- Tags:: 🗞️Articles , Data team vision and mission, Measuring a data team impact
- Author:: Emilie Schario and Taylor A. Murphy
- Link:: Run Your Data Team Like A Product Team - Locally Optimistic
- Source date:: 2021-04-20
- Finished date:: 2021-05-01
100% support prevents high impact:
Without intentional space, they are unlikely to be anything more than ticket closers
For example, say Johnny McFinance wants to know about reactivated customers and Sally McMarketing is wondering about the performance of a retargeting campaign in digital ads. If Donny McData’s job is just to pull up the next ticket on the docket, he’ll never have time to dig into the data and see if there’s a connection between the two, even though he’s uniquely poised to see these connections.
Again, data is a product, as in the Data Mesh philosophy:
When you view your colleagues as your customer and the Data Team as building and supporting a Data Product, then you’re able to unlock the opportunity of your data and data team.
So what is the Data Product? It is the collection of every piece of data, and the tools used to generate, access, and analyze that data, within an organization.
Users are key then:
Taming the wilderness means starting out with some of the basics of product management. A good product organization will center the users and their experience with the product.
You need to talk and hear a lot:
When moving your Data Team to the product model, you should expect some pushback from other people in the organization. As a leader you must have strong 2-way communication. This will require a great deal of empathy as you’ll have to constantly balance the need to share your vision and goals with the need to integrate the feedback from your users (colleagues).
And measure:
align with your stakeholders on what that measurement looks like to them; for example, what KPIs is your team supporting and how are your initiatives supporting them. Like most functions, it is a worthwhile endeavor defining success and getting alignment early on.
Note the headcount:
Data teams should be 3-10% of the total headcount, depending on the nature of the business. If data isn’t something that’s actively part of the company’s product or your Data Product is more mature, then closer to 3% might make sense