Data matters. You don’t need to be a professionally trained futurist to see that a critical driving force in the global economy for the next 10 years will be data exploitation (creation of value with data), data sharing and data protection. (Let that data Exploitation, Sharing and Protection be your ESP.) Executives need to examine what they know and how they think about data.
That’s because data matters, now more than ever. The recent CES in Las Vegas drove this home (even for those of us who only read about it rather than suffering the crush of humanity). If you hadn’t accepted the reality of the internet of things (IoT), you couldn’t escape it at CES 2017. When the IoT becomes dominant, every object will be collecting and sharing data. Smart beds will be sharing data with smart thermostats, smart refrigerators will be sharing data with smart product packaging, and smart hairbrushes will be sharing data with human hair brushers. And everything will be a source of data. Proof, a prototype wearable from Milo Sensors, measures blood alcohol level through your skin. Aspiring baseball superstars can use a virtual batting cage in which they practice against a database of every pitch ever thrown by a particular pitcher.
The nature of relationships will change. Everything will have a relationship with everything — objects with other objects, objects with their manufacturers, objects with their human users. The robots showcased at CES 2017, such as Mayfield Robotics’ Kuri and LG’s Hub Robot, were notable not so much for what they could do as for the relationship their interface enabled — their personality. The Yui interface of Toyota’s “Concept-i” concept car collects data that apparently can tell when the driver is happy or sad and adjust the mood inside the car accordingly. The NeuV concept vehicle puts Honda on a path that will “enable machines to artificially generate their own emotions,” according to the company.
Data is power
For 420 years, no one has challenged Sir Francis Bacon’s formulation that knowledge is power. But in 2017 and beyond, data is power. The differences run deep. Knowledge is gained through study and experience. Data is merely collected, and in such a quantity that no human mind can begin to contain it.
And those who collect it are divvying up the spoils in a data cold war, with Google accumulating a data set that reflects what we want to know, Amazon what we buy, Apple what we listen to and where we go, and Facebook how we connect. What is the Geneva Convention that governs what can be done with that data? And, with carmakers entering the fray with a focus on what we feel, are there different rules for collecting, managing and acting upon emotional data?
Who determines what data will be shared with what devices under which circumstances? Will we need a database to keep track of all the devices we have relationships with, another of which devices have relationships with which other devices and yet another of data permissions we have granted and revoked? A question looming in the not-so-distant future is how much of machine-to-machine language humans will need to understand.
Two ways of considering the balance of power between individuals and the data colossi are data empowerment and transparency. Data empowerment is the degree to which you can decide who knows what about you and when — now and in the future. Transparency is how knowable an individual or organization is. In this early stage of our digital society, individuals are becoming more and more transparent, while some organizations are becoming more opaque. But marketers tell me that consumers will influence companies by valuing transparency. To be successful, brands will have to be transparent about diversity in their workforce, sources of their raw materials, their eco-behaviors and more.
Sadly, although we live in a data-defined reality, the vast majority of executives leading major institutions today have received no formal training in data management. It will be fascinating to see what path individuals and organizations follow as they seek to hone and enhance data skills and rectify data deficiencies. Will universal measures of data skills be created? To be employable in the future, will one need to possess as-yet-unagreed-upon data skills certifications?
The bottom line is we exist at a moment when individuals have infinite choice regarding what data they wish to collect, analyze and act upon.