Under the umbrella of S&P, Rich Karpinski and the 451 Research team are dedicated to delivering real-time analyst insights and consultation for enterprises across IoT, infrastructure, DevOps, and more.
In this episode, Bospar’s Eric Chemi digs into the art and opportunity of GenAI for market intelligence, the evolution of IoT adoption, and the role of analyst investment.
Click To Read Transcript
0:05 I’m Eric Chemi and this is Politely Pushy. Welcome to Politely Pushy. I’m your host, as always, Eric Chemi.
0:11 Today, my guest is Rich Karpinski. He’s the head of all IoT analyst work at 451
0:16 research, which is a which is a division of S&P Global. Lot of work you’re doing, Rich. You know, the the company
0:23 obviously was acquired by S&P many years ago. So, when people look you up on LinkedIn, they see a lot of different
0:28 titles. So, you’re you’re a very busy guy. Tell me just tell me like what are you doing today? I know today we’re
0:34 recording on a Friday in the home office there. What’s on your what’s on your agenda today? Yeah, it’s it’s it’s an interesting day
0:40 and thanks for having me, Eric. Um, so uh doing some some inquiry work, some responses to uh some vendor requests
0:47 around um edge compute on the one hand, around some uh IoT standards on the
0:53 other. Um, also we’ve been doing some internal work, uh, a lot of work around Gen AI, uh, internal tools and such. So,
1:00 I’ve been leading some of that effort and, um, you know, you mentioned 451, we’re we’re a a relatively small group.
1:07 Uh, we’re part of a large organization now, S&P Global. So, we have access to developers and resources that, you know,
1:14 small analyst firms or when we used to be a small analyst firm, we didn’t have. So, we’ve got some developers who are working with us to build some tools for
1:20 our analysts to do their work, some Gen AI tools. And so I’ve been real involved in that. So um been working
1:25 with the developer team today sort of uh building some uh user stories around how
1:30 we use Gen AI, how we build reports and those sorts of things. So that’s like an interesting sort of sidelite kind of
1:36 work from the day-to-day analyst stuff. You know, we’re usually working on you know
1:42 a lot of people who are outside the analyst game, it’s a real black box to
1:48 them, right? It’s how do I get coverage? Is it pay-to-play? What do I need to do? I
1:53 can’t get their attention or I can talk to them and they steal what my knowledge is for their reports but then I don’t
1:59 get anything you know good written about myself right there’s a lot of outside confusion especially small smaller
2:05 companies like you’re doing a lot of IoT a lot of startups in that space and they just have no idea how do I get how do I
2:11 get some traction here yeah yeah I mean I I think you know the way the way to look at it as a as an an
2:18 a vendor right so um there’s different different sorts of analyst firms And there’s different sorts of
2:23 relationships. I mean, I think what what we tend to do here at 451 is try to have really close relationships with with
2:30 clients, right? So, paying clients, quite frankly. So, we’re sort of not an influencer shop. Um, we’re not a
2:36 pay-for-play shop. Um, we’re not even with all respect to Gartner, you know, you got to be on the magic quadrant.
2:42 That’s the thing, right, that AR folks have to think about. Um, we’re very close to our our our clients and and our
2:48 prospects in terms of getting to know them, um, helping them out with what they’re doing, you know, being an
2:53 extension of their firm, whether it’s strategy, whether it’s go to market, whether it’s, um, sales enablement, etc.
3:00 um you know and and as firms try to be lean these days um hopefully they look at us as a partner right rather than
3:06 somebody that’s just trying to take uh uh some as you sort of described it take take some of something that they have uh
3:13 they’re they’re sort of um you know crown jewels and use it for our own good right so we’re definitely trying to
3:19 understand the market uh understand innovation understand understand where things are headed then then we’re trying to help our customers do that as well um
3:26 and again they they they need that in a variety of ways whether it’s you again whether it’s informing their strategy or
3:31 trying to tell their story out to the market we hope we can be a partner for that and I think that’s the way um you
3:36 know a small firm should think about it and I think large firms obviously have a multitude of ways of of working with us
3:42 and are pretty sophisticated in terms of how they view the analyst uh and the analyst role within their world right
3:48 go into that a little more so like they’re sophisticated for how they view the analyst role in the world what like
3:54 just more on that sure I mean I I think you know they uh you know a larger vendor is going to
4:00 have a an experienced AR staff, right? An AR team. Um, many of them will have
4:05 come from the analyst world. Um, so they know the game inside and out. Um, and they’re going to be uh they’ll have
4:12 various ways of working with us. Sometimes they’re more tied to a competitive intelligence group, right? So they’re being a front end and that
4:19 competitive intelligence groups uh is looking for data and information and so they’re frontending into our analyst uh
4:25 our analyst insights, right? Other times they’re fronting uh business units whether they’re sales or marketing or
4:31 product or whatever and those and those groups need um you know need some help from the outside right again whether
4:36 it’s an input into their world whether they want some survey data or some market forecast data etc or whether they
4:42 need some help in telling a story out to the market and out to their customers right um and you know the thing that we
4:48 always tell um our clients is in the way we position ourselves with our clients is this is even more so since we became
4:54 part of S&P which um is very um you know we have parts of our business that are regulated, the ratings business where
5:00 we’re we’re we’re very uh strict uh around um being independent, right? So
5:05 we’re trying to tell an independent um unbiased story out to the market. Um and
5:10 there’s definitely a place for large firms to want to ride along with that kind of story, right? The authority, the
5:16 independence that we can bring and telling a story because, you know, clearly if you’re a vendor and you’re telling a story to a customer, you know,
5:22 you’re trying to sell them something. Everybody knows what the the interaction is, right? So if you can have some independent view to back up uh the the
5:29 way that your product or your service or your or your strategy is is moving in the market, that’s that’s always very
5:34 helpful. So um you know, when we’re dealing with larger vendors, um it’s
5:39 very much a peer-to-peer relationship and that they’re spending money on us and we’re we’re we’re counting on on
5:45 helping them. And um you know uh every all the cards are pretty much on the table. Sometimes it’s easy, sometimes
5:51 it’s hard in both directions, right? But um it’s I think it’s just part of of how the tech world does business right you
5:58 mentioned smarter smaller vendors it’s challenging I think these days especially a lot of startups in the
6:04 world of AI as I mentioned earlier you know uh how to make use of a of an analyst firm it’s it’s not as clear-cut
6:10 maybe as it was once right a lot of companies I talk to that are smaller especially they’re just like
6:16 what am I supposed to even do with analyst you know you’ll ask them like hey what’s your what’s your AR probe like huh what what are you talking
6:22 about. Yeah, it’s a it’s a fair question and I I think there’s a a a degree of, you know, size and maturity to when you even
6:29 need to worry about it, right? Um, if you’re if you’re funded, right, you may be more interested in talking to and you
6:36 may you may need an investor relations type person, right? Um, you may need to be doing some sort of PR to get some
6:41 sort of message out to the market itself, right? I mean there’s different there’s different levels of maturity and
6:47 um you know an analyst firm I think you know comes in um when you reach a certain level of of uh of maturity
6:54 you’re trying to talk to customers your customers are more sophisticated they’ve got more money to spend they’re looking
6:59 for third party validation or a third party story to go alongside the vendor story um and so with smaller vendors
7:06 yeah I I think it’s it’s it’s questionable there was a time back when 451’s early days and so we still try to
7:11 figure this out where the smaller firm would come in, you know, buy buy our service really just to have
7:17 a relationship with an analyst and maybe to be even written about, right, by an analyst firm. I think, you know, that’s
7:22 sort of an old style of of a relationship. Um, you know, today I think it’s much more about um again
7:30 unique insights, market data, forecast, survey data, etc. Things that they um uh
7:37 could generate themselves, but it’s more efficient to work with an analyst firm. Again, you get that third party sort of independent view that they can bring
7:43 into their story. What about for you guys themselves? Right. 451 was a small firm, now it’s
7:49 part of a big firm. You’ve you’ve been there for that change. How has it changed, you know, the business model a
7:55 little bit, right? Because there’s probably much more of a hey, you’re just a division. It’s it’s a P&L focused thing, maybe more. It’s a corporate. You
8:02 gotta you got to make sure you’re you’re kicking in your margin upstairs and it’s not just whatever you guys feel like
8:07 doing. Yeah. We’re we’re um very akin to a tech startup that’s been acquired, right, by by a larger firm.
8:13 Welcome to big corporate. Everyone’s getting a new ID card, right? Yeah, exactly. There’s culture issues. There’s political issues. Um as as I
8:20 mentioned with S&P, you know, this is a regulated firm with a lot of the market data it has. And so we have to march to
8:25 that that step too. And I I think it’s it’s good for us. Um the other thing is there’s just massive opportunities being
8:31 inside a firm like this. Um right now we’re doing a lot of work in 451 around data centers and AI utilities and power
8:39 you know the whole story around you know what’s required of AI data centers and where’s the energy going to come from
8:44 and how are they going to expand and etc. Um and so you know we can tell that from the technology side but we’ve got
8:51 um we’ve got uh data and we’ve got insights within uh 451 about you know the global supply chain of energy right
8:58 we have a a massive uh uh event called Sarah week where is sort of called the
9:03 Davos of the energy sector right big uh thing from Cambridge Energy Research Associates
9:09 exactly and Dan Jurgen’s going to be at our uh a data center event we have a 200 person data center event in DC coming up
9:16 because these worlds are intersecting technology and his world of energy. And so um those kind of opportunities to be
9:22 part of those big platforms, bring our tech vendor partners who have known us for 20-30 years into these environments
9:28 as well is is really really exciting. So um it’s not without challenge to be a smaller group within a large company,
9:34 but those are the kind of opportunities that open up for us and our clients. You know, I’m sure AI is being discussed
9:41 all the time. There’s the AI of what the vendors are doing, but the AI just how are you guys doing your business better
9:46 with AI? Because I I know other analysts that are saying, “Hey, I can use AI now and it’ll go through the data and make
9:51 me a 30-page report.” Boom. Like it’s it’s crazy. I don’t even need a junior analyst for this kind of work.
9:56 Yep. Yeah. And know and um I’ve been at this a while. So a a a few decades ago
10:02 that was offshoring like analyst or journalism work you know like you know
10:07 so that that was always kind of an iffy thing but it was the same idea. Um and it’s the same it’s the same play here to
10:14 some extent I think if you’re not really looking at it in the right way. Um I think the right way to look at it is the
10:20 analyst still has you know so I I I work with a lot of industrial uh firms right who run mana who help uh uh companies
10:27 run manufacturing plants and the and the key area there is as they bring in AI um they don’t want to replace operators you
10:33 know the people who run plants run assembly lines they want to augment them so this idea of human in the loop is
10:38 talked about all the time so there’s all this expertise and capability within that human workforce it’s the same
10:44 around analysts right um you can augment it But it’s still extraordinarily necessary to have a human in the loop of
10:50 this equation. Um, and there’s various reasons why, you know, LLMs tend to hallucinate. Um, they’re only as smart
10:57 as the data they’re trained on. Um, they’re, you know, which means they’ve got a training base, but also the data
11:02 you share with it, right? Um and then you know um as well they um I sort of
11:08 lost track lost track what I saying here but you know to have that human in the loop it you have a point of view that
11:13 you’re that you’re generating from talking to all these companies and that’s still a human process. Maybe at
11:19 some point an AI agent could go out and have all these conversations. It probably wouldn’t be as fun for any of
11:24 us if it was just machines talking to machines. Um but today, you know, we still go out and we talk to people
11:30 within these companies. We talk to enterprises. um and we bring that back in and drive all of our analysis based
11:37 on that broader discerning view of what’s important and what’s not. And that’s still today um a human function,
11:44 right? And we’re also dealing with humans on the other side, right? Our customers uh ultimately are humans. So
11:50 it’s it’s good to have relationships. It’s good to understand what their needs are, where they’re coming from, etc. So in a lot of ways, it’s no different than
11:56 using Google to to do search for for information, right? It’s a lot more efficient. Um but it’s tricky as well.
12:03 So um it’s a lot of art, a lot of opportunity and a lot of sort of
12:08 misinformation both in terms of what you have to deal with but also just how the whole sector views what this means for
12:14 it, right? What’s the number one question that you’re getting right now?
12:22 Um within my practice? Yeah. Like question like questions from Yeah. from like like questions that
12:28 people want research on questions from clients that like hey what like answer this for me what is that yeah yeah I mean a there’s I guess
12:35 there’s two big things is everything’s AI right and so um everything’s about what’s the infrastructure necessary to
12:42 support AI how does AI uh impact um the the the way our customers as vendors do
12:50 their business um how does it impact our service models service delivery and
12:56 business models, right? Um everything around AI. Um at the end of the day,
13:01 we’re an infrastructure um uh analyst firm, right? So, we’re looking at digital infrastructure. So, the biggest
13:08 stories for us or the biggest questions for us are what what what is what are tomorrow’s data centers going to look
13:14 like? How are those workloads going to be uh distributed between the cloud and
13:19 the edge and the very uh near edge on site? um what what it what within an
13:25 industrial enterprise is that edge going to look like? Um you know all all of those sorts of questions around um the
13:32 digital infrastructure um supporting in support of AI are really the big questions for us these days.
13:38 What did you think about that new announcement from Facebook meta on the big uh data center? Yeah, I mean I I
13:45 think whether it’s Meta or you know AWS or or um whatever there’s a big push and
13:51 pull between uh supporting these large frontier models um and these large companies that that have these large
13:57 data center strategies um and then again there’s models and there’s inferencing
14:03 and other AI capabilities that can be done on a in a smaller sort of way um out towards the edge. And so it’s it’s
14:11 the same push and pull we’ve been seeing forever. you know, client server, um, on-site versus cloud, um, massive data
14:19 center versus distributed AI workloads. Um, it’s all it’s all sort of the same thing. Um, you know, there are some
14:27 really interesting just geopolitical um, things to be looking at when you’re talking about meta and, you know, those
14:34 sizes of data centers. you know, where they’re going to land, how they’re going to be regulated, what they mean for the
14:40 energy ecosystem, all of those things. So, yeah, it’s it’s definitely an
14:45 interesting time and um it’s it’s a lot of really what we um are are working with our clients on these days, trying
14:51 to understand those dynamics. How big are they going to get that? This
14:56 one’s like, oh, this is going to be the size of Manhattan. What how much bigger can something get? It can get as big as you think. I mean,
15:02 so we it we’ve seen I I I don’t spend as much time looking I I don’t work in the data center area, but I mean there there
15:08 was there are some, you know, smart cities of the future being built in the Mid East from scratch that have just
15:14 basically data center infrastructure throughout it. And if you look at these things, you can see them from space, right? So right um they’re going to be
15:22 but at the same time it’s interesting there there there um you know coming out of China recently with the deep uh the
15:28 deepseek stuff there was there was a look at smaller models and so there’s going to be this push and pull um you
15:34 know big data centers um are is consolidated tech right so large vendors
15:39 are going to want to build in that direction the Metas the Microsofts the AWS’s etc um but you know uh the the
15:48 internet, the web tends to go in the other direction towards more distributed. You know, you’ve got things like open source, you’ve got, you know,
15:55 um mobile phones, etc. So, there’s always a push and pull between small and big. Um big definitely seems to be
16:02 winning these these days, and the implications of that are kind of massive, right?
16:08 You mentioned smart cities. I feel like smart cities have been hyped for years, right? Like at least 10-15 years in my
16:16 mind. It’s like, okay, we’re really going to do something. it’s coming soon and we’re working on this and that and and I feel like I don’t see anything
16:21 happening anymore. Yeah. I mean, it’s not a it’s so we’ve been working with clients in the IoT
16:27 area for a while trying to trying to help them understand what the the key the key verticals are, right? And there
16:32 was definitely a lot of hype, a lot of interest in smart cities, but it’s it’s it’s pulled back there. There there are
16:38 um you know, it’s there’s funding challenges. Um there’s large procurement cycles. They’re not the most adept uh
16:45 technology enterprises often, right? And they’ve got a lot on their plate these days other than smart tech. Um I mean
16:53 that said there are some interesting deployments in places and there’s some interesting opportunities in areas. Um
16:59 but again sometimes it comes and goes. Uh a couple years ago it was sustainability and ESG for cities and
17:05 now the political winds have shifted and so you know um they they have more on their plate than just to worry about
17:11 technology. Um, so yeah, I think there are definitely other vertical areas where it’s more tied to revenue. When
17:18 it’s tied to revenue, that’s where the investment flows to. So things like industrial and transportation, etc. You
17:24 know, energy for sure that that those are the areas where IoT is really making a a bigger impact these days.
17:30 Are you seeing IoT being a real growth driver for the mobile operators, the telecom guys?
17:37 Yeah, I mean it it’s a it’s a it’s it’s an always challenging business. I mean that’s my background in telecom. Um, and
17:44 you know, they’re selling network connectivity, which is typically, you know, a low ARPU business, and they’ve
17:50 been trying to get into the up the application stack forever, and IoT was one way they thought they could do it, but they always bump into what their
17:56 expertise is really the connectivity business. And so, um, you know, in the on the consumer side, I don’t think IoT
18:02 devices have generated massive amounts of revenue like smart devices or anything, you know, add-on sort of, uh,
18:09 tablet plans and and smartphone plans and things. That’s not a big revenue source. It’s still core sort of 4G, 5G
18:15 connectivity. And in the enterprise, there are certainly opportunities. It’s going to fall towards larger firms that
18:21 look larger telcos that look more like you know global SIs than they do like network providers. and it’s going to be
18:28 a part of their business where um where they’re working with um you know select very large customers on on um projects
18:36 where um you know those IoT endpoints in an enterprise or an industrial environment are generating a lot of data
18:41 and they need to do things with it whether it’s edge compute or just moving it around um you know so I yeah
18:48 is it a massive enabler or a generator of of a of revenue for the telcos no it’s
18:55 still it’s still a challenging sector But you know the sector itself it’s it’s all the data right so it’s it’s not that
19:02 it’s not important it’s just that it’s hard for telcos as always to sort of monetize that whereas if you’re in AWS
19:08 you just set up a cash register and you start moving that data into storage and in compute and it’s just like ching
19:14 ching ching the telcos just don’t necessarily have that that that cash register mentality or that engine right
19:20 right you know I’m always curious about when
19:25 people change their mind they’re surprised by something. You’re constantly surveying the market. What’s a stat or a trend? Something surprising
19:32 that you feel like you’ve learned recently that that just stuck out to you? Yeah, I mean I I I think you know the
19:39 the most amazing thing to to to me is Okay, so I I’ll I’ll step I’ll step back just a little bit. When we were when uh
19:46 I worked at Yankee Group uh and we were acquired by 451. So Yankee Group was very big into mobility and and and
19:53 networks and such. When we were acquired by 451, they were very much a data center firm uh cloud and data center.
20:00 So, one of the first I one of the first events 451 events I went to, we were sitting there data center crowd and they
20:06 started talking about power and cooling and I was like, what does this have to do with IT, right? I just it was foreign
20:12 to me to be that concerned about it. But that’s what data centers are largely about. They’re about the the power to
20:18 run them and and to keep them running. Stick them in the North Pole cuz it’s cold. All that kind of stuff. put them on a put them on a river so they’ve got
20:25 energy all of that stuff right so you know as we look at AI data centers which we talked about earlier just the massive
20:32 impact that these data centers are having on the entire economy the entire
20:37 global economy and the energy sector um I saw a stat recently that um data
20:43 centers uh could consume very shortly all of the current energy generated
20:50 right so like they can just swallow up. Now, of course, we’d be generating more energy and power and etc to keep up with
20:56 the pace, but like that’s how that’s how much that’s how consumptive these these these data centers and these
21:01 capabilities are. So, I think just, you know, just the fact that AI and the data centers to support them are are
21:09 basically swallowing everything is is the thing to be watching and and to
21:15 understand what that means for everything, right? It makes me that makes me have a couple thoughts. If I’m competing against giant
21:23 companies for electricity, what is that going to mean for my for my electric bill, right? Gas and electric, it’s
21:28 saying, “Oh, well, there’s a buyer of unlimited money and unlimited demand.
21:34 So, if you’re the utility company, why waste why waste sending money? Why waste sending power to Eric? He can’t afford
21:39 to pay the bills.” Well, I guess, yeah, energy haves and have nots. Yeah. I mean I that’s um I
21:46 mean I I think that’s certainly part of the equation that I’m talking about. You know what what what happens to the
21:53 energy sector what and how is how is um how is the value distributed and how is
21:58 that you know changed the the global economy. I you know it’s just it’s a it’s a massive question and sits at the
22:04 center of everything. Um and and again it’s not so much the data centers or the compute or the AI or the you know or the
22:11 applications or or ChatGPT. It goes down fundamentally to how is power generated, how is it moved, where you
22:18 know all of that and so it it become you know oil, gas, renewables, nuclear it
22:23 all sits at the center of of of the future in in much the way it has for the past you know 50 years as well.
22:30 Do you see an ability for more energy supply to
22:35 come online to meet all this demand? Is there infinite supply available? Yeah, I mean,
22:41 so I know that there I’m not an expert in this area by any means, but I what I what I’ll say is that there’s there’s
22:47 two sides to that coin. So, what we do in the more in the IoT area and um it’s definitely be of it’s been of secondary
22:54 interest to the market itself. But when we work with vendors who serve energy
22:59 providers, there’s a tremendous opportunity to make today’s grid more
23:05 efficient, right? So to be more able to to to take signals from the energy grid
23:11 and from the demand world and to match them more efficiently and take what
23:16 being delivered on today’s grid and make it 10 20 30 40% more efficient that’s 40% more capacity you don’t need to
23:23 build out. So um that’s AI and that’s automation of the grid. That’s automation of the manufacturing sector.
23:30 Um all of that is driven by the data that comes off machines that comes off the electrical grid that comes you know
23:37 that you can put into a you know to an oil refinery or uh you know a mining or
23:43 operation to make all of this more efficient. So you know in my world that’s a lot of what gets talked about
23:49 but but clearly the the sort of the the macro view is is building more capacity
23:55to match the the the construction of new data centers. I mean that’s that’s just
24:00 that’s exactly what’s happening. When you talk to executives, what are they most worried about right now?
24:06 Yeah. Um so it you know if if we’re talking to or talking about the
24:12 customers of technology vendors um there’s a couple of different things. So we we spend we do a lot of work in the
24:19 industrial sector. So in in that sector there’s an aging out um of the
24:24 workforce. Um and so a lot of the expertise is going away. it’s harder to hire in tech uh technically capable cap
24:32 uh uh college grads into manufacturing when they all want to go into software and AI and you know quantum and all of
24:37 that. So there’s a real concern uh in those sort of bread and butter industrial
24:44 sectors about workforce sunsetting and how you’re going to replace that capabilities. Now here comes AI ready to
24:50 say I’ll we’ll take it over, right? We’ll we’ll we’ll we’ll we’ll capture all of that knowledge and we’ll build agents and we’ll replace them. But you
24:56 know it’s it’s not it’s not really that simple. So in in in those worlds it’s a lot about skills and and workforce etc.
25:04 in the world of more enterprise IT, right? Um, you know, it’s really about
25:09 managing um managing infrastructure and what that infrastructure is going to look like and
25:15 where it’s going to sit, right? Is it going to be do you need to have some edge uh some massive edge presence to
25:21 have high performant for robotics or um something that’s really low latency or can you push it all to the cloud as
25:27 we’ve been doing? And as you do that, how do you modernize your applications? When and how do you modernize them? Um
25:33 and then AI swoops in and you have to recalculate everything you were you were planning to do around um supporting AI.
25:39 So um you know there’s sort of those those two different worlds. Um some are
25:45 just very practical physical things like people retiring or uh you know the
25:51 dealing with uh uh you know power requirements in the smart grid and and in the other world it’s it’s that sort
25:56 of how is digital infrastructure going to evolve right and and and what does that mean for how how you build or you
26:03 know lease or or um you know uh software as a service it right and so there’s just different models as well it’s a
26:10 complicated thing if you’re a CIO these days to figure out exactly where you need to ahead of the puck, you know, 5
26:15 10 years down the line. We we talk about this at home a lot, my wife and I, is we think about if you’re
26:20 an executive, it’s so hard to figure out, well, do we invest in what has made us money in the past? We know it maybe
26:27 it’s shrinking, it’s a melting ice cube, melting glacier, but we know it works. Yeah. Do we then instead divert
26:35 resources and money and time and management and all this into something new that we know is the future but
26:41 derails us right now and we may not make money on that thing later. And it’s hard because it’s like the payoff might not
26:47 be for 5 or 10 years. You that executive might not even be there at that point. Yeah. And you need to you need to meet
26:53 your numbers the next quarter, right? Um yeah, absolutely. So you can see it in certain businesses like retail, right?
27:01 It’s just a a catastrophe if you’re in brick and mortar retail the past decade, right? Um now you might be out the other
27:07 end and the and the industry looks completely different than it did. Um but that’s a great sort of um you know
27:14 warning tale of you know what happens when a sector just becomes completely altered and you’re having to deal with
27:20 today’s infrastructure and the and today’s customer while looking out ahead and you’ve got Amazon coming in and
27:25 changing everything with the different business model right under your feet, right? And so that happens again and again and again these days. And you know
27:32 um you know I I think you know if if anything you have to be somewhat
27:38 discerning this gets back to what we started talking about why analysts are important. You have to discern fad from
27:43 reality. You have to put a business front and focus on on looking at technology. Um you know you can’t deploy
27:50 it for the sake of it and you have to watch out for um for hype right. And so that’s that hasn’t changed. It’s just
27:57 become much much more complicated I think. What’s the biggest hype right now that
28:02 you’re hearing or that you think is hype? Yeah, it’s interesting. I you know I
28:08 think in some ways there’s a lot of this is underhyped um in terms of technology in the sense that things are going to
28:15 change so fundamentally in ways that um are not obvious. I think if anything’s
28:20 overhyped, it’s consumer tech. um like you know like um you know I don’t know I
28:28 don’t know what would be a good example um I think our our home lives are not going to change as radically as a a
28:37 manufacturing plant’s going to change right um as fundamentally um and as
28:42 impactfully um I think sometimes we get new technology they’re it’s nice to have
28:48 um but our sort of consumer life goes on the way it is we just sort of shift to the left or shift to the right. Um, and
28:56 it’s not completely different. Um, so I say if anything’s overhyped, it’s it’s
29:01 no worrying that it’s going to change your it’s going to change you as an individual drastically. I I think we can
29:07 all sort of adapt to what’s coming at us, whether it’s ChatGPT or whether it’s um, you know, um, you know, we’ve
29:14 been looking at sort of VR goggles and things like that forever. eventually they’re going to, you know, play a role in some way, shape or form, but it’s not
29:20 something those kinds of technologies don’t come into our lives and, you know, completely change us overnight. I do
29:26 think in in the enterprise and industrially and those sorts of spaces, it’s extraordinarily fundamental,
29:32 impactful changes that that aren’t overhyped, right? You know, you’ve been covering tech for a long time. What is something that that
29:40 you’ve had to change your mind about over the years? like maybe something that you thought would never happen but it did or vice versa.
29:47 That’s pretty interesting. Um so I mean we could talk about sort of just the publishing world, right? So um the the
29:56 fact so I grew up in B2B magazines, right? Uh publishing
30:01 magazines that were super thick and um you know, one of I worked with one of your colleagues at Telephani magazine.
30:08 We’d put out a weekly magazine as a print magazine. Um, and then the internet came and all of that just sort
30:15 of melted away. But in a lot of ways, it’s it’s it’s back again because there’s a fundamental need for
30:23 information, for communication, for commerce, for marketing in the B2B
30:29 realm. So, you know, everything broke down and then everything sort of reassembled in some ways. It doesn’t
30:35 look the same way it used to. Um, but I’m surprised by how many B2B
30:40 publications there still are that are websites and uh data resources and um,
30:45 you know, newsletters, etc. that have a that have a strong business. So, I mean, I think at one point we thought
30:50 everything around publishing was going to disappear. The fact was it just sort of reassembled in a new form. Um, and
30:57 um, it’s a necessary thing. It just looks different. So, um I I I think
31:03 sometimes when you’re looking at change, you have to look what was what is the fundamental thing about something that’s
31:08 going to be maintained even as everything around it changes. Right. Um
31:13 and so things don’t tend to disappear. I think they tend to morph more than anything. Right. Right. Tell me tell me about that
31:20 journey from journalism into the analyst world. Was that gradual? Was it sudden? Did you wake up and say, “Oh, yeah.
31:26 Publishing’s going away. I got to get a different job.” Like how did that happen? No, I I I rode publishing out to
31:32 the end, right? So, uh you know, I rode like a, you know, a 50 million plus
31:37 dollar uh print publication down to a submillion dollar newsletter and
31:43 website, you know, um and you know, then it basically went away. And um when
31:50 I made the leap into the the consulting or analyst side, um you know, I had relationships and I and I and I made the
31:56 jump. In a lot of ways it’s the opposite side of the same coin, right? We were sort of in the same business just doing
32:01 it in different ways. Um the biggest change was to uh you know on the first day I have to go tell these companies
32:08 that I used to get information from what they should be thinking, right? So that that that’s you know if if you want to
32:14 talk about impostor syndrome on day one that’s a big that’s a big thing, right? Suddenly you’re the expert telling them
32:19 what they should be thinking. But I mean I’ve been doing this for a dozen plus years now. I don’t even know probably more. And so um you know it’s it’s
32:27 really the it’s really the same game. And I mentioned how sort of um publications are are morphing a bit. I
32:33 think even journalists today um have to feel and look and work a little bit more like analysts, right? They’re not not so
32:39 much a reporter because all that information is out there. It’s a different role. You’re not a journalist or a reporter. You’re kind of an analyst
32:44 in some way, shape, or form. Um which I think is good, you know? So when we go to trade shows and stuff, we see a lot
32:50 of uh sort of publishing peers who, you know, are kind of in the same role. They
32:55 they just they just uh execute it in in a in a different way. Um but it’s it’s a
33:01 lot of fun to be able to have these two-way conversations um with um with vendors for instance and to you know to
33:09 be able to help them as much as they help you um you know and and be more of a peer. So I I I think that’s the
33:15 biggest the biggest difference. Do you still feel like you have the impostor syndrome or you’re good now?
33:20 Doesn’t I’m pretty good at this point. Yeah. I’m trying to think what I would still feel an impostor about. No, not not so much.
33:27 Yeah. Um you know I think I think you know the one thing you do learn when
33:32 when you’re sort of taking uh inquiries in from companies um is that nobody sort
33:38 of knows everything, right? And so when you can exchange knowledge or or value,
33:44 um, everybody’s sort of brings something to the table. There’s no one out there that knows everything. So everybody’s
33:50either a slight impostor or a slight expert and usually someplace in the middle, right?
33:55 Nobody knows everything, but nobody knows nothing as well. Yeah. Everybody knows something.
34:01 Yeah, it’s true. Yeah, it’s true. There’s a lot of value to be gained, you know. So we have um it’s been interesting. I so I I’m an individual
34:07 contributor, but we all I also manage our team and we’ve got folks who have been in the business as long as I have
34:13 and we’ve got some some new analysts that have come in. It’s really interesting to see when an analyst can take off very quickly, how they can
34:19 apply some some basic skills into an area that can be pretty challenging to, you know, get yourself up as an expert
34:26 quickly. Um but yeah, it it happens and um you know, I think you know, it’s it’s
34:32 it’s it’s an interesting area now these days and I think um being able to uh to
34:39 work with analyst relations teams and communications teams as they’re evolving in your business is also interesting as
34:45 well. Um I I imagine just how you guys have to work and and talk to and talk to the folks that you talk to is is has
34:51 changed tremendously as well. Absolutely. Absolutely. Rich, this has been fascinating. Thank you.
34:57 Sure. For for chatting with me. I could talk to you all day, but it’s like, okay, we’re at 35 minutes now. That’s that’s
35:02 good for our audience right there. I don’t want to make it a whole hour, but then they got to pay you for that. If it’s an hour, they got to pay you.
35:08 So, um, Rich, I appreciate the time. This has been fantastic. Really insightful to hear how you’re thinking about things,
35:14 what’s changed, what were, you know, as a what a lot of normal people may not realize about what’s going on in the
35:20 business and and yeah, look forward to talking to you more. Okay. Yeah. Thanks, Eric. Appreciate it again. Take care.
35:26 Thank you to my guest and thanks for listening. Subscribe to get the latest episodes each week and we’ll see you
35:32 next time.