Show Notes

In this episode of Foresight Radio long-time colleague and serial entrepreneur David Friend joins me to look at the dramatic ways in which data storage and affordability will change not only the way we do business but also make some of the greatest innovations of the 21st Century, such as AI and machine learning, possible.

About David Friend

David Friend is the co-founder and CEO of Wasabi, a revolutionary cloud storage company. David’s first company, ARP Instruments developed synthesizers used by Stevie Wonder, David Bowie, Led Zeppelin and even helped Steven Spielberg communicate with aliens providing that legendary five-note communication in Close Encounters of the ThirdKind.

Transcript

TK: Welcome to Foresight Radio. I’m your host, Tom Koulopoulos. On each episode, we explore the many trends that are shaping the way we will work, live and play in the future. Our focus is on the disruptive and transformational trends that are changing the world in ways that are often invisible. Our objective is simple: to give you the knowledge and the insights that you need to better manage the future. Foresight Radio is sponsored by our good friends at Wasabi. You can learn more about them at Wasabi.com. In this episode, I’ll be speaking with my long-time colleague, David Friend. David is currently the CEO of Wasabi Technologies, the sponsor of Foresight Radio and my co-author for the “Bottomless Cloud.” His career spans an amazing seven start-ups. Prior to Wasabi, David and long-time business partner, Jeff Flowers, founded Carbonite, the world’s largest consumer backup company which today has a market cap of over $1 billion. Our conversation covered some very diverse topics from his early days developing synthesizers for The Who, Led Zeppelin, Stevie Wonder and The Beach Boys, to his vision of the future in which data is the fuel of innovation and progress. Here’s my conversation with David Friend: Dave, we’ve got an interesting connection. Back when I was a kid, I was a little bit of a geek as well and my Dad was an audiophile so he taught me all about audio components and believe it or not, the first thing that I remembered doing with my Dad was checking out a vacuum tube at Radio Shack to make sure it still worked. You started your career as a bit of a geek. Tell us about your first company, ARP, and what you were doing there because you had some pretty cool experiences with some interesting characters. DF: Yes, even before ARP I also have a music background and always been interested in music since an early age. When I was a kid growing up in Westchester County, every spring there was house cleaning day. I lived in a relatively affluent neighborhood and people would throw away perfectly good radios and TVs and things like that, and I’d go around with my little green wagon and collect them all and bring them home and strip them for parts. [Laughter] TK: That’s a great image. A little green wagon, not a little red wagon. DF: Yes, a little green wagon. I still remember that wagon. I continued to pursue my interests in both electronics and music through high school and into college. At Yale, I had a bursary job building equipment for the Electronic Music Studio, being an Electrical Engineering major and also a major in Music. So, I would sit around with composers and also was a composer myself. I’d sit around with the faculty people who were composers and trying to understand what they were trying to do in terms of creating new sounds, and new textures and thinking up electronic devices that I could design and fabricate for the Electronic Music Studio there. I went on to pursue that in graduate school, and then my work at Yale had gotten written up in the alumni magazine, and one day, I get a call from somebody in Boston who says “Gee, I’ve got some money. I want to start a company and make synthesizers and I read about you in the Yale alumni magazine. How’d you like to come up and join me?” TK: What year was this? DF: That was 1970. TK: The ARP synthesizer was an incredible breakthrough technology. You can hear it in so many different songs from that era. Deep Purple used it in Space Trucking and Elton John used it in Rocket Man. Even Herbie Hancock had used the ARP but here’s a less well-known tune. See if you can guess this one. [Audio Presentation] That’s the soundtrack for the BBC’s Doctor Who. While ARP synthesizers were not digital, they did lay the foundation for the ultimate datafication of music which today has resulted in us carrying thousands of digital songs in our back pockets. Back to my conversation with David: Synthesizers must have been pretty damn new at that point, I would think. DF: Yes. There was one company in the market called Moog. They were mostly used in electronic music studios at universities for making avant-garde music, but somebody had made a record called “Switched on Bach” that was all done of Moog synthesizers and this really opened people’s eyes to the idea that you could create this huge variety of sounds with a synthesizer. We thought we could do a better job than Moog and, indeed, over the course of the next 10 years, we’d be really came to dominate the synthesizer market. TK: You worked with some pretty cool folks, Led Zeppelin, The Who, Stevie Wonder; are there other familiar tunes that I might recognize that includes some of your handiwork? DF: There are countless ones and I used to judge our success on the basis of how many tunes could I hear on the radio in my car between leaving my house in Back Bay and arriving at the factory out in Lexington. One of the things that you learn as an engineer and as a start-up person, once you’ve designed your product and you build the first one, somebody’s got to go and sell it, and the five people that were around the table at the founding of ARP, I was the least worst. [Laughter] TK: The least geek among the bunch? [Laughter] DF: Yes. At least I had a Liberal Arts education, so I was elected to go out and sell the first one, and it didn’t take long to really realize that we weren’t going to make a lot of money or be a very big company selling one-off synthesizers to The Who and Stevie Wonder and Led Zeppelin and that sort of thing, or the universities. That the real market was all those thousands of high school rock bands, and that they want to buy whatever their idols were using. So, if Stevie Wonder had a hit on an ARP synthesizer, all the high school rock bands would go out and buy ARPs. If somebody had a hit on a Moog synthesizer, that was not good. They’d go out and buy Moogs. So, I spent really the rest of my career chasing rock bands for endorsements. TK: I remember you telling a story about a particular rocker being a little disappointed with one of your products and calling you out on it. DF: When people are in the middle of a recording session and their synthesizer dies, sometimes they’re not very forgiving, and usually, this is at like 2:00 or 3:00 in the morning when this happens, and I did get a phone call from the keyboard player with Steely Dan one night and his ARP synthesizer apparently had died on him, and he called up and not very politely asked me to listen to this crunching sound, which turns out was the sound of him pounding a railroad stake through the middle of an ARP synthesizer and attaching it to the wall of his recording studio where it stayed for probably the next 10 years. [Laughter] TK: That’s great. DF: As wall art. TK: You were an artist as well as an engineer, then, by definition. You’ve had a heck of a run. By my count, Wasabi is your seventh company. There’s a bit of a trajectory here. You and I first met when you were at Pilot Software back in the mid-’90s. We were talking a bit about imaging and the importance of storage, but back then, less than 1% of all information was stored in digital form. The rest of it was in paper or in some kind of analog format. A lot has changed since then. Tell us a bit about the trajectory and how you got to Wasabi. DF: Most of my career has been in applications that are involved with the presentation of data or the manipulation of data, data analysis, data visualization and that sort of thing, but underneath all of these things ultimately is data storage. Anybody who likes gadgets and stuff has owned countless string of iPods and iPads, and PCs and laptops, and mp3 players, and all that sort of stuff, but underneath all of those things is a lithium ion battery. [Laughter] I’ve sort of decided that why not make the lithium ion battery and be in that business? That’s what Wasabi really is about. So, the world is generating more and more data, and as the cost of storing that data drops, it just encourages people to create even more data because there’s no point spending any effort creating it if you can’t store it somewhere to use. So we’re in this cycle of - I think we’ve gone over the cliff to the point where data storage is now getting so cheap and so reliable that people aren’t really thinking about it anymore the way they used to. You and I have had this conversation before but I can remember not too many years ago when my IT guy would come running down the hall screaming at me because my mailbox was within 100 megabytes. Now, the cost of storage is so low that why take the risk of deleting something that you might find valuable in the future. With all of the AI and the data mining that’s going on and everything, people are now worried that data they feel has no use today might turn out to be extremely useful tomorrow when somebody comes up with an algorithmic way of analyzing that data that provides them with new value. I think we flipped that point where we now no longer have to worry so much about the cost of data, and I use the analogy of electricity. Unless, you’re doing something that’s like mining bitcoin or smelting aluminum, who cares what the cost of electricity is? Just plug it in and go and nobody thinks about it. That’s where we’re headed with data storage, and that’s where I think Wasabi is leading the charge. TK: This notion of affordability is central to the evolution of every technology. You talk about the lithium ion battery. I think of the transistor. We were talking about vacuum tubes. The transistor made so much possible through miniaturization and affordability that certainly could not have been done with vacuum tubes, so the guts, the infrastructure that drives these applications and these devices is certainly as important if not more so than what we see on the surface when we get enamored by the device. On the other side of that coin, though, you’ve got affordability, and then you have these entirely new industries and value propositions that emerge as a result of the incredible drop in cost. So, by way of example, if I think of AI, I’m not sure AI is even possible with this little storage infrastructure that we have today. You and I have talked about this. It would be too costly. It would be much too cumbersome to develop an autonomous vehicle using today’s cloud. Here’s a little known fact that makes that last point about the importance of data affordability for the evolution of AI absolutely crystal clear. An autonomous vehicle today generates somewhere in the neighborhood of 20 terabytes of data per hour. So, if it’s driven just one hour each day, it would generate seven petabytes of storage yearly. That would cost over $2 million a year. Add the increase in onboard sensors from a few dozen to hundreds of sensors as AVS progress to full autonomy and you may be increasing that cost tenfold. Meaning that storing the data using traditional cloud solutions would cost tens of millions of dollars a year for just one vehicle. That’s just one example of how the affordability of data is absolutely essential for the evolution of AI. Back to my conversation with David: So, when you think of the future, what are the sorts of applications that you think are going to be enabled with this new generation of storage technology and affordability that you talked about? DF: You can see where things are headed. One of the miraculous changes that we’ve seen as the result of affordable storage is GPS and mapping systems, things like Google Maps. People can’t get from home to the supermarket without turning on their GPS system today. TK: My kids certainly can’t. [Laughter] DF: Yes! My son-in-law, the first thing he does when he gets in the car is pump in the destination even if it’s only a couple of miles away. When you think about the amount of data and the completeness of the data that has to go into that, if you were half the time you get in your car and it sends you down a one-way street the wrong way because it changed the direction or a street is blocked off anywhere in the world that you want to go literally, from a metropolitan city like New York to a little tiny island in the Caribbean. It’s all in there. That would not be possible where it not for very inexpensive storage. Where do we go from there? See more and more things like that that are coming up whether it’s surveillance, facial recognition video is just a huge area for growth for Wasabi because you might found that there are things you would never have considered five years ago because they would have been too expensive. Nowadays, it just seem like, wow, that’s a no-brainer to do that. The potential value is huge. As data sets become more complete, then you can start to think up lots of ways to get value out of that data. [Pause] TK: You’re listening to Foresight Radio and we’re taking a quick break to thank our sponsor of this episode, Wasabi Technologies, the leader in the next generation of cloud storage. Find out more about Wasabi at Wasabi.com. Male: Wasabi Hot Cloud Storage is a proud sponsor of Foresight Radio and their mission to help rethink the future of how we work, live and play. At Wasabi, we’re rethinking cloud storage. We’re less expensive than just the maintenance on your current on-premises storage, and we’re 80% cheaper and six times faster than Amazon S3 with no egress fees. See for yourself with unlimited storage for a month. Go to Wasabi.com, click Free Trial, and use the offer code, “Foresight”. TK: Back to my conversation with David: What occurs to me is that many ways the data sets are incomplete today because we’re still using this industrial era model where we want to tier the storage and we want to have archives because archives are less expensive and we want to put things into cold storage or into vaults because the floor space is less in Idaho than it is in Boston. Are all these artifacts that you see going away? Is “archive” even a word that will make sense five, 10, 20 years from now when we think about data? DF: Yes. I think they are going away. You start with very fast and expensive storage down to very cheap and very slow storage and then, the final one is you throw it away. I think all of that, by and large, is going to go away and we’ll have a world where most things are stored forever. It’s just not worth the time and effort to think about how you could cut back on your storage costs. If you have 10,000 photos on your phone, the likelihood is you’re going to have 11,000 and then 12,000 because who the heck has the time to go and get rid of all the ones you don’t really need? TK: I wish I had 10,000 photos. I think, at last count, I have about 27,000. [Laughter] DF: Yes. Well, you’re an extreme case and so that becomes a problem, and then finding what you’re looking for then becomes the job of something like facial recognition or AI, and if you’ve got 27,000 photos and you’re looking for all the photos of your dog, that’s not something you’re going to do manually, but it’s something you can teach an algorithm to do, and this really changes the way you think about your data. So you no longer worry about throwing the old photos of the dog away because there are new techniques coming along that will let you deal with the quantities of data that you have, and I know this is true in scientific experiments as well. If you have a big telescope that’s taking pictures of the nighttime sky, and 10 years from now, somebody discovers a new kind of astronomical phenomenon, you’ve got years of years of old photos you can go back and search through to see if you can find other instances of that. That’s what people are finding right now, is that you can take these data that’s been accumulated from scientific experiments and all kinds of things and mine it over and over again. People are saying “Wow, I didn’t anticipate I was ever going to need that again but guess what? I’m glad I kept it.” TK: There’s a touch of heresy when I hear you say that because we’ve all been raised to think about scarcity is the model by which you build a business because natural resources were what the Industrial Revolution was built on. When we begin to talk about data, we’re switching to what you call this abundant model of data. Data is limitless. It’s infinite. It’s not a natural resource in the sense that you have to preserve it and use the principles of scarcity. I’m curious as to when it dawned on you that that transition was happening, because at Carbonite, I’m sure you began to see some of the volumes of data that people were dealing with. Was there a seminal moment when you said “Oh, my goodness. This is a big problem we haven’t yet addressed in.” DF: Yes. It’s the function of the ratio of the value of the data to the cost of saving it, and at Carbonite, we introduced a much more affordable computer backup product. Affordable in the sense of absolute dollars but also in the sense that we said you can back up as much as you want for one flat price. TK: That was radical and this is 2006 or thereabouts, right? DF: It changed people’s behavior because people used to worry and when you’re paying by the gigabyte, you sit around and you worry about “Gee, I could save $20.00 a month if I went back and eliminated all these old backups,” and then when you went to our model, which was unlimited backup for a flat price, suddenly you see people’s behavior changed and they stopped worrying about their backups and they just let it run. It changed the way they thought about the data from being something they have to worry about to being something that was just there and just worked. So, I think with every decrease in price or increase in value, a whole new wave of things become possible that you couldn’t think of before. Other good examples of that are things like Instagram which is ad-supported and most of the content are photos, it takes up a lot of space. In an era of scarcity where you’re thinking about how do you minimize storage, you probably would never come up with an idea for a product like that. You dismiss it out of hand because who knew what the value was going to be? How much advertising could you sell to support this thing versus the cost of the storage if the cost of the storage is above the value that you can create by selling advertising? It’s not even worth trying to start a business like that. We’re now seeing wave after wave of new ideas coming along where people say “Hey, the storage part is so cheap now. This completely changes the kind of businesses and use cases that I can consider,” so it just creates a wave of innovation and I think in our book, “The Bottomless Cloud,” we talk about the effect of abundant and cheap electricity, and what effect that had on the Industrial Revolution. People were no longer tied to having to locate your factories along rivers where they could harness water power. You could put your factory anywhere. So, it completely changed the way manufacturing took place in the United States and I think the abundance of data storage and the abundance of data itself is changing the way people think about their businesses. TK: [Pause] By 2035, the world will have over one yottabyte of data. That’s a number larger than the number of stars in the visible universe. That’s why David and I teamed up to provide a clear and straightforward understanding of how the incredible power of the cloud and data abundance will fuel the next era of progress through AI and machine learning. Our book “The Bottomless Cloud” is an entirely new way to think about the value and the role of data in building tomorrow’s enterprises. The book challenges the scarcity driven mindset by taking a hard look at how Industrial Age business models are failing us by regarding data as a commodity and a cost that needs to be constrained rather than a near infinite resource that can be mined to build entirely new sources of value and insight. To find out more, visit thebottomlesscloud.com. Back to my conversation with David. DF: Take even something like jet engines. Jet engines now have thousands of sensors on them and every time you take a flight, your engine is going to create terabytes of data which is used to predict maintenance issues and you no longer get your competitive edge by figuring out how to make your jet engine a little bit less expensive or a little more efficient. You get your edge by understanding how to use the data that the engine creates to create more value and so I think every business now has the opportunity to look at data and figure out how data can actually can give them an edge in the marketplace for whatever they’re making. It doesn’t have to be software. It can be hard goods. It can be distribution. Look what Amazon has done with logistics. Data is really changing even the most basic old line businesses. TK: You mentioned Amazon. I look at Netflix, Uber, Google and Facebook. These are all companies whose fundamental business model is predicated on massive amounts of data and much of what they’re doing with that data is attempting to predict actions and behaviors and next steps. Amazon wants to ship you a box filled with goods before you even know that you need to order it. It just shows on your door step and you open it up and you say “My God, how did I not think to order this? I can’t live without it now that I’ve seen it.” Uber wants to predict where you’re going to be for your next ride before you hail it. This predictive capability is predicated on what you said earlier that I need to have all the data available so I can make the right decisions and forecast because of it. When I begin to throw data out, I suddenly lose that competitive edge and that advantage. DF: Yes. There’s a reason why companies like Uber and Amazon suddenly appeared in the world at the time when they did and not 10 years earlier because they wouldn’t have been possible 10 years earlier. TK: A lot of that comes back to the affordability of storage. DF: That’s right and when people ask me why am I so excited about Wasabi, what’s so exciting about data storage? We have our own interests in how to do this stuff but beyond that is what are we going to unleash on the world by providing this utility and think about all of the ways in which that’s going to change thousands of other businesses. TK: When Tom Davenport was here for a podcast we did earlier, we talked about the fact that, in many ways, AI, machine learning are technologies that will help ensure the survival of our species. We’re getting to the point where data is becoming fundamental to how we survive, how we create progress, how we bring people online globally and how we deliver healthcare and education. All this is, in some way, hinged to data and yet still, I can’t help but think, Dave, that we’re still stuck in this old mindset of how we deal with data when it was on paper, when it was on its analog form, when it took up space. It’s a difficult thing to change a mindset, so when you talk to executives and when you have these conversations about abundance with them, are they getting it? What’s your sense for the sentiment when you talk to folks about this? DF: It’s in transition, right? Iron Mountain still has trucks running around picking up boxes of documents. You go outside and stand on the corner for 20 minutes and one will go by, and the storage of that information is probably more driven by a sense of liability or compliance or something else than it is “Gee, I really want to use that data in the future.” Because if it takes you 48 hours to get it back and it’s going to cost you $50.00 to get one piece of paper back, you’re probably not going to want to do it. When you get to the other extreme, which is Wasabi where everything is available in milliseconds and very cheap, that’s a very different kind of mindset to the extent that managers are recognizing the importance of data in their businesses. I think it varies from business to business. By and large, I think most businesses are starting to recognize that more and more, your competitive advantage is going to come from your ability to know about your customers in great detail, and to be able to service them in ways that your competitors can’t, and the data that you collect is proprietary. So, what I know about you may be different from what somebody else knows about you, even if my information is more complete and more accurate, I have an advantage. One thing that I’m not sure people really get in general is that there’s a difference between GPS data, which all the world can access, and data that I might have that’s proprietary to me that becomes my corporate asset, the fuel that’s going to drive my growth going forward. Companies that get a leg up are in a good position. So, a company like Facebook that already has a lot of information about its users has a strong competitive barrier to the next guy that comes along. TK: Movements often have mantras. When I think of the data storage or the cloud movement, one of the mantras that you hear repeatedly and I have talked about this so many times is that data is the new oil. I understand where that’s coming from and that there’s a power to that mantra, but to follow on what you just said, data is not the new oil because I’ll trade you a gallon of my gasoline for a gallon of your gasoline but I don’t think anyone would, in their right mind, take all their data and give it to a competitor, or take all their email and give it to someone that they hadn’t met before. Data is very versatile and very proprietary. DF: Yes. Maybe data storage is the new oil but the data itself is not. You can take oil and put it in a Porsche and you can put it in a Honda Civic. TK: That’s a great example. DF: You get very different results but they both run on oil. It’s what you do with it that matters. TK: Going back to what you do with it, when I look at specific industries, entertainment, surveillance, retail, manufacturing, healthcare, each of these is having some challenge, a moment of truth with data. Like in healthcare, let’s take that as an example. So many different systems that the data is stored in, even having a common patient record. How is the affordability of storage going to help in those industries to overcome some of these barriers? How does it become catalytic to their transformation? DF: Let’s take healthcare for a moment. There are a number of different things going on in healthcare that are very data intensive. Medical imaging progressed from simple things like X-rays to 3D imaging where you can rotate the view of an organ in three dimensions and things of that sort, and obviously those create an explosion of information. You have to store that data for, in many cases, the life of the patient. So, when a hospital decides to send you to the lab where you’re going to get a 3D CAT scan or something of that nature, they’re making a commitment to storing that data for a long period of time. So, financially, it’s something they have to worry about; so the cost of storage there becomes a major factor. Also true in genomics because a lot of progress in cancer research and research in genetically linked diseases is coming about by being able to analyze the genetic data from large populations. Finding out which genes are responsible for this or that disease leading to drug discoveries to address these things. So, again, data storage is underneath all of this. Hospitals, particularly, used to be obsessed with running their own data store. You go into a hospital like Mass General, somewhere there’d be a data center with rooms full of storage servers and an army of IT people babysitting this storage and so are hugely expensive and this really limited what the hospital was willing to do financially in terms of all the technology that creates data. I think those days of people feeling like they need to run their own storage farms is really limited, any more than you would want to run your own electric generating plant. It doesn’t make sense any more to have every hospital creating something that’s essentially a commodity because there’s no way that you can do it inside for anywhere near the same kind of cost and it’s a big distraction. Just the management of the people would have to do all that stuff is a huge distraction. So, I think we’re getting to this point where people are - that all the value that they’re creating is based on things that create and store and analyze data. It no longer should be something where you have to worry about the storage of the data. You should focus on that part of the application that creates the data and analyzes the data. TK: As an organization, it’s always critical to focus on what your competency is and detach yourself from everything else. Do that that you’d be best and for a hospital, obviously, it’s patient care. It’s not running the data center. DF: Yes, absolutely. I was recently out in Hollywood with one of our sales guys out there visiting a movie production studio where rooms full of artists and visual effects people and so forth and down in the basement is this huge data center full of whirring disk drives and I’m saying “What does that have to do with the value that they’re creating?” and yet, it’s always there worrying about how much storage am I using and do I really want to go from HD to 4K video, or 4K video to 8K video because it’s going to take up a whole lot more data and out networks are going to be too slow, and this and that and the other thing. These things are not core to the differentiating factors that make them competitor in the marketplace. TK: More importantly, you just said that you can’t keep up. The rate of data creation and storage is increasing so rapidly and so quickly that if you run your own data center, there’s just no way economically you can rationalize the investment that you have to make in keeping up with the increased burden of storage over time so you may just be able to tread water today but in two, three, four, five years, that will be impossible. DF: Yes, there may have been a time 20 years ago when in-house expertise at storing data gave you a competitive advantage, but it’s crazy to do that today. When you think of the thousands of companies out there running their own in-house storage, they’re all basically doing the same thing and reinventing the wheel over and over and over again for what? TK: I see the creation of entirely new industries. When someone like Uber comes along, we all feel like as though we’ve been blindsided, and soon thereafter, we all look at each other and say “How did we not think of that? That makes so much sense.” I think we are going to be littered with that kind of innovation, those kinds of new industries or the rebooting of old industries that simply weren’t serving us well, whether it’s healthcare, education or transportation or retail, and so much of that will be as a result of the fact that we have this entirely different attitude towards how we store and manage data. When you and I talk about it, we get it and we understand it but it sounds so trivial when you think about this to other folks. Is there a convincing fact that you found when you play this out with execs just really sticks and makes them finally get it, that the data is out with the key to their success? DF: The marketplace takes care of those things. Sears failed because they didn’t turn themselves into Amazon or some other business that makes use of data. They stuck with the same old model that worked for them for a long, long time. Good business executives look around and they see, “Gee, this company is doing really well and they’ve adopted a different business model from what we have. Either we stick to what we’re doing and suffer the consequences or we figure out how to adopt to a world in which information becomes a competitive weapon.” Great businesses that were dominating the American landscape 50 years ago have just disappeared because they didn’t adapt to the Information Age. TK: Sears is one of them certainly that’s top of mind recently, but the Classics, the Kodaks and the Blockbusters, they were bellwethers of new industries in their day. Richard Sears who started Sears took advantage of the railroad network that was burgeoning in the country at the time, sort of the present-day internet in many ways. Fantastic innovations but ultimately, I think it comes down to the market deciding who the real innovators are. In the late 1800s, Richard Sears was a just out-of-school railroad telegrapher who happened to come upon a refused shipment of watches, which the enterprising young Sears then sold using his fellow telegraphers as a distribution network. With the $5,000.00 profit from that sale, about $110,000.00 today, he started a mail order watch and jewelry business along with a local watchmaker, Alva C. Roebuck, and with that was born a century-old icon of the retail industry. It’s worth noting that the infrastructure which made the Sears catalog possible was the burgeoning railroad system. That catalog, in many ways, became the current day equivalent of the data warehouse that, today, is the worldwide web, but Richard Sears did one more thing that’s often lost in the telling of his story, something that Dave and I talked about in our new book “The Bottomless Cloud.” While the catalog was bursting with variety and choice, there was little in the way of personalization. The general store had the upper hand when it came to understanding the needs of customers who would share much more than just the transaction with the store keeper. The general store was not only a place to buy and sell. It was a place to be known and to be heard to share information about yourself, your family and your community. What Sears did was brilliant and became a role model for 20th century retail and marketing. One of his earliest mailings was a handwritten postcard to prospective buyers. You see, Sears understood the value of data in building a trusted relationship. In many ways, Sears made the first effort at scaling the relationship that customers had with the general store. It’s interesting that after nearly 150 years, we are now talking about returning to that general store model by using data to understand the customer in a way that personalizes every transaction. Back to my conversation with David: We were talking about Amazon earlier, Dave. Amazon gets me and they earned my loyalty, the degree to which they understand me and get me better than some other company will and I can go down to Macy’s or to Nordstrom’s or to my local retailer and they don’t know me from a hole in the wall, but Amazon knows me, they understand me, and that earns loyalty and that’s all based on data. DF: Yes, and there are thousands of new businesses that have sprung up over the last 10 years that are succeeding in often traditional markets that by knowing more about their customer. You know, Nordstrom has a subsidiary called Trunk Club. TK: Yes. DF: I used to shop at Nordstrom but now I go over to Trunk Clun and when I walk in, somebody has already picked out all the things that I’m likely to want and put them on a rack and I can shop in half an hour and get as much done as I would if I had spent three hours shopping in a store where people didn’t know who I was. TK: Who doesn’t want a personalized shopper? Obviously, what you have is someone who knows you that well. DF: Yes, those kinds of things are companies adapting. I’m still amazed that Walmart, for example, saw the writing on the wall and previous to very good competitor to Amazon in terms of their online business. They weren’t first. They weren’t even second or fifth, but they got there soon enough that they kept from being forced into obsolescence. TK: Sometimes being first is not always an advantage, because when it comes to the cloud – we talked about this- if you’re first, you may end up buying into a solution which is subpar which locks you in and which doesn’t allow you to move as quickly as the market requires you to move. DF: Yes. No, that’s absolutely true. We’re not first in cloud storage. Amazon, Google and Microsoft have been there for 10 years before we came in but we were able to look at what they were doing and say, “Gee, that’s definitely the right idea but we can do it better.” That’s a perfectly good business model. I like those kinds of businesses personally because a lot of the companies that I’ve had where the products have been transformative products. You have to hope that people care enough to be able to learn something new, to be able to change their behavior. At Wasabi, we’re not asking anybody to change their behavior. We’re just saying, whatever you’re doing, you can do it faster and cheaper, and by the way, that new thing you were thinking about that didn’t quite make economic sense before, take another look at it because, guess what? At 1/5 the price, something that didn’t make any sense economically might make perfect sense now. TK: I think one of the greatest influencers of behavior individually, or en masse as a society, is economics. Economics changes behavior probably better than anything else does. The neat thing about this conversation as we were talking, I was thinking about Frank Knight, who was a Chicago School economist from the early 1900s, and he said that the whole purpose of human consciousness is to predict the future. I think, in many ways, what we’re creating with these data enterprises is an ability to be so much more predictive and responsive to their customers, to the marketplace than they ever could have been before. We used to rely on focus groups. Now, Tesla knows instantly what your behaviors tell it about what you want in a car. You don’t need a focus group anymore. It’s a radical shift in how we run an organization and how we approach the marketplace. When you fast forward five years, maybe 10 years, what are the implications of this incredible plethora of data and this tremendous change in the economics of data that you think are going to influence us on the broadest scale? DF: Yes. I wouldn’t even begin to try to answer that question but I can tell you that new business models are emerging every day. With the previous generation of storage, we got Uber and we got Google Maps and we got a whole bunch of other things, and now, with this second generation of storage coming into the market that’s faster and cheaper by far than anything that’s ever been out there, there’s a whole new wave of innovation coming along that I can’t even predict and I think there are going to be lots of businesses started by younger people willing to take bigger risks than I am at this point, and I take great joy in the fact that we’re providing them with the shovels, the tools that are going to be used to create the next generation of applications. TK: It’s cool to think about what the prospects are but I agree with you that none of us are good enough or arrogant enough to really be able to predict that far out especially with something that’s going to have implications as deep and as profound as what we’re talking about here. Dave, thanks very much for joining us on Foresight Radio. It’s a pleasure. DF: Thank you, Tom. TK: That was David Friend speaking with me about the future of data. To find out more about David, just click the link on the Foresight Radio homepage at foresightradio.com. Thanks again to our sponsors for this episode of Foresight Radio, Wasabi. Take a look at how Wasabi is changing the rules of the game for cloud storage at wasabi.com and most of all, thank you for listening. If you enjoyed this podcast, please be sure to subscribe to Foresight Radio and to share it with your friends and colleagues. This is Tom Koulopoulos. I look forward to joining you again soon for another episode of Foresight Radio where we explore the future of how we will live, work and play in the 21st century. - End of Recording -