In this last blog of 2013, I want to make some serious points that should be front and center (he said coyly) for all analytic, BI and big data professionals next year. In fact, they should be already. And if not, I urge you to use some reflection time over the coming holiday to make them so. Let’s start with sex… toys. Consider the value of deep analytic big data monitoring to enforce the following two verified laws in the USA: (i) you may not have more than two dildos in the same house in Arizona and (ii) it’s illegal to own more than six dildos in Texas. (I refuse to speculate on why Texans may be less susceptible to moral degeneracy than citizens of Arizona.) I suspect most of us are mildly amused by such legislation. Many have probably long taken comfort in the belief that it is unenforceable; after all, who can imagine the local cops breaking into your home on suspicion that you are hoarding sex toys? But wait. Haven’t the authorities in the US and other countries been rummaging through your digital drawers for years now, and without any just cause for suspicion? Hasn’t at least one supermarket chain collated and analyzed data to determine if its (female) customers have recently become pregnant? Haven’t two technology companies applied for patents to spy on (sorry, gather behavioral data to enable better targeted advertising to) you via your living room TV? How far will government and business go in mining our personal lives, our sexuality, our bodies, our social circles to (allegedly) protect us, cure us or sell us more (unnecessary) stuff. The sad truth is that we have lost most of our privacy already, having entered into a Faustian pact to share, both knowingly and unwittingly, the details of our daily lives. That knowing part–the Facebook likes and Google +1s–may be said to represent a conscious tradeoff by the person sharing between a loss of privacy and a perceived increase in social capital or useful contextual information. Even the acceptance that our smartphones report our location minute by minute is driven by a consensual belief that we may be offered a coupon for a nearby coffee shop at any moment. The payoff for ultimate traceability. Apple iBeacon allows newer iPhones or Android phones with Bluetooth Low Energy devices to track their–and your–position in space with centimeter precision. Which aisle in the supermarket are you in? What about some very specific retail therapy recommendations? These, and other soon to emerge toys, have the addictive quality of sex to many of the current generation of CMOs and proponents of big analytics. However, the smartphone is but the pioneer species of the internet of things, the ultimate in small toys for big data boys. As sensors become ever smaller, cheaper and ever more powerful, the utopian vision is of systems that respond instantly to our needs, that anticipate our very expectations. We are promised houses that know we’re home and adjust lighting and heading accordingly. Wrist bands that sense when we awake in the morning, so that the coffee can be brewed, or know that our elderly aunt has not moved for the past hour and may have slipped and broken her hip. Software to the rescue, hardware to alleviate yet another chore. According to Computerworld, Gartner predicts that half of all BI implementations will incorporate machine data from the internet of things by 2017. Research conducted by EMA and 9sight during the summer of 2013, suggested that the future is already here; machine-generated data overtook human-sourced information as big data sources among our respondents. And the more details of our mundane activities that become available in the internet of things for analysis and correlation, the more specific and identifiable our individual patterns of behavior become and the more difficult it is to retain any degree of anonymity. IBM’s 5 for 5 this year includes “a digital guardian that will protect you online” within 5 years. But it’s mostly about security rather privacy, and already years too late. Realists may like to consider how useful such tools would have been to the Stasi in German Democratic Republic (East Germany) or the Soviet Union’s KGB in the second half of the last century. Would the world be as we know it if they had? The more dystopian among us conjure up visions of Franz Kafka’s The Trial or George Orwell’s 1984 only 30 years late in arrival. But, it is not my intention to propose neo-Luddism. The big data jinni is already well out of the bottle. Despite the silly-bugger games we are currently playing with it, big data does hold the possibility to understand and address many of the most intractable environmental, climatic and social issues we face today. Although, as I’ve mentioned repeatedly in “Business unIntelligence: Insight and Innovation Beyond Analytics and Big Data“, our success in acting upon, never mind solving, them will depend far more on our very human intention towards what we desire than on all the data, software and hardware we apply. So, as we look to 2014, I urge all of us to keep three resolutions in our minds, a subtle matrix underpinning every business need we evaluate and every design decision we make:
Understand and account for the relationship between big data and the traditional core business information long created and processed in existing operational and informational systems; each complements and contextualizes the other
In gathering and analyzing big data, consider how its use can impact personal privacy, especially the ways in which such data can be combined with other big data sets and compromise anonymity
Perhaps most importantly, consider the universal/global impact of the project: how does it contribute to or mitigate the real-world issues of environmental degradation, over-production and consumption, economic instability, and more. In short, how does it support the best in humanity and the world?
These, especially the last, may sound like utopian dreams. But, consider the almost unimaginable power unleashed by the unprecedented growth and interconnection of information currently in process. We are unleashing a potential for good or ill far greater than that created by a small team of physicists in Los Alamos during the Manhattan Project.
