"All or Nothing" or "At Least Something, Not Nothing"
An interesting thought woke me up this morning: Which is a better situation - having half-baked data and having "something" than nothing, or having nothing at all?
At first glance, some would prefer the "half-baked data" - it is better than nothing. Besides "something is always better than nothing". Right?
My first reaction is - no.
"Something is always better than nothing" is too overvalued. That "something" needs to be qualified first and foremost - specially, and most specially, if we need to make decisions based on that something. There is nothing far worse than making a wrong decision because "our data is showing this trend" - when the quality of the data is not correct.
It is perhaps the perfectionist and the disciplined in me to say "It's all or nothing, dude". But I know that it's economically not viable in all situations. However, saying that at least "we have something - better than nothing" - and taking satisfaction in that specially when it comes to crucial, critical factors that may drive a business - is also not acceptable.
"Perfect enough."
Those are words that I learned from Carly Fiorina's book. And I think that's applicable in this situation. Never cut corners - always conduct due diligence - always seek for perfection - and if there is the need to drop the human need for perfection because of reality, then drop it.
But because you've aimed for perfection, if you stopped 20% or 30% or 40% short of 100% perfection - you still have the confidence to say "Yes, we've got something... It is not perfect, but we've been duly diligent and rigorous".
Indeed, a careful balance - one that marketeers, decision-makers, and business executives ought to think about in these data-rich, information-flooded, yet "analysis-paralyzing" situations.
