In God we trust, everyone...

I think the only reason I even bring this up is because I've been looking at many, many spreadsheets lately — and with that, an awful lot of data.

This pithy term comes to me honestly because many years ago I was developing my function excellence skills and participated in Six Sigma Black Belt training. This humbling affair still resonates when I think about the onslaught of statistical and functional excellence models, playing with toy catapults (and the statistical analysis behind what was seemingly child's play), and my disheartenment when I watched people much smarter than myself in a daze after class. In the end I completed my project and because of the experience carry the following three truths at my core when it comes to how I need to think about things.

Truth 1. "In God we trust, everyone else bring data" — it's a reminder that only data offers an objective view of things.

Truth 2. The DMAIC model is very useful when you want to improve something — Define, Measure, Analysis, Improvement, Control

Truth 3. What we "subjectively believe" tends not to be the same as what "objectively is" — and sometimes it's worlds apart.

I'm hard wired to be subjective, figurative, and broad thinking (and I suppose I'm really an artist stuck in a scientist's body) and because of this, I hold these hard earned truths with passion and appreciation. 

Data is the currency of real understanding and it trumps words like "I think", "I feel" and "I believe" and enables you to use the words "I know". Data brings objectivity to the understanding of a situation, what's really happening, and helps you drive better decisions and actions. While I'm thinking about this, here's another pithy saying that warrants consideration, "Lies, damn lies, statistics" — it's a reminder that even numbers need to be vetted and confirmed for accuracy because, although data is objective, it still needs to be validated.

It seems there is actually a fourth truth that I almost forgot about —

Truth 4. When you bring data make sure you aren't bringing data for data's sake but for reasons associated with an objective (hopefully to move your goals forward.)

Forgive me for not remembering it sooner but the training was a while ago, and as you may appreciate, a little traumatic.

iamgpe