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The Bowdoin Group Launches Podcast Series Featuring Top AI & ML Executives

Posted by Lauren Kendall on August 13, 2020
August 13, 2020 The Bowdoin Group, a Boston-based executive search firm with deep expertise in leadership search and team expansions for companies across the Innovation Economy, announces the launch of a leadership podcast series called “Decoding the Journey: Stories from the Technology C-Suite.” The series is dedicated to sharing the stories of C-Suite leaders in the AI/ML and Data Analytics space.

As executive recruiters with decades of experience working with these technology companies, the goal of the leadership podcast series is to illuminate the journeys that tech executives have taken, sharing lessons and insights on their paths to success. The series will be hosted by Bowdoin’s own Jim Urquhart (Managing Director, FinTech), Paul Manning (Managing Director, Software & Technology), and Rachel Kohn (Principal). Twice a month, listeners will hear from one of our Technology and FinTech practice leaders and their conversations with CXOs from across the Innovation Economy, digging deeper into their leadership experience, their company’s positioning, and how they think about challenges in Artificial Intelligence and Machine Learning today.

In The Bowdoin Group’s first episode, Jim Urquhart speaks with RapidMiner‘s CEO and President, Peter Lee. As RapidMiner’s Chief Executive, Peter is responsible for the strategy and operations of the company and also serves on their Board of Directors. Before joining RapidMiner, Peter advised high growth companies disrupting established markets, such as Attivio, BlogTalkRadio, Ektron, Infomatix, Novus, NOPSEC, Reonomy, and SecurityScoreCard.

Listen to our series premiere below on Spotify, Apple Podcasts, or wherever you stream podcasts:

For more ways to consume this episode, check out the transcript of Episode 01 below:

JIM URQUHART: Hello and welcome to Decoding the Journey, a podcast where you’ll hear more about stories from the technology C-suite straight from the mouths of the leaders who built these companies. AI and ML have moved to the forefront in today’s enterprise software development, intersecting dozens of ecosystems. And as executive recruiters working with these types of companies, we’re always curious to dig deeper into how the leaders got to where they are today. I’m Jim Urquhart, managing director of FinTech here at Bowdoin Group and collectively, along with my colleagues, Paul Manning and Rachel Cohn, we will explore the stories behind these companies, their leaders, and from that perspective, what’s going on in the industry today.

JIM: All right, here we go. This is Jim Urquhart from Bowdoin Group. And we’re set to launch our podcast series Decoding the Journey. With us today, we have Peter Lee. Peter, thank you for being with us, and welcome.

PETER LEE: Thanks, Jim. What a pleasure to join you today on your podcast.

JIM: Awesome. Well, why don’t we—why don’t we dive in. I guess by way of kind of intro, if you don’t mind, maybe tell us a little bit about yourself. Professionally speaking, kind of, you know, what got you to where you are today.

PETER: Sure. So, I’m very blessed, I’ve had an opportunity to be—to have a number of little careers, I think of them. From an entrepreneurial perspective, I’ve had the opportunity to really work with great tier- one investors like Bain Capital, and Goldman Sachs and Intel Capital and was fortunate to start a software company and grow to just under 50 million bucks, and sell that business to a much larger company, TIBCO Software. And then had kind of a second career as kind of moving from a founder- CEO going through product market fit to really running a little over half of a billion dollar publicly-traded software company, and really kind of transitioning my career more into, you know, managing at scale as well. And then here I am, back working with founders again, as the CEO of one of the leading data science and machine learning platforms in the industry. And then in between all that I would manage to be an investment banker with JP Morgan, and a strategy consultant for a short period of time.

JIM: Awesome. Well, I guess sticking with current right, so today, you serve as president, CEO of Rapid Miner, hot AI, ML data science company, based out of the Boston area. Can you give us a little background on the company and you know, kind of where you—where you think the company fits into the market?

PETER: Yeah, we’ve been very fortunate to be widely recognized as one of the foundational brands in data science. That’s what Gartner calls us. Forrester rates us as the only innovator in the leader’s wave. And we’re the largest open source multi-modal data science platform. We have in the range of -—let’s call it just under a million users globally. They’re in over 100 countries. We’re adopted by over 4,000 universities who are teaching the next generation of citizen-data scientists and business analysts on about machine learning. And where we fit in the market is, we’re very, very focused on reinventing enterprise AI, so that anyone has the power to positively shape the future. So, that really speaks to, Jim, about a journey of democratizing data science. It really speaks to a journey about putting people at the center of digital transformation. And we are, you know, super excited about the opportunity and the market in front of us.

JIM: Awesome. And I guess to double click that a bit is that, in some of the ways we talked about, kind of where you guys fit in what you’re trying to do, I can imagine, right, I mean, given where we’re at in the state of technology I mean, going across the whole fortune 500, fortune 1,000 streaming … Tech is available and ready budgets are there. Everyone is at least saying they’re doing something AI-ML-deep learning-related is, yeah, is one of the aspects of Rapid Miner, and, you know, to help some of these firms like—some of them probably are doing it, because they feel they ought to and needed to keep up a competition, but you might not know where to dive in what’s up from down?

PETER: Yeah, what a great question—

JIM: Is it part of it to make it intuitive?

PETER: Yeah. What a great question. So, I think you know, where we fit in that world of opportunity and problems and so forth. We’re very focused, I think, on organizations that are really embracing digital transformation. So, I think, you know, kind of to double click, as you say, you know, what we really look for is enterprises who are very committed to digital transformation. If digital transformation is a key strategic imperative, then you know, typically the senior personas, the C-suite in that organization recognize that they need two things. They need tooling transformation. So, they need to adopt new and modern tools to facilitate that journey. As well as, I think this is the part of your double click that we really feel we differentiate in, they want organizational transformation. There’s a real belief and a desire, kind of like a Confucius like desire, if you will, that “teach me how to fish,” you know, “I want to upskill my people who are doing data visualization.” And, you know, basic analytics. “I really want to adopt advanced analytics, predictive analytics, prescriptive recommendations, so I can have competitive advantage. I don’t want to just know what my business is doing now. I want to take actions to seize opportunities and avoid risks in the future.”

And I think that journey—because it’s a journey, it’s not a destination, right? That journey really requires a partner to travel with, that’s committed, not just “I have the widget that can help you.” But, “I’ve put in place a process.” And, you know, we have something we call Rapid Miner Academy, that we certified thousands of professionals and upskill them to take advantage of machine learning and AI. And that’s been a really exciting part of the client engagement process for us.

JIM: Awesome. Well, so you kind of are leading me into the next question around—kind of engagement and customer adoption and so on. I mean, clearly, the space is getting quite crowded, right? I mean, I think, you know, m-my local coffee shop alleges to be, you know, AI driven in some way shape or form, right. So, whether it’s, you know, reality, or just kind of window dressing, like it creates a lot of, you know, kind of noise in the space. So how do you—knowing that, how do you differentiate? How do you kind of, you know, kind of get an edge in the market with a lot of players doing it?

PETER: Yeah, it’s, um, it’s such a great question. So, I’ve touched one—kind of one—one aspect of the, of the differentiation. I think, we step back, we really think there are five areas that differentiate us.

So, first of all, we have a focus on transformational business impact, measurable ROI. And in fact, you know, on our website, we just published 50 case studies of quantifiable ROI that have been achieved by our clients. And that’s quite different. A lot of the startups in this space, Jim, are focused on I would call them “science fair projects”, or, you know, the development of a technically sound or accurate model. But there’s really very little linkage to deploying a model in production to actually harness business impact. So, the first thing that, you know, I think differentiates us is the way our enterprise posture is framed and the way we kind of approach our clients, we’re well known for religious focus on business impact.

Okay. I think the second part is that we are focused as much on the upskilling of the organization, as we are on the adoption of the widget. You know, we feel very, very strongly that knowing how to use the tool is almost secondary to understanding how to map a business problem. And when you’re drowning in operating data, how do you use techniques, like machine learning, to be able to attack and resolve those business problems? You know.

I think third, we are a visual platform. But we support all different kinds of personas. So, we’re very, very focused on, you know, collaboration, on making sure that experts and novices can contribute to that journey. You know, novices may be novices in machine learning, but they may be deep domain experts, right embedded in the line of business really used to the really close to the use case—

JIM: Right.

PETER: Fourth area for us is that we’re easy to tune, explain, very transparent. We have some really unique capabilities to build complete visual workflows and to expose them as editable processes and that really lets people have a great deal of confidence that, you know, machine learning is such a black box Jim, it’s so hard to have confidence that “this is how I’m going to disrupt my business.” So, we make it easy to understand how the data, what the data shows. And then lastly, where, you know, as I mentioned before, some of our stats, but we are future proof, you know, there’s a very vibrant community and ecosystem of contributors around us. And we’re completely agnostic. So, those—those four or five traits have carried us well, and, you know, we hope that that sustains us into the future.

JIM: That’s awesome. And-the—and that all makes sense, I would imagine to me, because it’s—it’s mean that the price of admission, right to get into this market, right, the barriers to entry have got to be somewhat significant. Even if you have something that’s of worth, right, you’ve got a lot of big, you know, tech and internet platforms that have a ton of data and are building tech around it, you’ve got a lot of cool startups. So, it is tough to kind of gain that edge, obviously, Rapid Miner is at a point in time where you guys have done that, and have kind of certainly established product market fit and are, you know, differentiating? What have you felt like have been the biggest challenges, you know, both from a standpoint of getting in front of customers, as well as formally engaging with them in this market?

PETER: Yeah, those are almost different challenges to right, getting in front of the customer. Um, and really kind of engaging. I’m going to say, to kind of segue from some of the points you made earlier, getting in front of customers is actually not the challenge? As you mentioned, AI and machine learning are on the front page of The Wall Street Journal. So, getting a front is maybe not as hard as the qualification. And really, can you get them engaged? Right.

And so, to the second part of your question, I think there are three challenges that really come up. And I think they’re very consistent, you know, on the first challenge is really expertise. And when you’re dealing with artificial intelligence, when you’re dealing with machine learning, there’s, you know there’s—there’s some little bit of a barrier there to who understands it, you know, who’s going to be capable of engaging, and, you know, you’re already drowning in operating data, how am I going to really trust that my team can take advantage of these techniques? So, I’d say, expertise is kind of one area. And I think we approach it differently than others. Other people will just march their consultants or experts in, we’re very, very focused on the organizations that want us to upskill their people. So, that, you know, —and that they’ll often also have some— but they want more than two or three. Right? So, that’s going to be one barrier.

I think a second barrier that’s very, very common, Jim, in this industry, is data, you know, garbage in, garbage out. And there’s really so much that’s a topic in and of itself that could take several hours, but data, and really helping them understand what are—what’s the state of their data, what are techniques they can use to improve the quality of the data, what other data sources might add value to blend and wrangle into that that’s a second area. And then thirdly, in terms of engaging, I touched on a little bit in our differentiators, but it’s transparency. Just because you have people who understand the model, just because you have data in great shape that can produce a model doesn’t mean people are actually going to adopt the model. So, there’s quite a lot of governance that goes into the enterprise process of taking machine learning models and deploying them in production. And so, those three barriers to entry, if you will, to engagement, are ones that, you know, we consistently see.

JIM: Interesting. So, to your point, it made me think when you say kind of the data aspect I agree with, I mean, we work with a ton of data solution businesses, and so obviously, the blood that makes these things go. So, garbage in garbage out, totally resonates. What do you think about relative to bias? Right? I mean, bias in AI is a big deal. I mean, by—by almost definition, right? I mean, these, these systems are built by humans. So, they’re imperfect. And I think there’s a lot of work to be done around ensuring that there’s true integrity to the data sets, and then the ultimate kind of end result and inside so how do you how does Rapid Miner think about that?

PETER: Yeah, what a huge topic. I mean, that–that is absolutely a very relevant topic. And that’s one that no single vendor can, you know, make a huge dent in and of themselves. That’s got to be an industry-wide approach. There’s a consortium of approaches. So, in terms of our little part of heaven in this regard, we are working—we actually have one of our co-founders leads a dozen strong research team that we’re well known for being one of the select —In fact, that’s how we get started, is being one of the chosen vendors to collaborate on industry sponsored research. So, we are in the process of actually assembling consortia to work through some of these biases that you’ve talked about. We actually have some limited functionality that we’re looking to expand. We have capabilities in our platform today that, for example, can identify in any language, probabilities of whether certain names are male or female. So, we can, you know, already begin to use or see the hope that some tooling can help detect when bias is present.

And, so there’s that’s another theme that we’re—that we’re focused on. And then thirdly, our organization is looking at a number of other different industry-wide efforts to get involved with anti-discriminatory practices, and mentoring and things of that sort. And so, our teams are actually underway right now and figuring out where we can best pledge. So, I think it’s a big topic. It’s an important one, and it’s one that the industry as a whole has to work collaboratively to begin to address.

JIM: I would agree, yeah, that is definitely-there’s a—it takes a village kind of mindset to that—

PETER: No easy answers, no easy answers.

JIM: For sure. Well, I mean, hearing you talk about the business read about Rapid Miner, and I mean, you talk a lot about really bright people and teams and so on. So, you know, another topic would be, you know, given—or I should say, despite how, you know, this era that we’re in have really advanced smart technology and automation. And, you know, we’re leveraging more and more from machines, which is great. But at least for now, right, there still needs to be, you know, a human at the wheel. Right. So, so with that in mind, how do you think about your team building, your talent, your any sort of kind of general philosophy or best practices that have kind of served you well, you know, now and in the past?

PETER: Yeah, you’re talking specifically about team building? Right? Not so much the AI and team building, but just team building as a general? As a general practice?

JIM: Yeah. Thank you for the clarification. Yeah.

PETER: No, I think that, so, you know, we-we think of ourselves—so we use the words coach a lot in our organization. So, yes, I’m the CEO, but I’m more likely to refer to myself as the head coach than the CEO. And I think, you know, the—the notion of coaching is super important. So, I think of the very best teams as really being teams that are united in a common purpose. And, of course, there are different, you know, grades and specialties and all the rest. But, you know, I think of that is, you know, different position coaches. You know, there’s someone with a particular expertise in one area, but ultimately, you know, I’m a big football fan. So, offense, defense, special teams, you know, there’s three different, you know, subsets, but we all work for the common purpose, we all work to win the game and achieve a common goal. So, I think it’s very important—team building, in my mind, you’ve got to get people on board, who recognize that when they come and join a company that’s looking to do fantastic things, they’re going to have to subordinate their individual desires and goals to the overall success of the team. And I think that’s really, probably, the most critical aspect of team building is to get people who want to be part of a high functioning, winning team. You know, there’s many, many others.

But I would say if there’s one message I had, it would really be about a team is much more than the collection of, you know, the individual parts. There’s culture to it. There’s common purpose. There’s really, very strong alignment across team members.

JIM: I don’t, I don’t know where you’re rooting interests are sporting wise but that seems like it’s, you know, right out of the book of (Bill) Belichick—

PETER: Yup. That’s right, you spotted it. There it is. I live in New York, but I’m a through and through Patriots fan.

JIM: Oh, boy. Okay, well, let’s hope that doesn’t get out too widespread, but I respect it. So, let’s talk about kind of the, you know, most of the first half of this year, right, decidedly different than we’ve ever experienced, most of us. So, whether it’s hiring team-building related, really any sort of critical aspect to your business, what have been some of the biggest changes you’ve had to make from, you know, call it mid-March to now?

PETER: Yeah, I, um, what a great question. I mean, there’s so many right? It’s just like which ones you pick? I would say what has really opened my eyes—our team’s eyes is, and we’ve now kind of changed our policy accordingly, is that we have become as effective, if not more effective in having 100% remote workforce. You know, and so, in our business, we are very global. So, we have, you know, R&D teams in Europe, we have field teams in Europe, we happen to be in Germany, Hungary, and in the U.K. We’ve got people scattered across the U.S., we other folks in Spain, Sweden, Norway. And so, we were working somewhat distributed anyways, but we have four principal office locations, Jim. I think we have now really—rather than saying “Geez, when is this going to end, when get back in the office?” You know, “When is it going to happen is it going to be this summer is it going to be in the fall?” We’ve really gone the other direction. And we’ve said, you know, let’s really embrace the situation we’re in, let’s really get behind a “work from anywhere” policy. Let’s have our people start making decisions about where do they want to live? You know, what kind of lifestyle do they want to pursue?

And so, I would say one of the biggest things that’s happened the last six months for us is really embracing and moving towards a “work from anywhere” policy. And now we’re kind of working through the—okay, that doesn’t necessarily mean we’ll get out of an office lease, but it does mean we’re reevaluating what kind of office do we want to have? How often do teams really want to get together in person and you know, under what circumstances? So, that’s really, probably, one of the biggest things that’s changed for us and you know, a little bit about how we’re coping with it.

JIM: That’s awesome. And it sounds like you were, you’re really and well, you should be, you know, kind of proud of that pleasantly surprised at how well that’s, you know, people have kind of adapted to that. And we found it to, you know, kind of internally looking at, looking at that at Bowdoin Group talking to a lot of our clients. I think—I can’t think of any, you know, firm that I know of, you know, limited sample size. Sure. But that hasn’t been as at least as productive working remotely, if not more, right.

But then, you know, questions on the challenge. I’ve become, you know, what is the impact longer term on culture? What about, you know—

PETER: Yeah.

JIM: Yeah, bring new people in onboarding?—

PETER: Yeah.

JIM: So, it’s decidedly more tricky. So, on the flip side of it, what—what have you found to be? You know, most challenging or—

PETER: Yeah, yeah, I mean, and there are quite a few challenges. I think we um-so I think culture you—what a great segue. I think culture is the number one challenge. It’s-it’s, you know, the tools are there for us to work. You know, frankly, a lot of our clients are have really begun to embrace it. But you know, whether it’s reluctantly or forced to do it. But I have been very riveted on you know, we have a great culture radical candor, unvarnished feedback, you know, use the words, whatever words that you’re familiar with, but we’re very informal and collegial. So, we have a culture committee that we’ve established globally, this happened before, you know, COVID. But the woman who chairs that committee reports directly to me, and we have rotated so strongly to a very programmatic, active I—I would say interactive world with our team members around the globe, where we understand that we may be in this environment for the next several years. Right. And so, that’s kind of the mentality, I always say to them, you know, being a former marathon runner, we’re in month, six of a 26 month, you know, run.

So, in that regard, we’ve really done so many things. We’ve now got a schedule and a cadence of, you know, we do virtual, global puzzle rooms, escape rooms, you know. We’re doing—instead of our summer holiday party, there’s a virtual wine tasting with a sommelier. Yeah, we’re shipping the wine out to folks. We’re doing, you know, just a huge variety of virtual collaborative fun team events. We have a monthly and quarterly cadence across the globe. And, you know, we’re mixing in with that and kind of changing up our cadence of other types of things we’ve done like “ask me anything.” And ways in which we can get a lot more familiar with each other in a really fun and informal manner. So, that that’s been a real pleasant surprise, I can tell you, we—that’s been a pleasant surprise. I mean, there’s still no substitute for getting together. But you know, we’re doing the best we can to operate in a virtual environment.

JIM: That’s awesome. So, I was talking to one of our clients the other day, and she was saying that, and she-she started—I think she was six days in the office before they went in to kind of shut down and quarantine mode. So, it’s been a very different than expected experiences as a new executive at this company. And, you know, they like—like, Rapid Miner have some international offices. And, you know, it’s hard enough building relationships internally, when you kind of join at a, you know, a single office, let alone across, you know, different geographies. And her point—kind of a silver lining, for companies that are spread out to begin with is that, you know, imagine the conversations and the ability to kind of really get to know and afford meaningful relationships with people that you might not have otherwise really had a substantive conversation with had we not been in the scenario that we’re in right now. And kind of doing everything—

PETER: Yeah, yeah, that’s right.

JIM: So, there’s some-there’s some upshot to it—

PETER: We found—just on that point—we found that there’s some real advantages, you know, in our former weekly management meetings, and so forth, when we were you know, a lot of the majority of people are headquartered in Boston. And, you know, there’s a tendency, when you have a group of people in one location then others dialing in, that you really feel like, you’re very disconnected. Right? That the priorities to the people who are sitting in the room, the voices, the discussion, and so forth. we found is almost shockingly egalitarian, and balanced, you know, Zoom, or RingCentral, pick your poison, whatever people are using for, for getting together— it creates this extraordinarily level playing field, doesn’t it? Jim, that, you know, and, and we found that, as we collaborate across the pond, that there are no advantages to being in the office, you know, my head of field ops who, um, you know, sits with, you know, some of the team members in Boston, well, the people who are in Europe no longer feel like he’s giving priority to them, over the guys in Europe, you know. So, there’s some real shockingly interesting side effects in the, in the teamwork, you know. Never mind the hours saved, commuting, and, you know, the ability to accommodate what is a huge—hugely different, you know, personal circumstances and family circumstances for every single person.


JIM: Completely. I was actually talking to another startup CEO, I know, in Boston, and she was saying one of the biggest eye openers for her was like the-their first board meeting, via Zoom was, you know, the expectation leading up to that was that—because obviously, as you well know, right, getting people together for board, they’re important, but you’ve got people coming in from all different—you know, you’ve got to travel and it’s just it’s a—it’s a big deal to schedule it all, this was so much more efficient. And, you know, the expectation before this was, it’s probably going to go at least two hours more than it’s set for—they finished this one with a minute to spare and could not have been more efficient in that regard. So, I think there’s some, you know, I think there’s some longer-term takeaways on the efficiency side that I think we-we’ll keep here, regardless of how things start to evolve in the coming months and whatnot.

PETER: Yeah, totally agree. Totally agree.

JIM: So, I guess, you know, we talked a lot about Rapid Miner, we talked a lot about the market and kind of what’s going on in kind of the greater kind of data science and the ML world which is—which has been fantastic. Let’s-let’s talk a little bit about you individually. I mean, you know, you’ve—like you said you’ve done a lot of things. You’ve been a banker, you’ve been a consultant, you’ve been, you know, for a lot of years connected, in some way shape or form, into business, intelligence, analytics, data science, etc. What was initially kind of what was your inspiration? And you know, what keeps you motivated and keeps you locked into the market, this many years later?


PETER: Yeah, I am uh— so it-it’s—so first of all, just as a broad brushstroke, maybe something of using for your listeners is less about the BI and analytics, but more about the venture journey. You know, the entrepreneurial journey. I was raised by kind of a tiger lady, Asian mother, you know, Chinese mother. And she raised me with this one phrase, which is really stuck with me, which is, you know, “Peter, it is always better to be the head of the chicken than the tail of the dragon.” And so, a little bit as constant, kind of as a context for kind of the past 20 years of being involved in you know, startups in the entrepreneurial space, is that whole notion of that head of a chicken, you know, versus, you know, being the number two operating guy in a billion-dollar company.

But I really—what keeps me motivated is, you know, the people really—to be honest with you. The people and the problems that we’re solving. I really love the whole notion of Schumpeterian, Economics, creative destructionism. You know, yes, I have spent quite a bit of time in the analytics field. But I love analytics, as much as I love infrastructure software. And, you know, the ad tech and market tech ecosystems, I think they’re really interesting business problems in lots of different sectors, I’d say a common thread is people banding together to really tackle some humongous issues, some really value creation opportunities, and, you know, kind of overthrowing or disrupting the status quo. And I think that that’s-that’s such a, you know—either you’re in that mindset or you’re not, and there’s nothing wrong, or, with wanting to run a billion-dollar software company, there’s a lot of fun stuff, I’ve been one of the handful of guys to do that. Um, but you know, those are very different challenges. And those are very different opportunities relative to, you know, overthrowing the world order and challenging incumbents and really coming up with a great idea and finding product market fit, and then really going from product market fit to scale. Those are really exciting things. So, that’s been a common thread for me in my career.

JIM: That’s awesome. Well, looking at it from the flip side, what keeps you up at night?

PETER: Oh, there’s quite a lot. There’s-there’s—

JIM: (laughing) Pick your top two or three?

PETER: Yeah, I would say, you know—and it’s kind of funny, because, of course, I work in the predictive analytics business today. But, you know, the number one thing, I think, for me is just the total and utter unpredictability of the environment that we’re going into, you know, and despite my personal intuition, and I think we see certainly very strong signals in our business that things are, I wouldn’t say return to normal, but returning to the new normal and are doing well, and we’re growing and hitting our unit economic targets. But, I think it’s just this this macro-uncertainty, you know, will we ever get a vaccine? You know, when will we be able to kind of enjoy the city in a way that we use to enjoy it? You know, or will we ever? You know, I think those are really the things, those macro-macro things about, you know, what’s the path of this of this virus really mean for the world? And I think, you know, personally, I, I personally believe it’s a couple of years out before we’re, you know, back to some sense of normal, but, um, you know, I hope for the best—I hope fo-I hope, it’s soon—I hope it’s sooner, but I’m prepared for if in fact, it does take an extended period of time.


JIM: I think that’s a smart way to think about it, because likely, they’ll, you know, it’s—it’s proven to be difficult to kind of wrap our arms around it, and, you know, certainly getting control of it, but also the broader impact around different economies. And so, I think that’s probably a sensible view—

PETER: There was a great—there’s a great article, actually, Jim, I think was in The Atlantic, and I read it

about a month and a half ago, give or take, and they interviewed an admiral who, just to your question, who had survived seven years in the Vietnam—Vietnamese war as a prisoner of war, and they talk to him, a little bit in the context of COVID, about, you know, how was he able to persevere and survive and prosper, when so many of his fellow officers and soldiers were, you know, didn-didn’t make it. And he said, you know, the people who were over-optimistic, the people who kept thinking that salvation was just around the corner. They ultimately got beat down by the, by being a prisoner of war. And they were—they were unable to see themselves through and he really talked a little bit about how his mentality was, I don’t know when this is going to turn, but I am determined that I’m going to make it through. And he really talked about having that mindset and that’s really what enabled him to, to really survive for what’s an astounding seven years in prison.

And, you know, I think we don’t need to get to that level of gravitas, you know, in our organization, but certainly when I talk to our team members, I, you know, as a former marathoner, I use the analogy all the time. I think, you know, we’re month six of the 26-month marathon. And so, let’s pace ourselves accordingly. Let’s make sure you’re looking after yourself, take a mental health break, get out, you know, take advantage of the fact you’re working from home. You know, alter your hours, you know, things like that. I think we—we’ve got to be kind to ourselves, we’ve got to be kind to ou-our teammates, and really be as supportive as possible in this crazy environment.

JIM: Well said. I mean, I think the rules of engagement are just are decidedly different now, right? I mean, there’s no, you know—the morning commute going home early to be traffic or because you got to, you know, you’ve got a late meeting or this or that, I mean, it’s, it’s, you know, you kind of you could be unchecked, you could be kind of at your desk at 7 a.m. until 8 p.m. And some days, it feels like just one ongoing, long Zoom call. So, I think that those breaks, that the mental health piece is huge. We’ve been talking a lot about that internally, and making sure that like, obviously, this summer is a lot different than maybe not as grand as summers before it. But, that doesn’t mean you can’t still give yourself a break and a chance to kind of recharge, get outside and, you know, do a little something that’s different to break up the monotony a bit. So I-I completely agree with that. I guess in you know, whether it’s personally or professionally is, on the short term, you know, the for the remainder of this year, you know, call it the next six to 12 months? Is there anything that you’re optimistic about?

PETER: Yeah, I’m actually quite optimistic about the economy, to be to begin with you, I think, as unpredictable as the pandemic is going to be, I just—it’s hard for me to imagine that the world could be less prepared than we were in March. You know, less aware, less invested in ways to mitigate and fight the economic and the health effects of this pandemic. And so, when I think about the future, when I think about the next six months, and recognize that there will certainly be roller coaster events and so forth, it feels to me like the world has rotated from or, you know, swung like a pendulum from being totally unaware, almost ignorantly unaware, completely unprepared, to—there are there’s an emerging global consensus around fiscal stimulus, around policies. There’s multiple approaches for dealing with the health effects. There’s some great experimentation going on around the world. And we can see from the statistics and reporting, what are the tactics that work? And what are the tactics that don’t work in controlling the virus and in boosting economies. And so, I’m a firm believer that the future is better than the past, that we will learn from our mistakes, and that there’s a great opportunity for the world to learn from each other. And I think the future is going to be better, although it will be a roller coaster.

JIM: Yeah, I think that’s right. And again, well said. And, you know, like this is—you know, not to play a game of comparison, because it’s really doesn’t compare to any other, you know—many other past, you know, points in time in our collective history. But I think in, you know, in down markets and challenging times, I think, you know, emerging from those, there have been some of the greatest people and companies that that we’ve seen. So, I think, you know, we all should hopefully, you know, kind of, you know, take stock of that and hope that we can, you know, we can find some of that coming out of this one. But, I-I tend to agree with you.

I guess, kind of as we move toward wrapping this up, it’s been really fun talking with you. What do you think about as kind of the next frontier of AI and ML? Kind of where are we headed in your mind? And, you know, that could be, you know, from the viewpoint of Rapid Miner, it could just be from a higher perch, looking at the looking at the market.

PETER: Yeah, well I touched on it a little bit earlier. But, um, and I said, words like the “democratization of data science” and so forth. But you know, I think—Let me try and lay out a cogent argument for where I’m coming from. And I think it is very clear from our client assignments that most enterprises are quite literally drowning in operating data. They are absolutely besieged. There is a-it—it’s a tsunami of data, you know, let’s use any kind of description that you can that’s excessive or extreme. And so I think, you know, what’s the next frontier? I think that right now, the deployment of advanced analytic techniques like data science techniques, machine learning techniques and so forth, is really the province of a handful of enterprises, if you think about it. And I think the future is that since everyone does have meaningful opportunities to identify predictive patterns and take advantage of them, I think the future for AI and ML is that journey, is that you will see, more and more companies take advantage of the hidden and unexploited opportunities in their own operating data, for driving revenue, cutting costs, avoiding risks. I think we’re going to see that’s going to be a massive, massive trend.

I might be a bit skeptical on some of the more popular incarnations, like, you know, are we going to have self-driving cars? You call me a huge skeptic that that’s something that we are going to see and you know, at scale in the near future. Um, you know, maybe in limited use cases, like trucks on the highways and things of that sort. But I do think the widespread adoption of AI and ML approaches for dealing with, you know, everyday use cases to cut revenue—cut costs, drive revenue, avoid risks. That’s absolutely a big part of the future. So that would be m-my thinking about the next frontier, you’re going to see very, very widespread adoption.

JIM: Yeah, I think I—I concur. I think that’s well said. And, you know, we at Bowdoin work with a number of companies that are trying to apply AI, ML, to, you know, a broad set of call it middle-to-back office use cases from whether it’s financial services, enterprise, you know, you name it. And those are just so critical, right, being on top of, like you said, revenue opportunities, cutting costs, being more operationally efficient, lowering risk being, you know, aware of, you know, current and new legislation, regulatory—I mean, there’s all these operational elements that really can be hugely impacted by this type of technology. So, I think that’s—I think that’s spot on.

So let’s-let’s end on a personal note, let’s get a little bit more into the you know, the inside look of Peter Lee. Tell us your favorite movie, and tell us a little bit about why.

PETER: (laughing) My favorite movie? Boy, that’s going to be a toss-up. Okay, it’s going to be a toss-up. It’s going to be—they’re both westerns—


PETER: Um, one of them would be Butch Cassidy and the Sundance Kid. And on the other one would be the Clint Eastwood classic, The Good, the Bad and the Ugly. And it would be one of those two movies, Jim. And my favorite scenes—so in Butch Cassidy, for those aficionados, who followed the Butch—the Robert Redford, you know, classic. There’s this great scene where, you know, they’ve escaped to Bolivia, and they’re trying to make it on the good side—they’re no longer trying to rob banks, they’re trying to prove themselves as guardians of the money. And they asked the Sundance Kid to just show that he can shoot. And the guy tosses a can, you know, 12, 15 feet in front of the Sundance Kid and says, “Hey, shoot the can.” And he stays still, and he can’t hit the can to save his life. And then the guy turns his back, and is like, “You guys are useless.” And then the Sundance Kid says, “Hey, do you mind if—can I move? You know, can I do my thing? Can I be myself?” The guy says, “Yeah, you want to move, go move.” And then you know, six shots later, the cat is dancing at the end of his pistol.

And so I’ve always had that image of the you know, that and I think it’s a great—you asked me some questions about the team, but, you know, I really have that image of that movie of, you know, to find the best in people to get the best out of people, you got to let them move, you got to let them you know—kind of do their thing, you know. And so, that’s one of my favorite movies. And then of course, Clint Eastwood is you know, just a classic actor and if you’ve seen The Good, the Bad and the Ugly, its-it’s—there’s just so many you know, life lessons in that in that movie, it’s-it’s one of my all-time favorites.

JIM: I love it. That uh I like the uh—you know, giving us another kind of deeper dive into the “why” behind it and that’s great. I think it’s a—you know, we’re dating ourselves a bit here but I—if you’re going to push me on—you talked about Robert Redford, of course, you know, on the other side, you’ve got Paul Newman. You know, push comes to shove I probably have to go with Cool Hand Luke if we’re um—

PETER: Yeah.

JIM: Sticking to that. But, I agree with you. I’m a—I’m a Western fan as well, and you really can’t go wrong. I think growing up the one that sticks with me most in that genre would be The Outlaw Josey Wales, but you really—

PETER: Yes, yes, yes.

JIM: But you really can’t go wrong right with a Clint Eastwood western.

PETER: Right. What a fantastic movie. Yeah.

JIM: Yeah, for sure. Well awesome this—look, thank you for your time. This has been really fun. I’ve enjoyed talking with you. I think some great, you know, some great trinkets about you, some great insights and you know, we hope our listeners will- have a blast listening to it again. We’ve been talking to Peter Lee, president and CEO of Rapid Miner. So, thank you, Peter.

PETER: Okay Jim, all the best to Bowdoin Group. Take care.

JIM: Many thanks. Thank you.

PETER: Yep, bye.

JIM: Thanks for listening to today’s episode of Decoding the Journey here with The Bowdoin Group. Don’t forget to subscribe to unlike our podcasts on Spotify, Apple Podcasts, or wherever you stream. And subscribe to our blog at for the latest episodes when they drop.

Do you know an incredible tech C-Suite leader who has a story to tell? Send Jim Urquhart or Paul Manning an email if you have a suggestion for our next guest on “Decoding the Journey.”

About The Bowdoin Group

Founded in 1994, The Bowdoin Group is an award-winning executive search firm that specializes in leadership and strategic roles, recruitment process outsourcing (RPO) services, and major hiring projects for a wide range of companies, from small firms building out their executive team to larger firms sourcing talent for rapid market expansion. With deep expertise in BioPharma, Digital Health, FinTech, and Software & Technology, Bowdoin is a national leader with the ability to source talent and service companies globally. The company’s service reputation has earned it a ranking in the top 2% of the recruiting industry for client satisfaction year after year. The Bowdoin Group is also active in supporting the local entrepreneurial ecosystem as well as several non-profit causes, including Life Science CaresNEVCAHack.Diversity, and FinTech Sandbox.

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