Big Ideas around Big Problems in Big Data

Last Wednesday, IA Ventures held its first annual Big Data Summit. Attendance was restricted to our Limited Partners, portfolio company CEOs and CTOs, leading thinkers and practitioners in fields related to Big Data and a small group of co-investors. There were only 70 people in the room. Thomson Reuters, one of our LPs, was kind enough to allow us to hold the conference in awesome space at the top of 3 Times Square. The sky was blue, the sun was shining and the conversations even more dazzling.

The goal for the conference was to catalyze a series of conversations about how to best deal with problems and capitalize on opportunities in today’s Big Data world. At IA Ventures we structure our thinking about Big Data around three buckets: Visualizing; Learning; and Scaling. Every IA Ventures portfolio company is dealing with these issues day in, day out, but their issues are certainly not unique. One of the most interesting threads in the conference covered how hardware innovation has finally allowed us to tackle Big Data problems. The inexorable drop in the costs of storage, compute and bandwidth, with a related increase in network access has led us to a point where, in the words of Mike Driscoll, CTO and Co-founder at Metamarkets and author of the blog Dataspora, “The economic value of Big Data finally exceeds its extractions costs.” The implications are enormous: we now stand at the edge of a generational wave that will fuel innovation towards solutions for managing the chasm between Big Data problems and Big Data science.

Here are a handful of the Big Data insights I gleaned from the conference:

• Widespread adoption of real-time sensors will fuel a Big Data revolution.
  Real-time data collection is expanding on exponentially. Passive detection and measurement techniques will provide enormously valuable data to the tools developed by the Big Data community. The skyrocketing richness of data around context, preferences and behaviors will lead to new opportunities for analyzing our “offline” world.

• The ability to store everything can lead to problems.
  Plummeting cost of storage has enabled many to simply store all their data. Problem is, some of that data is valuable while some is not. The process of identifying and exploiting the data-containing signal can get muddied by avoiding critical thought on the front end.

• Algorithms are the game-changer.
  So much emphasis has been placed on advances in cloud computing and storage that the value of better algorithms has been lost in the shuffle. Today’s machines with yesterday’s algos or yesterday’s machines with today’s algos? Hilary Mason’s compelling presentation convinced me: I’ll take the latter, hands down.

• That said, AWS is a juggernaut and the power of its lock-in should not be underestimated.
  While the ease of creating and scaling a virtual data infrastructure has skyrocketed, the difficulty in moving large-scale data has not meaningfully decreased. Many companies who built their businesses on top of AWS will find it both painful and costly to switch.

• Scaling development using offshore teams often benefits from moving a core team member to manage the operation.
  Coordination between on- and offshore development teams is challenging in the best of circumstances, and as offshore components have grown the importance of global coordination has increased. Migrating the domestic development DNA to the offshore team is vital to achieving long-term success.

• Once the wrinkles are ironed out, Mechanical Turk can be a powerful and cost-effective vehicle for scaling data-driven businesses.
  We’ve seen several companies leverage Turk to aggregate and QA large-scale data sets with great success. When you let humans do what they’re best at and let machines do the rest, you can take on tasks that were only a few years ago impossible.

• NumPy / SciPy have impressed many with its performance.

• In the world of visualization, simplicity is king.
  Overly complex visualizations with too many data dimensions are almost worthless. Extracting small, highly relevant information from Big Data is where it’s at.

• Privacy is dead.
  What do we consider to be the boundaries of privacy, especially with respect to items like medical data? In a data privacy-free world, should we be regulating data usage instead? How do we deal with asymmetric access to our personal data, e.g., how is it that insurance companies claim the right to our personal information?

• If the past is search, the the future is prediction and suggestion.

• With open source and Internet protocols commoditizing software, the advantage will be derived through data.
  In this regard, context is king, e.g., contextualizing datasets to surface previously unseen relationships in the feed.

Tim O’Reilly wrapped up his talk with an important message: “Create more value than you capture.” Essentially the ethos of the open source movement. The magnitude of the problems discussed above do not subject themselves to “point solutions,” but larger collaborative efforts leveraging the global brain. The solutions require not only advances in technology but a wholesale re-evaluation of the way data is used, owned and regulated. Preparing for the future is not simply an issue of throwing money at the problem, but of being thoughtful and deliberate in building open standards to facilitate innovation on a large-scale basis.

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Constructive Dialogue: Just Business, Not Personal

I have been an online denizen for some time, and have engaged in countless online debates both on this blog and elsewhere. At time those debates get pretty heated, as reasonable but opinionated people can disagree but do so with passion and intensity. Sometimes language can become snarky and sarcastic, as emotion and reason mix in an interesting and often entertaining brew. But when these dialogues devolve into personal attacks, where assumptions are made about people’s motives and character, the value of the entire discussion thread drops precipitously. And this is a shame, because often a lot of excellent thought is missed in the wake of judgment and hostility. And the online age has sharply increased the incidence of this kind of messaging, as the depersonalized nature of sending a comment into the ether has made it perilously easy to communicate things you’d never bring yourself to say to someone’s face. Yet this should be the check for whether something should be written as well.

While the catalyst for my message are the blog entries and tweets of Chris Dixon and Jim Robinson, this is an issue I’ve been thinking about for a long time. It’s just that Chris and Jim’s interaction, given the fact that I know them both and many of the others who have taken a stance in the carried interest taxation debate (e.g., @fredwilson, @bussgang, @pkedrosky), has made it much more real and personal. Chris and Jim are two exceptionally smart guys with strongly-held views. As it relates to the carried interest debate, they happen to be on opposite sides of the issue. Big deal; the often-snarky Mr. Kedrosky has more than a few times roasted me on issues where he and I disagree. And I have tossed it right back at him. But those exchanges are focused on the issues, not on either of our characters, motivations or integrity. Based upon Chris’s tweets in response to Jim’s strong but reasoned blog post, it is clear that he doesn’t know the Jim Robinson I know. No matter, the criterion for engaging in spirited but respectful debate should not be whether or not someone knows the commenter.

It should be that basic respect is afforded anyone who enters the debate in a respectful manner. Jim’s language is strong but not personal. It addresses Chris’s views and others who have staked out a similar position. But Chris’s response to Jim’s post was highly personal, not to mention uninformed. In my opinion it crossed the line and, in fact, much of the thread of “good versus evil” that has been taken up in this debate is neither intelligent nor helpful towards getting to a better perspective on the issues. Believe me, I understand the technique of “shock value” and taking a bold, hard-line stance. But to paint everyone who happens not to specifically agree with you as somehow morally bankrupt is absurd.

In other words, I am not arguing for a world where debates become some form of sanitized drivel. I am arguing for an approach where people can use colorful language to express their views with passion and intensity but with respect and in a de-personalized manner. I think people entering the fray need to take a deep breath, pause and consider their words before launching them onto Twitter, blogs or other forms of social media. Would you say these words to the person’s face? Would you want to be dealt with in this manner? If the answer is yes, then let it rip. If not, then resist the urge and re-cast the message. There are so many smart people with so much good stuff to say. It is shameful when so much good content is lost to poor form.

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Seeding a Start-up Culture

About a week ago, James Kwak penned a very thoughtful post titled Why Do Harvard Kids Head to Wall Street? He provided a series of perfectly rational reasons as to why this happens, e.g., the job is billed as a good launch-pad for the future, recruiters make it easy, the money, etc. Whether he has all the right reasons is neither here nor there: he is asking the wrong question. The right question is: how do you lure the best and brightest into game-changing areas such as start-ups and social enterprises that can effect hundreds of millions of people or more?

One of the issues with making it easy to get into start-ups and similar enterprises is that persistence, focus and energy are often good screens for success in these fields. If you make things too easy it can lead to adverse selection. However, there are many things that can be done to change the calculus, some of which are already being done in Silicon Valley and Boston but less so in New York City. I know several venture capitalists in the Bay area who teach at Stanford and Berkeley, in the Business school as well as the Computer Science (CS) and Electrical Engineering (EE) departments. They use their positions as vehicles for identifying top students, building relationships that ultimately result in ideas getting funded or students placed in promising start-ups. The students are steeped in not only start-up lore, but myriad perspectives on the challenges and opportunities of start-ups as told by experienced Founder/CEOs. I can assure you that these discussions are a lot more interesting, colorful and compelling than presentations on the worlds of Wall Street or consultancy. My friends Larry Lenihan at FirstMark and Ed Zimmerman of Lowenstein Sandler both do this. They are not enough. And we need more technical lecturers as well.

The venture capital and start-up industries need to do a much better job selling, serving to funnel desirable candidates on the basis of excitement, impact and long-term rewards as opposed to (perceived) stability, basic training and short-term cash. Yes, it would be great if NYC’s great universities did a better job of this at an institutional level, but I’m not suggesting we wait around for sclerotic bureaucracies to change. I’m talking about a grass-roots effort on the part of local venture investors and successful start-up executives to get into the classrooms and onto campus to re-orient talented students away from the money culture and towards the building culture. Alter their utility functions through education and exposure and get them early.

I think many equate start-up enterprises with uncertainty and fear, and only appropriate for those with massive risk tolerances. This is bad marketing, plain and simple. Yes, doing a pre-revenue start-up is gut-wrenching, all encompassing and horrifying at times, but it is also mind-bogglingly stimulating, exciting and requiring all of a young person’s skills and abilities. There is not a job on Wall Street or at a top consulting firm that gives a young technologist or business person the exposure and responsibility of a start-up, even one that has received venture investment. There are early-stage companies all along the risk continuum, any of which can offer up great experiences for the right people. And every student that goes into these companies or or starts their own is part of creating something, and contributing to the engine of growth that can help the US and other Western nations fight against the weight of their aging populations and economic malaise. And the skills obtained while working at a start-up are applicable to a wide range of future opportunities, whether at another start-up, one’s own start-up or more established enterprises.

And once the ball gets rolling it becomes a virtuous cycle, with this enlarged crop of entrepreneurs and start-up athletes having an increasing number of successes, and subsequently investing in others start-ups and their own new businesses. This is part of what has made the SF/Silicon Valley community so vibrant, the recycling of capital from successful entrepreneurs into the businesses of others as well as their own. And so it goes…

But it is hard to escape the fact that education and re-orientation has to start in the universities. Because by the time these talented students get seduced by the fancy conference rooms and the cash, it is difficult to bring them back. And each year a talented student gives to old-line money businesses is a year taken away from building something truly great and seeding the start-up culture. Is changing culture easy? No. Can it be done with the work of all interested constituencies - universities, Governments, venture firms and start-up businesses? Absolutely. Let’s get to it.

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For the Good of the NYC Venture Scene I’d like to see…

…some chunky IPOs of NYC born-and-bred companies - Everyday Health, Gilt Group, TheLadders and others in or approaching the $100 million revenue club. NYC has spawned some great companies; it is time for the world to see them on stage and get to participate in their future growth.

…Foursquare to sell out (to Yahoo, Google, I don’t care) for $100 million-plus. What a huge success story to put in the bank for the NYC venture ecosystem when exits of this magnitude are few and far between.

…some successful NYC-based serial entrepreneurs with $5 million of spare change to get super active in the angel investor ecosystem. Smart angels finance smart ideas, create jobs and lay the foundation for subsequent funding rounds. Silicon Valley/SF has probably 20x the number of “scale” super-angels as NYC. More of these people will help turbocharge the creation of a vibrant, self-sustaining NYC venture community.

…the NYC area schools to get serious about entrepreneurship. Foster a culture of entrepreneurship within the Engineering and Computer Science programs. Get professors out into the real world, not of research but of commerce and creativity. Turn professors into feeders of great talent into NYC-based start-ups. Look at Stanford. They do it right. A little benchmarking and emulation wouldn’t hurt.

…more early-stage funds started in NYC. You can count the number of early-stage firms in this town practically on two hands. Not enough capital, not enough mentoring, not enough cross-fertilization. The early-stage ecosystem is developing with firms working together more and more, but we are in the first inning of a nine inning game. Greater collaboration. Greater communication. More capital required.

…tax policy support, not restrict, investment in early-stage businesses. Also, policies and programs need to be better communicated in order that start-ups can avail themselves of the benefits. Navigating NYC is neither easy nor cheap, and it is an impediment to starting a company here. Given its natural resources, e.g., home to seven of the largest industries on the planet, NYC should be a magnet for start-ups. Smart policy changes can help.

…a more vibrant hacker culture, where a few people, an Amazon account and some pizza and beer money can get a prototype built in a matter of weeks. It still feels like this town has a fear of failure. We need to embrace failing the right way as a badge of honor and praise pivoting into something more relevant and powerful as a natural part of the entrepreneur’s evolution.

…general adoption of clean, non-participating preferred term sheets with commercially reasonable protective provisions. The West Coast has had this right for quite some time, and NYC is getting there. But we need to fully get there in order to attract the smartest entrepreneurs and the best deals.

…less chest bumping and rhetoric and more results. There is a lot to be proud of, but until we see a spate of successful scale exits lingering doubts will remain. Put up or shut up. NYC will indeed put up; of that I am highly confident. But in the meantime, let’s just do good work, stay humble and kick ass.

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Brands: Authenticity and Pattern Recognition

There are two catalysts for this post: Chris Dixon’s recent tweet that said

“Does anyone really want to have a “conversation with brands”? I I want my relationship to Starbucks limited to buying coffee.”

And Doc Searls post which proclaimed that

“Brands are Bull.”

Two bright guys whose views I respect, but I must heartily disagree with both of them.

When it comes to conversations, and specifically those conversations that are deemed valuable, I believe the overriding issue is authenticity. People tend to be pretty good at discerning who is real and who is merely a self-promoter, and power and influence tends to flow to those who are authentic. Do people want to converse with brands? I think that is the wrong question. The right question is “Do people want to converse with people who are authentic in their support of brands?” Starbucks the brand can’t talk to you, but a passionate Starbucks employee can. These individuals could be employees of the brand, external representatives of the brand, or merely fans. But if the people having these conversations are authentic, my sense is that yes, people want (and do in large numbers) have these kinds of conversations every day. Twitter, Facebook and other forms of social media are very personal, and when they are de-personalized (by brands acting big, stupid and impersonal) interactions are bound to be unsuccessful. I am an investor and Board member of a company called Buddy Media, that has developed and manages a powerful Facebook Pages platform (like the Bud Light fan page) that is used by major brands to connect with their fans and potential customers. People flock to these pages to chat with and learn from engaged communities organized around brands, take advantage of special offers on these pages and enter contests to win products being promoted by the brand. This could only be successful if people found value in the brand as an organizing principle, with Facebook and Buddy Media as facilitators of this interaction. And let me assure you, it is successful.

Doc Searls, in his post about the uselessness of brands today, discusses how the mere presence of Tiger Woods in an ad means nothing relative to what a company does.

Nike, the brand, famously supports its sponsored athletes because
the company is about athletes and athletics. Which is all fine. What
matters is what the athletes do on the field, on the court, on the golf
course. Sure. But what matters more is what these companies actually do.

Here in Reality, companies buy
Accenture’s services. Individuals buy Nike’s shoes. None of what
customers buy from either company gets an ounce of substantive worth
from Tiger Woods, or from anything those companies do with their
“branding” strategies, no matter how much those strategies serve to
help sales and stock prices.

We live in an age when we can kick tires hard. Accenture’s and
Nike’s tires are not Tiger Woods. And Tiger Woods, even if he’s long
been a lying sack of shit, isn’t a tire either. He’s a human being, and
that’s what makes him interesting. Not what his golf game says about
companies that pay him.

What Doc Searls is saying reflects the view of an empiricist: tell me the features, give me the stats, and let me make a decision. This is not how many - if not most - items are purchased. Consumers, be they retail or business, are impacted by the perception of a brand. What people say about it and what they’ve heard about it are both relevant to the purchase decision. Do I perceive it to be high quality (separate from the cold, impersonal product specs)? Will it make me successful?  How do I project my experience as a result of purchasing the product/service? Issues of authenticity, trust and recognition all play a part in how successful a brand may be. Objective product features and quality clearly play a role, but if I equate Tiger (with whom I have a positive association) and his success with the outcome of using a particular product, then I’m likely more apt to buy the product. It’s just common sense and represents the underpinning of the entire advertising industry.

The issue isn’t whether brands are bull - they’re not. Creation of a successful brand results in pattern recognition that can help consumers more efficiently locate what they want and builds substantial value for the brand owner. The issue is whether it is bull (or just plain stupid) to choose an athlete or, for that matter, any single human being as the basis for selling a multi-billion dollar product line. As Doc correctly points out, humans are interesting - and volatile. Charles Barkley said it best: “I am not a role model.” Well, neither is Tiger or most people walking the earth. Building a brand around a successful individual is akin to leveraging up a corporate bond position and continuing to take on more leverage when things are good. However, when things go bad they go very, very bad very, very fast. Brands flee the fallen idol and the consumers (or the public stockholders of brand owners) flee the brands. We’ve seen this movie before in every market; why should brand management be any different?

Even in a long-tail world with increasingly available information, brands, like relationships, will continue to matter. In fact, they might even become more important as the flood choices becomes overwhelming, brands and offline relationships will become increasingly powerful tools in the product discovery process.

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