Ken Elefant is a founding partner of VC firm Opus Capital (formerly Weiss, Peck & Greer Venture Partners) focusing primarily on internet infrastructure and software investments. Opus has more than $1 billion capital under management and has participated in the successful outcomes of more than 80 companies (including 48 IPOs) in the U.S. and in Israel.
We’re producing data at an amazing rate. In fact, humans generated more data in 2009 alone than in the entire history of our species up to that year, according to Amazon’s former chief scientist Andreas Weigand. And IT firm EMC projects the quantity of digital information we produce will grow by a factor of 44 between 2009 and 2020.
Yet for all the money and effort being spent to collect and analyze this vast amount of digital information, most business data remains woefully under-used. Much of it is wasted entirely.
What’s apparent is that producing mountains of data is the easy part. Making sense of it is a different matter entirely. It’s what I call the “big data” paradox: Overwhelming quantities of information often paralyze organizations, leaving them unable to extract business insights from that data.
A big problem like this, of course, could mean a big opportunity for startups investigating the “big data” space. Specifically, there are three market trends that offer inroads to startup players:
Not too many years ago, CIOs and data analysts controlled the enterprise data kingdom. The average business user had little access to data or the complex costly business intelligence tools they needed to optimize decisions.
Qlik Technologies, a 2010 IPO, doubled its sales to almost $160m in 2009 by focusing on improved performance, ease-of-use for non-quantitative business users, and reduced cost of ownership. Another startup, Greenplum, recently acquired by EMC, uses two technical innovations, massively parallel processing and a “shared-nothing” architecture, to increase performance and lower costs of accessing data. In business terms, this means Greenplum’s customers can justify providing data and analytical tools more broadly throughout the organization.
Even with improvements from startups like Qlik and Greenplum, business intelligence tool penetration remains below 30%. This means that big opportunities exist for entrepreneurs who can drive costs down with hosted models; improve performance; and perhaps most importantly, simplify the user experience to reach large numbers of non-quantitative business users. At Opus Capital, we recently invested in SiSense to take advantage of this large market opportunity.
Here’s a simple recipe: Acquire users. Aggregate a novel data set. Sell ads or services using the insights derived from that data. Over the past decade, some of the most powerful businesses have taken this approach to generate huge revenue streams.
Google “organizes the world’s information” — mainly search data that Google uses as a proxy for consumer purchase intent — to sell ads generating $24 billion in total 2009 revenue. Facebook has grown from nothing to more than $1 billion revenue in just over four years by “connecting you with the people around you”. In the process, Facebook collects a ton of information about you and your friends, including location, interests, sites you visit through Facebook Connect, and relationship status, among many other things. Similar to Google, Facebook tightly controls its user information in order to sell ads, and increasingly, targeted goods and services.
Admittedly, these companies have been two of the most successful at creating useful technology as a means to collect and control broad-based information from hundreds of millions of users. But creating and controlling more focused data sets works too. For example, BlueKai is building a fast-growing business by partnering with e-commerce companies to amass anonymous consumer profiles and segment-specific purchase intent data that is independent of any particular site. BlueKai then sells this data to advertisers who combine it with other data sources to enhance the effectiveness of their online ad targeting.
Better Tools, Better Business Insights
There will always be a market for data tools that improve insights. Alert Enterprise, an Opus Capital portfolio company, provides organizations a comprehensive security and risk management capability by connecting data and corporate policies across IT, physical access control, and industrial control systems. It’s not rocket science, but providing organizations the ability to coordinate policies with physical and digital systems represents an innovative approach to data usage that lowers the costs associated with real-world problems like corporate fraud and risk management.
Even in niche verticals, optimized tools applied to relatively small data sets can provide opportunities. Borntosell.com focuses on one narrow slice of option trading, covered calls, where investors buy stocks and short call options against them. The trick is to know which stock to buy and option to write from the more than 170,000 combinations of stocks, option strike prices, and option expiration dates that exist at any one time. The raw data Borntosell crunches isn’t new, but the company has created an optimized database filter that quickly identifies the best possible trades from the universe of candidates. Before this solution, individual investors typically relied on home-grown, spreadsheet-based solutions using old data or traded without full information.
Exponential growth of digital information opens the door for startups that develop innovative ways to extend data and analytical tool access; create and control valuable new information sets; and build tools to improve insights that can be gleaned from data. These trends are just three among many in the “big data” world that will present tremendous business opportunities for years to come.