The Data and I.

In our new series The Data, the Cloud, the WiFi and I we want to talk about options. It’s still time to decide what to do with data, where to store and how to manage it, but for too many companies, functions and idividuals it is still an issue to outsource, hand over to IT or let consumer authorities, and digital giants take care of.

This first article is the opener of the series.

It all began with one of mankind’s biggest dreams. The encyclopedists, and some princes and archdukes of the 18th century thrived to “give the knowledge of humanity to the people of France, Austria, Germany” in the shape of arts and crafts collections, “chambers of miracle”, and written articles in alphabetical order. In the days of the early web, the dream persisted and moved the people behind Wikipedia, the Internet Archive, Google and many more, but in the more global formulation of Universal Access to all Knowledge. Or, as Google likes to put it: “Organize the world’s information and make it universally accessible and useful”.

What can possibly go wrong when the intelligent elite of one of world’s leading nations pursues such a noble goal? Murphy’s Law tells us that if there’s something that can go wrong, it will.

For nearly two decades now, we’ve been happily using for free the great messaging, search, navigation and analytics tools, and whatever outcome of ingenuity travelled from the valley across the pond to anywhere the Internet is allowed to spread such news freely. There were critical voices right from the beginning, and not only the occasional conspiracy theorist, but also common-sensed people cited an old, but true saying: If something sounds too good to be true, it probably is.

In 2006, when Google’s first navigator bar to be installed on virtually all consumer PCs worldwide was announced, the outcry came mainly from industry insiders and competitors, but it gained public attention, and the data exploitation subject has been here to stay. With varying focus, it’s keeping us occupied ever since.

When by the end of 2010 some interesting insights disappeared from the free version of Google Analytics, we could not say we haven’t been warned. In 2011, the Premium version was proudly presented – price: US$ 150,000/year. In the meantime, Google has launched the Analytics 360 Suite, and 150k per year is just the starting point for the most basic version.

Data has become a multi-billion-dollar industry during the last decade, and the companies who came up with the easiest to use, most comfortable and free information and communication tools are the big winners in this game. Now, while they’re reaping what they sew, the rest of us wake up to the truth that we’ve given away for free what they’re selling us now. To keep the discussion fair, it has to be said that it takes a lot of great engineering, craft, intelligence, and labor to build software products. Why on earth should anyone do all that for free? What’s wrong with them earning a lot of money by now?

Let’s come back to our initial question of what can go wrong, combine it with Murphy’s Law and another famous dictum from the late 16th century, often attributed to Sir Francis Bacon: Knowledge is Power. Now we’re down to the nitty-gritty. Those in control of massive amounts of data are able to predict and potentially influence human behavior.

Recent data breaches and incidents like the Facebook-Cambridge Analytica scandal have prompted governments and businesses to call for more data privacy legislation. But the EU’s GDPR and other countries’ similar laws and authorities seem to be fighting a losing game, as every day more and more data is generated faster than regulators can keep up. Two or three major players out there may have the financial and human resources to keep the pace, but governments or individuals usually don’t.

Beyond doomsday pronouncements or envy and tax injustice debates, being aware of two simple facts will help us to cope:

• The challenge lies in the scale: It’s not the data itself, it’s the massive accumulation and centralized analytics that make the money and are prone to risk. The average person’s data is seldom traded for more than 50 cents, not even the craziest of hackers would write a code to steal individual data bits. By the way: If you’re interested in how the value of your personal data is calculated and how much it actually is, check out this interesting calculator:
• The challenge lies in the structure: Every outsourced centralized structure for data storage, exchange or analysis is potential grist to the big players’ mill, and multiplies risk probability and impact exponentially.

A question worth asking is: Does data always have to be big to be useful? Obviously not. While it makes sense to consider globally collected data to track the pandemic influenza viruses most likely to affect a given area this winter, it may be useless or even harmful for deciding on distribution channels for a niche product in regional markets.

Another question is: Will a large amount of data help me, my family or my company, make my life or my company’s success any better? Probably not. Private or corporate success depend largely on decisions, but for a good data-driven decision, lots of data can be totally useless if we don’t have the ability to read them. We will need the right data, and the right understanding of analytics. And we need varied, appropriate structures for different kinds of data. Some may make sense to be centralized or outsourced, others may not.

A good thing is that governments, companies and individuals begin taking data more seriously. But instead of just complying with consumer data protection rules, every company should also be aware of the potential and value of their own collected data. Instead of giving away data control to IT staff or external services, they should promote and cultivate internal awareness and critical skills on all management levels. Informed critical thinking has to be cultivated from the early childhood days, throughout education curricula and professional careers. Data-savvy, yet skeptic decision makers will be one of the key factors to future success, and the ability to distinguish between different kinds of data and ways to manage them should be a core competence in every modern company.