correct, and therefore you’re not any longer calling a call center.

And so the secondary benefit was a few fold. One, the call center volume went way down. The experience for employees went way up and then if you want to carry this through as a story, the tertiary benefits were that people who were on leave had the right information, felt supported, the call center was able to be more proactive in outbound, so called you to say is everything okay, how can we support you, it looks like you’re scheduled to come back to work at this particular time. And so people came back to work on time.

And so experience was higher, retention was lower, and so it was extraordinary to watch this happen just because you automated a core process and the SLAs were shrunk way down, quality went way up, experience exploded, and so that was really game-changing, and obviously the financial benefits of not needing as many people in that transactional team focused on that particular scope of work was compelling as well. Long story. But one I’m really passionate about because it really did manifest itself. It’s all sorts of different blooming benefits as this thing blossomed as it went.

Guy Nadivi: That’s an extraordinary optimization to go from two weeks to two hours. When you mentioned now the support team had quite a bit of the call volume burden shifted off of them. I’m going to guess that that freed them up to work on other more important things that probably had been stacking up then. Would that be correct?

Ian Barkin: Absolutely. I call that “the extra hour scenario” and what I mean by that is if you walked into any organization, anywhere in the world, and you said “What would you do if I gave you an extra hour in your day?” I would chance a guess that no organization would say to you “You know what? We don’t need it. We’re pretty good. We got everything covered. You can have it back.” There’s every organization the world over has those tasks that they’ve been meaning to get to, they know are valuable, and obvious, and often create greater experience and yet they’re not able to get to them because they’re just so busy keeping the lights on, or the ship afloat, etc. Hitting the SLAs in doing the necessary transactional processes. So I love those extra hour scenarios and you’re absolutely right. They have other very highly value adding things to spend their time on.

Guy Nadivi: Yeah, I’m sure for everybody there’s never enough time in the day, so to get an extra hour is significant.

Ian Barkin: Or in this case, dozens or weeks. That’s one of the ways that the industry has taken to quantifying the impact of automation is the hours given back to the business. Partly because it’s less, optically it sounds better than FTE reduction but also it gets to a greater, bigger, more strategic point of what are you doing for the business. How are you adding value beyond simply reducing cost?

Guy Nadivi: Right. Ian, you told the BBC earlier this year that automation “is an evolution of work and the type of work we do will change,” and you followed that up by saying “there’s an urgent need for education reform. People need to learn design thinking, creativity, analytics, programming”. Should that kind of education reform take place in high school or even earlier?

Ian Barkin: That’s a great question. As a father of two young girls who are in now 1st and 3rd grade, I guess my opinion is somewhat slanted or informed by that, but I think that education needs to start as early as education starts. I think we really need to, from kindergarten, pre-school on up be teaching collaborative practices, teamwork. As you said design and iteration and teaching the high schoolers of the future, the employees of the future how to be more creative because ultimately the automation of the routine in mundane tasks will only continue.

The capability of the automation will only continue to get better so that anything that’s character recognition or voice recognition or just the rule base that we spend a lot of our time helping automate won’t be there anymore, and so people get to do the nuance, the judgment, the critical thinking but we need to make sure that they’re prepared to do that.

Guy Nadivi: Yeah. I’ve heard from many quarters, as I’m sure others have, that education is becoming a bottleneck on the path to the future. That we really need to overhaul the curriculum and really change some of the subjects that are taught from an early stage to prepare people for the future of work which is going to be very different. If you look at just 10 years ago, a job like social media manager didn’t exist, and now every company has one or a team of them or a contractor that provides that. Things are going to be changing very quickly along with the technological changes and the education sector definitely needs to keep pace with that.

Ian Barkin: Absolutely. I think it’s such a thrilling topic and somewhat scary topic sometime to explore and discuss, but it’s an imperative one. And I don’t think anyone has necessarily the single silver bullet or right answer. It’s going to be a collection of things. You see some of the educational programs that they have setup for instance in Germany where they’re training in more trade skills. That emphasis needs to come back too. Does everyone need to go to college?

What is the future workforce going to need of us and where won’t it need us anymore, and how do we really strip the curriculum down to the fundamentals and build it back up based on that reality?

Guy Nadivi: Right, maybe instead of shop class, we should be teaching Google Adwords, at the junior high and high school level.

Ian Barkin: Come on, shop’s a great class. I wish they had that more often.

Guy Nadivi: I loved my shop class as I was very distraught to hear that a lot of schools are cutting them out. I think it’s a mistake, but maybe replace them with something perhaps more relevant for the future, everybody can benefit.

Ian Barkin: I think auto maintenance, shop, how to do basic accounting, all that stuff should come back. I don’t know how to do any of those things.

Guy Nadivi: Ian, what is the single most important piece of advice you can offer to executive decision makers that are thinking about plunging into a digital transformation involving automation and AI and machine learning?

Ian Barkin: That’s a great question. I think first and foremost, I would say again approach this, so I’m going to answer with a few things. You said single but I don’t do single well. First and foremost, approach this with pragmatism and a wide open aperture, because the future of work in this automation hybrid is not just pulling on the brand new, it’s actually supercharging capabilities and technologies, and teams that have existed in enterprises for, in some cases, decades.

And I often spend a lot of time saying that there’s very little new under the sun and we really have to appreciate all of the hard work that continuous improvement teams and six sigma black belts have done, and enable them, rather than think that AI can magically replace them. So that’s what I spend most of my time with executives thinking through is just how do you mesh the existing, not necessarily old, that sounds pejorative, but the existing with the new to truly create this digital operations reality for the organization.

I guess if there’s anything else I’d just say be wary of smoke, mirrors, and hype because I think it’s sending too many people on journeys into woods that they realized too late that they just spent a lot of time and money pinning their hopes to things that just sounded too good to be true.

Guy Nadivi: All right. Well, looks like that’s all the time we have for on this episode of Intelligent Automation Radio. Ian, thank you so much for joining us today. I’ve really enjoyed our discussion and thank you again for being our guest.

Ian Barkin: Thank you guys for the thrill. Thanks for having me.

Guy Nadivi: Ian Barkin. Co-Founder and Chief Strategy Officer of Symphony Ventures. Thank you for listening everyone, and remember don’t hesitate, automate.



Ian Barkin

Co-Founder and Chief Strategy Officer of Symphony Ventures

Ian is an experienced innovator, and transformation leader. He has built several industry leading Innovation Labs and has been at the forefront of trends including Internet of Things, supply chain BPO, Robotic Process Automation, and User Experience Design. Ian’s focus at Symphony is to design digital operations strategies, incorporating the Symphony Digital Ecosystem of partners, and future-proof delivery models including Robotic BPO (R-BPO), Managed Centers of Excellence (M-COE), and Digital Design thinking.

Ian can be found at:

E-Mail:               ian.barkin@symphonyhq.com

Twitter:             @ibarkin

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

Quotes

“I call that “the extra hour scenario” and what I mean by that is if you walked into any organization, anywhere in the world, and you said “What would you do if I gave you an extra hour in your day?”


“one of the ways that the industry has taken to quantifying the impact of automation is the hours given back to the business.” 

“I think we really need to, from kindergarten, pre-school on up be teaching collaborative practices, teamwork.”

“What is the future workforce going to need of us and where won’t it need us anymore, and how do we really strip the curriculum down to the fundamentals and build it back up based on that reality?” 

“…how do you mesh the existing, not necessarily old, that sounds pejorative, but the existing with the new to truly create this digital operations reality for the organization.”

“…be wary of smoke, mirrors, and hype because I think it’s sending too many people on journeys into woods.”

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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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

Reskilling Your IT Team for Digital Transformation

The number of job openings for data scientists is steadily on the rise, with IBM predicting a 93% growth rate in data science skills, followed by 56% predicted growth for machine learning skills. Without question, artificial intelligence experts, machine learning developers and data scientists are in high demand, and as that demand rises, the number of qualified candidates to fill open roles will dwindle.

In fact, according to the 2018 State of the CIO report, 36% of respondents cited difficulty filling roles for business intelligence and data analytics. AI roles also made the top 10. Rather than hiring new employees, many organizations are instead looking to reskill existing staff to prepare them for the roles needed to achieve digital transformation.

Let’s take a look at how some companies across various industries are preparing their existing personnel for the AI era of tomorrow.

Back to School

There is no shortage of formal training programs available at higher education institutions across the globe where those interested in gaining expertise in the way of AI, machine learning and data science can pursue their professional development. The most advanced training typically takes anywhere between a year to a year and a half to complete. It also requires basic programming skills and a solid understanding of programming. There are also a variety of online courses and programs to consider.

Forward thinking companies looking to transform their existing workforce can offer tuition reimbursement and flexible work schedules in order to encourage employees to go back to school. The promise of a newer, better role at a higher pay grade can also be great incentive.

Formal In-House Training

Another way organizations are getting existing employees prepared for digital transformation is to create in-house training centers. These will often include test environments in which trainees can experiment with AI and other disruptive technologies. As employees learn and skills are mastered, the training can then be extended to other teams and departments, including the C-suite.

For those companies that don’t have the capacity to create learning centers, availing themselves of vendor-provided training can be the next best thing. For instance, Ayehu offers a free Customer Success Program as well as free Webinars each month aimed at accelerated training of various AI and machine learning applications.

Peer-to-Peer, On-the-Job Training

As companies begin to build up a pipeline of skilled internal talent, they can then begin investing in peer-to-peer mentoring opportunities to further spread knowledge and education. For instance, a department might attend a starter course to familiarize themselves with the concepts of AI, machine learning, etc. and then transition to a mentoring strategy thereafter.

This approach begins by incrementally exposing employees to smaller areas where the use of disruptive technologies can have a large-scale impact. Once comfortable, they can then move toward improving workflows and tackling other, more complex projects – all under the supervision of experience mentors. Many business leaders utilizing this approach feel that it’s much more effective and that employees learn, absorb and build upon critical skills much faster than they would in a traditional classroom setting.

Keeping Pace with Change

The challenge of reskilling to facilitate digital transformation is that technology is evolving at an incredible rate. Keeping pace with the rate of innovation is the key to success. That means developing and fostering new skills on an ongoing basis.

To address this, some organizations invest in regular educational sessions and AI-related training held either ad hoc or at specified intervals. Access to routinely updated educational resources, like online tutorials, onsite training and industry/sector conferences is another option. The thing to remember is that, given the rapid rate of change, you simply cannot overeducate your employees.

With a staffing shortage that’s growing by the day, business leaders must compensate by reskilling existing employees. Otherwise, they risk losing ground in the race to digital transformation.

Give your team a solid foundation by investing in top-of-the-line, Next Generation Automation and Orchestration. Give it a try free for 30 days. What do you have to lose?

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5 Ways Intelligent Automation is Impacting the C-Suite

The enterprises of today are raising the competitive bar by leveraging various forms of artificial intelligence. From virtual assistants and chatbots to deep learning and intelligent automation, companies are transforming how they operate. Leveraging these advanced technologies successfully, however, requires that the C-suite plays a pivotal role in identifying opportunities, risks and challenges, in particular, what type of impact it will have on the people and processes currently in place.

A recent study by McKinsey which analyzed over 2,000 work activities across 800 different occupations. The study found that 30 percent of what 60 percent of occupations involve could easily be automated. In fact, 5 percent of occupations could be automated entirely. As a result, more and more businesses are experimenting with the various forms of AI technology available to do everything from improve efficiency and forecasting to assisting with key decision-making activities.

One of the biggest impacts intelligent automation has had on the C-suite is the increasing scope of responsibility. Today’s executives are no longer solely responsible for managing people. They’re now expected to manage a new workforce of people and intelligent machines operating in tandem. They must also come to the realization that AI and intelligent automation are no longer just IT initiatives, but something that should be approached from a company-wide perspective. It’s a whole new world.

Regardless of where an organization happens to be in its journey, here are a few ways that intelligent automation is already having an impact on the C-suite.

Shift in Mindset

As the partnerships between humans and machines continue to grow and evolve, the very definition of “business as usual” also continues to shift. Technology is being used to automate more and more functions, streamlining departments across the enterprise, including finance, HR and procurement. Executives must take on a new viewpoint of labor, proactively pursuing ways to augment their workforce with artificial intelligence.

Opportunities Weighed with Risks

Intelligent automation is facilitating exciting new, competitive opportunities. These opportunities, however, are not without risk. C-suite players must thoroughly weigh both in order to avoid the unexpected and mitigate potential damages. When considering the adoption of a new technology, leaders need to examine their overarching goals and gain an accurate understanding of the implications that technology could potentially have on the company, its customers and its shareholders.

The Age of Hyper-Agility

Most executives are already well aware of the need for agility in order to remain relevant and competitive. But in today’s climate, simple agility won’t cut it anymore. By utilizing AI and intelligent automation, organizations can achieve a greater degree of adaptability and gain even deeper, more meaningful insights into customer preferences and behaviors. This will enable more data-driven decisions.

Eyes Wide Open

One obstacle many business leaders face when implementing intelligent automation is a lack of in-depth knowledge about the process they are trying to automate. The keys to successful automation adoption is good planning and proper communication. Mapping out precisely what is to be automated, tracking the current status and initiating the next steps. It simply cannot be viewed statically, but rather with an eye that is constantly trained on change.

Careful with Assumptions

Some companies approach intelligent automation from the viewpoint of workforce reduction when, in reality, it’s more about workforce evolution. For instance, a leader might assume a reduction of 50% of his or her staff with the rollout of automation. But, who will build out the workflows? Who will oversee and quality assure the process? Who will run projects and initiatives that are spawned as a result of the automation? The goal of intelligent automation shouldn’t be replacing humans, but rather making them better at what they do.

Without question, AI and intelligent automation are revolutionizing how organizations compete. In order to be successful in this respect, however, those operating in the C-suite must step up to the plate and be willing to consider a much broader spectrum that extends far beyond technology alone.

Want to experience the power of intelligent automation for yourself? Launch your limited-time, free 30-day trial and take Ayehu for a test drive today!

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Managed Service Providers: Could this be hindering your growth?

Making the transition from basic IT support to a full-fledged Managed Service Provider isn’t necessarily easy. There will inevitably be a number of obstacles to overcome along the way. Thankfully, many have gone before and essentially paved the way for newer players to enter the field. Learning in advance what challenges you can expect and the best way to meet those challenges head on will help you avoid potential pitfalls that might otherwise become a barrier to growth. Let’s take a closer look at the three most common issues today’s MSPs struggle with.

Fear of Change

Let’s face it. Making a major change to your business model is scary. What if things don’t work out? Will you be able to recover? The reality is, however, that success requires a certain degree of risk. If your team is feeling particularly leery of making the shift to Managed Service Provider and/or pursuing aggressive growth initiatives, the key will be communication. Be open, honest and transparent. Acknowledge the uncertainty many of your staff members are experiencing and take the time to address those concerns and put them to rest.

Additionally, there may also be an underlying fear that switching to managed services will result in the loss of business. Chances are very good that this will, indeed happen, as not everyone is suited for an MSP level of support. Understand, however, that while you may very well end up saying goodbye to a small portion of your customers, over time you will gain others to replace them. It’s just part of the shift.

Lack of Differentiation

Without question, the Managed Service Provider field is highly saturated. The organizations that thrive are those that have found a way to stand out from the competition. This is especially critical for those just entering the marketplace. If potential clients can get the same service from an established player that they already know and trust, why would they take a chance on you? It’s up to you to convince them otherwise.

To do so, you must identify what new and better services your company can offer. For instance, if your prospects are seeking growth themselves, focus on services that help maximize efficiency and empower them to achieve those goals. If you’re unsure of what angle to take, tap into your sales team to find out what they’re hearing in the field. Or, better yet – ask your clients and prospects directly.

Underpricing

Finally, there is the challenge of how to appropriately price your services. In fact, making a switch from fixed price to a more profitable pricing model can be a difficult transition. This is often compounded by a mere lack of full understanding and a subsequent underestimation of the true value of the services you will now be providing.

At the end of the day, you want your customers to pay you what you’re worth. If you are undervaluing your services, chances are you are also underpricing yourself, which means you will not be able to achieve sustainable growth. Be honest and do your homework. Figure out what you are worth and what you will need to make in order to bring your business to the next level and then implement the necessary changes to make it happen.

Now that you’ve got a clearer picture of what may be standing in your way, it’s time to get to work turning things around. Here are a few helpful pointers, to overcome these common issues:

  • Evaluate your current business plan and strategy, as well as team member skills and abilities.
  • Utilize technology and tools, like intelligent automation, to make service delivery much more efficient.
  • Build technical credibility through key certifications and specializations.
  • Understand your pricing model to ensure that it properly supports your level of service.
  • Keep in close contact with customers to recognize and capitalize on trends and opportunities. 

Making the transition from basic IT support to full-fledged managed service provider may seem like a daunting task, but it doesn’t have to be. In fact, with a well thought out plan backed by a confident team and advanced technology, you will be well positioned to compete in today’s fast growing market.

Want to experience the power of intelligent automation backed by AI technology? For a limited time only, get a free 30 day trial of Ayehu by clicking here.

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Ayehu Announces Free 30-day Trial Availability of its Newly Enhanced Next Generation Intelligent IT Automation and Orchestration Platform

The Free Trial Version Featuring an Enhanced Workflow Designer and AI-Powered Automation Engine is Now Available for Download from the Ayehu Website

San Jose, CA –- October 16, 2018 Ayehu has enhanced its Next Generation Automation and Orchestration Platform powered by AI. This latest release is designed to deliver IT and security operations teams even greater productivity and ease of use. To give enterprise users the chance to experience the platform firsthand, Ayehu is offering a free 30-day trial.

Today’s enterprises are overwhelmed by a massive amount of system alerts, incidents, and user requests. This is further complicated by the IT and security skills shortage. The need for streamlined processes and fast, quantifiable results has never been greater.

Ayehu’s Next Generation Intelligent Automation Platform incorporates artificial intelligence to augment human ingenuity, in order to enable the creation of the next generation of intelligent applications. The platform delivers no-code, automated workflows that help enterprises save significant time on manual and repetitive tasks, accelerate mean time to resolution, and maintain greater control over IT infrastructure.

The new version includes the following enhancements:

  • Productivity – For greater efficiency and results, the platform now features a full web-based GUI, includes power search capabilities, a library of over 500 pre-built activities and a codeless workflow designer. Out-of-the-box integration packs are also available, with advanced Rest API for rapid integrations with 3rd party applications
  • Scalability – Scaling to support a high volume of incidents and safe guard against a single-point-of-failure, the latest release features built-in automated load share, and the ability to run more workflows simultaneously
  • SaaS Ready – Ideal for hybrid deployments, the new version can run multiple instances on the same virtual machine, run different environments on the same station, and manage all environments from one place
  • Chat Bot Integration – Ayehu BOT platform is integrated with Slack, Microsoft Teams, IBM Watson, Microsoft Luis and other applications for the easy creation of a self-service interface

“Since we launched our intelligent automation platform, customers have realized that artificial intelligence combined with IT automation is a game changer,” said Brian Boeggeman, Chief Revenue Officer, Ayehu. “As we continue to make our solution even easier and more valuable, we are offering a free trial so that everyone can simply start automating today. IT professionals that experience it will immediately see a huge leap in productivity and efficiency.”

To experience Ayehu’s Next Generation IT Automation powered by AI, claim your free trial here. To learn more about the Ayehu Next Generation Automation and Orchestration Platform powered by AI, click here.

About Ayehu

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

How to Become an Intelligent Automation Leader in 4 Steps

Intelligent automation is rapidly transforming the global economy, delivering momentous gains to enterprises that adopt it at scale. One recent article by McKinsey revealed that some organizations have been able to automate 50 to 70 percent of their workflows, generating ROI that reaches into the triple-digits. In addition to cutting costs, intelligent automation can also deliver precision, speed and enhanced customer experience.

In order for organizations to enjoy the full value of intelligent automation, IT leaders must be willing to take a guiding role. Unfortunately, many IT executives find this challenging, whether due to the increased complexity of IT processes, lack of understanding and/or clarity, inconsistent or fragmented tools that hinder scaling, or the misconception that intelligent automation cannot be adopted without major re-engineering of existing processes.

How can these challenges be overcome? And how can IT leaders succeed in their automation initiatives? The answer to these questions lies in the following four key steps along the intelligent automation journey.

Step 1: Evaluate the high-level potential value

The first step in becoming an intelligent automation leader starts with the development of a clear business case. This involves assessing the potential high-level value of the company’s main IT activities. Some examples of what these areas of value might look like include:

Incident Response – A significant number of IT incidents are initiated through support desk requests. These typically result in tickets being created and assigned to Level 1 support agents. While these are the obvious candidates for automation, the portion of tickets that are escalated to specialized L2 and L3 agents are also ripe for the picking, thanks to the advanced technology behind intelligent automation. And since these activities are generally well-documented, categorizing and prioritizing them by automation potential should be relatively straightforward.

Planned Activities – In addition to the one-offs and unexpected support tickets that crop up, IT is also responsible for performing a number of planned activities on a regular basis. These activities typically include things like backups, upgrades and patching. They may also involve more complex security audits. The amount of time and resources required to perform these duties can collectively add up to around 20 percent of the IT budget. Calculating this figure can help determine the potential savings intelligent automation can deliver.

Introducing New Applications – From a business perspective, this activity is often viewed as the one that produces the most significant value. It can also account for an additional 20 to 40 percent of the time and resources put forth by IT. These activities are not exclusive of application development, either. They also include such tasks as testing and hosting. This places increasing demand on both the application team as well as the infrastructure group.

Step 2: Dig deeper to identify which specific use cases are best suited for intelligent automation.

Determining how to effectively implement intelligent automation requires a deep dive to uncover the root causes of issues. It may also involve the untangling of complex systems and the development of an accurate picture of how to leverage automation to extract the greatest value. In other words, the process is a complicated one and requires a certain degree of commitment. Let’s take the three potential use cases above as an example.

Incident Response

Automating IR begins with identifying which incidents are the best candidates, which can be challenging. The goal should always be digging deep enough to uncover the “why” of documented incidents. Without this information, efforts are futile. Text-mining can help by automatically reading ticket descriptions and extracting the necessary insights to sort them into three categories:

  • Automatable
  • Requires machine learning
  • Highly cognitive/manual

This analysis should leave you with a prioritized list of incidents to automate and the type of automation best suited for the job.

Planned Activities

Most enterprise-grade IT departments rely on industry-standard tools to manage their infrastructures. Unfortunately, due to factors such as advanced customization, adjustments due to mergers and specific user requirements, managing these systems often requires a significant amount of manual effort, diminishing the overall value.

For instance, despite the widespread adoption of infrastructure and application monitoring tools, support teams are often unable to respond effectively to the logs being generated, either because there are too many of them or because of the many reasons why they are being generated in the first place. As a result, IT leaders are often unclear on how to approach intelligent automation implementation.

In situations such as this, machine learning technology can be “trained’ to identify the reasons behind alerts and then either recommend or autonomously make better decisions on which action to take. This eliminates much of the complexity for the IT team.

Introducing New Applications

Many IT executives fall into the trap of focusing solely on the reduction of manual labor. As a result, they fail to see and achieve the full value potential of intelligent automation. Faster and more accurate delivery of applications requires the development and design of a new operating model, with an emphasis on DevOps and agile.

Reviewing this entire process to gain an understanding of how to make the most use of this new operating model can result in entirely new approaches to work. Intelligent automation can facilitate some of these new ways of working. For instance, automating the testing process will enable applications teams to iterate more quickly. Likewise, developing a self-service model for things like automated server provisioning allows the operations team to become more responsive. The list goes on.

Step 3: Execute your proof of concept

In order to demonstrate the true value and validate your case for intelligent automation, the next critical step is executing a proof of concept. A great place to start with this is incident management. Organizations that have successfully deployed intelligent automation for incident management have been able to achieve substantial cost savings in a relatively short period of time.

Thankfully, there are many different incidents that can quickly and easily be automated to support your proof of concept, including such tasks as password resets and employee onboarding. In its most basic form, a proof of concept requires the following:

  • Collaboration with subject matter experts to identify where automation can best be applied and understand all the steps and systems involved in a particular process or workflow.
  • Careful selection of an intelligent automation platform. Look specifically for products that can be integrated with existing systems and applications and offers pre-packaged, no-code options. (This will enable rapid adoption and time-to-value.)
  • Obtaining necessary IT and overall business approvals with regard to regulatory constraints, security guidelines and access limitations.
  • Ongoing testing and monitoring to capture results and document value

This phase is also an ideal time to consider building stronger internal intelligent automation capabilities; for example, developing a team to spearhead a future automation center of excellence (CoE). This team will ultimately become the foundation and engine that drives all IPA initiatives.

Step 4: Build intelligent automation capabilities to scale

Achieving the full benefits of intelligent automation requires the development and nurturing of certain skills and capabilities, in addition to rolling out an entirely new company-wide culture. This is essential as successful adoption of IPA requires that automation become embedded into the very heart of the organization itself. There are plenty of ways to accomplish this, but generally speaking, companies that have been successful have done the following three things:

Build on success to expand into new areas of IT (and beyond).

Once the basic tasks and workflows have been automated, it’s time to move on to more advanced level-2 and level-3 activities. The IT team should be expanding beyond incidents to begin leveraging the AI and machine learning technologies to assist with things like analytics and decision support. The goal is to eventually roll out intelligent automation to as many routine and complex processes as possible.

Spread the word.

With a strong foundation of capabilities and experience, IT leaders can begin to position themselves as subject matter experts for the rest of the organization. This process involves continued outreach, such as connecting with other leaders across the enterprise to advise them of the specific benefits IPA can have for them. This outreach also provides the opportunity to identify additional areas where automation might be beneficial.

Explore the advanced elements of intelligent automation.

While the majority of organizations have thus far only focused primarily on simple process automation, the future belongs to those with an eye toward artificial intelligence and cognitive learning. These solutions are already making an impact on companies with forward-thinking leaders. The best way to break into this arena is to start working on small AI initiatives. From there, just like basic automation, you can continue to build, expand and grow.

Intelligent automation is maturing rapidly and quickly becoming a core component of the IT landscape. IT professionals who recognize the importance and understand how to develop their automation capabilities have the potential to become respected leaders in the process – a title that will serve them well throughout their careers.

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