If a tree falls in the forest…

Like it or not, we live in the data age.

Each of us, in nearly every sphere of our lives, generates data exhausts that are increasingly used to weigh, measure and categorize us.

This is not only true for individuals, but at every level at which human effort can be aggregated — companies, cities, regions, states and countries.

As you zoom out, the power of individual human narratives is drowned out by data and the patterns that lie therein.

This topic kept popping up in my newsfeed this week as…

  • Leena Rao of TechCrunch published a great piece on the rise of “big data” pattern sifting among venture investors;
  • Danielle Morill pivoted her referral commerce startup Referly to become Mattermark, a data anlytics platform for (you guessed it) VCs; and
  • The Atlantic published a Richard Florida piece titled “The New Global Startup Cities” using data ┬ásourced from CrunchBase and analyzed by SeedTable to rank the top global cities for tech innovation.
I’ve always believed that quiet excellence was more valuable than noisy mediocrity, but — for better or worse — we have entered an era in which private actions must be accompanied by public data to ensure discoverability and create opportunity.
As patterns that drive decisions are increasingly discovered by machines, claiming our place in the economy will require all of to emit machine-readable signals.
What does this mean for each of us, our companies and our ecosystems?
  • As individuals, we must each find ways that are authentic to us — depending on who you are, that may be Twitter or Facebook, GitHub or Dribble, LinkedIn or WordPress — to generate a steady stream of public signals about who we are, what we believe and how we create, so our identities can be weighed by these non-human judges.
  • As businesses, we must carry out all those same individual actions, but also generate readable signal in the form of media coverage, regulatory filings, financing events, key hires landed, partnerships won and patents awarded, site visitors, app downloads and customer reviews, to establish relevance and momentum in the eyes of the machines.
  • As city-states competing in the global marketplace for talent, money and media attention, we must aggregate and promote the actions of our individuals and companies, but also share data about job growth and budget surpluses, infrastructure investments and educational achievement, property values and crime rates, to feed the same machines.
Like so much about our technology-fueled future this accelerating requirement to generate machine-readable data isn’t inherently good or bad, it is itself an exhaust — a consequence, to use a more loaded word — of our society’s growing mastery of automation. Wring your hands all you want, but then get busy producing signal, because the machines don’t care how you feel about it.
If a tree falls in the forest and no machine is there to process the data, does it generate any?