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mixed messages

scribbleMeet Emily

Emily is a talented, long-haul union organizer.  Her analysis is spot on; she can 1-1 like nobody’s business, complete sharp opposition analysis, and agitate, agitate, agitate!  She’s been keeping a contact list of worker leaders in her shop, but it’s gotten sloppy over the last few months with duplicates, phone numbers in different formats, outdated notes, extraneous tabs, and confusing column names.

Emily is planning for a big action and so she wants to call through the list to do some turnout, but the list has fallen into disrepair.  She decides to re-type everything into a new version.  She feels mad at herself for always messing this up, but she never has time to make a clean version.  She feels hopeless and at the end of her rope.  Plus, time is running out before the big action.  Not again!  Sound familiar?

Meet Rachel

Rachel has taken stock of things after a few dead-end jobs and she’s ready for a career change, so she enrolls in a computer coding boot camp.  The first few weeks are challenging, heck – the whole program is!, but there’s plenty of support in her cohort and the teachers promise to connect her with a high-paying employer upon completing the program.  In the boot camp, she learns about coding, web development, project management, and marketing.  Even though these skills don’t come naturally to her at first, she picks them up with some practice and starts to hone in where she wants to specialize.  It turns out that there is a lack of User Experience designers who focus on accessibility needs, like making screen-reader-friendly websites, so this becomes her niche.  Rachel is ready to start her new career!  Sound familiar?

Contradictions

I know a lot of Emilys and a lot of Rachels.  I think this phenomenon speaks to some of the mixed messages that we receive from mainstream culture.  (By the way, these are archetypes, not actual people!)

On one hand, data skills are impossible to learn (and we blame the individual).  On the other hand, companies tell us that advanced coding skills are easy to develop, 1, 2, 3!  How can these be true at the same time?  Who benefits from these messages?  It’s classic capitalism doublespeak: make non-data people feel insignificant and intimidated, then sell us a solution to our problem.

Among activists, the contradictions run deep in a different way.  We are suspicious of people who know their way around a spreadsheet, database (or even code!) despite desperately needing to build stronger systems to absorb all of the recently activated volunteers in social movements.  We blame ourselves for our inadequacy, but we also we take pride in being scrappy – it’s a sign of authenticity.  But scrappiness doesn’t scale well, so we reach an impasse.

These are the waters we swim in – and they are poisonous!  They are disastrous for personal growth and for successful social change movements, so I’m here to call bullshit on the messages we receive about spreadsheets and data – both from wider culture and from other each other.

Pep talk for Emilys and my inner Emily

We inherited messed up notions about technology, social media, and our own agency.   For many of us who are women or gender nonconforming, we weren’t encouraged to learn math and spreadsheets in our math and science upbringing.  But that doesn’t make your present predicament your FAULT or your downfall!

You are applying your MUCH NEEDED skills to build justice movements – that is amazing and we owe you a debt of gratitude.  Just like other organizing skills, spreadsheets are learnable!  I am so excited for you to have clean spreadsheets and more time for other types of organizing or plain old hanging out.  Life is too short, and our political crises are too urgent, to kick skilled people out of the cool kids activist club.  Let’s work together – we got this!

Here’s the first steps I take when I encounter a messy spreadsheet.  You can do them too and they will help right away!

This post was partially inspired by Sam Knox and the good people over at Salesforce.org who write documentation and make it as down-to-earth and people-centered as possible.  Thank you for showing me how it’s done and including me in the work!

There’s a counter-narrative in the nonprofit Salesforce ecosystem where “accidental” data administrators can follow a clear path toward super-skilled data stewardship.  This is the kind of change I want to help foster and I stand on some pretty awesome shoulders on the way to that goal.  Thanks to all of you travelling along with me!

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