Does the data tool matter?
The headline: The data tools we use matter... but not for the reasons we think. Fit, features, and financial requirements aside, I think feeling may matter more.
What it matters: Our technology selection processes often emphasize the former, but data nerds (like me) are quirky. As hyper-logical thinkers, we're drawn to our profession because the data never lies and often forget people (and feelings) do. We even lie to ourselves.
I got a new pair of shoes
The backstory: My last 4 pairs of running shoes were Saucony Guides. Here's the data behind every step I ran in them. They were recommended by my local running shop after a fitting.
I injured my foot July 4th. I was running too many miles. I've had to lower my mileage the last few weeks. Every run was a bit more fatiguing on my foot. I needed a fresh start.
A new pair of Oxfords? Yes, I went shopping for Oxfords instead (read why at the end). But, I saw these On Cloudsurfers on clearance. I heard they were ultrasoft. I was curious.
A gimmick? I've heard a lot of hype (and criticism) of On running shoes. And I've stuck to tradition (and the advice I received) with my Sauconys. But yesterday, I fell for it.
What I learned: The fatigue in my foot faded. There was a fresh pep in my step. Maybe it was the fit and features. Maybe it was the feeling. Was it the facts or just in my head?
It started me thinking: When play a new guitar, is it really the fit and features that inspires a rush of creativity? Does my favorite pizza peel really help me make better pizza? That recent iOS update is absolutely slower, but why does it feel like a faster, new phone at first?
We're not as logical as we think we are. When fit, features, and financial requirements between options are negligible, the feel may matter more. If "the feel" gives energy, stimulates creativity, and boosts output, does it really matter if its just in our head?
Back to data
A popular opinion: I "talked data" in Denver and Detroit last week, frequently on the fit, features, and financial requirements of data tools. From analytics and BI tools to data integration to data governance (and even GIS) tools, it focused on these factors:
The next step: These may filter out a few data tools, but how do you find "the best" tool in the remaining field? How do find the differentiating features (and know if they matter)?
One strategy: Try something new. I love the feeling of a technology. Sure it's hard to leave the familiarity my current data tool, but the freshness can make a real difference. And, each time I learn a new tool, I get a rush of ideas how and when I can use it. I add to my toolbox.
An example: On Running Shoes makes a shoe to fit any foot. Their soles look unique in appearance, but I'm still not convinced the features are really that different. Are they different? If I'm honest, I avoided them... financially. They're expensive.
But how much does cost matter? If I spend $150 instead of $100 on shoes that last 500 miles, should 10 cents a mile really be the defining factor?
So is there really a difference between On and Sauconys?
Feel matters: My first run in them yesterday was fun. It was fresh. My foot felt better. It wasn't fatigued. And it may have been in my head, but does that really matter?
The takeaway
When deciding on data tools (or running shoes), start with the fit, features, and financial requirements to filter out the field. After, don't forget about the feel and remember:
Final thought: Why did I go shopping for new Oxfords? I have a few BIG meetings this week and hated my current Oxfords. Not for the fit or features, but how they made me feel. I wanted a fresh pair that would help me feel confident this week! Feeling matters. Wish me luck!
This article is part of my blog, Running Thoughts on Data. My first post, The Story My Data Cannot Tell, shares the genesis of my blog. The views and postings on this site are my own and do not necessarily represent those of Plante Moran.