The Curse of Analytics and the Big Data Hype

I'm getting a little tired of these succinct blog posts which I think I'm going to start calling "toilet confessionals"; someone gets some grandiose epiphany while sitting on the can, and then bangs out a few paragraphs for a blog -- complete with massive hand-waving and over-simplifications (such as using shallow metaphors like comparing a business activity to a Snickers bar) -- and then pats themself on the back before calling it a done deal.

> Here’s the problem – analytics are expensive. They take time, they take knowledge, they take investment in analysis tools and data systems, and crucially, they require we be willing to change our behavior based on what we learn.

VERY broad generalization here; "analytics" is arguably the cheapest thing that you can do, unless you go and buy million-dollar software packages to do it for you. Nothing about analytics says that you must have your own private server farm, an enterprise copy of MicroStrategy (or w/e), and a building full of PHD's to get results.

> Moreover, analytics without purpose and no tie to decisions keep us from focusing on the most important tasks ahead of us.

Oh, come on. Replace "analytics" with 1000 other words and the quip still fits; this isn't a revelation on analytics, it's a fact of productivity: you'll never get to where you're going if you don't know where it is that you want to end up.

Certainly this reminds me of many of my past experiences in larger businesses. Analytics using bad methodology, producing untrustworthy statistics for the sake of having statistics. What a waste of money and productivity that is.

However, just because we think we know the answer doesn't mean we actually do, so I would strike that consideration off the list. Often it is good to measure what we already think we know so we can be sure we actually have evidence to back it up.