Algorithms For Competitive Advantage

Analyst firm IDC predicts that by 2020, the amount of data generated each year will reach 35 zetabytes. Companies are fighting this deluge in numerous ways. Some archive data for analysis at a later point in time, some purge data as quick as they obtain them, while others capture, ingest, analyze, and use data for competitive advantage—sometimes in microseconds! And in a sea of plenty, it’s often the best algorithm that wins.

An algorithm is simply a step-by-step approach for solving a problem. Think of an algorithm like a formula; it can be complex, or relatively simple in design. Now add compute power from today’s super fast computers coupled with the know-how to design, build, and maintain these formulae and you have a winning combination! Companies across the globe use algorithms to make recommendations (think: If you like this product, you’ll probably also like this), choose optimum delivery routes for packages, and even route calls to agents that can best diagnose a particular problem.

How can an algorithm confer competitive advantage? Depending on the type of business you’re in, it’s easy to see how algorithms can reduce all available choices into the very best options. Take for instance, Google. In the February 22, 2010 issue of Wired Magazine writer Stephen Levy points out, “For years, (Google) has used its mysterious, seemingly omniscient algorithm to, as its mission statement puts it, “organize the world’s information.” Google’s algorithm is constantly tweaked, honed, tested, and improved to better interpret searchers’ requests, no matter how awkward or misspelled, says Levy. And this competitive advantage in its search algorithm has (so far) confirmed a 65% share of the search market for Google.

In a sea of data, algorithms can also help reduce choice overload. Online dating sites often use proprietary algorithms to divine appropriate partner matches based on user inputs such as preferences for race, religion, eye or hair color, and more.eHarmony’s algorithm for example, helps select potential partners based on a 258 question personality test. eHarmony’s algorithm takes too much choice (sea of available singles) and distills/simplifies millions of choices into much more manageable options.

And while companies like eHarmony rely on data input by a user, a new recommendation engine called Wings mines your social media “bread crumbs” left on various websites (including Facebook, Netflix, Twitter, Foursquare and others) to feed into its algorithm to pick a suitable dating partner. A MIT Technology review article on Wings says, “The idea is that the computer’s analysis of your behavior provides a richer analysis than you’d say about yourself.”

More data has been created in past three years than in past 40,000 years, says Teradata CTO Stephen Brobst. Indeed, today and into the near future, companies that can sort through, analyze and utilize this rich trove of data treasure faster (in some cases with blinding speed) than competitors will dominate over those enterprises slow to comprehend this critical transition.

Related: “Social Network Analysis: Hype or Help?” and “The Zero Latency Future is Now


  • Are recommendation engines becoming more or less reliable? Think of a website you often use that uses recommendation algorithms. How “close to home” are its choices for you?
  • Do you think a computer can discern your tastes in romance better than you can?




  1. Funny thing. This morning I was sitting with my client. He’s some 55-60? And he’s an engineer, building houses for most of his life. He’s amazing guy, created a company 20 years ago just because he didn’t agree with the management board. He takes things to the latest corner to make them perfect.

    First, we discussed technology. He wanted to know about web site optimization, what can we do further. Went to google analytics.

    Then we talked about sales. And how we’ve correctly found out that he’s loosing business at the point when he’s putting the offer to the prospects. He sends it by mail or email. And not in-person.

    His company in Italy delivers every offer in person. Each time. They close some 45% of deals. He’s up to 5% at most.

    So data and internet are ok for him, but personal, human approach, makes the deal. In his case.

    1. Are recommendation engines becoming more or less reliable? Think of a website you often use that uses recommendation algorithms. How “close to home” are its choices for you?

    Far. Most of the times still. It seems that they’re still mostly done by tech-people.

    2. Do you think a computer can discern your tastes in romance better than you can?

    Have to try some day and check it up. :-))) I would assume that it should. I think that our senses are limited by our experience, prejudices and other things that can make a difference.

    So I would buy a house from people and a girlfriend from computer? 🙂

  2. Hi Dusan, right up this alley, I was having a Twitter conversation with someone who was asking if she should send mail or email Christmas greetings, or if it mattered. She was concerned with costs for mailing to all her customers. I mentioned she should segment her customer base, and send personalized Christmas cards with a handwritten note of appreciation to high value customers and those who are not yet customers or low value, a nice e-greeting. She liked the strategy. Nothing like the personal approach is there?

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