In this podcast, Motley Fool analyst Asit Sharma and host Deidre Woollard discuss:
- Why this quarter has been so good for ad revenue, and if that might change.
- How Meta's spending on virtual reality could pay off.
- If Apple or Meta will triumph in the great headset race.
Motley Fool analyst Tim Beyers talks with author and New York University professor Melissa Schilling about traits shared by the world's greatest innovators.
To catch full episodes of all The Motley Fool's free podcasts, check out our podcast center. To get started investing, check out our quick-start guide to investing in stocks. A full transcript follows the video.
This video was recorded on Oct. 26, 2023
Deidre Woollard: Ad revenue is back, and that's good news for Meta Motley Fool Money Starts now. Welcome to Motley Fool Money. I'm Deidre Woollard here with Motley Fool Analyst, Asit Sharma. Asit good to see you again.
Asit Sharma: Deidre, so good to see you.
Deidre Woollard: Advertising is back I think yet this has been such an interesting week to look at earnings on yesterday's show. Ricky and Nick, they covered Alphabet, strong ad revenue, strong search revenue, strong story for YouTube. But we've got a similar story today with Meta Gap advertising revenue up 24% year over year. I think sometimes we get distracted by all of the other things that Alphabet and Meta do, but these are ad businesses. That's where the money is. This is only one quarter though. How should we be the thinking about this? I'm happy but I'm a little I'm cautious. How are you?
Asit Sharma: I think I'm cautious too, Deidre. I think this quarter reflects businesses that were previously shell-shocked last year, have slowly adjusted to the business environment. They're spending a little more. The caution is being cautiously pulled back. Businesses have to spend on advertising after all. To raise revenues and bring in the profits. I think that's good, but we're not out of the woods yet as you know, the macro environment is so volatile, interest rates are still sky high, seem to be ever climbing. Inflation is persistent, student loans are starting up against student loan payments. With this uncertain environment for discretionary spending among consumers, I wonder too. For me, two data points make a trend. Let's see, one more quarter like this among all these players and I might feel a little more comfortable.
Deidre Woollard: Yeah, I think so too. The GDP numbers came out today and they came out higher than expected. But consumers are feeling the pinch the savings rate is going down. It'll be interesting to see holiday season and the impact on that for these companies as well. I mean, when even Snap is getting solid ad revenue, I start to think maybe this is something real.
Asit Sharma: I know. Even Snap's making money.
Deidre Woollard: Exactly.
Asit Sharma: It's been a good quarter for advertisers.
Deidre Woollard: Well, so we've got the money coming in. But this is Mark Zuckerberg's year of efficiency and on the earnings call, he made it clear he wants to keep that going. He likes where things have been and yet this is the huge ad yet is of course reality of labs. They are still spending like crazy on this $3.7 billion loss this quarter. They've said they're going to keep on spending, it's necessary for them to build out AR and VR. But at some point, this has to stop. At some point you can't just keep spending without any real benefit to it.
Asit Sharma: You have to stop at some point. I mean, what a couple $100 million in revenue. Then as you point out, a $3.7 billion loss. What is working in Mark Zuckerberg's favor of course, is that tremendous margin that comes from the advertising business and the fact that in tightening the belt in so many other spaces, I think he's bought a lot of goodwill among shareholders. Making the whole of the business more efficient gives him some leeway to continue with the losses even though they're significant in this one area. But I think at some point you'll have to show a better return on all this investment for shareholders to countenance it any further.
Deidre Woollard: Yeah, and I think one of the things that the analysts are looking for that came up on the call was, you're spending all this money, is this transferable to other areas? Is this benefiting things? CFO Susan Lee, she didn't quite give them the answer I thought they were looking for. She said most of the spends on headcount and costs related to directly to reality labs. It's pretty clear that what they're doing is directly related to just the AR and VR. It's not really going to go over and help the family of apps, which is of course where the money is made.
Asit Sharma: I think they actually can get some benefit out of that Deidre. I was surprised too at the answer that Susan Lee gave. When you think about reality labs, you and I think most members think of company within Meta that's trying to build out the Meta versus trying to build a virtual reality, immersive environment through the use of their audiovisual devices, and then some augmented reality which is blending physical and a virtual environment. But the things that they're investing in are wide, they're vast. If you ever have a chance to watch some videos on what exactly goes on in all these research dollars into reality labs. There's much investment in kinetic experiences.
There's much investment in understanding what happens when the human face smiles or frowns or raises an eyebrow and that has a direct application to the avatar business that Meta is in they're working on avatars once they get those to a super realistic degree of competence. You and I, because we're recording this audio in Zoom, I'm looking at your pleasant face just now and I can see you just reacted with a smile. Now imagine the avatars that can interpret simultaneously these micro-expressions and really give this realistic environment to both of us that we are in, like the synchronous communication environment. You actually don't need a VR experience for that. You don't even need an AR experience for that. That can conceivably occur over two laptops. If you can make the avatars very realistic and some of this investment, you can see how they can just port it over to other places. It doesn't have to exist solely within virtual reality, and I wish she had talked a little bit more about all the money that they've poured into bridging this divide between physical environments and virtual environments. What if the Meta verse fails? I think there's some yield there and I've said this before, I'm here on Motley Fool Money. I think business collaboration could be big for Meta. Now whether any of this gets commercialized or not truly is anyone's guess. I say if you're pumping in tens of billions of dollars over a multi-year period, there's got to be something that can translate and give you some decent revenue out of this.
Deidre Woollard: Yeah, I certainly hope so. I want to talk about the business aspect a little bit later, but first I want to talk about the gear. Meta has not had a great track record with devices. You had Facebook phone that didn't work, you have the Meta portal that did not take off. But when we were at the Motley Fool 1 event earlier this week, our colleague, Kirsten Guerra, she said she was looking at the Apple Vision Pro as one of the things that she thinks is going to be trans formative. I think Zuckerberg would prefer that she of course say Meta Quest or the Ray Band smart glasses. But there's this pressure right now to deliver the thing that goes on our face, and do you think that Apple or Meta is going to be the winner in this space? Obviously, Meta's device is far cheaper and they've had more swings here to make this work but it's Apple. How are you thinking about these two?
Asit Sharma: Deidre, it's Thursday. What you throw in such a hard question. The weekend is right in my sight. Let's see. Apple, their device is like seven times more expensive than the Meta Three. But it's a beautiful device from what we've seen and we know that it's going to deliver an unparalleled experience in some respects until we can actually try it out. I can't say that it's going to be a game changer or not, but certainly ditching the controller which use with the Meta Quest to something where you can just use hand gestures to control a pointer object like a mouse. I think that's so Apple delivering this bespoke experience. I'm sure the form factor is going to be elegant. It already looks great and the experiences are going to be immersive and they're going to be fun. We already know all this about Apple. The thing here that strikes me is a little different than other great products they've rolled out is just the delta of the next best product and this new product, I mean, it's an even bigger gulf than when the iPhone first came out versus the phones you could buy in the market. I do question the first generation, how much uptake it'll have at $3,500 per pair. But what we will see is a trickle-down effect. Meta will try to pack more features into its next versions and Apple will also work on second and third-generation devices where as they've done in the past, they'll give you some lower price points with fewer features. At some point, the two of those converge. Which ultimately wins out if I had to bet, I'd have to bet Apple just because of their track record with device in. What you point out about Meta stumbles. But I still feel that we shouldn't underestimate Meta's ability to make their device more widespread in the marketplace. Let's go Apple.
Deidre Woollard: Well, and I think it's interesting too, that Apple, they thought potentially about doing smart glasses. They decided that that wasn't the first swing for them. We've seen Google Glass with Meta keeps trying to make this happen. Snap that we talked about earlier didn't do well with it, the smart glasses thing. It's still hard for me to figure out that one. I think I'm more interested in the fully immersive headsets as a real changer, but we'll see.
Asit Sharma: Yeah, the Ray-Bans are sleek.
Deidre Woollard: They are sleek.
Asit Sharma: Meta partnered with Ray-Bans parent and you have actually a fun form factor for a lot of people. I do think since the last iterations of smart glasses that hit the marketplace, there seems to be more acceptance and fewer privacy concerns so I wouldn't be surprised to see this sell pretty well. This is, again, not like a VR or even mixed reality type device, it's simply smart glasses but you can take video, you can communicate with an AI agent through the day if you want. They look pretty sleek, not for me, but I can definitely see a generation of consumers maybe buying up and I believe the price point is just like 299 entry point, Deidre some where up there so not super expensive.
Deidre Woollard: Yeah, not too expensive. Well, you just mentioned AI agent and that brings us into talking a little bit about business which you teased earlier because one of the things that Meta is doing, you've talked about making the avatars, they're now creating AI for businesses and these agents, these experiences. The way they see it is basically every business is going to have an AI for customer interactions. They were already talking to bots probably more than we'd like to, but this is supposed to be better. But I have this question. This is one of the things I must really think about with this. If I'm spending my time with Meta to develop my AI agent, maybe I'm putting things into a large language model, I'm really working on this thing, you've got multiple apps, you've got like WhatsApp and Instagram and Facebook, but it's still a walled garden. Are companies going to have to invest in creating multiple AI avatar experiences across multiple customer input points, multiple walled gardens? It all seems like a lot of work for companies and a lot of money too.
Asit Sharma: A lot of work, a lot of money, and uncertain return. I think companies are going to pick one model and work with that on one Cloud provider or maybe one portal. Snowflake offers a portal for training, you can actually work directly with Nvidia depending on your industry. But I think that's more of what companies will do, whether it's Meta or another company. They'll choose a training model, a large language model, they'll figure out, with this provider, my dataset secure and then they'll experiment and no one is going to create multiple bots at this point in time on multiple platforms unless that ROI is there. If it doesn't improve your customer service, if it actually degrades it because you've got different bots giving different answers, you're not going to keep investing. I like that Meta is pushing this and I like that their large language model is open source, they're kneecapping the idea that other large language models will be proprietary and businesses will spend only on those. They're using a playbook they've used many times before, that's smart business on their part. But it does further, the AI cause it makes it easier for people to innovate. There's some mercenary goodwill that Meta is creating out there where their particular large language models is concerned.
Deidre Woollard: But I'm going to push back on that a little bit just because of the Cloud thing. Because companies, when they were first moving to the Cloud, they generally picked one horse. Now I've been listening to our friends Tim White and Tim Beyers talk a little bit about this. Now we're seeing more multi-cloud where companies are expanding out. I'm wondering if over time you start with one AI, but then you have different needs, different purposes and maybe it becomes multi AI the same way it becomes multi Cloud as it evolves, talking years in the future.
Asit Sharma: Not totally. Actually, Tim Beyers and I were having a slight conversation last night about multi Clouds and Cloud providers cooperating with each other to sell businesses so I'm with you there. What I was talking about is simply the context of, let's say, a customer facing bot on a Cloud provider where you're giving your dataset to the Cloud provider and working with their models. I don't think in that particular instance like where it's customer service, many businesses will want to do that on multiple platforms. But within businesses you could have different divisions who have no idea of what the other side is doing. One will be on an Nvidia platform in the future, one will be using Snowflake to maybe also go to Nvidia. Some will be on Amazon Web Services and their particular Cloud based AI training ground. I do see that for sure as businesses get used to working with AI models, there probably isn't going to be a single winner, one size solution. But for specific use cases that I don't see like you're going to use six different models for one purpose.
Deidre Woollard: That makes sense. Well, last quarter was just when Threads was starting to pick up and there was a lot of talk about it in the earnings call and a lot of excitement. This quarter, I think they mentioned it maybe twice, maybe three times. You've got about 100 million monthly actives who knows how active they really are but Zuckerberg said it'll take a few years but he thinks over time it could be a one million-person public conversation app that is more positive. Given that they're not really putting that much effort to it, do you think that that's actually correct? It didn't seem like there was that much enthusiasm for Threads at least this quarter.
Asit Sharma: I think it's personal with his rival Elon Musk. I think he wanted to say something about Threads just for the community to understand that they're still investing in it. But more telling was Zuckerberg spent more time talking about consumer-to-business conversations and how that's really getting monetized. Specifically, the example he used WhatsApp in India where he said some 60% of users have used a click to message interaction with a business. Meaning you see a businesses ad and you click to message them because you need something. I was just in India and I certainly experienced that myself. That really is going to be a more money maker for Meta is working on where businesses and consumers are interacting. I really don't see at this point the potential for Threads to be some great monetization engine. Still, the user interface needs work from, my experience, like browsing around and I see as we're talking you seem to be agreeing with me, Deidre. I think that was just like and we're still there, don't think we're not fully invested here. But look where the money is going, it's going into like pumping up that WhatsApp ad revenue, which is blossoming, frankly.
Deidre Woollard: The ad revenue and the growth of those business services that we talked about. One thing that wasn't in the earnings and that they can't really talk about is some of the regulatory concerns that Meta is facing. This week, you had multiple lawsuits come out from a variety of states and some joint lawsuit. Same company violated consumer protection laws related to how it markets to children and teens. Neither one of us is a lawyer, we don't know what happens next, but the thing I'm thinking about is the court of public opinion. Does this make a difference in how people start to consider using Meta's products and exposing their children to it when they turn 13 or even earlier.
Asit Sharma: This is a perceptive question, Deidre. It's hard to remember now, but before the pandemic, before all the investment in reality labs, before all this economic upheaval we had, Meta had the solid advertising business and it competed with its peers but seem like whenever retail investors and institutional investors were plugging valuation stuff into their models, they always valued Meta, then Facebook a little less versus peers with similar models. It never quite traded at the premium that it should have and why was that, it is because I believe investors were really concerned with their inept handling of privacy almost since Day 1, and that always seemed to hit their results. We saw lawsuits being filed in the past, we saw Meta, then Facebook as an organization, not really being the most stringent in terms of protecting user's privacy and this seems to be an ongoing issue with Meta, might be one reason among some others. I still don't own shares myself and part of that too is maybe an unease with the company. If you really don't value your customer's privacy, is that a company that I just personally want to invest in? I've never been able to get over that hump and here it flares up again in some of the lawsuits that you've mentioned. We'll see. I think that has the potential to be a drag on the valuation in the future. Right now, all the attention has been on, first the plunging of capital into reality labs and then this memory we had this year that wow, there's a great digital advertising business here and Zuck is cutting cost, so the stock has benefited but it's like now what. What happens from here and this would play into anyone's valuation thesis, I think because it's happened in the past and it's hit that valuation in the past.
Deidre Woollard: So much to consider with this one. Thanks for breaking it down with me Asit.
Asit Sharma: So much fun, Deidre. Thanks a lot for having me.
Deidre Woollard: The analysts you hear on the show have a whole other day job providing premium coverage and recommendations for the Motley Fool suite of stock investing services. We're giving our listeners a discount on Motley Fool's flagship service, it's called Stock Advisor. If you're interested in more analysis from our team, two stock recommendations per month and access to Stock Advisor's full scorecard of companies, visit www.fool.com/mfmdiscount.
Earlier this week at a special event for Motley Fool 1 members, Motley Fool analyst Tim Beyers interviewed Professor Melissa Schilling, author of the book, Quirky: The Remarkable Story of the Traits, Foibles, and Genius of Breakthrough Innovators Who Changed the World. They talked about the fascinating things she discovered while researching some of the world's greatest thinkers.
Tim Beyers: Melissa, thank you for being here. I think the mic is hot.
Melissa Schilling: Thank you for having me. It is hot.
Tim Beyers: Yes. Let's talk about breakthrough innovation and let's talk about maybe the most talked about breakthrough innovation right now, which is AI. Let's start there. Big picture first. Which companies to your mind, and based on the research you're doing, are most threatened by AI and which ones stand to profit the most, do you think? If you could name a couple.
Melissa Schilling: You want specific company names?
Tim Beyers: Well, or types of companies. If you've got some specific names, I know there are a lot of people here that would be very interested in that.
Melissa Schilling: Obviously Nvidia. You can't talk about AI without talking about Nvidia. I think that that's a really interesting story because I think they accidentally end up poised in a perfect place to capitalize on AI, in that they were developing extraordinary microprocessors and data processing capability for the video game industry and ended up basically creating products that are perfectly positioned to now be a dominant player in AI. They're doing a lot of the hard, heavy lifting of AI. I think also any company that's working in Cloud is going to be a big benefactor of AI because what AI is going to allow us to do is utilize a lot more data and a lot of companies that will adapt to AI won't have to do it in-house. They're going to do it via the Cloud and via Cloud service providers who are helping them tap the capabilities of AI without having to bring that capability in-house, which is something else I want to talk about AI if possible. First let me say something that's a trap. It's a trap to look across industries and think this industry will be decimated, that industry will be decimated. I think on average, that's not what we'll see. What we'll see is that AI is going to change what creates a winner in an industry versus a loser in an industry. I like to use an analogy, I'm a big fan of analogies because I think it makes it really concrete. But if we think about how spreadsheets affected the accounting profession. Spreadsheets like spreadsheet programs like it was Lotus 1, 2, 3 in the beginning.
Tim Beyers: Sure.
Melissa Schilling: Now Excel. They didn't put accountants out of business. Maybe a few accountants who decided, I don't want to work with spreadsheets. That's not for me. Those accountants probably ended up being.
Tim Beyers: I need my ledgers. Those accountants.
Melissa Schilling: Yes. Those accountants who want to use a pencil and a big adding machine. Those accountants are probably gone. But for most accountants, what it did was it enabled them to do more better, faster, more precise. More regular updating, more precise measures, more segment accounting, and so that's what you want to look for. Who are the players in an industry who are going to pick up this tool and use it to do bigger, better, more exciting things?
Tim Beyers: Taking that as gospel here for a minute, who do you think then is the group that's threatened by AI, the ones that don't want to do more, bigger, better?
Melissa Schilling: In my business, being a professor analyzing companies, you can spot them structurally sometimes. They tend to be companies that are older, that have really strong hierarchy and hierarchical norms. They're a little bit rigid. Counterintuitively also, very decentralized companies will have a harder time responding to the shifts that are required by AI. We tend to think of decentralized companies tend to be promoted as like flexible and fast, and they're really good at incremental innovation. But decentralized companies where you don't have a lot of authority at the center of the company, have a harder time making big systemic changes fast. For a big systemic change fast, it's easier if you can have more centralized control. On the one hand you want some centralized control to be able to make that change quickly, but you also want to have a company that embraces change where there's no sacred cows, there's not a lot of power distance, everyone has a voice. Companies who are being proactive about saying, OK, how do we disrupt ourselves instead of how do we defend our business? That's the positioning you want to look for. Also, frankly, companies that have some slack. Companies that have had some free cash flow that is leaving them sitting on a bit of capital where they feel comfortable that they can make bigger, bolder moves. Because in a company operating on razor thin margins, in an extremely competitive industry, they're looking a month out, a quarter out, it's very difficult for them to do big changes and to invest in those. They're going to perceive it as too risky.
Tim Beyers: Then we'll pivot to your book here. But that sounds like you just said industries where the profit margins are thin, you're looking out a quarter, maybe not five years. That sounds like retail, that sounds like consumer products, that sounds like in some industries that maybe are a little bit more industrial. Do you think that's fair?
Melissa Schilling: Well, again, I don't think it will serve us to label a whole industry as going to be a loser or a winner in AI.
Tim Beyers: But the structure of the company itself.
Melissa Schilling: The structure. I think retail is a great example of an industry that will be completely transformed by AI because it's a data heavy industry where you can really utilize that data. I think the ones that adopt AI early and aggressively are going to vastly outperform the ones that don't.
Tim Beyers: That makes a lot of sense. Well, this is interesting. Let's pivot then to breakthrough innovation because you wrote about this in your book, which is fantastic. I really think everybody should read this, particularly if you are investing in any way in Breakthrough Innovation. This book identifies, in a very thoughtful and narrative driven way, some of the greatest breakthrough innovators in history and I'm sure you are very familiar with the names. I'll name a couple. You mentioned Thomas Edmondson, you mentioned Albert Einstein, you mentioned Elon Musk, Steve Jobs.
Melissa Schilling: Marie Curie always have to include some women in there.
Tim Beyers: Yes, Marie Curie, which is a fascinating story as well. How should we be thinking about as investors, some of the key traits that you identify here? I'll focus in on one, which is separateness. I'd love for you to maybe define that a little bit. These breakthrough innovators have a view of separateness and you define it in a very interesting way. Can you talk a little bit about that?
Melissa Schilling: Yeah, sure. Let me first preface this by saying, before I started this project, I was working on a bunch of stuff related to networks, social networks, collaborative networks among firms, and so I really had this ex-ante expectation that innovators would turn out to be hyper connected. They would have these really big, robust, replete social networks that would enable them to get lots of ideas. Then I was very surprised to actually find that most of the Serial Breakthrough Innovators in my study, you couldn't help but call them anything else. They were separate, they were socially detached. Sometimes it was a personality trait, like extreme introversion. In Edison's case, he was deaf. Sometimes it was periods of depression or sickness like in the case of Curie or Tesla. Sometimes it almost looks like Aspergers, that's where Elon Musk said he has Aspergers. Einstein clearly had some little bit of spectrum disorder. But that separateness that it gave them that sense that they were different and that they didn't quite fit in with the social world, ended up being incredibly liberating. Because it meant first that they weren't socialized to buy into all the norms that everybody else had bought into. Norms can be constraining, paradigms can be constraining people who are extremely well indoctrinated or trained in a particular area have a harder time coming up with a radical innovation than people who haven't been indoctrinated in that way. Part of it is what you've been exposed to and what you've learned. If you've learned really well, what the field thinks works and doesn't work, that can trap you. In some sense these people who weren't part of the norm didn't have that trap. But there's a second side to it and that is that a lot of these people were also very rebellious. That was part of the separateness. They had this view that I'm not part of the social world, its rules don't apply to me. They were sometimes difficult people or people who didn't care that much what you thought of them. We certainly see that with Marie Curie, we see it with [inaudible]
Tim Beyers: See it with Steve Jobs and the Reality Distortion Field.
Melissa Schilling: Yeah. You see it with Elon Musk. He does not care what you think about him. Now the way that unfolds is multi faceted, shall we say. There's some ways in which he comes across is a jerk, like when he manages, he's not a warm, fuzzy manager at all. He has said things on Twitter that he shouldn't have said, in my opinion.
Tim Beyers: I think that's fair.
Melissa Schilling: Yeah. It's because he's a low self monitor and he doesn't care that much what you think of him. But that ends up serving him because you know most breakthrough ideas. The first time you see a breakthrough idea, you're generally not going to react favorably to it at all. Because it's going to feel weird, it's going to look jarring. It's a breakthrough because it breaks with something. It breaks with your expectations, or it breaks with the way we do things, or what we believe. Breakthrough innovations tend to be ugly and unsettling, and people who want the approval of others are going to have a real hard time both introducing those and sticking with them in the face of criticism. But if you are someone like Musk, he believes in his ideas. He doesn't care whether you do. He has confidence that he will make it work, whether you think you can or anyone else can or not. He sticks with these ideas, even when other people say that's dumb or that's impossible, or what are you thinking, it's almost a disagreeableness, but it's a very beneficial disagreeableness.
Tim Beyers: I mean, let's transpose this on ourselves and the Motley Fool. But all of us individually as investors. How can we foster a little breakthrough innovation in ourselves as investors, as people, as you know, people in the world. How do we do this for ourselves?
Melissa Schilling: There's probably three things I think are most effective I can do right away. One is, when you have an idea that you think a breakthrough innovation idea, don't show it to people early. Don't seek early feedback because there's only two feedback you'll get. You'll either get negative feedback or you get people blowing smoke up your backside because they want to make you happy. You probably won't get the useful feedback you were hoping for. You have to have enough conviction that if you believe it's a really cool idea, pursue it and elaborate it on your own, and wait for a while before you expose it to other people. That's one thing I would do.
Tim Beyers: Okay.
Melissa Schilling: Actually along with that I'm actually going to get sneak foreign here.
Tim Beyers: All right. Good.
Melissa Schilling: Forget about credentializing norms. One of the things you learn over and over again when you study breakthrough innovators is that they're very often outsiders. They may not have had the PhD that you were expecting, or they may not have worked for the company that you were expecting. Those credentializing norms are also homogenizing norms. Be confident in your ability to enter an industry that you aren't trained in, if you want to do something in an industry and you don't have the right degree for that area, don't let that stop you, and don't make that stop other people. The third one. Find your own idealistic mission. Find those things that you feel like would be worth doing, even if nobody pays you for it or pats you on the head for it. Because once you find those, that's going to make you work harder. Think bigger, move faster. That's really powerful. Then I had a fourth one and I just forgot what it was.
Tim Beyers: No, that's OK. I mean, I think what's interesting in what you just said, there maybe a bit of stubborn willingness to pursue the things that are very interesting to you. When you're looking at companies right now or maybe in some of your own work with start-ups, is there any identifying characteristic of say, like a stubborn willingness to do something that really stands out to you when you do your consulting work? Maybe a company you've run across or a founder you've run across?
Melissa Schilling: When you have a manager, for example, that understands what the big picture is and is willing to let go of current business to get to that big picture that's actually really powerful and that probably sounds really big. I'll give you a great, I'll give you a specific example from a company just down the street here, Bloomberg Corporation. I'll tell you something they were doing wrong and then something they did to turn it around. If that's OK. Am I allowed to talk about Bloomberg?
Tim Beyers: Yes, you can. We got five minutes. We can do it.
Melissa Schilling: It'll be really fast. Bloomberg was founded basically because Michael Bloomberg figured out that he could lay these computer lines between investment companies and get more information faster to people, instead of having bond runners, you could get the bond prices just beamed to you basically over a computer line. His whole original success and competitive advantage was quantity of data, speed. Those two things and what they would produce on their monitors were beautiful, visualizations and data that had been curated and calculated, that humans would perceive with their eyes. Investment bankers would look at that and process that data with their eyes. That was the whole business model. What that meant was that when mobile was just a baby, when smartphones were just coming up, it was very unattractive to Bloomberg. A mobile solution was not attractive because it was going to be not as fast, not as much data on a little bitty screen. Which was just so it wasn't very sexy to the company, there were not a lot of people who wanted to work in mobile because the metric of performance at Bloomberg had been speed.
Speed and data, cool algorithms, that just didn't compete with mobile. We did this exercise where we took apart the performance dimensions of their industry and thought about where the payoff was, where the utility payoff was for each of these dimensions. They came out of that realizing, Oh my God, we have to go mobile. Because mobile is where the room for more utility was, they'd actually basically maxed out speed from a human perspective, I'm like I asked them at one point, how fast are humans? You know, if your data is coming even faster, can investment bankers process that even faster? I got a lot of blank stares to that question. But we had this meeting and a big argument broke out. They ended up moving 60 people over to the mobile division and invented an award-winning mobile application that was crucial to the success of the company. That willingness to tear down parts of their own business model to move forward is super, super important.
Deidre Woollard: As always, people on the program may have interest in the stocks they talk about and the motley fool may have formal recommendations for or against, so don't buy or sell stocks based solely on what you hear. I'm Deidre Woollard. Thanks for listening. We'll see you tomorrow.
