Soft skills for the sharp data elbows
How to sustain the data agenda in an organisation
The Elbows of Data post by the great Data Science community voice Katie Bauer has really resonated with me. Glad we now have a term "elbow" to put on the banner!
The next question for me is - how do you deal with people resisting your changes? For example, if a PM gets worried about losing parts of their role, intimated by your data elbowing? Here is how I ran into these troubles and pointers to some books that helped me turn my "sharp elbows" into a "soft force for change".
I once had a job where I managed elbow my way in, understand the domain, build a great relationship with the stakeholders, expand the data science work from one project to many, and grow the data team to execute the new projects. The elbow poster child!
It was all going pretty well... until my PM's boss asked me to stop contacting stakeholders directly - to forward all their emails to my PM to reply and to stop my weekly newsletter... A month later they moved me to another department.
Looking back at it now, me and my skip-PM really failed to build a relationship.
I was aware that they don't like some things I do. And I did nothing about it as I didn't want them to be involved in my work. A bit arrogant of me, huh?
Now, having experienced good working "Radical Candor"-style relationships, I would have solicited direct feedback from them, and emphasised how important PM-data collaboration is to our joint success.
And I would have understood their incentives - following the organisational norm for software teams that "PM is the only stakeholder contact", and how this change was negatively affecting their work from their perspective.
This story of struggle for a great "engineer-end user" relationship against Product Manager/Owner gatekeeping is re-told a thousand times by the software engineering agile coaches. I think the data community can learn from the small-letter-agile https://holub.com/reading/ a lot. For example, I learned that pairing/mobbing on data validation parts of the pipeline, do wonders for Data Science - Data Engineering collaboration culture.
In general, change in an organisation is hard. In addition to "generate excitement" strategy, there is an awesome long list of ways to change an org in a book "More Fearless Change”. I learned about it in a great blog by Lisi Hocke on org culture change around software testing