Beyond Consulting

15: From Consulting to Enterprise AI

On this week’s episode of Beyond Consulting, Ken hosts Dan Calpin, a former Bain consultant, and current President at Hive. Dan joins Ken to discuss all aspects of the business…including technology, sales, and customer success.


The Beyond Consulting Podcast is hosted by Ken Kanara.



Ken Kanara: Hello and welcome to Beyond Consulting, brought to you by ECA Partners, the only podcast dedicated to navigating your career after consulting. I’m Ken Kanara, host of Beyond Consulting and CEO of ECA Partners, a specialized project staffing and executive search firm focused on former management consultants and private equity. Each week I host guests that have successfully transitioned out of consulting and gone onto interesting career paths. This week I’d  to welcome Dan Calpin to the studio. Dan, thanks so much for joining us.


Dan Calpin:  Thanks so much for having me.


Ken Kanara: Dan, maybe we could start with you giving a little background about your career, in general, and then we can dive into your consulting experience and transition to your current role at Hive? Does that work?


Dan Calpin:  Yes, that sounds great. I will go back…probably two chapters as we talk about my career. In the second piece, I’m  moving to Silicon Valley and AI is probably the least expected path for me or people who knew me. On the other hand, my past in consulting was probably far more linear, maybe actually atypically so. It started for me, really literally in my first class of freshman year at USC, where I went to undergrad. Part of that curriculum had a practical component there half of the class was involved in a real world consulting project. I didn’t know what consulting was, but I loved the opportunity to learn about business and help improve it. I pretty much decided from that point forward that consulting was what I thought I wanted to do for a career. As summer came around, the next step was finding an internship in consulting, which, , turns out is not super easy to do as a freshman, but I was persistent. I sent probably 20 cold emails to different consulting firms in Seattle, where I grew up. One of them responded to me and agreed to give me a chance for the summer, which is how I got my start. It was a three person company—four with me, so very small scale, but focused on consulting to businesses with a social mission. During that summer I had the opportunity to do real work that had real impact and generally validated that this was the path that I wanted to go down. That said, I knew I wanted to work on higher profile issues in a larger company, but also knew that wasn’t feasible after my sophomore year. I pulled back the focus. I was fortunate to have an opportunity to intern at Citigroup Smith Barney after my sophomore year in private wealth management.  From that exposure, I really got the experience of being in a larger company with more resources and a corporate environment. I really d that element of the work, though I didn’t necessarily find the work to be as mentally stimulating as consulting, so after my junior year I finally had the opportunity to work in a large consulting firm. I ended up spending my summer at Mercer Consulting in Los Angeles. They, really since freshman year when I learned about the company, had been my dream. When I got an offer to join full time, I accepted on the spot. That was how that journey started. I knew where I wanted to work, or I thought I knew where I wanted to work, and that turned out to be the right answer, but I didn’t exactly have a great sense of what I wanted to work on. I think one of the huge value propositions of consulting is the ability to work across different companies, in different industries, on different problems and from that, understand what I did or didn’t want to focus on in my future. Probably,  many people who started consulting in, my first three years I think I worked across probably ten different cases. Most memorable to me was working in the music industry during the digital disruption. I loved the idea of working in an industry where I was also a consumer. I understood and was passionate about the product and I really d the teams I was working with, both on the main side, as well as the client side. That was the seminal case of my first few years. Then I had the opportunity to go back to business school, I got my MBA at Wharton and took sponsorship from Bain. Two years later I returned to LA as a consultant and, at that point, was able to specialize, probably sooner than is typical. I spent the next several years focused in and around media and entertainment. Through that I had an opportunity to work with some of the most prominent senior executives and some of the highest profile companies in the world on truly industry changing topics, which was really personally fulfilling and mentally stimulating. From that, I was fortunate to have a pretty quick path to partner. I had every intention of continuing a longer career at Bain over the years. I had, over the years, a number of interesting opportunities with clients or others who approached me, but none that had really convinced me to make a move. That’s the linear part of the story…enter Hive, which I can maybe get to next.


Ken Kanara: Excellent. Yes, I do want to learn a bit more about your current role at Hive, but in a different take on things from the normal show format, I want to talk about consulting first.  Dan, you have a really unique story. You went all the way to partner and then transitioned out of consulting, which is a bit unique. Before we do that, I wanted to ask you about the cold outreach that you did in college, as a freshman, to get your first internship. How did you even think to do that?


Dan Calpin: I don’t know exactly why. I guess I’m glad that I did, and it was maybe a good sign of being either overly confident that people would respond to emails, which I’ve probably since been disillusioned by, but it seemed reasonable. I wanted to do consulting and these people have e-mail addresses, so I may as well make that connection. Dumb luck more than anything educated.


Ken Kanara: Well, you’re hitting on a point that I always try to make on the show which is that a job doesn’t have to necessarily be there for you to apply to it, right? You can just reach out to people and you’d be amazed at the people you meet. I always compare it to the Dr. Seuss book, Oh the Places You’ll Go…Oh the People You’ll Meet…if you just try, right? You just have to put yourself out there. That’s awesome that you did that at such a young age. Tell us a bit about Bain—you went on a direct path to partner, you focused on media and entertainment. What  projects did you work on in the media and entertainment industry?


Dan Calpin: I was fortunate that I really had a very wide breadth of different parts of the ecosystem and different problems within it. I mentioned my first exposure was in the music industry going through the digital disruption. We were working with a large radio operator that was essentially starting to face disruption from, at the time, Pandora and others. There was a thought of, “How do you evolve this company into leaning into that disruption instead of running away from it?” I’d say that was very much a true transformation working with the board, the owners, the executive team…really on how  given a company and have a copilot seat at that point, at 22 or 23 years old. That’s where it started. In the post-MBA years, it really touched a lot of other industries. I spent a lot of time in large traditional media companies in lots of different parts of the business—either corporate strategy and the very top level working with the CEO and executive teams on board updates, and otherwise down to business unit strategy in certain areas  ad sales or the launch of streaming products. Then I also got to work in other parts of the ecosystem, including sports leagues, which I’ve always been passionate about, again, as a consumer, so the opportunity to actually be a part of those companies and the decisions that they were making. Those cases really revolved around how they monetize their content, and how they think about licensing versus direct distribution was one of the linchpins of that work. It was really broad spectrum. Then the final piece of this, and this is actually a little bit of the segue to Hive back in 2018, is that I was working with one of the major media companies. One of my teams was focused, at the time, on the ad sales business for this company’s TV networks. Much  the digital disruption in the music industry that started my interest in media and entertainment, now 10 years from the digital disruption were starting to touch television and film. As that was accelerating, that had wide reaching impact across many parts of the ecosystem. The impact that had on our clients in the ad sales business was that they felt the need to transform their sales model in a way more consultative and insights-led approach that would let them bring their clients, not just relationships or associations with the brand of the content,  but actually faster and more granular data that was actually more similar to what clients were getting from digital platforms  Facebook and Google. What they realized was, un Facebook and Google, which owned the platform and so as a result had the ability to bring data on who you’re reaching and how it’s working, that was an opportunity in the traditional space where, based on how television has traditionally been distributed—through cable companies—the programmers themselves actually didn’t have that data. That was one leg of the stool of the industry opportunity and, what I would say, was really starting to be more of the convergence between media and entertainment and technology. Then, similarly and internally within Bain, we have been exploring opportunities to invest in digital products alongside our core consulting services  and looking for ways to extend or expand our relationships with our clients. Fairly opportunistically, I got introduced to the co-founder and CEO of Hive, where I now work, and learned that they started to build some interesting technology that seemed well-suited to solve some of the problems in the industry that I was seeing emerge through our client work. So I pulled back from that and pitched Bain on the idea of digital products business or marketing media use cases with Hive as our launch partner. We ultimately got the support and funding to launch what became known as Bain Media Lab and, really, almost as soon as I was in the partner role at Bain, I transitioned from serving clients into being the GM of this new business and focused on leading a team within Bain, in collaboration with Hive, to build what became Hive’s first application, Mensio, which I’ll talk more about later. About a year into that partnership, I was approached by the cofounder and CEO of Hive to join him and the team in building and leading into the next phase of growth for that company. At that point I had diligenced Hive twice for Bain, once as a partner and then as an investment. I was very bullish on the company and knew from the partnership that I could work well with the team. While I was hesitant to cross sides, I received really, nothing but support from the main system and specifically, the group of senior partners that I work most closely with gave me the courage to make the jump. That was the bridge from the Bain world over to where I am today.


Ken Kanara: That’s a perfect segue, Dan. Tell us a bit more about Hive.


Dan Calpin: Great. Let me start with the elevator pitch on Hive because I think that’ll be a helpful foundation, then we’ll get into how I spend my time now. Hive is an AI company. We provide cloud based AI solutions for what we call, “content understanding.” What this means more tangibly is that our technology enables human- inference on tasks such as understanding what’s happening in a video, what’s present in the image, what’s said in audio, and what’s meant in text. We work with hundreds of customers and those range from some of the largest and best known brands in the world,  Disney, Walmart, Anheuser-Busch, Visa and more, to a diverse set of digital natives where we might actually be the second vendor they on-board after cloud hosting. An example of this would include some of the breakout social apps.  Some of your listeners may have heard of a company called BeReal, which has spent the past several weeks at or near the top of the App Store…so a really diverse set of clients. We work with those in one of two ways. First, is what we call “developer solutions,” and think of these as technical products for technical clients. These have the objective of accelerating the adoption of AI by providing developers access to best-in-class, pre-trained API’s that they can easily integrate into their own applications, which, in simple terms, is outsourcing the development of  widely applicable but technically challenging content-understanding challenges. We have a broad portfolio of these pre-trained models, but one example, just to make this a little bit more real, is our API’s around content moderation use cases. Traditionally, your content moderation across social platforms has been largely reactive and manual, and this has resulted in, well-documented challenges. But in some cases, tens of thousands of employees literally work in warehouses eight hours a day looking at user-reported content. That is harmful for users who get exposed to content that they shouldn’t see. And frankly, for the people who’re doing that work, there’s a lot of trauma because you’re essentially seeing the worst of humanity. So we’ve used technology, and through that, we have been able to help hundreds of social networks and online communities, including well-known platforms  Reddit, to reimagine moderation, to be proactive and comprehensive, where every piece of user-generated content is processed by Hive’s models in real time, and developers on the client side then match our responses to their content rules. That’s an example of the bucket of developer solutions. The second piece is what we call applications. Those are non-technical products for less technical or more analytical clients. These products have the objective of expanding the market for AI-powered solutions in areas where we see an opportunity to reimagine legacy businesses with AI. In this case, we’re actually building the application layer on top of our models ourselves running our models over a massive amount of public content from sources  television, the open web, now, even some of the largest blockchains, and from that, creating proprietary datasets and then subscription-based software on top of that to unlock value for clients. Earlier I mentioned the Bain partnership with Hive and a product called Mensio, that Bain collaborated on with Hive through our partnership to help launch and incubate, and this allows brands, agencies and right holders to reimagine how things  sponsorships and branded content are measured. As viewership moves from traditional, linear television, actually reaching an audience on a platform  Netflix, with no ads, or through a baseball game that now might be across three or four different platforms is actually harder for marketers to do, so more folks are leaning into sponsorship and branded content where your brand actually appears in the content itself through signage, product placement, etc., but that has notoriously been very manual and very hard to measure. That is one example of how we can use AI in a way that is very “point and click” for the users. So that’s  what we do. The company is about five years old. I joined about three years ago—October 2019. Since I joined, we’ve raised two additional rounds of venture capital, so we’ve now raised the little north of $120 million and have about 250 employees. Our US headcounts are concentrated across San Francisco, Seattle and Los Angeles.


Ken Kanara: That’s incredible. So on the first example that you gave, for the more technical products…in theory, someone could be on, instead of user-reported content, not a platform that you mentioned  Reddit, but  Instagram or something, you’re technology is actually able to almost watch that video content without having a human say, “This is bad,” or “This is deplorable,” and go ahead and flag it already, and is the theory that that cuts down on the total  top of the funnel amount that humans actually have to see and make a judgement call on?


Dan Calpin: Yes, that’s exactly right. So there’s two pieces to this. The first is that that level of human  inference or the ability to see an image and understand what’s in it is technically a very hard thing to do. There’s a small set of companies in the world that would have the resources to build that technology themselves. If you think of the full spectrum of digital communities, including a lot of the startups that are just getting started, if you don’t have that ability, your platform will never scale because if you have,  pornography or violence or hate speech or drugs, that’s not going to allow you to scale. So our belief is that actually, that’s something that is important to everybody, but not important for everyone to build themselves. That’s a general utility where we’ve now built models with north of 50 classes, hand-trained on hand-labeled data of more than a billion pieces of data, which is something that no individual company would be able to build and train themselves, but they can plug in and then effectively what they’ll get back are the responses. For a youth-focused or professional-focused platform that might not allow something  a shirtless male, which on Instagram would be completely fine. Developers are less focused on the machine learning, computer vision or deep learning, and more focused about how do they take that response and make it relevant to their community. Essentially, our belief with those products is that we can take those generalizable but technically challenging problems and let folks outsource them so that they can focus on what actually differentiates their product to consumers.


Ken Kanara: Not to totally geek it out here, but just because I find that technology really interesting…is part of the data and inferences that are drawn based on characteristics of the users, as well? It’s not just the image or video, but also data points from specific user types or anything  that?


Dan Calpin: Yes. That’s a great example of, ultimately, what clients can focus on if they don’t have to get to that core content understanding. If you were to think of what Hive is being used for is, we’re not the arbiters of, “This is what content should go on this platform or not,” but what we’re able to say with the high level of precision is, “This has a gun in hand,” or “This has a lot of blood,”  or “This has…” whatever else. If you think of that on the platform side, you can now start to build this user graph…this handle has posted five things with objectionable content in the last two weeks and that can allow you to bring that more holistic view. We’re really very narrowly focused on being able to take that technically challenging problem around content understanding and then let our clients focus on more important, more advanced issues  the one that you mentioned.


Ken Kanara: That’s excellent. Now flipping to the other side of your business, which is the application side, or you mentioned Mensio. It sounds , conversely, on this side…this is more about promoting what is good across multiple platforms. Dan, could you maybe give a real world example, just because I’m not a very sports-savvy guy, but maybe, can you make it more real for us?


Dan Calpin: Sure. I’ll stick with the example of sports sponsorship. If you go back to the legacy of how that work was done, that industry or that measurement has been happening for decades, essentially, as long as there’s been sports and television. Traditionally, it’s been defined, again, by manual processes of analysts or interns….pen, paper, stopwatch…watching a game and saying, “I see the Coca Cola sign and I think I saw it for five seconds.” That obviously has challenges with scalability and consistency, and probably from employee morale because that doesn’t sound  an especially fun way to spend your time. I think AI provides again the opportunity to reimagine that. It’s not just to be able to do what was done before: “I can recognize this logo and how long it was on screen” and do that more consistently and more accurately, but actually unlock a broader scale of measurement. As an example, with Mensio we ingest essentially every second of just about every network of linear television—all national networks and regional sports and our models are running across that content looking at the presence of more than 8000 brands. What you’re actually building is this “always on” database of brand exposure, which isn’t just whistle-to-whistle of first pitch to final out or kick off to final horn, but it’s actually everything, which includes highlights on Sports Center, amplification on news and talk, replays, etc., etc. From that you can both get a more comprehensive view of what your brand is getting exposed through, which lets you measure more returns. If you’re a brand, you can actually attribute more dollars of essentially equivalent media value to the dollars that you invested. If you’re a property you can say, “No, you’re not just getting the in-game exposure, but you’re getting another 20% from highlights. And so therefore this should be priced at a higher level.” Then and then it unlocks different metrics where, typically, you might look at only your brand, whistle-to-whistle in a sample of games because every game you looked at was a linear function. Now you can actually look at things across the landscape, so new metrics  share of voice, where if you look at any of our clients, they could actually look across their competitive set to say, “We actually want a 40% share of voice of this category in  streaming or in baseball” and then be able to actually measure that with a level of confidence. A very similar approach,  but being able to reimagine it with scale, speed and breath.


Ken Kanara: That’s an incredible technology and service that you’re providing on both sides of the different business units you mentioned. Tell us a little about your role and what you’re doing for the company.


Dan Calpin: I joined in 2019 and really, my mandate at the time was to come in and help the founding team grow the business. That takes a bunch of different shapes and sizes, but has really focused on a couple of different areas. One was really building out our applications business. That piece that we just talked about of “How do we take what is best-in-class technology and find ways to get that into more customers, in new markets and new opportunities, etc., etc. Actually, this ties back very well to some of the consulting skill set, which we can get to. But in that case, it was really a cross-functional team where I’ll oversee the product and engineering side, the sales and marketing side, the client success and so much more at the business-unit level. Then the other one, frankly, is complementing our co-founder and CEO in any way that I can to help him grow the business. That’s everything from marketing, as we figure out, “How do we talk about the company?,” and “How do we connect what we do with our customer’s needs?,” talent, and any other way that we can move forward. One of the other areas of focus for us has been, “How do we find the right strategic partners?” Not just investors, who put capital in the company, but actually use strategic partners that can have a role in helping us go to market tied to their brand. That’s been another major area of focus


Ken Kanara: How do you think about growing? For example, the applications business, given that what you describe is inherently a large, complex, highly technical sale?


Dan Calpin: It’s a great question. Actually, a lot of this goes back to some of the skills that were developed in consulting, at least in my perspective. One of the things that I think you do very well in consulting or are forced to do, is really adopt the client perspective. What matters to this client, what will make a difference in their business or in their roles and, ultimately, “What is the problem that you’re solving,” more so than, “What is the product that you’re selling?” That was one of the main areas of focus for us. If you think of that umbrella category of content, understanding that could literally apply to millions of tasks, millions of processes, every industry. For us, we needed to build the discipline of, “What are the opportunities that we actually think are scalable, that we think we can compete in?,” and “How do we strategically place our bets behind areas that we think are the right bets for the company?”


Ken Kanara: How big is customer success as part of what you do? And, let me caveat this with…the reason I ask is because more and more we see former consultants going into either  sales roles where it is exactly  you said…A) It’s more about the problem that the end customer is solving or B) We see them going into customer success roles because this isn’t just about, “We sell the product and now we walk away…” It’s usually about getting things right and optimizing and then showing that value on a long term. So just curious to hear your views, maybe not just on customer success, but also on the sales role in general for your company.


Dan Calpin: For sure. I do think customer success is a very, very important element. You’re probably in a slightly different way than it might be for a typical software company. If you think of most SaaS  businesses,  for the most part, it’s that the product makes sense of what it is and really customer success is, “How do I drive engagement? Retention?,” You’ll be there to help and is much more, I would say, a client relationship-based role, not to take away from that, but I think a lot of it is being able to build trusting relationships, be responsive, etc. When we think of customer success at Hive, we actually don’t call it customer success, but we call it enterprise analytics. And on that team we’ve actually recruited a lot of former consultants to join. Folks from McKinsey, from Deloitte and otherwise. Really, the thought there is, “How do we help tell data-driven stories?,” which is actually very similar to the consulting role, and that fits into a few different buckets for us. If you think of our developer solutions business, and the API side of the world, the reality is, that’s a very low-touch service model once that product is integrated—because it’s a plug in—and it’s the client application and you don’t necessarily need a lot of back and forth other than general health checks, but convincing a client that this is the right solution for them actually is something where curating the right evaluation and communicating that to a client is really important. If you think of one of the core skills of consulting: “How do you take a tremendous amount of data, synthesize it and analyze it in a way that is accurate, robust, etc., but then simplify it in a way that is really easy to understand for someone who’s not on cell Z 7500 of your spreadsheet. For this role it is really, “How do we take these massive data evaluations,” which could be millions or tens of millions of pieces of content across 50 classes, but ultimately, summarize it for a client in a way that helps them understand if this is what they need, if it’s better than what they’re using, etc., etc. That’s  one piece of it. Then the second one is on the application side of our business, which does have a little bit more of a customer success motion. A lot of that customer success isn’t about, “Are they engaging with the platform?,” but, it’s really, “Are they able to make the right insight extractions from the data in the platform. And so it’s a much more value-added level of customer success where that team ,again, can almost be side-by-side with the client, understand how they’re interpreting the data and, help them structure to the analysis that they might be doing on top of it. Again, I think it’s a great example of where the consulting skill set has really complemented  what we what we do as a company.


Ken Kanara:  Are data scientists part of that equation as well?


Dan Calpin: Exactly. We do have, in our core product teams and engineering, more traditional data science. Think of those as in-between, writing the code on the product and you’re ultimately, engaging with the clients. I would say, over the last few quarters, we’ve actually shifted or grown more head count in that enterprise analytics group that is really using consultants as five-tool athletes that can play some of those data science roles, but we do still have your role for that independently as well.


Ken Kanara: Excellent. Well Dan, that’s really interesting—the way you’ve grown the business and the type of talent that you’re using. I want to transition to any advice that you have for folks that are maybe in consulting and thinking about making a transition to tech, a startup environment or a venture capital-backed company. Any advice or thoughts in general?


Dan Calpin: Yes, it’s a good question that’s going to be different for everyone individually. The analogy that I used to use is that I thought of consulting as a highway which was, effectively, the fastest way to advance in a general direction: high speed, no stoplights, etc. At some point, when you know what your destination is you need to get off the highway and get to a specific street address, you need to be careful to not keep driving if you should have gotten off a few exits ago. But, it would be hard to convince me that anyone interested in business who had the opportunity to work at a top management consulting firm shouldn’t take it. I’m very bullish on what consulting can be. When considering when to make the transition, ultimately, there’s probably a few different things I would think about. First, you have to actively commit to being in consulting. This goes in both directions and for me, obviously, I actively committed many times to get to where I was, but the reality is consulting firms have a very thoughtful retention program  such that, if you are performing well there’s always a nearing promotion and an upcoming raise and added responsibility. Given that, it’s easy to get swept up in the tide. I started with a class of about 15 people at Bain Los Angeles out of undergrad and when I left in 2019 I was one of two people remaining. As I would talk to my old classmates over the years, many whom are still close friends, there was always this loaded language around “still being at Bain.” On paper, being a partner at Bain was arguably the hardest to get and maybe most accomplished role of that group, but there was always some feeling that it wasn’t bold, or that the grass is always greener on the other side. I think that in my early years, because I was happy at Bain and had no intention of leaving, I never took calls or responded to emails from headhunters, or explored opportunities for many years. Ultimately, I found that the process of evaluating the few roles that did come my way very clarifying—that I was actively choosing to be at Bain versus any other company. Honestly, probably some of the best career advice I ever received was from, a now very prominent executive in the media industry, who, at one point, I was discussing a role on his team some years back. I was evidently waffling in my conviction on what I wanted to ultimately do and he said in a blunt way, that only he could, something that would be more PG paraphrased as you can’t be on the fence about what you want to do with your career. You’re either fully in where you are or you should leave. At the time the answer for me was being fully in on Bain, but that advice has stuck with me. Something that I think everyone should continue to evaluate is where you are getting you to where you want to be? Are you still learning? Do you feel supported? Can you tie yourself to mentors and do you have a sense of what that end destination is, and is it still north of where you’re driving?


Ken Kanara: I love that, especially around actively committing to being been consulting, if you’re in consulting, because at least for me, and a lot of folks that I talk to that are in consulting is as soon as you get in consulting, you’re already thinking about what’s next. Ironically, that’s the topic of this podcast, but I think one thing I observed, and I actually wrote this down when you were doing your intro, is that it seems that you were really intentional about the projects and the clients that you were working with at Bain. Could you talk a bit about that, or am I incorrect in that assumption?


Dan Calpin: No, I think you’re totally right. If you look through hindsight, I’d say in the other direction, probably one of the really unique elements of consulting is that it’s a field that embraces, frankly probably almost seeks, really smart people who in many cases don’t exactly know what they want to do, but then by design exposes them to you an incredibly diverse set of potential “next careers” through their work with different companies and different industries, on different problems, etc. I think there aren’t many other professions that, if you think of a doctor,  you have to have the conviction—not only that you want to practice medicine, but conviction around specifically what you want to practice for the rest of your life. You then go straight to years of grad school before practicing. Say you become a dentist and it turns out you don’t actually like that. It’s really hard to pivot. You can’t become an optometrist, you can’t become a surgeon, you can’t become an investment banker. Consulting on the other hand basically bundles a series of internships into a cohesive resume item, and along the way you understand what you get energy from and what you want to do more of. Frankly, and equally as importantly,  what you don’t. I was pretty lucky that I got exposure to areas that I was passionate about and then had built a group of mentors who really helped me navigate getting more of those opportunities in the future. I’d say that as I spent longer at Bain and had a sense of what I wanted to do, I was really fortunate in the ability that, if I could write a bucket list of companies that I thought I would want to work with, I actually got to do that with several, if not most. I definitely was able to get to that level of specialization, but it started from essentially throwing darts at the wall and seeing what interested me.


Ken Kanara: Was there anything about consulting where you maybe felt underprepared, given your role now at Hive? I know your path is a little bit different. You dipped your toe in the water before jumping in, but I’m curious to hear your thoughts there.


Dan Calpin: Listen, I believe post-consulting jobs should build on, not rely on, the consulting skill set. Said differently, if you want to do corporate strategy, I don’t think you could convince me that there’s a better place to do that than Bain, McKinsey, BCG, Deloitte, etc. You will work on the most critical issues, have the opportunity to work around multiple influential executive teams, and be coached by a rotation of exceptional business talent that care about you as a person and a professional. I think you leave consulting when you’re ready for the next challenge and the skills and experience that you have gained in consulting opens up new opportunities where you should feel like you’re drinking from the fire hose. For me, that’s exactly what consulting did,  and getting, what was described to me by a close advisor as I was making the decision, as a “once in a lifetime role or opportunity” at Hive, but one that that I would have a ton to learn because it was a step function above what I’ve done before. Just to highlight some of the things that I maybe went through as I ramped up, first of all, I was entering a highly technical company at Bain. Our cofounders were both technical, as was probably  90% of the headcount when I joined, and I have zero background in computer science. I wasn’t  hired to be technical, but I knew that being effective on the business side required a deep understanding of the product and the technology, frankly, as did earning the trust and respect from the rest of the team, where in some ways, I was the outsider or someone who looked different from the prior mold. One of the best skills you learn in consulting, and this is a cheat on the question, is the ability to get up to speed on new industries or new skills quickly. I deployed that from day one. Even though I hadn’t had exposure to anything technical, I knew how to do that and what that playbook looked like. I would watch Stanford CS lectures on YouTube, I would look up every term or acronym that I didn’t understand, I even jumped into the deep end of trying to read code just to understand how things worked. That was a very critical knowledge gap to fill that, again, consulting wasn’t supposed to position me for that. but it was to get me into a world where that was the challenge that I had to tackle. I’d say that the second difference, and this one’s probably more generalizable, regardless of what point someone leaves consulting, is that when you leave into a role like this, it’s much more operational—especially at my level, you have greater autonomy and ownership. In consulting, by definition, you are an advisor. As much, if not more of the time that you spend getting to the answer is actually packaging the answer and working with your clients to drive them to action. At Hive, some of those constraints were relaxed. It was my job to make decisions, and to do so at a faster rate with far less data and analysis than we would have at Bain. What might have been six weeks and 100 slides at a consulting firm, was sometimes condensed down to a few bullets, slack and a quick conversation, but that was really incredibly empowering. It’s probably the part of my role that I appreciate the most, but it’s definitely a different muscle when you come from that conditioning of getting every piece of formatting right, getting every argument anticipated, etc. Finally I would say, not necessarily a gap per se again, but just being in a fast paced startup environment you really realize the opportunity cost of your time. In consulting things are fairly bounded. You have a certain set of objectives, and a certain  number of weeks or months to get those accomplished. In a startup environment  like Hive, really, velocity wins. Not just the speed of how fast you’re going, but how fast you’re going in the right direction. If you can make the right decision two weeks sooner and let us move to the next one and realize those benefits sooner, that’s really impactful for the business. That really forced me to challenge what was probably a perfectionist mentality that I built at Bain of,  “How do you get the top of that asymptote of the productivity curve, one tick higher?” I really realized that many times, done is better than perfect. Test and learn is almost better than the textbook answer.  That was a really important muscle. One final one, just to add to the list. It’s a bit of a non-sequitur, but it’s funny because in consulting, especially out of undergrad, when you’re in your early 20s, but really for most of the time, you’re working with clients that are older and more experienced than you are. I think part of the job, in a way, is to act UN “older” so that you can earn their trust and respect. That paradigm flips now. At Hive and Silicon Valley, I’m in my mid 30s and nearing retirement, it feels. My boss, our CEO, just turned 30. Most of our employees are squarely in their 20s. I actually found the adjustment in the other direction of I needed to make sure that I was actually approachable and that I hadn’t aged out of being relevant. I learned a lot of new emojis and so, the journey continues.


Ken Kanara: That’s something I’m picking up on, just by getting to know you, is that you did your homework. You’re never going to be as technical as your team, but you did your homework and then you’re also making yourself vulnerable and showing people what you can and can’t do. That probably really helps. Your point around the job being much more operational is definitely well taken, and it’s something that we’ve definitely heard before. Excellent. On the theme of advice, we’re all a bunch of nerdy former consultants, so the last thing I guess I’m curious about, Dan, is any recommendations on books that have made an impact on your life.


Dan Calpin:  That’s a good question. I over-index in an attempt to be very broadly aware of current events and industry news. For the most part I probably favor news alerts and articles and podcast to books…the traditional “mile wide and a couple inches deep.” On the podcast side, I now mostly consume content in the tech startup and investing space. My daily or weekly habits…it would be a podcast called, This Week in Startups and the All In podcast, which I think do a great job of  bringing together relevant people in the industry talking about relevant themes. Then, I’ll seek out any long form tech executive or entrepreneurs interviews wherever I can find them. I think the through-lines to books is that I’ve started to consume audiobooks which I seem to do a better job of than getting through print . The last one I read was from Bob Iger, the former Disney CEO. His autobiography, Ride of a Lifetime, which was a great read, both as a  fan of the brand on a consumer and professional level, and I think, just a very iconic leader to be able to get into his mind over the course of decades was really interesting. I’m currently listening to a book called The Founders, which is the story of what’s called the “PayPal Mafia.” It’s a unique constellation of transformative, Silicon Valley executives that includes Elon Musk, Peter Thiel, Reed Hoffman—executives and investors that initially came together starting and growing PayPal, but have since left to create iconic Silicon Valley, and frankly, world companies. This looks at the founding story, how they came together, worked together and that’s my list for now.


Ken Kanara: Excellent. I’m on the same page as you, as far as audio books go. I can’t imagine,  right now, cracking a book open if it’s in an old-fashioned format. Dan, thanks so much. This has been incredibly informative. I’ve really enjoyed having you on the show. For our listeners interested in learning more about Hive, could you share a website or contact information where they might want to do their research?


Dan Calpin:  Absolutely, back to the earlier comment, we are very aggressively hiring across all locations, and especially for consultants. We see huge value in that role. You can see any of our current roles at careers.thehive.AI but if you want to e-mail me directly,  [email protected]  I’m happy to put you in contact with the right people on our team and would love to bring more former consultants into Hive.


Ken Kanara:  Excellent. For those listeners that want to hear past episodes, be sure to check out and make sure you subscribe to the podcast, either on Spotify, Apple or Amazon. Lastly, if you want to get in touch with us directly it’s going to be Until next time , thanks so much and we will talk to you next week.



Connect with Dan on LinkedIn and visit for more information.



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