FOBO – The Fear of Becoming Obsolete (And How to Navigate It)

Rob Collie

Founder and CEO Connect with Rob on LinkedIn

Justin Mannhardt

Chief Customer Officer Connect with Justin on LinkedIn

FOBO – The Fear of Becoming Obsolete (And How to Navigate It)

In this episode, we embark on an engaging journey with a twist—it’s Rob’s first solo venture! Today, Rob dives deep into a thought-provoking question: Can platforms like LinkedIn ignite FOBO – the Fear of Becoming Obsolete? He deftly navigates the intricate world of FOBO, exploring its potential ties to platforms like LinkedIn and posing some tough questions. Are these digital landscapes fostering the Fear of Becoming Obsolete?

But our exploration doesn’t stop at social media. Rob’s known for tackling hard-hitting topics, and today is no different. He also addresses another pressing concern: the fear of new technologies and the looming presence of AI. Are these fears genuinely justified, or are they as fragile as a house of cards?

Stay tuned, dear listeners, as we dive deep into the essence of FOBO, using it as a catalyst for growth and an enduring source of learning. And remember, if you enjoyed this episode, please leave us a review on your preferred podcast platform to help new listeners discover our show!

Episode Transcript

Rob Collie (00:00): Hello, friends. We're going to be doing something a little bit different this week, so I'd like to welcome you to the first ever solo pod episode of Raw Data by P3 Adaptive. That's right. This week it's just me. Is that a good thing? Is that a bad thing? Well, you get to decide that, don't you? Basically, the idea here is that I've got a number of things sort of forever rattling around in my brain that lend themselves more to a narrative where I just kind of lay it out there in a deliberate order and it would be kind of awkward and unfair to drag Justin, Mr. Co-host, through a format that's really just me talking. Once you're done listening to this one, if you liked it, please let us know. We'll never make this a large percentage of what we do here, but it is a potential ongoing format that we could dip our toes into periodically, and today we're going to be talking about ... oh, wait a second.

(00:48): No, I'm going to be talking about FOBO, the fear of becoming obsolete. It's an epidemic sweeping the internet. What are we going to do about it? Well, I'll give you my thoughts here in just a moment.

Announcer (01:01): Ladies and gentlemen, may I have your attention, please?

Announcer (01:05): This is the Raw Data by P3 Adaptive podcast with your host, Rob Collie, and your co-host, Justin Mannhardt. Find out what the experts at P3 Adaptive can do for your business. Just go to Raw Data by P3 Adaptive is data with the human element.

Rob Collie (01:31): FOBO, F-O-B-O, fear of becoming obsolete. We're going to make this a thing. There was a time when FOMO wasn't a thing, fear of missing out, and then suddenly FOMO is now like a word in the language. One of our goals here, we're going to make FOBO a word in the English language. So if nothing else, please, please, please, let's start using this term in conversation as if it's already a term, and then people ask us, what does that mean? You go, "Oh, it means fear of becoming obsolete." And the value of giving it a name is that it's kind of like being able to face your accuser, know your enemy type of thing. When you give something a name, you can actually focus your attention on it. You can focus your attention on that symbol because I think that FOBO is already doing a tremendous amount of harm.

(02:15): If you're listening to this, FOBO has been hurting you and the invisible thing's hurting you. Oh, those are the worst. So we're going to bring it out into the light. FOBO, the elephant in the room, it was an invisible elephant. Now we're going to paint it and everyone's going, "Oh, that elephant?" Right, yeah, that one's been sitting on my lap. It's kind of hard for me to breathe, isn't it? So let's start with what I think, in a way, the number one culprit that's inflicting FOBO on us. It's not the only thing. I have a very, very, very conflicted relationship with this thing called LinkedIn. Some of you listening spend large chunks of your days on LinkedIn. Some of you listening maybe check LinkedIn very infrequently, but either way, I'd like you to, as a thought experiment, imagine when you are looking at LinkedIn and you're scrolling your newsfeed and all this stuff is going by, yeah, there's content going by and there's words and words and things like that, and people and things and your computer or your phone or whatever device you're using, when you're scrolling this, it's whispering at you.

(03:15): It's whispering, "You're inadequate. You're falling behind. You suck." And even though it's being subconsciously whispered, you're hearing it. You're absolutely hearing it. A lot has already been made of the impact that other social media platforms have had on us like Facebook and Twitter. There was a pretty famous article went by recently that talked about how Facebook's algorithm, they just arbitrarily decided that an angry reaction to a post was going to be worth five times the amount as a like in terms of promoting how much that was going to be seen in people's feeds. I mean, that's bad. Social media in general, the people who are publishing the most on social media are 100% giving you a filtered view of their lives. Facebook becomes a FOMO vector. Your friends all seem to have more money than you. They're going cool places.

(04:09): They're wearing the cool clothes. They're at the cool bars, whatever. Seriously, we take pictures of our plates of uneaten food at fancy restaurants and put them on Facebook. Why do we do that? It's for FOMO points. Anyway, I don't want to get too sociologically deep on this one, so let's get back to LinkedIn. So that same sort of filtered positive spin on things, when that vibe is happening with your livelihood, oh, it has a way of really striking even deeper than what the purely social unprofessional versions of social media do. One of the number one ways that an influencer on LinkedIn can keep people engaged, can keep people enthralled, is to keep them off balance. Think about that for a moment. If you weren't going to become a LinkedIn influencer in some field and all you were doing was telling people that they were okay, you're all doing fine, you're doing great, there wouldn't be much reason for people to hang on your every word now, is there?

(05:09): Not a lot of reason to keep coming back. It's a lot easier to destroy than create. Maybe a daily affirmation type of LinkedIn influencer could work. Every day they had something to say about, "Yeah, you're doing great. I'd tune in for that. What about you?" But it's a lot harder to do that, isn't it, than it is to constantly say things like, what are you doing about X, Y, Z? And you better hurry because this other thing is going to make you obsolete. Another famous form of social media posting in this space is, let me show you all the ways in which I have been kicking ass with new technology, X, Y, Z that makes me look like a different species than you. That's a really, really, really common one.

(05:51): In fact, just yesterday on Twitter, there was one going around about how, this is really awful, how this company used AI to steal a tremendous amount of search engine traffic from one of their competitors, and then of course, at the end, guess what? The company that did this, they're an AI company that used their own AI tool to do this, and so they're really just talking their own book, but along the way, the amount of FOMO and FOBO that they're inflicting on the world is intense. That's another thing about being a LinkedIn influencer. First of all, an unstable and wobbly audience is much more likely to tune in on your every word. So you got to keep people off balance, and you also got to keep people off balance with something new all the time. You can't be saying the same thing over and over again, so you have to find new things to make people feel insecure with. This is the formula.

(06:41): And the good influencers on LinkedIn might not even really consciously know that they're doing this, but this is the thing that works. So first of all, we've given it a name, FOBO, right? We brought it out into the light. Secondly, we've identified one of the primary vectors, which I think it really is LinkedIn. That thing is powerful. I hear it whispering at me all the time. So let's break it down. I've got at least three categories of FOBO and an antidote of sorts to each. One form of FOBO that I'm seeing, and I think it might even be the largest one, is people who are essentially still stuck on the starting line with things in our space. Now, of course, this is a data focused podcast, P3 Adaptive, we're a data services company, so of course we're going to take this through the data lens specifically.

(07:26): I'm sure this applies in lots of other places as well, but so, so, so many organizations are still on the starting line with regard to data modernization and to be told about 40, 50, 60 new things next to big things on LinkedIn, and in theory, according to the influencers, this is where you should be, and you're like, they're talking about something 60 steps down the line from where I'm currently at. I'm still trying to get off the starting line and do the basics. And so the first antidote to this is to realize that if that describes you, that describes your organization, oh my God, are you not alone? Every organization that we work with, sooner or later, someone's going to say something to the effect of, "Yeah, we're really behind. Our company is really behind. Or our industry is really behind." And I want to reach over and sort of pat them on the shoulder and say, "There, there. You're saying that because you think you're, in some sense, alone in being behind."

(08:26): The reality is, because I get to see all of these people, the person telling me this works one place and has worked that place for a while, but me and my colleagues here at P3, we get to see lots and lots and lots of organizations, and we see basically the same things everywhere. So that's the first piece of antidote to this starting line FOBO, it's okay. Almost everyone is still on the starting line or within sight of it. If they've started, they haven't gone over the first hill, they're still visible. Now getting off the starting line is really the next antidote to the starting line FOBO, and it's no accident this is a huge part of our business here at P3. It's not the only thing we do, but it's a very, very, very large percentage of what we do, and it's definitely our favorite thing to do.

(09:12): Let's get moving. You can absolutely get moving and you can achieve so much in such a short period of time, so it's okay to be where you are and it isn't really that hard to get started. And if you allow me just this tiniest bit of commercial self-promotion here, I want you to know that it's really easy to get off the starting line with our help. Okay, moving on. One of the things that's been coming up in our Steering Committee group, the LinkedIn group, which you can still join, just search for Raw Data by P3 Adaptive on LinkedIn. Tortured relationship we have with this platform, isn't it? Anyway, one of the things that's been coming up in there is that Microsoft's pace of innovation with this whole fabric thing is really unsettling, I think primarily to practitioners of BI in this space, but also to business leaders who've been leaning in on it.

(09:59): Whether you're a practitioner or a business leader and you've been leaning in on Power BI and you've felt like you've done well with that, does it feel like Microsoft has now come and pulled the rug out from underneath you saying, "Hey, you thought you were doing great? Now look at all of this stuff you don't know." I think this is the easiest one to deal with. So good news. A big part of the FOBO associated with fabric, we can just attribute it to Microsoft's marketing, and I don't really think they're really doing anything wrong here. I'm not criticizing their marketing. It's just more sort of a side effect of how they're doing it. To talk about it the way that they are, which is sort of like this vague umbrella that does everything and changes the entire world, that is the right way at a high level anyway.

(10:42): That's the right way for them to be talking about this in the marketplace. But if you've spent the past N years of your career getting up to speed and getting competent with the Power BI power platform centric version of this world, vague and changes everything are kind of kryptonite to here. Reading between the lines, I can sort of see that some people are thinking like, "Oh my gosh, we're going back to zero, square one." They're almost feeling like it was the day that they first cracked open a DAX book or something. And so here's an alternate version of Microsoft's marketing, and see if this one feels a little better because it's every bit as true as the other one. It goes something like this. Power BI conquers all. Or everything you know about Power BI just became three times as valuable. In the same way that you or your organization incrementally got to know Power BI over the years, some of you might've even started in Power Pivot in Excel.

(11:40): There's that first day where you build a data model, a Pivots file in Power BI desktop, and maybe you didn't have the cloud service yet. You didn't have a place to publish it, or you did have a place to publish it, and you weren't able to schedule automated refresh immediately because you were missing a gateway or one of the data sources was improperly configured, AKA requiring manual intervention in order to be auto refreshed. Maybe there's that first time someone tries out like row level security or something like that. In all of these cases, you've got something confident to stand on. You've got this island of confidence and you're adding on little bits at a time, like a little sandbar here, a little sandbar there.

(12:20): If you feel comfortable with your environment, you can add to it incrementally, and if fabric were being marketed as Power BI+++, I think it'd be a lot clearer to you that, oh, yeah, you look down, oh, wow, I'm still on this island of competence, this island of confidence even, and they've just dumped a whole bunch of new sand out there in the water that I can start using to expand the island again, your existing Power BI models being a jumping off point for creating AI, holy cow, Power BI professionals and Power BI savvy organizations can now become AI savvy through an incremental add to the island type of model. Data activator, the thing that scans, looking for outliers, looking for alerts. You're looking for things that you'd want to know about. Guess what it's looking at? It's looking at your Power BI model. Oh, yeah, that's that thing we used to call dataset. I call it data model forever, but it was called dataset and now it's called semantic model. Yeah, got to love that naming. But yeah, net net, the fabric induced FOBO, I think that's going to be completely okay.

(13:28): Okay, now let's come to the third flavor of FOBO. It's the AI FOBO. Oh, boy. First of all, in the movie Gremlins, you throw water on the gremlins, they multiply. AI has been throwing water on these LinkedIn influencers. AI is the perfect umbrella of topics for LinkedIn influencers to use to keep you off balance. Couldn't have been designed to be a better thing for inflicting FOBO. Number one, it's very different. It doesn't resemble all the other things that we've been doing. Writing formulas, creating script. Heck, even just looking at charts, right? All the things that we know, AI is very, very, very different from it. That's number one. Number two, it's also many different things. Which kind of AI are we talking about? Are we talking about generative AI that writes stuff for us? Writing paragraphs? Are we talking about writing code? Are we talking about writing script? Then there's another flavor at least where it's looking at your data and coming up with things, sort of telling you things that a human being wouldn't necessarily notice.

(14:30): It can be making predictions about how certain things are going to go in the world, how certain customers will behave. There's chatbots. And when a single topic decomposes into many subtopics that are all very different from each other, that just adds to the confusion. Again, perfect for unsettling people. But there's something else about AI that is kind of like this time it's different. We don't know how far it's going to go and when. For example, I had a brief exchange conversation on LinkedIn a few weeks back. I think this was during all the OpenAI drama with Sam Altman and all of that. I think someone was saying something like, Microsoft has such a huge lead in this space, in this AI space, thanks to their open AI partnership that no one's going to be able to catch them or something like that. And in a moment of deliberate vulnerability, I waited in and wondered aloud, to what extent is this AI thing capable of providing a durable competitive edge to a software vendor like Microsoft?

(15:31): Is it incremental where you get out to a strong lead and you can defend that lead, you just keep running and the other people like Google or whatever are slow to keep up, versus is it leap froggy where there are tech breakthroughs that suddenly erase all previous competitive advantage and put it back to zero? The consensus that came back at me was, oh, no, no, it's very much incremental and it's just all about training data. Microsoft's got access to all this great training data and all of that. But even in the OpenAI case, as the story came out later, best we can tell, the reason that the board wanted to throw Sam Altman out was because he had been aware of what sounded like a leap froggy jump in capability in their models, their AI models, and hadn't been telling the board about it.

(16:21): So even though in some way the LinkedIn consensus in that brief exchange I had was it's incremental, it's all about the training data, it's very grind, grind, grind type of thing, 10 days later, we're hearing about an example of something that sounds more leap froggy, and I think we all kind of intuitively understand that. We understand that a year ago we weren't really even talking about any of this stuff, and suddenly in the blink of an eye, we're completely robbing a competitor of half of their web traffic via AI tools. Is that exponential pace going to continue? I said this on a previous episode, if we could all know where this was going to end, even if where it ended was a very radical, radical place, I think we'd all feel better about it knowing that it's going to be 10 times more capable than it is today, and that's going to be where it plateaus, if it does plateaus. That's the thing, right?

(17:15): So there's that asterisk. We just don't know how deep this AI hole is going to get. We don't know how many jobs essentially it's going to come for. Before I come back to what I think this means for us data professionals and the people we work with, what this all means to us, I want to just briefly acknowledge some of the humanity of all of this. Those of us who are now looking at AI and going, what does this mean for our profession? Deep, deep, deep down, the fear of obsolescence that it causes us, stop and reflect just for a moment on how this same sort of thing has been coming for others for a very long time. A big, big part of the social divide that we're feeling here in the United States in particular here lately is because so many formerly good jobs have in one way or another disappeared over the past few decades, and that's largely been a blue collar phenomenon, but there was a time when there were a lot of really good blue collar jobs in this country.

(18:13): Many, many fewer today. And those of us in the knowledge worker space have been sort of insulated from all of this, and now that we can all feel these forces turning and looking at us, in the midst of navigating it, in the midst of defanging the FOBO, what I've been trying to do is also use it as a moment of empathy. There are echoes of the steel mills of the 1970s in the copilot of today, and thus concludes this mini episode of Deep Thoughts by Rob Collie. I am kind of helped by the fact that in some sense, I've seen this movie before. Take for example, in 2010, I was already outside of Microsoft. The number of people in the world at that time who believed that this whole DAX and Tabular thing that was in its infancy in Power Pivot, that this whole approach to things was going to replace SSAS Multidimensional.

(19:06): Now, it doesn't matter if you don't know what that is, who cares? But there had been a dominant technology in this space for a decade plus, and a whole community of professionals had grown up around it, and Microsoft was now producing an alternative to it that was aimed to be learnable by far more people than had ever been able to learn SSAS Multidimensional. And I was one of them. I was one that had tried to learn SSAS Multidimensional and was unable to. So now in 2010, I'm running this blog and I'm just over and over and over again saying this is the future, and I was mostly intending that to be an encouraging message, encouraging other people like me to take it up, to come on board, but at the same time, I was also in a way running afoul of the community that was established in the old tech.

(20:00): I was a threat to them in a way. I was someone causing a form of FOBO to them. Now, this version of me we're talking about is 13 years younger than I am today, and I probably relished the FOBO spreading component of what I was doing a little more than I should have. I would be a lot more, I think, gentle about that today. Of course, part of the dynamic, if you're the person spreading FOBO, whether intentionally or not, is that the existing crowd comes for you. They come after you. So counter-attack, I would fight back a lot. Anyway, if I was doing that today for the first time, knowing what I know now, I'm sure I would handle it differently. I have been the interloper. I've been the one that came along saying, I'm the meteorite, you are the dinosaurs. And let's take a look at what happened in that first round.

(20:50): So the people who practiced SSAS Multidimensional thought their jobs were at risk, and unless something different happened in their career just in general, all of those people transitioned over from SSAS Multidimensional to SSAS Tabular, and they ended up loving it. And most of them didn't really lose their expertise edge either because there's so many different degrees of skill that you can have with SSAS Tabular. Marco and Alberto, the SQLBI crew, they're still at the top of the mountain and it just so happens it's a much, much, much bigger mountain. Even more importantly, the amount of work available to the SSAS crew, and if you use Power BI today without even realizing it, you're part of the SSAS crew. The amount of work available to SSAS professionals has exploded. I don't even know how many zeros we would put on the multiplier, but if it were 10 or even 100,000 times the amount of work available today that was available before, that wouldn't surprise me.

(21:52): And similarly, if you were coming from the Excel world and you've been slinging VLOOKUP, VLOOKUP, VLOOKUP, or if you were one of the cool hipsters, you were doing index match and you were writing these things over and over and over again, this wasn't valuable thinking. This was like sweat equity, and then Power BI comes along with its relationship model and just wipes all that away. Power BI comes along with Power Query and all of your manual data munging that you've been doing with a hodgepodge of macros and sort and copy paste and all that kind of stuff, all of that goes away. No one cried. It created time for you to go do more valuable things. So here's the statement I'm going to make. If you're a data professional or if you're a business leader who has been gaining a lot of competitive advantage by adopting as an organization data technology, everything that's coming for us in the AI space is going to be incremental in terms of what it does for us.

(22:52): We're not going to wake up tomorrow and discover that this new AI breakthrough has suddenly replaced us. Something like copilot that helps us quickly generate some DAXs for a measure, okay, think about it. If all that's doing is saving you keystrokes, fine, what's the problem? Just like if you wrote the formula yourself, you're still going to have to go validate that it works. You're going to have to test it. Remember, AI is really just machine trained intuition, and we all know that intuition is unreliable, and you turbocharge intuition, it's still going to be unreliable. It's still going to miss things. It's certainly not going to be able to connect all of the dots to form a cohesive picture of all the things that you're trying to do with your business. It's not going to do that. Now, I did say earlier that one of the scariest things about the AI FOBO, the asterisk on it, is that we don't know how deep that hole is. Here's the thing. The day that it becomes capable of replacing the things that we're doing is the day that the world ends anyway. The world that we know anyway.

(23:58): That's the point at which there's no need for humans and we're all either going to be sitting on the beach sipping machine created pina coladas because work isn't necessary anymore, or we're going to be living in some sort of dystopian terminator matrix style world, in which case, lacking a job is the least of your worries. The middle ground where this stuff makes us obsolete in a world that remains relatively recognizable, I just don't see that at all. Can't ignore this stuff, if Copilot's there, you want to learn how to use it, you want to learn for yourself what its pros and cons are, what its limitations are. If there's something you can be doing connecting AI up to an existing Power BI model that's now stored in OneLake, whether to glean insights and patterns that you wouldn't have been able to spot on your own or to fill in additional predictive columns in the model, assigning a probability of closure or a probability of a win or things like that, again, these are incremental things you add to your island.

(24:54): Go add to your island. It's okay. In the end, it's probably going to land in a place just like before, there's a lot more work to be done, a lot more opportunity to apply it, and you spend an increasing percentage of your time as a valuable thinker and less and less of your time as like a monkey banging on a keyboard just typing out the same code over and over and over again. The same formula over and over again. No one's going to object to that. All right, so in closing, number one this week, make sure you drop FOBO into conversation at work at least once. And remember, don't define it ahead of time. Make a mask. Number two, FOBO of all three varieties we're talking about here, they're all going to be okay. If you're on the starting line, guess what? Everyone is, or very, very close to it. Fabric FOBO, oh, no worries, is 100% an adding to one's island. They just need to modify the marketing to make us feel better.

(25:48): Power BI conquers all. AI is going to be just like every other technological leapfrog step that we've taken, including the leap from SSAS Multidimensional to Power BI. And if it's ever not like that, you're not going to worry about it. All right, hope you've enjoyed the first ever solo pod. Please let us know, and we'll be back next week with one of the normal format episodes. Until then,

Speaker 3 (26:10): Thanks for listening to the Raw Data by P3 Adaptive podcast. Let the experts at P3 Adaptive help your business. Just go to Have a data day.

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