“The song will never work. It’s too long, too complex, too confusing

and doesn’t fit into any musical genre.”

– Radio stations’ feedback to Queen about Bohemian Rhapsody

Data is a funny thing. It’s used by marketers, bloggers and managers as the ultimate proof of truth. 78% of women agree. 21% more people converted on the new design. 63% of projects hit their deadline. We put a number against it. A cold hard NUMBER. You can’t argue with a number. It was measured.

I used to take a lot of measurements. I studied astrophysics for almost seven years, and for the last two of those I helped to collect four-dimensional data sets about the Local Group of galaxies. The data had to be recorded, reduced (processed), analyzed and coerced into giving enough results to publish peer-reviewed papers and keep the funding coming.

It’s also where I studied chaotic systems, where minuscule variations in inputs can have considerable effects on the later state of a system, with no way of retrospectively linking the cause to the effect. I think of chaotic systems whenever I see that common financial disclaimer and truism, “Past Performance is Not Necessarily Indicative of Future Results.”

Of course it isn’t. Almost everything changes all the time. A statistic or data point is a tiny speck floating in a sea of ever-changing context. People change, attitudes and behaviors change, tastes change, the economy changes, our minds, bodies, relationships and priorities change. The Observer Effect describes how something can change just by the process of measuring it.

There is so much invisible, fluid context wrapped around a data point that we are usually unable to fully comprehend exactly what that data represents or means. We often think we know, but we rarely do. But we really WANT it to mean something, because using data in our work is scientific. It’s not our decision that was wrong — we used the data that was available. Data is the ultimate scapegoat.

Our capability to measure and record data is rapidly improving, at a time when more and more leaders are trying to protect their status and image by walking the middle ground, pre-calculating every decision and spoken word. The result is that the world increasingly uses and relies on data-driven decisions, from the smallest trivial matters, to policies in large corporations and entire countries. Sometimes it works. Sometimes it’s critical. But sometimes it fails, or results in unintended consequences that we may not notice for years.

Data-driven journalism gave us Buzzfeed

Data-driven music gave us X-Factor and Pop Idol

Data-driven movies gave us 25 Hollywood sequels planned for this year

Data-driven education gave us Key Performance Indicators and Teaching to the test

If you know any teachers, ask for their opinion on the way success in education is measured. One of the most nuanced and important things we do as a society is often handily reduced to a single percentage score so that it’s easy to compare and fight over the “top” spots.

The modern obsession with data is perhaps most noticeable among tech entrepreneurs, Internet startups, and the bloggers and media in the tech industry. Even regular data isn’t exciting enough for us any more, we now need even better data. BIG data.

“If you don’t measure it, you can’t improve it.”

That’s the tired cliché repeatedly told by the kinds of people who have to put a number on everything. These are the people who are responsible for the existence of Klout, and buy the self-help books in their millions because they believe that there must be repeatable secret rules and quantifiable steps that determine success and failure. Either millions of people didn’t read those books that they bought, or it turns out that the steps weren’t as easily reproducible as the book cover suggested.

Startup data obsession can give a false sense of security. A set of numbers measures a limited number of factors in a limited context, and therefore should be used rarely to make major decisions in an early stage startup.

As counter-intuitive as it sounds, I hypothesize that an early startup guided primarily by gut decisions from a strong strategic vision will be more cohesive and deliver a stronger offering than a startup created from a random walk of data-driven decisions. Though I don’t have the data to back up my claim.

To clarify, I’m not waging an all-out War on Data. It would be naïve to exclude data from all decision-making, or to not seek it out. But I don’t believe that an early startup should be driven by data. It should be assisted by data, using it as one of a number of inputs when making tactical decisions. Data shouldn’t guide strategic decisions.

“Never make [a] mistake again and include data in your

decision-making process” – Source

“A data driven startup involves making every business decision

based on data” – Source

“Our founders decided that the company should be more data-driven

and take key decisions based on data” – Source

An early stage startup team that reads the countless blog posts about measuring and numerically assessing every minutiae will eventually realize, perhaps too late, that you can’t micro-optimize your way to success. Sure, you can improve many things by measuring and comparing, but you can’t optimize nothing into a hit. As the old saying goes, “You can’t polish a turd.” Unless you use Turdle-Wax, of course.

It’s also incredibly difficult to measure the long-term effects of those decisions. A long time ago someone found that the phrase “You should follow me on Twitter” produced the best results. Then a few other people started using it, because data. Then it was EVERYWHERE. You can bet that within a short time, the desired effect was no longer being achieved, and instead the people who used the phrase looked tired and unoriginal.

But maybe that’s accurate. Maybe the kinds of people who do this are tired and unoriginal. Turning to data to make every major decision about an early startup feels not just potentially incorrect, but utterly joyless and uninventive. The desperation for success is more important than the cohesive vision of what they want to create. These people would rather be Michael Bay or Coldplay than David Lynch or Radiohead.

“If I had asked people what they wanted, they would have said

a bigger keyboard.”

– Steve Jobs didn’t say this about the iPhone, but should have,

in reference to the adage that Henry Ford didn’t say, either.

Of course, the radio stations were absolutely correct about Bohemian Rhapsody on all their points except one. Compared to the data on what the market wanted, the song was too long. It was too complex. It was too confusing, and it didn’t fit into any best-selling genre. Even though it was a massive outlier compared to the data, somehow it worked.

Bohemian Rhapsody went on to become the only song to reach number one in four different years. But even better than that fleeting data-point of success, it went on to change what popular music could be, and made countless people happy.

“We are the music makers, And we are the dreamers of dreams.”

– Ode, Arthur O’Shaughnessy

Follow Backchannel: Twitter | Facebook