Intelligent Automation Radio is the #1 podcast for IT executives seeking insights on the impact and opportunities for innovation that automation is delivering to businesses around the world. Featuring thought leaders in AI, Machine Learning, Orchestration, Security Automation, and the Future of Work.

January 2, 2020    Episodes

Episode #32:  How To Upscale Automation, And Leave Your Competition Behind (Part I)

In today’s episode of Ayehu’s podcast we interview CEO of transformAI & Chair of the IEEE Working Group on Standards in Intelligent Process Automation

Automation in the enterprise has proven efficient, cost effective, & mature enough that early adopters have begun scaling up their deployments to increase returns & amplify their competitive advantage.  The long-term repercussions of this will likely widen the gap between market leaders & laggards.  In the short term, this expansion will raise questions about the best way to approach sweeping organizational change management for what is proving to be one of the most profound changes organizations & their personnel will ever go through. 

In Part I of this 2-part episode, Lee Coulter, CEO of transformAI joins us to examine the issues surrounding how automation deployments should be upscaled, the value propositions most effective in persuading a CEO to move forward on automation, and which senior executive is best-suited to lead an organization’s intelligent automation initiative. 



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 Lee Coulter, CEO of transformAI and IT services provider that leverages the world’s most sophisticated automation solutions to massively scale their clients’ operations and drive business value. Since automation seems to have crossed the chasm from innovators and early adopters to now being rapidly embraced by mainstream organizations, it seems that the issue of scaling up automation is going to be a hot topic going into 2020.  So with that in mind, we’ve asked Lee to come back onto Intelligent Automation Radio, and share his considerable insights with us on scaling up automation. And Lee is also Chair of the IEEE Working Group on Standards in Intelligent Process Automation. So we’re also wanting to tap into the unique insights about automation that he’s gained from this very important industry role, and how it impacts the digital transformations now sweeping across so many organizations.  This will be part one of a two part podcast we’re publishing with Lee. Lee, welcome to Intelligent Automation Radio.

   Lee Coulter:  Thanks so much, Guy. I really appreciate coming back. It’s great to talk to you as always. 

   Guy Nadivi:  Lee, you co-authored the Global Intelligent Automation Market report for the first half of 2019 which was published by the Shared Services and Outsourcing Network, and there was something you said in the intro to that report that caught my attention. After discussing why it was critical to make an internal commitment to change, you pointed to an interesting example when Jack Welch was CEO of GE, and he decided that not only would his company commit to change by going all in on Six Sigma, but that it would be forever transformational.   And you then write, “The case for change was made and Welch then enrolled thousands of leaders across the enterprise into training and built a new operating methodology to govern tens of thousands of projects across the company. It was based on his belief in the power of math and science to identify both the root cause as well as the solution to problems of any kind.”  Now Six Sigma, I think everybody knows, produces an outsized ROI, but so does implementation of intelligent automation. And as a bonus, automation can also eliminate the potential for human error, for mission critical processes, thus mitigating extremely expensive outages. So Lee, with all that in mind, why do you think more CEOs aren’t taking a cue from Jack Welch and announcing a commitment to enterprise-wide automation? 

   Lee Coulter:  It’s a fantastic contextual question, Guy, and it’s an interesting one. And I think it boils down to one of attention and courage. When Jack was convinced of the power of the application of Six Sigma and its inevitable contribution, he made a big bet on it. It was very courageous. And a case for change was a calculation that said that there was about $6 billion worth of waste across the organization.  And he successfully took that out and a little bit more over the course of five years. Intelligent automation is similarly poised, I think we can say successfully that it’s been proven. The technology works, automation stitches together our systems of record and vastly enables the work of our modern digital enterprises today.  So I think that, and I’ll acknowledge that the Gartner adoption curve remains unchanged as long as I’ve been around and I don’t anticipate we’re going to see it change much where you have the innovators and early adopters and early majority and then the late majority and finally the laggards.  And I think that we’re standing in the early majority and so there are organizations that are being deliberate now. The big conversation, to your point, is about scaling. So now we’ve done enough tinkering and we know we’ve thrown some simple, some medium, some hard use cases at the stuff. We’re now able to engage with some unstructured data and do some other pretty clever things.  And it’s now making its way to the CEO’s chair. Intelligent automation typically has a penetration point somewhere in the organization. It’s more often horizontal, meaning it comes in through a function. So supply chains, finance, HR, order to cash, call center, someplace in one of these processes is a typical entry point for intelligent automation. And there’s some spreading, and then it eventually gets to an EVP level of awareness, and finally, it becomes a conversation that is in front of the CEO.  And typically, somebody asks, “What is the total enterprise value? What is the impact that this could have if we made a full blown bet on it.” So I think in a lot of cases, the only CEOs that have been presented with that question and that opportunity are those that are really on the leading edge of the early majority. And this will increasingly become the conversation, whether we call it digital transformation. And I cringe when I use that word the same way I cringe when I have to use the term artificial intelligence. Because the difference between intelligent automation and digital transformation, I wouldn’t know how to describe them.  So I think that the call out here is for CEOs listening or for EVPs that are senior folks that are listening, formulate the question, what is the total enterprise potential and how long would it take you to get there in order to really drive intelligent automation across the enterprise? And keep in mind that the typical three to five years savings potential or G&A, not SG&A but G&A of an enterprise is between 20 and 40% and that’s not my data, that’s data from other analysis. Depends on what industry you’re in.  But every dollar that you take out of G&A is a dollar of net income, and every dollar that you take out of G&A is a dollar you can use to invest into front office activities that change the customer’s experience and then begin to deliver effectiveness gains, which actually drive strategic business value. There’s a lot more to unpack in that, Guy, but I’ll leave it there. 

   Guy Nadivi:  Okay. Now intelligent automation has a lot of value propositions. Cost reduction, error reduction, risk mitigation, et cetera. You just mentioned that intelligent automation is making its way to the CEO’s chair. So Lee, in your experience, which value proposition has been most effective in persuading a CEO to pull a Jack Welch and fully committing to taking the automation plunge? 

   Lee Coulter:  I would say there’s a fairly typical journey map to the way that this comes in. So it comes in and it starts as an efficiency play. So the first question is how much is it going to save me? Right? And the only way you’re going to have that conversation at all is if it’s at least 20% of whatever. If you’re talking to a controller or a CFO or an SVP of supply chain, if you’re going to come in and say, “Hey, I’m going to save you 5%,” it’s not a conversation that’s going to get very far.  But if you’re talking about saving 20% and a typical return on investment for an individual piece of automation is measured in weeks, this is the place where it starts.  And that’s kind of, if you will, the ticket to ride. The table stakes, Guy, is the efficiency piece. There are cases, and I’m familiar with many, but they’re far less common, where intelligent automation started with an opportunity to deliver some sort of an effectiveness gain. So what I mean by that is instead of running purchasing with 40 less people, the objective was to reduce DPO and therefore working capital.  Or instead of reducing the number of contact center agents, the idea was to dramatically improve the quality of the engagement between the agent and the caller by using intelligent automation to perform the mini and micro automations necessary to support that agent during their engagement with the customer. So there are those cases where it starts with effectiveness, but they’re probably nine out of 10, it starts with some sort of savings.  And then once the savings has been proven out, then you take some of that savings, those hours that have been returned to the business and you reinvest them in something that is more strategic in value. That usually takes a year or two before you’re at a point where you’ve got enough hours returned to the business where you’re looking at this and you say, “Wow, without any incremental cost, I could have five or 10 dedicated people working on the next automation use cases that are really strategic in nature.” And that’s when the program begins to really turn a corner and become far more strategic and catch the attention of senior executives. 

   Guy Nadivi:  Lee, the report that you wrote for the Shared Services and Outsourcing Network makes it crystal clear that change management is, “The key differentiator between success and failure,” when it comes to implementing intelligent automation. You also provide very specific recommendations around IT change management, business process change management, and organizational change management. When we last interviewed you a little over a year ago, you emphasized that automation is a business activity, not an IT activity. And that being the case and assuming that a CEO is all in on automation as a driver of digital transformation, who in the C suite would be best suited to lead an organization’s intelligent automation initiative. 

   Lee Coulter:  So Guy, I spent a lot of time on that particular paper and looked back at our own evolution in change management and, as we had been advising customers, the change management required. And it’s interesting, I’ve drawn analogy to the Six Sigma era, the ERP era, the outsourcing of offshoring era. Each of these eras involve what is fundamentally the same activity. Removing an end-to-end piece of work, looking at what can be digitally enabled, optimizing what remains and reimplementing the new work.  And whether you are using your low cost labor from offshore or whether you’re using technology, the work of change management is a business activity. And I use a simple example which usually resonates for people. And that is if you are a frontline operator in an organization and you care about this automation thing and you’ve been reading the newspaper or your feed at all in the last two years, you’re going to automatically assume that there’s going to be cost savings and reductions in labor.  And in the absence of hearing a specific organizational plan that may include re-skilling, up-skilling, that may include taking on new work, higher value work, whatever it might be, you’re going to make up your own story. And so there are aspects of change management that are just true. They’re just the core of human existence and it’s been proven over the last 30 to 50 years as you implement technology and process transformation that you need change management.  So I’ll come back to your question which was who’s in the best position to lead? My general recommendation is that it would be a business lead. So if there is a Chief Operating Officer, I would say that’s probably the best place. In truth, the leadership really needs to come from the CEO for it to be truly effective. because true enterprise scaling means that intelligent automation and the use of digital technologies is truly going to be embraced enterprise-wide.  That’s rarely the case. Typically, again, there’s a penetration point here into a function and there’s a natural progression in which there’s proof in an increasingly large part of the organization, which then motivates other parts of the organization to now embrace automation. Your point that this is not an IT project is something that I’ve said literally hundreds of times.  The use of digital labor, and that’s what intelligent automation turns out to be, it’s literally configurable digital labor, is a business activity. And therefore, the change, the pace of change, all of these things needs to be driven by the business. There are very definite roles, supporting cast roles for audit and controls and for IT and for HR and for other parts of the organization.  But it’s a business activity and if you learn from the lessons of the past, if you look at successful ERP implementation, who did businesses, successful businesses, who did they put in charge of those? They typically chose a senior experienced business leader to be in charge of the ERP implementation. Same thing with continuous improvement.  There was actually a role called Business Quality Lead, which, again, was a business person. So when you put accountability in the business and for business results, it sends the right message and establishes the most predictably accurate structure or correct structure for success in this kind of an effort. 

   Guy Nadivi:  Speaking of senior leadership, you were recently named CEO of transformAI, who I mentioned earlier is an automation service provider whose focus is massively scaling an organization’s intelligent automation operations. Scaling up automation is a hot topic we’re starting to hear about more and more. Does this indicate that the cadence of automation deployments has accelerated to the point that it’s gone mainstream? And if so, Lee, what key characteristics differentiate a successful upscaling from one that is unsuccessful? 

   Lee Coulter:  I think automation was a curiosity, I think, initially. What is this RPA thing? Unattended server-based task automation was … Everything has to start somewhere and that’s where this started and now, when you bring in intelligence services and incredibly sophisticated technologies that we can access via an API, and you can combine attended automation and unattended automation, and you can augment and supplement the way people get their work done and allow them to focus on higher order work.  These are game changers. So we’ve gotten to this point where we as a provider of technologies and services to an organization have reached a point where we know what the key components are for successful scaling. At the same time, the technologies have evolved significantly. I have to tell you, in my role with the IEEE and seeing, just watching over the last four years as the technologies have just advanced in just a remarkable fashion, this is where the game changes.  So we had all of these experiments and these proofs of concepts and we had limited technologies to do that. Now we know what the organizational requirements are, we know what the technological requirements are and we have much greater tooling than we’ve ever had before. And that is why it’s going mainstream.  This this is no longer a “I need to see it proven”. This is more a case of “where should I choose to start”. And those are some of the key characteristics.  Picking the interesting, a couple of data points I’ll share. One is that with very few exceptions, and they’re industrial exceptions. So like BPOs may be an exception to this statement. But in almost no case do intelligent automation programs result in reductions in force. And that’s a very interesting observation.  Another interesting observation in the analysis of stalled programs or failed programs is that a very high correlation, almost a 1.0, I think it was 0.92 or 0.93 correlation between a successful program and one feature is, is there a human being that wears the title of something of automation, right? So are you the VP of Automation, you’re the director of RPA, you’re the SVP of intelligent automation. Somewhere, is there a person that wears the title of being responsible for automation? So if there’s a person, a leader that wears a title, then they will almost certainly have a strategy.  And if they have a strategy, then they have a budget. And if they have a budget, then they have some business outcomes that they’re being held accountable for. And if they have some business outcomes that they’re being held accountable for, then there’s some visible stage on which the achievement or not of those outcomes will become public.  So these characteristics that I just listed out now, it seems maybe counterintuitive, maybe not, but if there’s a VP of automation, then you can assume that VP is going to have a team. That team’s going to have a strategy. There’s going to be a budget, there’s going to be governance, there’s going to be goals and objectives and measures, and there’s going to be some public reconciliation at some point on the enterprise’s investment in all of that in terms of what was achieved.  And so interestingly enough, one of the features or characteristics that differentiates a successful upscaling is literally having somebody in the business who’s accountable for it. Because as I just mentioned, all of those things are connected to that. 

   Guy Nadivi:  This concludes part one of our two part podcast with Lee Coulter, CEO of transformAI and Chair of the IEEE Working Group on Standards in Intelligent Process Automation. Stay tuned for part two as we continue our discussion with Lee on workforce re-skilling and up-skilling, the stall points that can be lethal to scaling automation in an enterprise, and Lee’s predictions for what disruptions we’ll see from intelligent automation over the next few years.   



Lee Coulter

CEO of transformAI & Chair of the IEEE Working Group on Standards in Intelligent Process Automation

Lee Coulter is a globally recognized thought leader and experienced senior executive with expertise in Intelligent Process Automation, disruptive technology, shared services, BPO, change leadership, customer experience (CX) and practical innovation 

Coulter is currently CEO of transformAI, a hypergrowth automation business. Previously, he was founder and CEO of both Ascension’s globally recognized captive BPO subsidiary as well as Agilify, the nation’s largest IA technology agnostic services business. He brings 30+ years experience in executive leadership positions at companies such as General Electric, AON, Kraft Foods, Ascension and transformAI. 

Lee has published more than a hundred papers, podcasts, and blog posts as a thought leader, is a frequent speaker and leads numerous industry bodies such as serving as Chair of the IEEE Working Group on Standards in Intelligent Automation, the Chief Intelligent Automation Officer of the Shared Services and Outsourcing Network (SSON), member Abundance360, founding member of The Conference Board’s Council on Intelligent Automation, and many others. 

Lee can be reached at: 

Email: lee.coulter@transformAI.com

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

Twitter: https://twitter.com/rleecoulter

Quotes

“Intelligent automation typically has a penetration point somewhere in the organization. It's more often horizontal, meaning it comes in through a function. So supply chains, finance, HR, order to cash, call center, someplace in one of these processes is a typical entry point for intelligent automation. And there's some spreading, and then it eventually gets to an EVP level of awareness, and finally, it becomes a conversation that is in front of the CEO.” 

"…once the savings has been proven out, then you take some of that savings, those hours that have been returned to the business and you reinvest them in something that is more strategic in value. That usually takes a year or two before you're at a point where you've got enough hours returned to the business where you're looking at this and you say, "Wow, without any incremental cost, I could have five or 10 dedicated people working on the next automation use cases that are really strategic in nature." And that's when the program begins to really turn a corner and become far more strategic and catch the attention of senior executives." 

“…the Six Sigma era, the ERP era, the outsourcing of offshoring era. Each of these eras involve what is fundamentally the same activity. Removing an end-to-end piece of work, looking at what can be digitally enabled, optimizing what remains and reimplementing the new work.” 

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?

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Disclaimer Note

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