With the growing popularity of BI (Business Analytics) in today’s competitive world, felt it important or at least of value to discuss our ole friend Heisenberg and his involvement in modern analytical modeling as our friends in the science communities have been dealing with him for some time now and why should they have all the fun, right?
Now don’t worry as my intent here is not to delve into a full blown dissertation of the “Heisenberg Uncertainty principle“, however we will give you just enough of it to apply it to your “analytics” thinking and toss out a few cool ideas at the water cooler Monday morning to get your coworkers to look at you in a different light.
So in short what Heisenberg (a physicist) said is you cannot measure “both” the “direction” and “motion” (speed) of a quantum particle “accurately“. The key words here for our discussion are “both” and “accurately“. Ok so what does this mean to me your asking yourself? Well let’s pull ourselves out of the quantum world for a moment, and return to our practical one to see how things work.
Here, you’re driving down the road (this is a thought experiment only please do not actually do this) in your band new shinny red car. Here if you would imagine for me that you’re focused on the speedometer for a second. Now how fast are you going? Oh, by the way you need to maintain that speed within a 1/8 mile an hour range for your total trip too.
Now lift your gaze up from the speedometer and look over at the GPS affixed to your windshield and note what direction are you going? Ok, now hold that heading within less than one tenth of a degree (keep in mind you still have to drive the car too).
Ok, let’s hop back, how fast are you going now? Bet dollars to donuts that you’ve drifted from your goal haven’t you? Be honest about it. So in very simple terms you see the complexity of this along with the challenges it creates even at the macro level. Those cynics out there are now saying “Yea that little bit who cares! That’s rounding error on petty cash, go away boy your bothering me”.
However what if you’re piloting a jetliner, a little bit sure does count and the key ingredient to success is picking what is your focus. As the airline pilot is more concerned with the area at this small target (think of the precision for a trans-oceanic flight to hit little a strip of runway halfway around the world) then arriving on the second.
The moral of this story is the first rule; know what is of primary value in the datasets. As data will bring with it a form of “duality” (two interrelated values) when associated with multiple data elements. As this Raises the second important axiom related to this discussion as my Texan friends like to say, “don’t chase two horses as you will not catch either“…