THE BLOG
04/03/2013 06:57 pm ET Updated Jun 03, 2013

In Big Data, We Hope and Distrust

"In God we trust. All others must bring data." -- W. Edwards Deming, statistician, quality guru

Big data helped reelect a pesident, find Osama bin Laden, and contributed to the meltdown of our financial system. We are in the midst of a data revolution where social media introduces new terms like Arab Spring, Facebook Depression and Twitter anxiety that reflect a new reality: Big data is changing the social and relationship fabric of our culture.

We spend hours installing and learning how to use the latest versions of our ever-expanding technology while enduring a never-ending battle to protect our information. Then we labor while developing practices to rid ourselves of technology -- rules for turning devices off during meetings or movies, legislation to outlaw texting while driving, restrictions in classrooms to prevent cheating, and scheduling meals or family time where devices are turned off. Information and technology: We love it, hate it, can't live with it, can't live without it, use it voraciously, and distrust it immensely. I am schizophrenic and so am I.

Big data is not only big but growing rapidly. According to IBM, we create 2.5 quintillion bytes a day and that "ninety percent of the data in the world has been created in the last two years." Vast new computing capacity can analyze Web-browsing trails that track our every click, sensor signals from every conceivable device, GPS tracking and social network traffic. It is now possible to measure and monitor people and machines to an astonishing degree. How exciting, how promising. And how scary.

This is not our first data rodeo. The early stages of the customer relationship management movement were filled with hope and with hype. Large data warehouses were going to provide the kind of information that would make companies masters of customer relationships. There were just two problems. First, getting the data out of the warehouse wasn't nearly as hard as getting it into the person or device interacting with the customers in a way that added value, trust and expanded relationships. We seem to always underestimate the speed of technology and overestimate the speed at which we can absorb it and socialize around it.

Second, unfortunately the customers didn't get the memo and mostly decided in their own rich wisdom they did not need or want "masters." In fact as providers became masters of knowing all the details about our lives, consumers became more concerned. So while many organizations were trying to learn more about customer histories, behaviors and future needs -- customers and even their governments were busy trying to protect privacy, security, and access. Anyone attempting to help an adult friend or family member with mental health issues has probably run into well-intentioned HIPAA rules (regulations that ensure privacy of medical records) that unfortunately also restrict the ways you can assist them. Big data gives and the fear of big data takes away.

Big data does not big relationships make. Over the last 20 years as our data keeps getting stronger, our customer relationships keep getting weaker. Eighty-six percent of consumers trust corporations less than they did five years ago. Customer retention across industries has fallen about 30 percent in recent years. Is it actually possible that we have unwittingly contributed in the undermining of our customer relationships? How could that be? For one thing, as companies keep getting better at targeting messages to specific groups and those groups keep getting better at blocking their messages. As usual, the power to resist trumps the power to exert.

No matter how powerful big data becomes, if it is to realize its potential, it must build trust on three levels. First, customers must trust our intentions. Data that can be used for us can also be used against us. There is growing fear institutions will become a part of a "surveillance state." While organizations have gone to great length to promote protection of our data -- the numbers reflect a fair amount of doubt. For example, according to MainStreet, "87 percent of Americans do not feel large banks are transparent and 68 percent do not feel their bank is on their side.:

Second, customers must trust our actions. Even if they trust our intentions, they might still fear that our actions put them at risk. Our private information can be hacked, then misused and disclosed in damaging and embarrassing ways. After the Sandy Hook tragedy a New York newspaper published the names and addresses of over 33,000 licensed gun owners along with an interactive map that showed exactly where they lived. In response names and addresses of the newspaper editor and writers were published on-line along with information about their children. No one, including retired judges, law enforcement officers and FBI agents expected their private information to be published in the midst of a very high decibel controversy.

Third, customers must trust the outcome -- that sharing data will benefit them. Even with positive intentions and constructive actions, the results may range from disappointing to damaging. Most of us have provided email addresses or other contact data -- around a customer service issue or such -- and then started receiving email, phone or online solicitations. I know a retired executive who helps hard-to-hire people. She spent one evening surfing the Internet to research about expunging criminal records for released felons. Years later, Amazon greets her with books targeted to the felon it believes she is. Even with opt-out options, we felt used. Or, we provide specific information, only to repeat it in the next transaction or interaction -- not getting the hoped for benefit of saving our time.

It will be challenging to grow the trust at anywhere near the rate we grow the data. Information develops rapidly, competence and trust develop slowly. Investing heavily in big data and scrimping on trust will have the opposite effect desired. To quote Dolly Parton who knows a thing or two about big: "It costs a lot of money to look this cheap."