 Live from Boston, Massachusetts, it's theCUBE at the HP Vertica Big Data Conference, 2014. Brought to you by HP. With your hosts, John Furrier and Dave Vellante. Okay, welcome back. When we hear live in Boston, Massachusetts, this is Silicon Angle and Wikibon's theCUBE, our flagship program. We go out to the events and extract the signals and the noise. I'm John Furrier, the co-founder of Silicon Angle. Dave Vellante, co-founder of Wikibon.org. And our next guest is Tom Davenport, Distinguished Professor in Management at Babson College. Also author of 19 books now in management practices, analytics. Really an expert in data analytics, the use of data, process improvement, all of the above in terms of business, across the board, seen decades of innovation. Welcome to theCUBE. Are you saying I'm older? You're definitely not born in the cloud like us, so check that box. But you know, this notion of mobile first, born in the cloud, we coined the term today, born in big data, which is about the new cultural shift that's happening in the mindset from the new way of thinking. And so like other disruptions, going back to client server, PC revolution, mainframe, all the above, you've seen these inflection points. So I want to get your first question take on is, you know, where are we in the tectonic plates? Are we, is it the earthquake has just started, or where are we in this evolution of true impact of big data? Well, I think it's still early days. I mean, it may be late days for the term big data, people are getting a little disenchanted with the term, but the idea that, you know, we'll have massive amounts of data, much of it unstructured and of a different type than we've seen before. I think we're in the very early days of, I think it was an IDC report that suggested we have analyzed less than half of 1% of all of the data out there. So that suggests, you know, and it's coming at an increasing rate. So we need to accelerate our efforts to analyze it, make something meaningful out of it. And I think, you know, we've had all these various trends in technology over the years, but to me the big one now is we're shifting from accumulating data, mostly putting transaction systems in place to figuring out what is, what difference does this make? How does it help us make better decisions? How can we create better products and services with this stuff? And that I think is the big C change that's gone on over the last couple of years. The thing that Dave and I talk about, we've been doing all the big data shows live from the original Hadoop world through here. And one of the things that really get, we get excited about, and we actually have our own data product with the crowd chat showing you is that for the first time in the history of business ever, you can actually measure everything. And so that brings up the question of the value chain and what they teach at Babson and other business schools is value activities, make up a value chain, process improvement, and you can go back to the printing press and all these things. So I got to ask you, so with that involved with Internet of Things, the US Postal Service, which spoke here, has a legacy business that has to compete in a modern era with Amazon FedEx. And so it is out there, the genie's out of the bottle. How do people make sense of this as a company? You got it, and you have the data, and there's no excuses. Yeah, well, it's interesting. I write a blog post for the Wall Street Journal and I'm writing it today on optimize or digitize, sort of do I optimize my existing business with analytics or do I digitize it and change it dramatically? And I met, had lunch yesterday with Jim Cochran of the Postal Service, and I went into that meeting thinking, you know, this organization losing mail volume, everything's going digital, they really need to digitize and optimization is not nearly enough for them. He said they were doing a lot of that with analytics. But then he said, well, a couple of problems. One, we don't have any evidence that these organizations that digitize mail are being terribly successful. I mean, obviously email providers are, but taking existing paper mail and digitizing it, nobody's making any money. Two, he said we have a lot of products as it is. Three, we'd be competing with our customers if we did that. So yeah, I think there are probably some cases where it makes sense to go a little slower on digitization, but there's not much doubt that's the long-term future for them and everybody else. So what does a company do that is in a reconstruction or looking at their value chains and value activities to get a competitive advantage? I mean, also this competitive strategy involves overlaid on top of business objectives, which is top line and obviously reducing costs. How do you consult and advise on that front? Well, I think there's so much cultural and organizational and strategic change involved that it's really hard to do it inside the main business. So let's just say the Postal Service was going to be a big digitizer and change their business dramatically. It's much, much easier to do it in kind of a separate business unit where you're not competing with the rest of the organization. You're going to lose money in that for a considerable period of time. You're comparing that to a business that might be making money, not really at the Postal Service, given their huge pension payments that they have to make. But so I think you need to set it aside for a while and let it grow until it can compete substantially with the mainstream business. Otherwise, it's just not going to fare well. Well, this optimized digitized thing is pretty interesting. I had the same thoughts when we were interviewing, Jim, so I guess I get his point, but I'd like your take on this. I mean, had they had the idea of doing Street View before Google did it, why couldn't they have done that? Put cameras on all their trucks. I mean, so they don't necessarily have to compete with their existing businesses, right? I mean, where do you fall on that optimized or digitized? I mean, some have said you got to digitize your business. I mean, flat out. You sound like you're maybe more pragmatic. Well, you know, I was writing this blog post that I had written last year. I was visiting professor at Harvard Business School and I wrote a case study about Procter & Gamble, which is really good at the optimized thing. You know, they still have basically a physical set of products and services or products primarily that they sell through physical channels. And so I was teaching this case at an executive education program at Harvard this year and everybody kept sort of dissing them for not being more digital and saying, well, so what if they're getting their information faster from syndicators? If they had an online channel, then they'd get it immediately, you know? So I don't know. I mean, Procter & Gamble's been in business for 176 years. It's still selling Tide and Ivory Soap and Oil of Olay and so on. I don't know if people really want to buy those digitally yet or not. I think it's worth some serious examination to say just how digital we need to be and not in a kind of a knee-jerk reaction and say, oh, you know, everything, everything has to be online and digital. So I got to ask you about the web and how that relates to today. So we saw the web come on the scene, laughed at it first. Oh, it'll never be anything real. It's a kid thing. Websites are for kids. Digital becomes the, how we do things, e-commerce, everything else changes. Social media, same thing, right? You're seeing people laughing at social media. It's a PR thing. Social business now is on the table. Omni-channel analytics are a big part of social. Retargeting has short-term gains, but yet this is people off. We were complaining yesterday on Facebook. So this is an attention economy and you wrote a book with that title. So I got to ask you, with Twitter, with the connections now with mobile, how would you write that book today with the attention economy because attention now is the new aided awareness and everyone's making all this noise, but there's signal in there somewhere. So how would you kind of redo that book today if you could overlaying the whole attention, getting Twitter, social media? Yeah, well, one thing I would do is I would not publish it the day before a huge terrorist disaster. That book came out on September 10th, 2001. So poor timing, I would say on my part. The world's attention went elsewhere pretty quickly. I mean, there's not much doubt that it's more of an issue now than it was in 2001. We have a huge amount more information. We don't, God's not making any more attention out there. We're all trying to multitask and not doing terribly well at it. So I think it's even more important now to have some sense of what the important information to your job and life really are because otherwise, you see people doing this all the time. My kids do it to some degree. They're just kind of surfing through life and seeing this, a little bit of this, a little bit of that. Don't really get into detail at all. BuzzFeed got $50 million in financing, got an $800 million valuation and they were doing top 10 attention getting posts. Now they're competing with the New York Times and quote, you know, highly valuable, but that brings up the attention. What to pay attention to is an analytics problem. Certainly getting someone's attention. I mean, a streaker can run down the street and get everyone's attention, but is that really good, authoritative product? So the question is, attention is now a scarce resource from what I hear you saying. If that's the case, what analytics could we have out there do you see possible that could help pay attention to what's going on, notifications and so on? You know, all right now advertising, for example, is a struggle for attention. And I think it's fair to say, despite all you mentioned retargeting, retargeting is a very primitive idea. If you were interested in it before, you'd probably be interested in it again, you know, over and over and over again. So most, the vast majority of targeting that we do now is really bad. Let's face it. It's stuff that we wanna sell that the customer's not necessarily interested in. It's stuff where we may have a good intention, but we don't know that much about the customer or where they are or what the context is. Simple things like retargeting that, surely we can do better. It's a hard problem to deal with. It is hard. And I don't think anybody's really cracked it yet. So we have this idea of attention-sensitive marketing. We just haven't really executed on it. So I think in the next decade or so, we'll see some people really start to get it right. And the ones who screw it up will, I think, get less and less attention themselves from customers. So I wanna get your take on this data economy thing. Obviously Facebook uses our personal data and they make billions of dollars out of it. And we trade that data for the right to use the product. Twitter has created a data model where they break news and people pay attention to what's happening on Twitter. And so the role of the user now is now the consumer is part of the equation. Their data is the currency. So two questions. How do you view the new crowdsourcing trend where the actual people are part of the production process? They're part of the value creation. And is there compensation for that? That came up in our crowd chat this morning from one of the AT&T executives where he said, hey, what point does the user's data be worth something? So what's your take on this whole connected crowd? Well, it certainly places a premium on having a really good set of lawyers who negotiate some agreements with your customers. One of the things I'm gonna be talking about here at the Vertica conference is big established companies that get into the data economy. So Monsanto, for example. Monsanto is historically a seed and a pesticide and herbicide company. They're now selling data to farmers to help them selling data and analytics to help them figure out exactly what to plant, when, how much water to put on it, when you need to put out the pesticide based on what we know about weather in your area. They bought a billion dollar, they paid a billion dollars for a field level climate data company so they can make better recommendations. And the farmers are saying, well, this is great stuff, but a lot of it comes from us, you know? Are we gonna pay you to get back our own data? Well, it turns out they're not just selling data, they're selling insight and analytics and so on. So far, they've shown that they will pay for it. I think you just have to add a lot of value to user data in order for them to say, okay, fine, it's worth it to me. Think of the banks, they've had our data for years, but they haven't really added much value to it. They're gonna start doing that soon, I think. Tom, you've written about big data projects, what makes them succeed or fail. And you could probably take your prescription and apply it to many IT projects over time. So is there anything different today? Is it so we sort of recycling the same misalignment stories between IT and business, or is the world more in tune because they're so-called data-driven? What's changed? Good question, Dave. I mean, I was just a few minutes ago over at a big pharmaceutical company over in Cambridge, and we were talking about the need for these hybrids. Now, we've always said you need to have sort of business and technology hybrids, but it's gotten a lot more complex. I mean, these people were saying, well, we need people to understand computation, they need to understand biology, a little bit of chemistry maybe, statistics. By the way, it'd be really good if they could program in Python as well. And can you imagine how common or uncommon people like that are? So I think it's just really getting much more so. We had this issue of alignment. Now we have a kind of an indimensional alignment issue, and we need people who can kind of communicate across all these boundaries. It's getting really tough, I think. What are your thoughts on data quality? You've got all these big data projects, spouting up all over the organization, which is maybe not a bad thing. It's good, experimentation is great. But it feels like there's nobody in charge of sort of the data governance, the data quality. Is that the role of the CIO? Should that not be an IT function? Where do you come in on that? Well, you have all these emerging chief data officers. I tend to like chief data officers who work not just on kind of how good is the data and how integrated it is and how well managed it, but also what are we doing with it? The kind of combination of chief data and analytics officer, Wells Fargo, just named a friend of mine to that role. I think it's a huge issue. It gets worse with big data. We have more and more sources and types of data that we have to integrate, and we haven't really kept up in terms of our productivity in that regard. I think it's fun in a way to come to the Vertica conference because Vertica was started in part of the ideas of Mike Stonebreaker, an MIT professor, and now he's really focused on data cleansing and curation productivity with this new startup Tamer. So I think we'll start to apply some innovation to those areas as well, and maybe get a lot more productive at it. Yeah, the Stonebreaker's new process is very interesting, but I got to ask you on a personal note, what are you excited about right now? I'm obviously, you're writing a lot of books and you get a lot of materials to pull from these days, and I think there's a lot of transformation going on, disruptive, and a lot of people are restructuring, but what are you personally excited about? What are you watching closely? Well, I'm a sociologist by background. To me, it always comes down to what does it mean for us humans, and I look at analytics and automated decision-making and business rules and so on, let's face it, a lot of knowledge work-type jobs are getting automated. I wrote a blog post a couple of weeks ago about business reporting at the Associated Press as being done by this automated decision engine. Automated news story engine. So what I'm working on now is how do we humans sort of make sure that these systems and analytics and so on are augmenting our jobs rather than automating our jobs? So we can still play an important role. We can be even more productive and effective than we would be otherwise if we make friends with our computers as opposed to submitting to our new masters. I remember the social class I took as a computer science undergraduate in Northeast and it was called Computers and Social Change and email's going to kill our and social interaction capability. That was kind of the theme, but I got to ask you this question with social in mind today. If data is transparent and highly available and frictionless from an iteration standpoint where I could play with data, wrangle data at any level, how does that change the social behavior? If, for instance, in California in the VC circles of South California in Silicon Valley, some are saying that the transparency is kind of lifting up the aura of this cloak and dagger kind of secret society around venture capital where- Well, yeah, you know, that industry has been very intuitive, surprisingly intuitive for, you know, being so focused on technology, but there are some companies now. Google's venture capital arm is one of them where they started to articulate, well, which of our investments really paid off in the past, and what are the attributes of those effective investments? You know, Google is analytical about almost everything, and I think these more analytical strategies will end up driving out the ones that are based on intuition and gut feel. Well, we also have the whole whistle-blower thing with Snowden. Is the information freely available gonna change the social behavior of government, society, and- Well, yeah, I mean, it's certainly changing behavior at places like the NSA and Target and so on, where they had these huge leaks and breaches and so on. So, you know, unfortunately, I think we're, the hackers are making faster progress than the people who are protecting us from them, and so it's gonna be, I think, a tough decade or so. You may see more, I was always focused on kind of the upside of analytics, but I think preventing the downside is going to become a really important issue. Thanks for coming on theCUBE. We really appreciate your comment. I know you got a keynote here, but I want to give you the final word. Share with the folks out there that are watching that might not be in the weeds of the big data world, and who just want to know, bottom line, why is this moment in time really important for a technology shift standpoint? The seed changes here, what does it mean? Why is it happening, and what does it mean to me? Well, you know, we've been putting in systems after systems in organizations to kind of pile up data to figure out, you know, how much vacation do you have left in your vacation balance, and how many orders did we send to this address, and we just never did anything with it. We sort of thought, well, maybe someday we'll get around to making better decisions or understanding the business better. Now is that time, and it's a, I think a huge change in all of our priorities. You look at CIO level spending, it's all on analytics and cloud, and things that let you digest all this stuff rather than creating a lot of new stuff that we're not going to look at. So the future's about data, and we're going to use that data, that's the prediction, hopefully you get some good out of it. This is theCUBE, you're watching John Furrier and David Laughlin. We're Tom Davenport, distinguished author and professor at Babson College in Harvard. Thanks for joining us. We'll be right back with our next guest after this short break.