- Tags:: 🗞️Articles , Data team topologies, Data culture, Data team vision and mission
- Author:: Erik Bernhardsson (built the Spotify recommender)
- Link:: https://readwise.io/reader/shared/01h3fry89w7etz0am01ysng595
- Source date:: 2021-07-07
- Finished date:: 2021-07-08
Going from data democracy to data anarchy, a classic:
- That team started out with their own “business analysts” (outside the data team) but need the data team to run queries for them to get data.
- Those business analysts are starting to run queries themselves with the help of the data team.
- They start to build up “shadow tech debt” (in this case monster SQL queries) which first causes a bunch of friction with the data team.
- The data team starts embedding into the team and helping them get to a better place.
- Because of the embedding, the need for business analysts goes down and data scientists goes up.
Culture is always at the root of the problem:
A culture that fundamentally is at odds with being data driven. A culture of celebrating shipping, versus celebrating measurable progress and learnings. To the extent teams actually use metrics, they are inconsistent, poorly measured, and in some cases at conflict with other teams…
Conversion is also responsibility of Data:
Another insight has been that traffic from different ad campaigns have very different conversion profiles once they land on the site. It turned out some campaigns had very cheap clicks but converted terrible. Some other campaigns were quite expensive but those users convert extremely well.
Since you’re now tracking the UTM parameters and tying it to the account creation, you can now measure the conversion rate from ad click to purchase. This wasn’t possible before all the data was brought into the same data warehouse and normalized so you can query it easily. Working with the marketing team, the main KPI is now end-to-end customer acquisition cost, rather than cost per click.,
And embedding is the future:
Instead, push out the resource management to other teams. Given them a handful of data people to work with, and let them work with them. Those data people will be able to iterate much more quicker, and will also develop valuable domain skills. This reduces the need for other teams to work around the data team and hire their own resources.
but with centralized management
On the other hand, you don’t want to decentralize the management. Strong data people want to report into a manager who understands data.
The beginning of the nirvana:
When the turn comes to the growth initiatives, the lead PM presents a new splashy landing page redesign that they launched. (…) Everyone looks at the CEO to see what she thinks. She’s quiet for a while but then opens her mouth. “What are the metrics so far? Do we know if the customer acquisition cost went down?” she says, and you smile to yourself, because you’ve been hoping for this question. (…) The excellent news is the CEO is pushing for teams to use data as the truth. Once there is an organizational pressure to be more data driven, this is a time to accelerate the way the data team works with other teams.
And the true nirvana:
Of course, all outcomes aren’t positive. There’s been a lot of tests that didn’t work out. One of the first slides describes a test you ran where shipping is baked into the price rather than charged separately. It’s quiet in the room for a while until the CEO starts talking. “What did you learn from this?,” she asks.