For over a decade, data has been at or near the top of the enterprise agenda. A robust ecosystem has emerged around all aspects of data (collection, management, storage, exploitation and disposition). And yet in my discussions with Global 2000 executives, I find many are dissatisfied with their data investments and capabilities. This is not a technology problem. This is not a technique problem. This is a people problem.
Those enamored of data often want to eliminate the human from the equation, but it can’t be done. And so, as climate science considers the impact of man on the environment, data science must wrestle with the inverse: the impact of data on man.
You can fill a library with books talking about the data revolution. There’s Viktor Mayer-Schönberger’s Big Data: A Revolution That Will Transform How We Live, Work, and Think; Steve Lohr’s Data-ism: Inside the Big Data Revolution; Malcolm Frank, Paul Roehrig and Ben Pring’s Code Halos; Bruce Schneier’s Data and Goliath: The Hidden Battles to Collect Your Data and Control Your World; Christian Rudder’s Dataclysm: Who We Are (When We Think No One’s Looking); Andreas Weigend’s Data for the People: How to Make Our Post-Privacy Economy Work for You; and my very own The New Know: Innovation Powered by Analytics.
These are fine works of nonfiction focusing on the potential and perils of a rapidly informating world. “Informating” is a term coined by Shoshana Zuboff in her book In the Age of the Smart Machine (1988). It is the process that translates descriptions and measurements of activities, events and objects into data/information. “Datafication” is a synonym for “informating” — the trend associated with turning many aspects of modern life into machine-readable data and transforming this information into new forms of value.
What about the muggles?
The question that has not received much attention in technology circles is how and via what time frame the masses (a.k.a., the general public, regular humans, the muggles — those who are not trained, credentialed or particularly facile in data management and use) will respond to the accumulation of massive data. Sociologists and anthropologists need to weigh in here.
Some of the most interesting thinking about the impact of all this data is happening in literature. In Circles, David Eggers gives us a fictional portrayal of what a totally informated workplace might look like. It is not a pretty picture. I think this is a must-read for those who seek to understand the human side of the data revolution.
Some scholars contend we are in the middle of a personal-data gold rush (see “Personal Data: Thinking Inside the Box,” by H. Haddadi, et al.). It is not obvious that the beneficiary of this gold rush will be the source of the data gold — people. How many average Joes realize that if they are not paying for the service, they are the product? Data “accumulation is generally occurring with minimal consideration of us, the individuals at the heart of this process,” as Haddadi and his fellow researchers write.
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