Some people who were more kind of the data leads were acting as a long-lived enabling team effectively. Their goal was more to identify the gaps across organization help grow the data science capability across organization and so they were not as much on the day-to-day helping address specific gaps of teams. That's why I think you end up for certain capabilities at least needing combination of long-lived that now we started calling sometimes structural enablement teams.
Manuel Pais delves into one of the concepts covered in his book “Team Topologies”: platform and enabling work. Manuel shares how he views the strategy behind when and how to invest in platform or enabling work. This conversation also goes into each type of work in more detail, covering topics such as measuring cognitive load and where platform engineering may be heading in the future.
- (2:13) How enabling teams and platform teams are different
- (10:28) What it looks like for a team to own both platform and enabling work
- (17:04) How to deliver enabling work in an organization
- (22:28) Whether enabling teams should be temporary
- (30:10) Platform team anti-patterns
- (47:10) Measuring cognitive load