Big Data, Brother

Posted by on May 22, 2015 in blog, personal, security | No Comments
Big Data, Brother

Can’t shake the feeling….

Yesterday, I attended a conference up in San Mateo entitled “Data Alchemy—Emerging Trends of Predictive Analytics for Business Leaders.” On almost any given day, the Bay Area has one or more such events going on: seminars, conferences, and workshops—both paid and free to attend—where ambitious small companies strut their inventions, services, and business models; accomplished managers and executives tout their intelligence, business acumen, and books written while holding—or between—vice-presidencies at big tech companies; independent consultants, bloggers, and occasional press writers trade questions and business cards. They tend to be educational in several respects.

“Data Alchemy” was devoted to emerging—or, depending on your viewpoint, well-established, merely rebranded by the Digerati—trends in statistical and predictive analysis. These are driving, part of, influenced by, and/or complementary to other trends, such as Big Data, the Cloud, cognitive systems, social networking, and the Internet of Things. But since this conference was aimed at businesses and future business users, the thematic upshot was technology’s promise to deliver sales results: a happier, healthier world in the form of a personalized, streamlined, twenty-four-seven shopping experience.

Mike Gualtieri of Forrester Research opened the conference with a keynote about treating customers like #Royalty. He championed the use of continuous intimate data monitoring as a way to personalize “experience”—which, in context, is reduced to “consumer experience.” Antiquated attitudes toward privacy might interfere with businesses’ well-intended desire to bring you the fastest, plushest, most convenient route to personal luxury. As he put it, “I use Uber. They know where I am,” and, “We know lots about the Royal Family, don’t we?”

So, this is the coin of the internet realm today: “free” means “not paid for in hard money” but instead “in exchange for information about you, your activities, whereabouts, and/or habits.” I have seen it written elsewhere that one characteristic of “Millennials” is the willingness to trade personal information for “value”. I admit it sounds a bit like the currency of an older profession to me, especially once the subsequent transaction involves a credit card. Here things become a bit less free.

This wasn’t a consensus view. Several speakers emphasized the importance of data security not only to fraud prevention—predictive analytics are being used increasingly to anticipate, not merely detect, fraudulent credit card transactions and identity theft—but as a sign of “respect” for consumer privacy. Dr. Vadim Kutsyy of PayPal went so far as to state that he would investigate and, if Spotify really does monitor his GPS position in order to customize his playlists, he would be closing his account; I note, without irony, that he is no more a Millennial than I am.

There were several presentations about the use of analytics inside the enterprise. As you might guess, these tend to be in “enablement” and workforce development (i.e., training and HR) rather than in the more-easily tractable business-process and production quality areas. Email and social media conversations contain a wealth of metadata that’s readily discoverable, plus in an employer-employee relationship, message content itself is a matter of record. A little data mining and analysis can spotlight all sorts of little harbingers of disgruntlement: the words you use, the people you mention, those you address, carbon- and blind-copy. Skip-level communication is an especially interesting marker, and may suggest training and reinforcement are in order; so might “insular” conduct in general. These are cases where Fortune-1000 size companies “have the data so might as well use it.”

Well, I suppose if we all read the fine-print in our employee-at-large contracts many of us would choose poverty with dignity over full-time employment, right? Even Millennials? Of course, we might then end up on the wrong side of the digital tracks, which is pretty rough territory now that all the squats are being listed on AirBnB….

Today’s Cloud follows the smart phone-, iWatch-, FitBit-equipped Person of Tomorrow around like rain once did Joe Btfsplk in Li’l Abner. It emits a steady hail of consumer opportunities in the form of clickable links and targeted adverts. It may send back to the Mother Ship various useful data about You, the Customer—it’s all about You—such as how long you’ve been running, how close you are to the nearest Starbucks, what music you’re listening to, the tempo of your stride, all so the targeting algorithms can automatically place you more squarely in the Crosshairs of Commerce.

Dean Abbott, of Smarter HQ, an entertaining exemplar of the Data Scientist, made a statement about his early career that happened to summarize not only the day, but the state of the art:

“The same technologies used to pilot smart missiles in the ’80s are used for targeted marketing today!”

Happy shopping.