Data v "The Business": The Literacy Divide

I've resumed reading Malcolm Hawker's The Data Hero Playbook, now that I have some time to reflect and write again.

I'm halfway through Chapter 4, and it's as if I'm reading the script of my own journey over the past five years; it resonates so much with me.

The section on Data Literacy spoke to me.

There are armies of analysts in spread across business functions that intimately understand the value of the data and how it can be used to measure the effectiveness of the execution of their business function. 

These individuals are the most underserved and valuable stakeholders of any data program in which I've been involved.  Why?  I point to Malcolm's premise of limiting mindsets.

Not every data problem requires a data engineer or a conformed star schema.  And most certainly not yet another dashboard.

Sometimes all a data function needs to do is remove nonsensical barriers and drop the learned helplessness that causes them to blame "the business" for not knowing how to articulate "requirements" or understand how a data pipeline works.

Sometimes all it takes is a little lift, a helping hand to apply what you know to what they know.

Once upon a time, I was tasked with harmonizing manually compiled spreadsheets that captured end of month headcount for HR reporting to the executive leadership.  When I arrived on the scene, they'd already been waiting for an IT solution and a dashboard for two years.  In the meantime, they kept slogging through an hours-long process to give the leadership these monthly updates.

Two years, and the data team STILL hadn't provided them with a source-faithful repository of point-in-time, month-end headcount data.  But THEY had preserved all of the Excel versions of the data they'd reported for nearly four years.

Of course, there were issues with the quality of data.  But the default posture of the data team was that it was up to them to fix their spreadsheets before we could help them.  Arggggggh!!!

Er, couldn't someone write a Python notebook to ingest, examine and clean data quality patterns that were obvious to me within 15 minutes of looking at the spreadsheet?

"Oh no, that's not our job.  If we help them now, they will never learn to keep their data clean."

Really?!?! 

Might they not instead become more trusting and accepting of the value of the data function, instead of remaining entrenched that IT and its data team do nothing more than make their jobs more difficult?

Hmmmmmm…

Today, my feed had a teaser link to Robert S. Seiner's latest article that posits another one of his language shifts - to stop talking about data literacy and start emphasizing data fluency.  I like that, mostly because it also encourages a shift away from the limiting mindset that our customers need to learn stuff that they really already know.