Was it worth buying?

I wrote the following post for my LinkedIn account, in response to a viral post that urged data analysts to do a better job selling their work:

I used to spend a staggering amount of time listening to music podcasts.

Every now and then, a song from one of the podcasts would stand out from the rest, and I would write down the title to listen to it again later.

But sometimes, by the time I got around to listening to the song again, not only did I not particularly like it, but I couldn't figure out what I might have liked about it the first time.

I eventually realized what was happening. The first time I heard the song, I was comparing it to the other songs on the podcast. When I re-listened, I was comparing it instead to my collection of favorite songs. Different standard, different judgment.

What does that have to do with data analysis?

A lot of data analysis is drudge work: Cleaning data, sifting data, standardizing, finding anomalies, explaining anomalies, documenting. Seeing a pattern in the data is exciting by contrast. Like so many things in life, data analysis is hours of work for the sake of minutes of joy.

But sometimes that pattern...the one that looks so penetrating and interesting? Well...sometimes it looks that way only when you need something to be excited about after hours of drudgery. And when management shrugs it off? It's not because you didn't sell it well enough, it's because you had nothing they wanted to buy to inform their more expansive view of the overall situation.

Maybe what you brought them this time was not the proverbial needle in a haystack. Maybe this time it was just a shiny piece of hay. It happens. My advice? Get lost in a good music podcast until the disappointment passes, then dive back in. You might even hear a song you like!