On this week’s episode of Beyond Consulting, Ken welcomes Mike Sterling, a former Director of Client Impact at SparkBeyond, and founder and current CEO of Quantegy Analytics to discuss how they drive value for middle market companies by blending strategy and advanced analytics solutions.
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 helping our listeners navigate the wide variety of options they have after a career in 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 spent time in consulting and made a career change. The goal is to help our audience understand all the options they have available, and ideally learn from our guests, both in terms of what they did right and things they wish they would have done differently.
Today, we welcome Mike Sterling to the podcast. Mike is the founder and CEO of Quantegy Analytics, a tech-enabled services company that uses advanced quantitative and strategic techniques to help middle market clients drive value for their businesses. Prior to starting Quantegy, Mike was the Director of Client Impact at SparkBeyond, an advanced analytics and technology company, where he led teams of data scientists, data engineers, business strategists, and account executives, serving clients in a wide variety of industries on a wide variety of advanced analytics, data science, and machine learning projects. He oversaw end-to-end advisory and delivery from early ideation through production deployment and business value generation. He also served as a key contributor to the firm’s product development and commercial strategies. Prior to that, Mike led product development for an early-stage ed-tech company and did strategic project work as an independent consultant. Before venturing into the technology though, Mike was a Strategy Consultant for Booz & Company, where we first met in 2006. Mike, welcome to the show.
Mike Sterling: Great to be here. Thanks for having me.
Ken Kanara: Thanks so much for joining. Today I want to jump into a couple of things. I want to go through Quantegy and learn a little about what you’re doing, the company and the value prop and that sort of thing. We can dig into that and then rewind the tape and learn a little bit how you got there, because a lot of our listeners are going to be interested in how you made the switch from consulting to technology, and specifically advanced analytics, because I know that’s a hot topic right now. Maybe we could start off by learning a bit about Quantegy and what it is you all do.
Mike Sterling: Sure thing. We build analytical systems that put the right information in the hands of decision-makers when they need it and in a way that they can act on it. We really see this as the next generation of business intelligence solutions. This is going well beyond piping data out of databases and into dashboards, which is useful, but doesn’t always lead to clear answers or actions and sometimes even leads decision-makers to the wrong conclusions and counterproductive actions. We take a top-down strategic perspective, really getting at, “What is it that an executive or management team trying to accomplish or improve in their organization? What’s the strategy? What are their value-creation levers? What are the right metrics?” We marry that up with a bottom-up quantitative grounding using analytics techniques that cut through the data noise and provide clear, actionable levers and recommendations.
As I mentioned, this is a new paradigm of business intelligence. Two dimensions along which it extends that business intelligence paradigm. First, we put a model of how the business or organization functions at the core of our approach—embedded in the system. This is the logic for how inputs drive outcomes. What are the steps and the mechanics and the dynamics involved in that? We can establish cause and effect relationships and measure them and understand them, which we believe is critical to affecting positive change in a complex organization.
The second dimension that we build up on, the current state of business intelligence tools, is that we infuse advanced analytics right into the system—right in the solution. That means automatically analyzing granular data for patterns, trends, insights, identifying predictors, segments, things that in a turnkey way—things that are inaccessible to a lot of companies that are starting to use business intelligence. If I were to sum it all up, I’d say, borrowing some lingo from industrial technology world, it’s a digital twin of your organization. You get a virtual, digital representation of the system, of your company or your organization, how it works, a live view of how it’s performing, actionable insights that the decision makers can use right in that context. That’s the top-down view.
Ken Kanara: If I’m understanding this right, you’re bringing a look at the KPIs or the business system the same way that financial reporting is done for the finance function. Am I oversimplifying that?
Mike Sterling: I think the comparison to financial reporting is an interesting one. So financial reporting is the de facto management information that most companies have relied on for a long time. What it is, is a snapshot in time—the main financial flows of a business summarized into the income statement, balance sheet, cash flow. Of course, it’s useful, and a necessary thing for accounting purposes, but it lacks a number of dimensions. It lacks the cause and effect. A financial report on a monthly basis will tell you what flowed in that month, but it won’t tell you what drove that flow, which is oftentimes something that happened many months prior in the operations, in the sales org and then something happened in operations. Finally, you get a revenue stream down the chain and the financial report captures some of that, but it breaks it all up in time.
What we do is we take a cause and effect. We map out exactly how does the business actually generate, how do they turn sales leads into opportunities, into customers, into repeat revenue, into a sell-on, into etc., into referrals, which turn into more business, for example, in that kind of business. Mapping out the different levers along the way, the flows and the KPIs. Yes. Very much about the right metrics, the right KPIs along the way. And really how those KPIs interact with one another. I mentioned that example of the sales flow. If something upstream is not performing well, then something downstream may actually be performing well, but it’s impacted by the upstream knock-on effect of a prior step. You’d want to know that as a manager. So that you know where to focus, what needs maybe more resources, more attention, or more focus on improvement. We really are marrying up both the financial flows of the business with the true operations of the business, how different functions and teams and processes work together to drive outcomes, which is revenue and profit and cashflow. It is very much taking a holistic view from the executive perspective.
Ken Kanara: This is what gets me pretty excited about Quantegy because most of our clients are private equity, middle market portfolio companies. Often after an acquisition, the first thing that comes up is there’s some lack of financial reporting or some lack of sophistication with the finance function and just getting some top-level finance reporting is a huge boon to the business. Now, if I double-click that for a second, there’s usually a value creation plan that’s also part of the investment thesis and there’s a number of strategic initiatives that need to happen. If it was a manufacturing company, maybe there’d be a pricing strategy initiative. Maybe there’s some inorganic growth opportunities that have been identified. This, if I’m understanding this correctly, Mike, Quantegy marries up the finance component with the strategic or operational lens, that, Mike, in the case that I’m describing, an investor would have for the business, but replace that investor with a CEO or what have you, is that right?
Mike Sterling: Yes, that’s right. So we’ll take, in that example, we would build off of a value creation plan that is put in place. Oftentimes, let’s say, when an investment is made. And those plans are often a strategic plan. “Hey, here are the three to five main levers that we want to execute in the next couple years.”
What we do is, we say, “Well, let’s be the quantitative grounding against those.” We will map or design a full set of KPIs for the business, especially ones that shed light into the value creation plan progress. The idea is to grow the top line through XYZ initiatives, then we’ll make sure we have the right measurement and monitoring of metrics that give transparency there, as well as the cause and effect drivers of those KPIs. As a management team and as a PEO on operations team, you’d get live KPI metrics, measured, monitored automatically straight from a lot of the raw core, transactional data sources of the business, financial system, ERP, CRM, et cetera. Within a few clicks, you’re actually getting some root cause analysis, also. If some metric is performing well or not performing well, the first question you’re going to ask is, “Why? What happened? What’s the root cause of this?” We actually provide that drill down, tracing back on all the drivers of why a KPI might be off in a particular week or a particular month, and bringing that all in a unified solution.
Ken Kanara: You’re picking this up from a technology and a service point of view. Is that right?
Mike Sterling: Yes, that’s right. The service components, I’d say there’s probably two parts to where we are using service as part of our offering. The first is we are innovating on what we see as gaps in how analytics and business intelligence are done in the field right now. When you’re trying to improve upon something, when you’re trying to innovate, it’s really helpful to do it case-by-case, client-by-client, doing it, let’s say, by hand enough times where you can understand the nuances of the problems and the pain points, and actually test out which parts of that can be productized, start to develop those product components in the flow of real client work and figure out which components of that actually hang together as a good, cohesive, holistic product. We’ve used services to find product-market fit. Maybe later on, we can talk about how this is where the consulting toolkit can actually be a really useful thing for someone trying to find product-market fit, because you can go and do it as a service to start and then understand where the product opportunity is from there.
I’d say, on the innovation side, services first, has been really useful for us to really hone in on what product to build and what different components of it should be there. As a second part, what we’re providing is important information to decision makers of companies or organizations or business units. So getting this right could be the difference between that organization succeeding and not, making the right decision or not, the right investment or the wrong one, or focusing on the right area to improve versus missing the target. Working with clients to make sure that this is all set up right and that accurate information is coming, is aligned with the strategic goals. It’s measuring the right things in the right way and really cutting through that last mile to getting to actionable insights. That is something that we don’t think, in the analytics space, comes right out of the box very easily, especially when the stakes are high. These businesses are complex, so our services are used as a real strategic support for our clients to make sure that this is done right. It is high stakes and fills in some of the gaps, either in terms of bandwidth or skillsets that they may have, and it lets us be on the front lines and see how this solution is helping and where it still has gaps. We use it as a way of also constantly improving our own offering, and that’s really important for the long-term of what we’re doing.
Ken Kanara: That makes a lot of sense, especially since you’re early on. In fact, some of the best software solutions or enterprise solutions I’ve seen out there actually started as a service offering, and then they honed in on what clients needed and then built and productized around that. Now, I know you’re in early days here, but in terms of the clients and customers that you’re seeing so far, what did they look like and what have you been doing for them?
Mike Sterling: We are focused on middle-market companies. This is really anything up to, let’s say, 500 million in revenue or maybe a billion in revenue, and ranging all the way on the lower middle market side of that, a few hundred employees type of scale. Especially organizations that are rich in data, which companies at this scale tend to be actually pretty rich in data—transactional data, the data that lives in their core systems that they know have strategic value and are looking to harness it to better understand aspects of the business or drive increase in visibility, improved performance, great value. We’re working with management teams of those kinds of organizations that are eager to use their data to drive value, maybe have some reporting, some business intelligence dashboards in place, but are looking to take that to the next level and truly get that top-down, cause and effect transparent view of business performance and help that drive best decision making.
Ken Kanara: That’s good. I see why the middle market and, I know that middle market is a very general term, but I get why that size would be a good fit for you. The thing that I’m a little curious about is on the upper end of that, why has this not evolved more than we would think it is? If I look at all the solutions out there, you’ve got Looker, you’ve got a lot of seemingly off the shelf, advanced analytics tools and techniques, why the time lag is what I’m curious about?
Mike Sterling: Well, I’d say, analytics is a business domain in and of itself. It’s just like, let’s say, marketing or digital marketing or sales or operations. There’s a learning curve to analytics and it’s not just the technical side of it—the data infrastructure and the analytical tools, some of which are, sometimes it’s hard to know what’s what, and what’s different from the outside, from a lot of the marketing websites that are out there from these. There’s a lot of great tools, but there’s not necessarily a large body of talent in these companies that know how to use it right out of the gates. There’s a long learning curve. There’s some coding skills.
Beyond the technical side of it, there’s also the technique side. I think this is what often gets overlooked, is that, yeah, you can go learn the tool and there are a lot of great tools that you can go learn and people can go learn, but the technique side of it is harder to learn in a quick way. There’s a lot of pitfalls, years of trial and error, successes and failures in a variety of settings and functions and use cases in industries. Having people who can draw on that kind of experience is pretty key to a successful analytics implementation.
You mentioned some of the tools and there are some great business intelligence tools, but they do require the right skill sets to truly get value from them. We’ve seen a lot of implementations of tools that do extract data and they do provide visibility into data, but there’s still a lot of gaps. It still leaves management with the “Okay, so what?” I’m seeing this, and sometimes, there’s clear actions and sometimes, there’s not. We’re taking that last mile of the “So what?” and trying to productize that. We’re not just showing you what happened in some slices and dices of data, but really why and what to do about it, which is what often gets left to guess work or speculation or is just a skill set that’s harder to cultivate. It takes years of working in this space. There’s some cross domain things that are really useful. You could do a use case in some interest, like bank fraud detection. You’re looking for needles in haystacks. Well, you can take that same set of tools and methods and go and apply them to different needles and different haystacks in different domains. There’s a lot of cross learning, cross pollination there.
So, back to your question, why does the middle market need this? Well, we think it’s a little bit of the technical skills, the experience, the technique. Having learned a lot of these lessons, we can really accelerate the success of an analytics implementation and really help do that last mile of critical thinking and analysis of what to do and what are the actions coming out of the analytics and designing the analytics, such as they provide those things, as turnkey a way as possible.
Ken Kanara: It’s funny that you talked about the techniques, because I threw that word around like I knew what I was talking about, when in reality, I didn’t. This is actually something that I’ve observed just in my own work, talking to candidates. I feel like this is a space where a lot of consultants—we don’t even know what we don’t know. I see folks in one of two camps. One is super deep in data science and having a lot of experience with AI and advanced analytics in general. Then you’ve got folks that are, call them, businesspeople and have a decent understanding of how to run an Excel spreadsheet. But I very rarely see the combination of those two things. Is that something you’ve observed as well?
Mike Sterling: Yes. There are different skillsets and typical career paths probably haven’t brought them together as much, but it’s starting, and we see more of that. I generally agree with that. Each takes years of mastery. Stacking both on top takes years and years of that. But there is more talent coming that can do this. We’re trying to both help by bringing that talent, but also by helping build a set of tools and a system that can help bridge some of that gap, as well.
Ken Kanara: Okay. I want to tie this back to consultant in a minute, but first, and maybe this is how we do it, but could you walk us through maybe a client example or something that you’ve done recently, and the results achieved? I think for our listeners, and myself included, it’s hard for me, and I guess I’m speaking for everybody else now, but it’s hard for me to disentangle, call it advanced analytics and reporting, and then a consulting engagement. It seems almost like you’re merging the two, but again, I’m probably oversimplifying it. Do you think you could walk us through what a recent example would look like?
Mike Sterling: Sure. Part one is usually implementing our primary system, which is, as we were talking about, you work with the management team to really understand the business model. We work with them to map out the right KPIs and metrics. A lot of times they have that in place already. What you’re doing in the system is you actually build the model of how the business works. You lay out the different functions. You lay out the flows and the handoffs between functions and the right metrics for each function.
Now, you essentially have a model of how the business works. “Okay, if we put this many resources upstream into our business development group, then we expect this amount of sales leads coming down the pipe and we need to resource our sales team at this level and manage to this conversion rate and land this many deals of this much size and onboard those clients within this much time, and retain clients at this level, or sell repeat work,” or whatever. Depending on the business model, of course these things will look differently, but we lay that out. It’s essentially that digital twin view of the business. Then we connect into the data sources that will give live views of those metrics, working from the most critical place first, and then expanding out. Now you basically have a system that is monitoring business performance. As part of that modeling, we also work with the team to put in place a plan—how do we project out the next year to go or the next few years? Now you’re working against the plan and what the system will do is actually monitor how performance is actually progressing against that plan and automatically doing the root-cause analysis for where things are off.
On top, the advanced analytics is constantly scanning the granular data for changes, patterns, places where, let’s say, a conversion rate is not performing as well as it should, and allows the organization to run experiments. “Hey, if we try this split tests, AB tests and measures, is the underpinning quantitative layer that is measuring, monitoring and managing…,” all of that. That’s a typical client engagement: set the KPI, set the management, the monitoring of them up and then implement the right auto-analytics, advanced analytics modules, depending on the metric. If your metric is a retention rate, let’s say customer retention rate. There’s a certain set of modules that are relevant for retention rate that we’ll put in place. So those are monitoring cohorts and finding predictors of churn, finding segments that perform better otherwise. Those kinds of modules would be put in place for that kind of metric. This is implemented in quick sprints, so we’ll tackle one piece at a time and knock out the whole thing rather quickly, connecting each data set—each data source, I should say, at a time. Sometimes within days, and if not, certainly within a few weeks, management is getting increasing visibility into the business from a top-down perspective. They are gaining the ability to basically get a pulse check on everything on a daily or weekly basis, depending on the velocity of the business. So, very quickly, they’re starting to get a view of things in a new light that is usually pretty impressive.
Ken Kanara: This is really cool. It’s funny, you keep using the word “system.” I can’t help but think that you’re almost thinking of the business itself as a system, as the convergence of call it… at least it feels like to me, again, a lay person, it feels to me like the convergence of finance KPIs or operational metrics and consulting. I feel like, without that upfront piece where you’re working with the management team to approach things from a top-down, it feels like…let’s put it this way, it feels like a missing link if you try to approach it from a purely technical or purely from a consulting point of view where you just go in, super narrow, focus on one thing, solve a problem at a particular point in time, come up with an output. Then it’s not a living thing. Whereas, this feels very living, I guess, is how I’m picking it up.
Mike Sterling: I completely agree. Coming at it from a tech, “our product first” perspective, there’s usually a strategic nuance or there’s usually the strategic angle that is super important that getting that right, and no two companies are alike. No two companies’ strategies are alike. Really understanding and measuring the right things in the right ways that actually is giving meaningful, accurate, and actionable outcomes or outputs to leaders is super important. We don’t take that lightly. It is really a blend of a consulting kind of project, but the output of that, like you mentioned, is a living, breathing system that continues to give insight and value over time. And again, against a plan, against a one year, two year plan, like a value creation plan, let’s say, that a company is undertaking.
Absolutely, it’s kind of that hybrid ground. We see it as the best of both worlds. You get the scalability and the automation from the technology side that can live on, but you also get us making sure it’s right, and that it’s useful and it’s actionable for leadership, then actually solving and shedding light into their most critical business challenges and opportunities from the consulting side of it, especially the upfront piece, but also as an ongoing support, as well.
Ken Kanara: That’s awesome. Let’s talk about that a little bit, the consulting angle. Before Quantegy, as I understand, you did two things, right? Well, I know you did consulting because that’s where we met, but then you also did a stint in product, as well. Talk to me a bit about how consulting prepared you for this, and we’ve already talked a little about where it has its tentacles into what you’re doing at Quantegy, but I’m really curious how consulting prepared you for this.
Mike Sterling: I consider consulting to be one of the key ingredients to this recipe, especially the top-down analysis of a business, distilling the complexity, which, these organizations are hundreds of people, or even a few thousand people in an organization. The complexity there is just mind boggling, The people, processes, handoffs, teams, subteams, all these little micro initiatives, all these small forces at play all throughout the business. For management, there’s so much complexity to that and opaqueness. What consulting helps with is, “How do you distill that down into the core things that matter most to the business, conceptually and quantitatively?”
As consultants, we try to get our hands on data sets and things and try to analyze quantitatively, as best as possible. The thing about consulting that was critical to all this and is critical to this recipe too, is the people side of the business—getting to know the people and the organizational dynamics, all of the ideas and motivations and all the little things that are happening out there every day. All that nuance that you actually don’t get from the quantitative representation of the business are so critical to something like this. In consulting, that is a core part of the job and the skill set that forms a bedrock for all that, so that’s not to be overlooked. I think that coming in purely tech product, quantitative data numbers is all well and good, but there’s absolutely the human side. Organizations are people—groups of people—and understanding that element, that aspect to this, and how the quantitative side can help shed light into some of the qualitative people side. I think they do complement each other, but consulting is being there with the people, working on the problems day-to-day and rolling up your sleeves. So that was, like I said, definitely a core foundation to this venture for me.
Ken Kanara: That makes a lot of sense. So you made a pivot though, right after consulting. You went into, first, it was product and then advanced analytics. Talk to us a bit about how you made that pivot and why?
Mike Sterling: I have always had a technical itch, I guess. I mean, I was an engineer and an undergrad and I’ve always been a quantitative thinker, in a way. So I think I had a technical itch to scratch. And at the time, there was this new emerging field of AI and machine learning was coming about, which was starting to get some traction. I was very curious about it. More than anything, out of curiosity, just as a hobby, I started dabbling in that space. Going back to my roots a little in tech, I started dabbling with brushing off my coding skills a few years ago and started dabbling into data science and the technical tools that are available there.
For me, I just let my curiosity take me to different directions, some were seemingly random and probably useless, but still, maybe interesting. I realized, “Well, maybe there’s an itch, there’s something here I’m gravitating towards naturally. So let me follow that instinct and look.” What I found was that there’s a lot of tech companies or tech products and things that really also need people with a consulting background. The lens we bring to stuff, our structured approach, our whatever it is, the whole toolkit that we get trained on over the years of consulting. That was a natural way of pivoting, but still being able to leverage the many years of consulting background that I had.
For me, it was following my curiosity, just really dabbling, is one way to get into it. I started reading a lot of stuff, playing around with some coding, doing some side projects, building some things, simple at first. Then just building up the skills and finding roles that would actually take me deeper into that specialization at companies that were small enough, where the general consulting business skillset was still really relevant, because we were building a business as much as we were building a product. It definitely was a pivot over the span of a few years, and I ended up going deeper and deeper into a specialization.
Ken Kanara: It’s funny, we’ve known each other. One of my favorite parts about doing this show is even with people that I know already, I learn something that I completely didn’t know before the actual podcast recording. For those of you that don’t know, Mike and I have been friends, but one of the things that I wanted to do at ECA is to build a tech platform for our clients. I came to Mike and I said, “I don’t know what the hell I’m doing, man. What should I do?” He actually gave me the same advice, which was “You just need to immerse yourself in this stuff.” What I did, actually having listened to Mike, say a year and a half ago, is I just went down a YouTube rabbit hole. I started reading a bunch of stuff. Then I found myself taking a product manager course. Hundreds and hundreds of hours of independent nerdery later, I can now confidently say I have the ability to build technology product, which is really cool, but actually it wasn’t until this conversation, Mike, that I put that together, that your advice of just what did you say, “dabbling” or whatever? It makes a ton of sense. If you want to learn about something, if you want to make a career pivot, you can’t just, “Okay, I’m going to go do this,” right? You have to immerse yourself in it. That’s, for me, I guess, a pretty big takeaway.
Mike Sterling: I agree. There is a way to find a hybrid role, where you’re still relying heavily on a general business skillset or your consulting skills and you’re getting exposure to a new domain, product or software development or analytics or something that. That’s maybe a way of dabbling on the job, I suppose. Oftentimes, you get swept into the day-to-day and it actually can be harder to carve the time to do the, like you said, the off-line nerdery of getting your hands dirty with some projects.
On that note, I’m trying to think of the right analogy for this, but the at the beginning, when you’re trying to get into a new thing, trying to learn a new technical skill or a new whatever, the hill in the beginning is pretty steep. You get burned out every so often and you need to take a rest, but there is some point where you reach that plateau where the hill flattens out and you can run faster and then that part is really fun. I mean, hopefully the whole thing is fun, but I recognize it can be frustrating along the way, but man. When you hit that plateau, then it’s a long run towards mastery and that’s the really fun part where you’re able to take advantage of everything that’s out there and connect a lot of dots and build and actually connect that domain or that skillset with other things. That’s where cool synergies and things happen, but you do have to get up the hill first. I would say, if someone’s just starting out, have a little patience and get up that hill. When you get to the plateau, then you can look over their horizon, to continue the analogy well past where it should be continued, but you get where I’m going with that.
Ken Kanara: No, I totally get it. I mean, there’s a steep learning curve to anything, right? That’s exactly what it is. It is steep, but the curve can’t be steep infinitely, and once you get over a bit of a tipping point, I completely agree. Then your eyes are open to all these things. You didn’t know what you didn’t know, right? The unknown unknowns.
On that same line of thinking, we’ve talked to a lot of folks that are interested in maybe joining a very enterprise tech or technical business, or maybe starting a technical business, doing something with product or solutions beyond geeking out. Any other advice that you have for folks that don’t have the technical background, maybe, that you had to get started out, again, just beyond geeking out? Anything else you would advise, because we do talk to a lot of folks that are interested in making that transition?
Mike Sterling: I think there are a lot of roles in tech and product that aren’t technical, so it doesn’t need to be a barrier. I think, as I said before, being able to come in and have a good well-rounded view of how to create value for customers, stakeholders, whoever it might be in the role, that is actually a really important complement to the technical skills that technical people may bring. Without it, you can build things that are interesting and maybe are technically impressive, but aren’t actually driving or creating value for the customer or internal stakeholder or whatever.
That can be your value add on a team, that you are the one bringing the “Hey, let’s keep our eye on the value creation here. How is what we’re going to build going to be used and how is that going to solve problems and create value? How does each feature that we’re proposing do the same?” Sometimes, it’s almost nice to have someone who’s not super technical, not super close to that, with that lens of, “Is this the right thing? Can we quantify it? Can we talk to the right people? Can we draw on the right information to make the right decisions?”
There are those hybrid roles where you’re interacting with the technical people or product people, but you’re bringing that business lens, which is super important, always, unless you’re solving some really technical problem. Then I suppose less so, but most of the products being built are there to solve, create value in some market. That’s a hybrid way. Find those roles. We were talking about earlier, in enterprise software and enterprise tech and analytics, there’s also a lot of client-facing roles, implementing, doing some of the services strategy work around it, implementing things, working with clients, being a solutions specialist, even if you’re not as technical. There are a lot of those roles that require you to sit at the client-facing edge. Those are good places also to start to dabble in products. Maybe you serve in that role, but you plug into a product group or you are a business input to the product team and you can get in the mix that way.
So there’s those roles. But there’s also a lot of resources out there, you mentioned the YouTube wormhole, rabbit hole, whatever, there’s a lot of stuff out there. It can be a little daunting, but if you’re interested in something, usually there’s some good resources that are a few clicks away. You can just start diving in and do some reading and research, as well. There’s really nothing stopping anyone from learning stuff these days for the most part.
Ken Kanara: What I take away, and sorry because I asked the same question twice, maybe because I wanted an expanded answer, but what I took away from that is, on your own, you can obviously do a lot of independent research and get into it that way. There’s a lot of self-paced learning out there. Then the second thing is, from a career perspective, you could find a role where maybe you’re the driver of something that is very business-oriented, but you’re sitting in the passenger seat on something that is more technical.
There are a lot of roles out there that address both things. So we see it a lot in customer success or non-technical product management roles, stuff that, where, again, by being the passenger, through osmosis, you’re going to learn a ton. On the first point, Mike, we always ask our guests what book recommendations that they might have because we’re slowly building a library on Beyond Consulting. And just wanted to see if you have any book recommendations for our guests.
Mike Sterling: I’ll throw in a recommendation that has nothing to do with what we talked about today or theme of the podcast.
Ken Kanara: But it is PG though, right?
Mike Sterling: It’s been a few years since I read it, so I don’t know for sure, exactly if all of it is PG, but it’s nonfiction. I’ll just go ahead. Really anything by David Foster Wallace and he writes a lot of nonfiction and he wrote a lot of nonfiction essays. One way to start would be Consider the Lobster. It’s a collection of essays on widely varying topics. If you’ve never read anything by him, be prepared to think, laugh, learn and observe the world through the lens that, somehow, he has this ability to see it through.
Ken Kanara: No, that’s good. Actually, what’s funny is a lot of the folks that we’ve talked to who are really great experts in their domain, and they’ve gotten super deep, but all their book recommendations tend to be completely different very abstract, which I am starting to see a trend, which is neat. If you asked me my book recommendation, it would probably be very boring, but we’ll save that for another episode. Mike, thanks so much for joining us on Beyond Consulting. If we want to learn a little bit more about Quantegy where should we go? How can we get in touch with you?
Mike Sterling: The best place is one our website, it’s quantegy.ai or on LinkedIn. We’re on there, as well. You can find me on LinkedIn, as well.
Ken Kanara: Your LinkedIn name is Mike Sterling, right?
Mike Sterling: Yes, Mike Sterling.
Ken Kanara: S-T-E-R-L-I-N-G. Correct?
Mike Sterling: Yes, and Quantegy should separate me from all the other Mike Sterling’s out there.
Ken Kanara: Okay. Good stuff. Well, everybody, thanks so much for listening this week and be sure to check out our next episode. We’ve got a lot of interesting guests coming up, and if you want to be alerted when we do new episodes, make sure to subscribe, to Beyond Consulting on either Spotify or Apple. And if you’re interested in learning more, check out www.beyondconsulting.info as well as www.eca-partners.com. Until next week. Thanks so much and see you then.
