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April 15, 2020    Episodes

Episode #39: Accelerating Enterprise Digital Transformation Could Be IT’s Best Response To The Coronavirus Pandemic

In today’s episode of Ayehu’s podcast we interview Joe Garber – VP & Global Head of Strategy and Solutions for Micro Focus. 

Worldwide spending on digital transformation services is expected to reach nearly $2 Trillion by 2022.  However, anecdotal evidence suggests the COVID-19 pandemic is accelerating digital transformation initiatives ahead of schedule at many organizations.  This has more than a few IT executives wondering how they can best move faster in the midst of a global health emergency, while contending with the notoriously high failure rates digital transformation projects have become known for. 

In seeking insights & advice, we turn to what may seem to some a bit of a surprising source.  Micro Focus is the company most synonymous with COBOL, a legacy programming language entering its 7th decade of operation.  Yet Joe Garber, its Global Head of Strategy and Solutions, explains why Micro Focus’ primary focal point today is helping enterprises with digital transformation. During our conversation, he provides insights on a number of use cases, one of the most important things to consider when formulating a digital transformation strategy, & what organizations need to fundamentally do right now in response to the changing work reality. 



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 Joe Garber, Global Head of Strategy and Solutions for Micro Focus, a British-based multinational software and IT business with over 10,000 employees worldwide. Those of you who have been around a while in the IT industry, like myself, will certainly be familiar with Micro Focus, which was founded in 1976 just one year after Microsoft. Micro Focus is involved with a number of different technologies these days, all with the goal of helping organizations digitally transform their operations. A market that’s expected to reach almost $2 trillion in worldwide spending by 2022. Since our audience is keenly interested in all things digital transformation, we’ve asked Joe to come on the show and share some insights about the market, in general, and the state of digital transformation in particular. Joe, welcome to Intelligent Automation Radio.

Joe Garber: I appreciate it. Thanks for having me.

Guy Nadivi: Joe, when I think of Micro Focus, I think of COBOL. And that goes back to when I started in technology a few decades ago. And, by the way, lest any of our listeners think COBOL is no longer relevant, according to one consulting firm, COBOL supports close to 90% of Fortune 500 business systems today. It comprises 65% of all active code used today, and it runs 85% of all business transactions. But, COBOL clearly isn’t the only thing Micro Focus does. And I was intrigued to learn that Micro Focus actually touts itself as a vendor that helps organizations seeking to power their own digital transformations. So, can you please tell us a bit about this strategy, and how a vendor so closely associated with the legacy reputation of COBOL is driving digital transformations?

Joe Garber: Well, I’ll be happy to do it. My first response is, you’re absolutely correct. COBOL is a cornerstone of IT for so many companies around the world, and even today, to your point. And the key reason for that is it generally serves as a system of record for some of the most core functions of the business. Companies maintain it’s business critical, which is why we keep helping customers leverage it and innovate around it. If you followed Micro Focus as you have over the last 40 years plus that we’ve been in business, that portion of our company has certainly been with us the longest. And would stand, therefore, to reason that you might think of us like that first. But, it’s also worth noting that a lot has changed in the last several years as Micro Focus has grown precipitously via M&A, and its own organic growth as well.

Joe Garber: In fact, over the past few years, we’ve made about 15 acquisitions, including the software assets from Hewlett Packard Enterprise in 2017. During that time, we’ve built a portfolio of more than 300 product lines, and have been methodically integrating them, and aligning them to where we see the market going. And of course, where we see the market going is in the area of digital transformation as a number of forces have been coming together to force executives to rethink their IT strategies and to look to become more digitally advanced. So, that’s what our customers were demanding of us, and hat’s where we’ve placed our emphasis from an R&D and an M&A perspective. I think that answers your question on the evolution. Let me just tell you just briefly about what I think is the second part of your question.

Joe Garber: That’s, how do we actually help customers transform? As we look closer at digital transformation, what we noted was that there is a common thread in what companies are really trying to do. They want to move faster. They want to have greater agility. They wanted to, and frankly, secure what matters most, and then, leverage insights to drive value. It turns out, those four objectives aligned very closely to four core markets – Enterprise DevOps, Hybrid IT, Security Risk and Governance, and Predictive Analytics. And, that’s really where Micro Focus plays today and what we call the four core pillars of digital transformation. I guess you could say that we’ve evolved or transformed ourselves, if you will, to serve a market opportunity we felt was underserved at that macro level. And, that’s where we’re laser-focused today.

Guy Nadivi: Okay. Speaking of digital transformations, it’s been said, Joe, that the failure rate for digital transformation is as high as 84% inferring, of course, that the success rate is only 16%. So, since this is now your bailiwick, what is your prescription for reversing those numbers?

Joe Garber: I have two parts in my answer to that question. The first is, I think it’s important to look at those statistics through the right lens. Digital transformation is a relatively new term still, and it’s important to understand that this isn’t a one-and-done or a short-term project. Oftentimes, companies are looking at a series of interrelated initiatives over a period of many years to digitally transform. One take away, as you look at those numbers, is probably, it’s still way too early for companies to be celebrating victory at this stage or determining if the overall plan was a success. So, that’s one thought in terms of how organizations can drive the success rate higher. In my mind, the big answer isn’t necessarily tied to, “What? What am I trying to solve,” but instead, “How? How do I go about it?”

Joe Garber: What we’ve seen over the last several years is that many organizations kick off a digital transformation project, and their first thought is that they need to start all over. Their belief is, what they have right now isn’t serving all their needs, and they need to essentially rip and replace everything, and start fresh. And, this will certainly get you bleeding-edge technology, but what organizations often forget about is that they have some core business systems like the COBOLs we talked about earlier, that had been in place for many years, often with IP and processes that have evolved over time that are delivering real value.

Joe Garber: And often, these systems of record can’t be recreated overnight, and especially without degrading ROI or introducing added risk. So, what we’re seeing is a better solution, which is to pursue a modernization strategy where you bring in technology that effectively bridges the old and the new. If you can find open, integrated, backwards-compatible technology, that’ll supplement what you already have, you can effectively run and transform your company at the same time. That’s what we talk about often as, “smart digital transformation.” I believe that’s how we can bring that success rate up.

Guy Nadivi: Okay. Smart digital transformation is creating a lot of demand for data to be fed into smart technologies like machine learning and artificial intelligence systems to make predictions about all kinds of things. This is still viewed as a black art among many people. Could you, please, break down for our audience from a high-level perspective, how putting data into one end of an analytics black box so to speak, and getting predictions coming out the other end drives digital transformation?

Joe Garber: Right. Artificial intelligence and machine learning are talked about quite a bit these days. And to your point, not just as a standalone big data system as they were even in the recent past, that’s still very important. But, in the context of digital transformation, I’ve spent a lot of my career actually talking about advanced analytics in one form of it or another. In fact, I’ve cut my teeth talking about advanced analytics and how it can streamline e-discovery or searching for relevant information for legal matters. I have a lot of depth in what’s called non-typical uses of AI and machine learning.

Joe Garber: And the first thing I’d say is that it’s really not a black box. If you break it down to the fundamentals, it’s really simple, in terms of what’s happening. The organizations need to access their information, understand it, drive efficiencies, and each one of those steps is complicated. Being able to access all of your information, not just part of your information across the enterprise, not just in one repository, not just one geography, as an example. The key part of that process flow, if you will, is the “understand” part. With structured information, typically, obviously, in rows and columns, the challenge is the sheer volume. You need to be able to separate signal from noise, if you will, out of petabytes of information that come in from sensors and IoT devices, and many other things. So, you need technical horsepower to accomplish that. And in many cases, of course, many other things as well.

Joe Garber: And then, with unstructured information, the challenges are a bit different. Here, you have to understand the context to get, what I often talk about, is the “about-ness” of what you’re analyzing. For example, the example I always use is, if I say to you, “I’m thinking of a bridge,” you probably think immediately of a structure over land, over water, or something along those lines. But, if I change the context, and say, “I just had dental work done,” that’s a different example, of course. If I say, “I was playing cards with my grandmother,” it’s a different context. And so, that’s the challenge with unstructured information, and you need to understand your information from both sides, and be able to gather insights, and to drive a top and bottom line. That’s where we start to see the intersection with digital transformation. You’re looking at a top line, you see organizations leveraging data mining to boost and sustain revenue, or chatbots to drive customer engagement, or even applying it to the DevOps world to improve, I should say, test automation.

Joe Garber: And, on the bottom line, the yin and the yang of where AI and machine learning intersect with digital transformation, you see organizations improving quality and delivery with AIOps to reduce event volumes, and get to the root cause sooner. Automating the back office is the case, of course, with RPA. Or even helping manage risk with user entity and behavior analytics, looking for insider threats, abnormal logins, time of work processes, those types of things. You can see that AI & machine learning has widespread benefits to the organization as it’s tightly integrated to digital transformation. In fact, I’d say a robust analytics ecosystem may be one of the most important things you should look for as you start to formulate your digital transformation strategy.

Guy Nadivi: So, let’s drill down a bit on some of the abstracts you referenced with real world examples. Can you talk about some interesting use cases you’ve been involved with at Micro Focus, which highlight the impact that analytics and automation have on your clients’ projects in particular, and digital transformation in general?

Joe Garber: Yeah, absolutely. We have about 40,000 customers around the globe and 6,000 partners and alliances we work with. So, we have a number of really interesting stories to tell about how organizations are leveraging our technology to evolve and digitally transform. I’ll give you a couple of examples. I’ll put it in categories. One way our customers are using our technology is to drive efficiency, as I said. We have a company that’s using our predictive analytics technology as the cornerstone of sustainable farming. They have 120 million acres of geospatial and satellite imagery, and are using our technology to optimize farming resources and maximize their yield. Another is monitoring healthcare worker efficiency by analyzing electronic medical records. And, in fact, they’ve even used this information to model sepsis and save lives, hundreds of lives that they’ve been able to identify at this point.

Joe Garber: And, we have, of course, retail companies, many of them that use us to forecast accurate sales, to track sales, to provide improvements in merchandise allocation and distribution, just as examples there. Another way that our customers are using us is to manage risk with analytics and automation. A big transportation authority uses us to monitor things like bike lanes to keep people safer, and apply tickets to people that are swerving in and out of lanes. And, in fact, they actually use our technology to triangulate data from multiple different sources like video surveillance, and license plate tracking, and even social media feeds to proactively detect terrorist threats. Or, a government agency in the Middle East uses us to monitor devices like pipe leaks to make sure their citizens have access to some basic things and needs that they have like water, which, of course, is especially important in the Middle East.

Joe Garber: In fact, other customers are using our technology to effectively build their products and drive the business. For instance, the biggest broadcaster in Spain uses us to analyze archive programming data and understand what their customer’s interests are, and then, help produce new content faster. So, you can see there are many applications of our analytics and our automation technology that are being applied in many different facets of digital transformation in many interesting ways.

Guy Nadivi: With 40,000 customers, I’m sure you hear lots of different perspectives as feedback. I’m curious, Joe, what do you think are some of the most unrealistic expectations currently plaguing the field of analytics and automation?

Joe Garber: I think the big one is that technology is a panacea. There is much that technology can do for us, but without active human interaction and management, it won’t be as efficient as possible. And again, there’s a reason for this. Humans generally understand context better than technology. We intuitively know something seems wrong based on our experience, and continue to take action to optimize and correct. You see that in terms of process automations. You need to have a human involved in the process often, not always, but often to develop seed sets, and help educate machine learning, and to monitor and tune the technologies that moves along in the process. So that’s one, I think.

Joe Garber: The other is something that I alluded to earlier, and that’s digital transformation isn’t something you can do quickly, and without, and I think this is really important, a long-term commitment from senior management, things tend to fall apart. Again, digital transformation, I should say, isn’t something you can ask a single team to do in a single quarter or a year. It requires a series of interrelated initiatives by a broad set of teams over a long period of time to get it right. If you expect too much too soon, or worse, keep moving the goalpost on what you’re trying to accomplish, you’re bound to realize suboptimal results.

Guy Nadivi: Digital transformation still relies on humans, and humans have fears. On this show, we occasionally talk about robophobia, which is a term 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. Have you experienced much robophobia in the digital transformation projects you’ve been involved in at Micro Focus? And, if so, how did you address that?

Joe Garber: That’s a good question. In some cases, the answer is, “Yes.” At least, at the outset. There are technologies, I mentioned RPA already. There are certainly others that are in use right now that are very clearly replacing the roles of some employees. It’s heartening to hear in many cases, however, is that what you’re seeing these displaced employees having done is they’re being retrained to add value to the company in new and different ways. Generally speaking there, and I think this is important as well, they’re adding to their resume, and they’re becoming even more valuable in the workforce, which ends up paying off for both them and the company in the short and the long term. As an employee, the way you address this is to be open-minded and to not be afraid of change.

Joe Garber: Even in my role, I see colleagues leave the company or struggle when they aren’t able or willing to adapt to new technology. Even if it’s something simple being introduced like collaboration or reporting software. That’s the employee perspective on how to best address that. From an organization perspective, you address this best by clearly defining objectives and laddering up to new technology to those objectives so employees understand why the change is happening. And then, of course, providing training and classes on how to adapt, and a heavy dose of communication to stay in touch with your staff to make sure that that fear doesn’t really take over.

Guy Nadivi: The analytics field is heavily dependent on data scientists. In August of 2018, LinkedIn published a workforce report stating that there was a nationwide deficit of over 150,000 data scientists. How do you think the analytics profession can overcome this staggering talent shortage?

Joe Garber: Well, clearly, you’re seeing supply increases. More people take classes in trade schools on the topic. But, the question is, will that be enough to match what is sure to be even greater demand. At minimum, organizations probably hoping to at least drive down the hourly rate of some of the data scientists that they’re able to command. But, right now, I’d say I’m seeing two ways that software vendors, technology is helping close that skills gap, if you will. The first is the technology itself is helping.

Joe Garber: For instance, you’ve got in-database machine learning that can be used to streamline each stage of the learning process from data preparation to deployment with existing data engineers and database experts that are already familiar with a given language. Then secondly, you have key improvements that are being made from a usability standpoint to help organizations operationalize machine learning at scale. Such as, enabling data engineers to import models that are being built by data scientists and other platforms and languages. And, I find that really encouraging by leveraging technology to scale, it’s possible that any analytics skills gap, perceived or real, won’t be a roadblock to digital transformation.

Guy Nadivi: Joe, for the CIOs, CTOs, and other IT executives listening in, what is the one big must-have piece of advice you’d like them to take away from our discussion with regards to driving digital transformation through analytics and automation?

Joe Garber: The question that I seem to keep getting lately because it’s so topical, and frankly, we’re all living through the same thing right now is, what impact does the current pandemic mean to digital transformation planning and that and… It should have an impact and have no impact at all. And fundamentally, what organizations need to do right now in response to a changing work reality isn’t all that different to what you already needed to know that you needed to do already, and that’s, to move faster, to have greater agility, to secure what matters most, and to leverage insights to drive value. So I’d say, don’t take your eye off that ball. And in fact, our research is telling us that those companies, that are already well down the path, or at least, even starting the path of digital transformation are now responding more quickly and efficiently to the new requirements.

Joe Garber: I just saw a story today from an Austrian engineering company that was told that they, on Friday, that the vast majority of their staff needed to work remotely the following Monday. And they report that they had 95% of their team working virtually with collaboration tools in accordance with GDPR requirements, which is, of course, important, within minutes for example. So, while the framework should remain consistent, both because it’s looking at a longer term horizon, and because it’s applicable to much of what you need to do right now, you should also be conscious that you have new concerns as well. And have those top of mind. The questions that are coming up are, “How do I prepare for additional online traffic?” Or, “How do I pinpoint and resolve issues quickly? How do I get information out quickly to remote workers?” Or, “How do I prepare and stress test for the stress test of my network or not?” Or, “How do I make sure that my employees can get access to the things they need to but not have access to the things that they shouldn’t?”

Joe Garber: Those are all questions that need to be looked at through the context of the framework that you’ve already had put in place, and apply some of these new technologies, and look at the problem holistically so you can solve the problems of today and tomorrow. My big recommendation to those is, stay focused, look at these new requirements again through the lens of digital transformation. And, of course, look for a technology vendor who can support both your immediate and your long-term needs as things evolve.

Guy Nadivi: Alright. Looks like that’s all the time we have for on this episode of Intelligent Automation Radio. Joe, given that Micro Focus is one of the biggest pure-play software companies focused on digital transformation, you’ve really given us all a lot of insights on the direction of the market, and I thank you very much for coming in today and sharing your thoughts with us.

Joe Garber: Well, thank you for having me. I appreciate it very much.

Guy Nadivi: Joe Garber, Global Head of Strategy and Solutions for Micro Focus. Thank you for listening everyone, and remember, don’t hesitate, automate.



Joe Garber 

VP & Global Head of Strategy and Solutions for Micro Focus.

Joe Garber drives strategic efforts to help customers map technology to commercial needs as a vital step toward digital transformation – particularly in the critical areas of hybrid IT, enterprise DevOps, predictive analytics, and security, risk & governance.  Specifically, he works with customers and partners, internal cross-functional teams, and industry thought leaders to recognize and interpret technology trends, and outline strategies to achieve business objectives by bridging existing and emerging technology.

Garber has more than 20 years of experience in the IT industry.  His management background spans both large technology vendors – such as Hewlett Packard Enterprise, HP, IBM, and SGI – as well as startup and emerging vendors.  He holds a Bachelor of Arts degree from Pepperdine University and a Master's of Business Administration (MBA) from Cornell University where he was awarded the prestigious “Park Leadership Fellow” scholarship for demonstrated leadership and academic excellence.

 Joe can be reached at: 

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

Article:               Getting to the “how” of digital transformation 

Article:               The Multi-Faceted Role of Advanced Analytics in Digital Transformation 

Article:               VMblog's Expert Interviews: Micro Focus Talks Unique Approach to Digital Transformation 

Article:              Privacy regs are a boon to business, not a drag 

Quotes

“As we look closer at digital transformation, what we noted was that there is a common thread in what companies are really trying to do. They want to move faster. They want to have greater agility. They wanted to, and frankly, secure what matters most, and then, leverage insights to drive value.” 

“Digital transformation is a relatively new term still, and it's important to understand that this isn't a one-and-done or a short-term project. Oftentimes, companies are looking at a series of interrelated initiatives over a period of many years to digitally transform.” 

"What we've seen over the last several years is that many organizations kick off a digital transformation project, and their first thought is that they need to start all over. Their belief is, what they have right now isn't serving all their needs, and they need to essentially rip and replace everything, and start fresh." 

“…digital transformation isn't something you can do quickly, and without, and I think this is really important, a long-term commitment from senior management, things tend to fall apart. Again, digital transformation, I should say, isn't something you can ask a single team to do in a single quarter or a year. It requires a series of interrelated initiatives by a broad set of teams over a long period of time to get it right. If you expect too much too soon, or worse, keep moving the goalpost on what you're trying to accomplish, you're bound to realize suboptimal results.” 

About Ayehu

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

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Links

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

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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