This post is a continuation of describing how Shift Sight, a Teal organization, is inherently different from what most of you know.
It explains our position on an increasingly wasteful and damaging technology: Big Data.
Today’s business climate demands omniscience. I am not kidding! There are buildings whose sole purpose is to house roomfuls of computers. These servers collect and analyze every electronic bread crumb that customers leave behind on company websites and apps. It is a continuation of what businesses have always done – attempt to understand a customer to know what they want.
Nowadays, it is “big” due to the quantity of crumbs that is collected on each customer. Every single electronic interaction is captured because customers have, knowingly or not, surrendered every bit of online privacy they used to have.
Big Power Use
Every bread crumb is now treated as a gold nugget of utmost importance. If it seems unimportant today, it simply means that we have not figured out its significance. Save it for later, and know all that is knowable.
This data powers “smart” businesses making data-driven decisions. Managers can partially avoid culpability for bad decisions, because the method has been “proven” – if the decision was bad, it must have been bad data. So we go on to collect more data.
We collect the data on disposable computers. These computers were manufactured with a stale date. They will need to be replaced by something faster, because more data demands more performance if we do not want to slow decisions and business. Hello, electronic waste.
There is an inherent problem with collecting data. When you measure something, you change it. More precisely, when you measure someone and label the measurement, you change them. (Of course, most people are subjected to the Big Data output rather than the effect of each measurement.)
Let me share a story. Please read it and come back.
The conclusion of the story applies to business as much as it applies to a classroom: if you tell yourself that your data is leading to the best decisions, you treat your data as though it is the single source of truth, and you believe it is accurate, you will never see a better alternative. You will just want more data.
The problem is that we sample one input, confirm its truth against an output, and build a more elaborate collector with two inputs. As long as we are convinced it is accurate, it grows. It eventually passes a point where it becomes impossible to separate signal from noise. Apparent cause is matched to effect while true cause is obscured.
It is like trying to predict which apple will fall off of an apple tree next based on weather, where the last apples have fallen, and the calendar year. It completely neglects the true cause: the individual biology at each branch.
Data-driven decisions now appear to be the best decisions simply because there is no “verifiable” alternative. In effect, the premise drives the conclusion.
Teal is Different
I have witnessed many data-driven decisions that were counterintuitive but carried out because “the data said so.” They produced ugly results. And afterward, the method was not blamed – the data was.
As you might suspect, Big Data has no place in Teal. To convey how out of place it is, I offer analogies of the mafia giving annual performance reviews, or a religious institution handing out a “most improved religious leader of the year” award. These scenarios are incompatible with these organizations.
One purpose of Big Data is highly targeted, manipulative advertising. Teal product offerings speak to the human heart. We have no need for roomfuls of disposable servers requiring megawatts of power simply to manipulate a customer into a purchase.
Teal businesses are a paradox. They are profitable because they have chosen to not focus exclusively on profit.
The darkness I am referring to in the title of this post is not literal. Current businesses are headed in a direction that increasingly defers trust to data. When we trust in the external method, we trust ourselves less. Some have already labeled the method as infallible. This is a darkness of human trust and human intuition.
Big Data businesses are heading into night. Can they learn to see in the dark?