Making Data Simple: End of tech companies
00:30 Connect with Al Martin on Twitter (@amartin_v) and LinkedIn (linkedin.com/in/al-martin-ku)
01:00 Connect with Rob Thomas on Twitter (@robdthomas) and LinkedIn (linkedin.com/in/robertdthomas) and read more of his work on his blog https://www.robdthomas.com/
02:30 Big Data Revolution By Rob Thomas & Patrick McSharry, The End of Tech Companies by Rob Thomas
04:35 Find Rob Thomas' first blog post here: https://www.robdthomas.com/robdthomas//2013/02/patterns-in-big-data.html
05:30 Connect with Dr. Patrick E McSharry on LinkedIn linkedin.com/in/mcsharry, his personal website mcsharry.net or Twitter @patrickmcsharry
14:10 Connect with Warren Buffett on Twitter (@WarrenBuffett)
14:40 Connect with Clayton Christensen on Twitter (@claychristensen) and LinkedIn (linkedin.com/in/claytonchristensen)
24:50 Learn More about DomusKids on their website http://domuskids.org/ and connect with them on Twitter @DomusKids
26:15 Above the Line: Lessons in Leadership and Life from a Championship Season by Urban Meyer & Wayne Coffey
26:30 Chasing Excellence: A Story About Building the World's Fittest Athletes by Ben Bergeron
Hungry for more? Check out our other podcast episodes of Making Data Simple:
- Episode 1: Making Data Simple: The big data problem
- Episode 3: Making Data Simple: A new definition of client care
- Episode 4: Making Data Simple: Will machines take our jobs?
- Episode 5: Making Data Simple: Growth Hacking - Not just for start ups
- Episode 6: Making Data Simple: From 2D to 3D -- Augmented reality data visualization
- Episode 7: Making Data Simple: The 5 areas businesses MUST get right
- Episode 8: Making Data Simple: How data science is helping to improve aviation
- Episode 9: Making Data Simple: Making data fun & easy with Caleb Curry
- Episode 10: Making Data Simple: Data movement at size and scale
- Episode 11: Making Data Simple: Cloud computing, part 1
You’re listening to Making Data Simple. Where we make the world of Data effortless, relevant and yes (music change) even fun
Al: Hey everyone, Al Martin here, welcome back to the series, Making Data Simple.
Today I have Rob Thomson joining me, Rob is the General Manager of Analytics at IBM.
Hey Rob how you doin’
Rob: I'm doing great Al, nice to talk to you.
Uh so Rob uh, the theme here as I said is Making Data Simple we went back and forth on a topic that best surrounds what we want to focus on and we landed on making data simple because, I want to talk about analytics I want to talk about client experience, I want to talk about data.
All those seem deeply complex and somewhat boring so based on simplicity and making it fun we landed on making data simple.
But what that essentially means is well talk about anything interesting and basically the rules are there are no rules and, we’ll just go and have like a water cooler conversation. I’m not a good interviewer I just want to have a chat, that’s all if you’re good for it.
Rob: Yeah, that sounds good and I think that’s a good headline topic.
So, what’s interesting Al is that if you think about the last decade, while we have a lot of new technologies there’s been major innovation open source. It really has not gotten fundamentally easier for users to get to answers. So That’s why it’s a good theme this idea of make data simple. Nobody has really cracked that in the industry yet. But I’m starting to see signs that’s were getting closer to that which I think is encouraging.
So we brought you in for a lot of different reason but two things above all.
One is your experience in analytics and all things data, secondly, you’ve gone farther than most in writing two books. The latest one being “The End of Tech Companies and the previous one, Big Data Revolution. You should know that I read both...
I contributed to both. So I hope you got rich and your charity got rich just as well.
I like the stories in The Big Data Revolution. The End of Tech Companies...that was to me was kind of like a Jerry McGuire mission statement. In a good way. And I got several questions on that one.
Al: Let me start though, just for the audience…you held many roles in your career> can you quickly talk to your experience, interest and passions. What brings you to your current role?
Rob: Yeah, I started with IBM in consulting and somebody gave me advice right when I joined IBM and they said: try to find a way to get multiple experiences with multiple companies really fast.
That was good advice.
Sounds very basic but it was good advice.
Consulting definitely gives you that opportunity. The main thing I learned from con. Is that, most companies don’t know what they should be doing and I don’t mean that as a negative its not that they’re not smart people it’s that they give within their role their business model their customers and its really hard to think outside of the organization.
The greatest value you could add in consulting is to bring a different perspective to how companies should be thinking about their challenges.
So learned a lot from that.
Went to different roles at IBM…microelectronics, then came into software doing M&A for a number of years and then you know, spend most of that time in analytics. So, A few diff things but the big learning for me all along the way is that, an outsider perspective can really help companies in terms of figuring out where they want to get going.
So the first book, I said I already enjoyed these stories, they were great and I have to admit that I still continue to use several of them in the presentations that I have.
What compelled you to write the first book and why did you start with the Big Data Revolution?
Rob: You know I never had a goal to be an author so it was kind of a fluke but, sometimes opportunity presents itself as flukes. I had actually written a blog post, I don’t even remember what the title was at this point and out of the blues I get an email from somebody at Whyley which is, top ten publisher in the world, based in the UK and she said, “Hey we… I came across your blog post, I think that would make a great book. Are you interested in doing that?” I never thought of it but based on that I said sure.
Kind of started the process, built and outline and my main thesis was, everybody knows they should be doing something around the topic of big data but most people don’t know exactly what it is and the best way to learn is from stories so I kind of set out to put it in terms of some diff examples and diff industries and so it was an interesting process.
It was a lot more difficult than I bargained as part of the research I was doing to find some stories, I ended up in touch with a guy, oxford professor and I was interviewing him because he’s done some work in actuaries in the past and he said through the interview process he said, “Hey are you interested in a co-author for the book” and he got me at a moment of weakness because I was dying for somebody to help at that point
Rob: So uh, he ended up being the co-author, Patrick McSharry is his name so learned a lot from him in the process as well.
Al: Well stories are definitely…your…you do them well.
Big Data Revolution, you know to oversimplify, you know I see it as industries transforming with data and then finding information through trans or patterns recognition. What is your much better definition?
Rob: I think that’s a great definition.
The company that sticks out to me the most, that I profiled in the book is a company called Co-Star which most people haven’t heard of but, they have basically gathered all of the data in the world on commercial real estate. And instead of being just a data provider, like you Brad Street who pretty much provides data. Co-Star had the insight to say we can actually build data products based on all the data that we collected and they have really built you know, knock on wood it appears to be a recession proof business because anybody who is trying to do anything in real estate, whether its building new commercial real estate, building new, acquiring, renting, leasing, if you want any data on what’s happening, you pretty much have to go to co-star and to consume one of their products and so.
Its not just the data assets they collected but it’s the way that they built them into the products that were consumable by anybody. Back to your point on making data easy. I thought it was one of the best examples I have seen of a company that has really converted this idea of data into a strategic asset.
Al: One thing I was curious on was whether, did you find when you did the research, did you find what you expected or were you surprised? And I guess it was what? couple years now. Now do you look back and do you say did you get anything wrong?
Rob: So two different questions there.
Definitely got a lot of things wrong. You know my main learning from the book is that it’s hard to write a book that is based in a period of time. It’s a lot more efficient to write a timeless book, because then you know nothing changes and the lessons are the same.
Look I mean as I got into the more technical portions of that book a lot of what I wrote about was ahu? There was no mention of Spark or any of the modern things that you see in and around Big Data. And so I guess I’m not sure I got it wrong, but certainly it became irrelevant quickly because were in a market that changes so fast.
That being said I think the stories of transformation, how companies move from one the next, some of that is still playing put. One of the chapters was on actuaries and how I thought data would really reinvent the insurance industry and what it meant to be an actuary. I would say that hasn’t happened yet. That’s still very much in the mode that its always been in because it’s a cultural challenge more than it is a technology challenge. So I think some things are now out of date, some things are still yet to happen. but that’s part of what you learn in the process.
Al: So you know to that point, what surprises me is that, we’re still seemingly in a very early trajectory of all things data.
Speaking of real estate, I listened to a podcast yesterday and a company called VTS, I don’t know what they stand for but they’re transforming asset management and real estate leasing. The owner was in software and then went into real estate and found that they’re still all using spreadsheets so this is what he started.
And if I could go on, IOT by example, I think that’s largely untapped. I hear about these smart buildings, I travel all over the world. I have not went in one true smart building that I can recall. Connected cars still on the very early onset I guess, and I think those that are doing some IOT are really aggregating in data lags versus performing analytics on the edge. Which all inspired me to do this podcast. But back to your point, are we still in the very infancy of this?
Rob: Yeah look if you use a baseball analogy I think the reality is that were probably in the second inning of how data really becomes a strategic asset and a competitive weapon.
You know the first couple innings was about how the economics have changed so it’s easier to collect massive amounts of data, it’s easier to analyze large amounts of data, but none of that has anything to do with actually back to your theme of making it easy, making it consumable, turning it into better business decisions. That’s why I said, were probably in the second inning so very early.
Al: You know I’m really encouraged about the opportunities in machine learning.
We tend to you know, data has always been in the past, we are always looking backwards to look forwards meanwhile were oriented to the future, so I think that is probably the biggest game changer or at least I see, in the near future. I don’t know if you see it the same way
You know I think all these things take a certain amount of patience. People forget this, if you use the automobile industry as an example. The first automobile was driven down the streets in Detroit in 1896 and it was 20 or almost 25 years later when Henry Ford developed the Model T, and actually brought that to the mass market. So it was basically a gestation 25 years period to go from the first example of success as something that was adopted to scale for a mass market.
And that’s where we are on data, you mentioned machine learning, I think we’re early days on that. I think the difference here is, what took the automobile 25 years, is going to happen in a period of 5 years for things like machine learning and data. AI, that’s much further out.
But machine learning is real and that’s going to put out really fast and I think the biggest cultural adjustment that most organizations have to make is that they think there is a system they’re going to figure out over the next ten years they’re going to be left behind, they’re going to be irrelevant. The pace is definitely increasing.
So let’s pivot to The End of Tech Companies. The End of Tech Companies, is that a catchy title or do you believe that we are truly in a paradigm shift where traditional companies and tech companies are going to be synonymous.
Rob: I do think it’s a catchy title. I think that’s why
Rob: Which has been good. But I thinks its effective because its true. I mean we always lived in this world where you are either a tech company or you are not and that’s been assumed and there are certain attributes and Oh, its great to be a tech company because you can grow really fast but you have to reinvent yourself every few years. That is now at the doorstep of every company, regardless of what industry you’re in. Which is, same rate of pace and change, every year the SNP500 20 companies drop out at a minimum.
That’s never been the case before where it’s this rapid of change. So yeah the idea behind being a tech company was, every company, Step one was that you recognize that you have to become a technology company. That’s step one. Just recognize it. Step two is understand the implications of that and what it means for you and then step three is to think about how are you going to reskill your work force to live in that world. And that’s what every company is facing, you know, to use a few different examples in this , it’s even industries like agriculture where you would say that’s the last place that you’re going to see a massive adoption of massive technology I wrote about that a little but in the first book, the second book brings that to a fevered pitch saying hey look its actually happening now. I think its very real.
Being a tech company is more about what does this mean culturally for a company and how our company is going to adapt in an environment that they have never seen before.
Al: You know one thing, you referenced Warren Buffett in the book and I, follow disciples of Warren Buffet, not nearly as well, but I try to follow it. And the interesting thing is he talks about the four M’s of investing, Management, Mode, Margin of safety and Meaning. And for the longest time his mantra well still, his mantra is that you got to understand that business end to end that’s the meaning piece and he would not invest in tech companies for the longest time.
He used to joke with Bill Gates that, “Na I just don’t understand it, that’s your business I’m not getting in that business”. The interesting thing and that’s what I thought of with your reference to End of Tech Companies and Buffet is that since that he has invested in Apple, he’s invested in IBM and could, so to your point it could lend itself to what you’re suggesting that everything is a tech company maybe everything is not but they’re all kind of blending in together. And, I guess that’s not so mysteriously because most companies are coming closer to client now.
I mean I think what’s changed is that, obviously, the economics have changed. So it used to be impossible for the average company to make big investments in software or IT, obviously with the advent of cloud it’s a lot more accessible to anybody so that’s definitely changed. Secondly is skills are more available on the market, there are a lot of people now that know who to write code, develop code, there’s people that are building new skills in that.
That doesn’t mean everybody has all those skills that they need. But it’ s certainly more accessible than it was even at the time that I came into the workforce a number of years back.
So the bottom line is, a lot has changed about the environment and now companies have to decide, one is, again I’ll go back to where I said, you have to one accept that’s the world that you’re in now and then two you have to figure out what you’re going to do about it and three is understand what is my workforce going to evolve to in order to compete in this environment. That’s going to be easy for some companies, it’s going to be hard for others, but certainly something everybody has to do.
Al: So I got a few more specific questions and they’re kind of around your …you talked to four macro shocks but let me list them here because I think they’re good.
Number one, the market is undergoing a digital transformation. Number two, the internet is democratizing traditional advantages. Number three, the price of computers plummeted and number four the skills of success in many professions and industry are changing. But one of the questions I had was within some of that is that, you talked to new measurements, and the value of human capital and you made a specific point to call out enterprise value per employee, and revenue per employee. Is you seeing Metrix as clear litmus tests in terms of whether your company is heading the right direction. Can you expand upon that, is that the same as the traditional E to R measures or is it looking at the industry completely different or looking at your company completely different?
Rob: I think the point is that a lot of companies’ kind of I’d say, their success is the multiple of the number of people they have. You certainly see that in traditional consulting businesses, or labor-based businesses and then you ask the question: What happens though when you start to automate a lot of those things?
Doesn’t mean that people go away, actually people become more valuable but the leverage that you get out the average person goes up dramatically. And so, the reason I did that was really just to get companies to think about: How do you get more leverage out of your workforce? It can’t be about, my productivity driven by how many hours everybody works. And that’s why I kind of went into you have to reinvent how you’re working look at the tools you’re using as a company, because you got give greater leverage. There a finite amount of time that anybody is weak. You got to give maximum leverage out of your employees and that comes down to your business model.
So one of the shocks I talked about was distribution. When a company’s primary route to market is through face to face sellers, feet on the street then by definition your upside is limited by the number of people you can hire. Thats very different than if you say look were going to do 60% of our growth goes to market through feet on the street through people and were going to do 40% through the internet. And you have the digital channel and the leverage on a digital channel is unlimited because you’re open 24/7. The good news is that the internet never needs to sleep they never need to sleep you know the internet just wants to work.
So it’s really rethinking distribution because it changes the economics per employee and that’s really hard for most companies to do. And you know I was tiling to an investor a couple weeks ago and I said the question you should ask in every board meeting is: What are we doing to change how we get to market? Can we sell our products through the internet and if you’re not a software company, most companies will say that’s impossible, but the reality is some of their competitors are doing it already.
Al: You know that leads me directly to a question that I had. You talked to the best business models in the internet era, being high volume and low price, and then you have a company in my mind like Walmart that could say, “Check, Got it”. But, they depended on a differentiated distributed, as well as low price for a long time so, I guess what I’m saying while they have high volume low cost are they using they losing their differentiator in distribution that makes them or puts them in trouble or in imperil.
Rob: You know you have to give Walmart a lot of credit, they kind of reinvented themselves throughout the years. Maybe not in the digital means were talking about but I mean they used to not sell groceries but now they have become the number one grocer in America as an example. So they have definitely proven the ability to do different things.
I think the opportunity for them is how do they merge online and offline worlds. When they launched Walmart.com they ran that as a separate business, separate financial and intentionally kept it separate which I think was the right decision at the time but clearly the opportunity is to merge the online and offline worlds that’s clearly what’s behind the Amazon and Whole Foods acquisition and it think that’s the opportunity for Walmart. And were rooting for them I think they’ll figure it out because they’ve always figured it out.
Al: So in retooling and reskilling, retooling I get and I agree, tools like Slack can change a culture and I truly believe that. In terms of reskilling though I know that the media is getting some play with ML and AI eliminating jobs which I feel to be garbage I don’t know what you feel about that but I think it will absolutely change jobs though so if you’re going to school right now, coming out of high school by example and you’re reading The End of Tech Companies, what would you advise your kids to do, what discipline would they head in?
Rob: Look I think everybody should learn how to write code. It doesn’t mean you have to spend your job as a developer but you know back when we were in school the fundamental, the core skill was learning how to type, I think now that course is to learn how to code., Not that you’re going to be a coder but just understanding it as a discipline is very important. I think it’s a great time to be coming out of school because if you know anything about coding and modern technology there’s going to be a job for you.
There’s actually kind of a job security if you chose the right thing. So, I think that I think it’s a really good time for that. You know my point on reskilling is that I think everybody, regardless of where you are in your career you got to have a curiosity about what’s happening and a willingness to go learn new things and there’s no better time for that, whether the topic is machine learning, python, software development you know just to name three I mean thing you know anybody just by putting the effort into it you can become smarter than 80% of people around you on those three topics and that’s going to give you a lot of job security. So I think people just got to have the curiosity to go learn it.
Al: So I have a several of questions, I wanted to talk about the seven vital signs that you have, how to optimize capital in the maker era but I’m going to ask you this question, and this was interesting to me.
You have actually referenced the innovators dilemma and it’s what I have read and listened to some of my favorite talks around Clayton Christenson, about disruptive innovation and the reason I guess I like him so well is that he talks about how great leaders can essentially give their business away and felt like that’s what you were kind of referring to in the end and I would like to quote something to get your reaction to it.
He says, based on you know essentially being good leaders and giving your business away is, he says, the reason is that good management itself was the root cause, mangers play the game the way it was supposed to be played, the very decision making and resource allocation processes that are key to the success of established companies are the very processes that reject disruptive technologies. He talks about carefully listening to your customers, tracking competitors, investing resources to design high quality etc. You know it’s almost like you’re damned if you do , damned if you don’t my point is how can you avoid those traps being big companies that are doing well and stay on the right side and continue to reinvent yourself.
Rob: Unfortunately for most companies it requires a crisis. Which is unfortunate, and part of what I was trying to get at in the book, a crisis has arrived whether you know it or not, because very company has to evolve to this new world. And so I hope most companies don’t wait for their crisis but sometimes that’s what it takes.
What I do like about Clay Christensen’s work is his whole mantra is he’s going give you a theory and then you can think about how that applies in your role. He is not providing recipes he’s not saying this is how you solve the problems, he’s saying this is the basis or a theory of how you could solve the problem and you have to think about how this applies to you and I think that’s a really important point for everybody to remember. There is no recipe, for becoming a tech company or surviving in this. It’s going to be different for every single company but I was hooping to give enough tools or stories so then companies can apply that in their world because it’s going to be different for everybody.
Can I just get a quick lightening round with you just to ask you a few questions?
Al: Number one I see all profits from your book are going to a charity called Domus I think?
Rob: Yeah Domus is the name. I started working with them a while ago, they basically for children that don’t have all the opportunities that some of us had, getting them through school and helping them learn how to earn a livable wage. So it’s not trying to send them all to MIT. It’s how do we get them on a path to where they can earn a livable wage which I thought was great.
Al: Fantastic, alright people should check that out, we’ll have it in the show notes
What are your daily habits that you find successful
Rob: I like exercising, love reading, try to write a little bit every day, may not make the light of day but it’s a good way to think.
Al: What, you know I think it is a great time to learn. Follow up quick question on that, I feel like there’s so much information out there to learn unlike never before, how do you create sanity around it and don’t overwhelmed while the material, I mean how do you keep focus?
Rob: It's difficult. I do think twitter is underrated is as a way to learn. But you have to be really careful about who you, there’s way too much noise on it so you have to curate who you follow and then focus. Picking a few topics or a few people you want to learn from or learn about, focus is key learning.
Al: Okay two more, favorite leadership book?
Rob: Urban Myers book, football coach called Above the Line it was actually really good, surprisingly its really good.
Al: What are you reading right now?
Rob: I just finished a couple, I just read a book about a guy that trains people in CrossFit, I thought that was kind of interesting. The name escapes me but I’ll send it to you later and you can add it to the notes. That’s the most recent book I read.
Al: Fair enough. Hey you been a really great sport man is there anything else we didn’t address that you wanted to get out?
Rob: No, I appreciate you doing this.
I think if we go back to where we started. its really hard to make things simple in the current environment but I think that’s probably a superpower so I would encourage everybody to think about that in anything you’re doing.
Al: So everybody as I close I want to say this to everybody, I want to say this to you as well Rob is that, having the ability to be an entrepreneur within a big company like IBM is unique and I greatly value that, that’s one of the reasons why I’m here. You know I think it’s one of the things that you foster and promote is change, so thank you and thank you for your insights today.
Folks, everybody, hope you enjoyed it, until next time, wheels up.
Outro: Thanks for listening to the Making Data Simple Podcast, where we make data fun, be sure to visit IBM.