A "scrum course" is to Scrum what a code boot camp is to programming. You're going to learn basics but you won't have the depth of knowledge to handle complexity in any form, nor how to answer questions about Scrum that inevitably are asked by leadership. There's a reason the Scrum leader (or master) role exists. It's supposed to be the person who has a depth of knowledge that goes beyond a simple "scrum course" and can guide an organization when complexity arises. Organizations rationalize why they don't need to hire someone into this role because a Scrum leader isn't a producing role. And they're right that Scrum leader isn't a producing role, it's a role that's supposed to make producing roles more efficient, a force multiplying role.
Pretty sure there isn't, otherwise FAANG would enforce it top down. They already enforce other practices top down like hiring etc, so if they had data saying that mandating Scrum would make the company X% more efficient they would absolutely do it.
It might be a force multiplier in other types of companies, but it probably isn't in FAANG style companies. Similar to how FAANG hiring can make sense to them but still be bad for typical companies.
I mostly agree with this perspective. Alternative agile methodologies may fit better with certain teams (e.g. Kanban, lean, etc) and so having a top down prescriptive method of "agile" doesn't make sense. Another perspective is that Scrum is agile training wheels. Once a team can discipline themselves enough to follow a Scrum workflow successfully for a significant period of time, it shows they are ready to follow a more flexible agile approach and therefore may no longer need a Scrum leader guiding the team.
> They already enforce other practices top down like hiring etc, so if they had data saying that mandating Scrum would make the company X% more efficient they would absolutely do it.
lol, as if their top-down hiring practices are at all driven by concerns for company efficiency.
Why do you think otherwise? The whole reason they do it is that they looked at other big companies and noticed that everyone ended up with mediocre workforces after a while, so they did this to avoid that scenario. Then as they grew bigger they could hire a lot of data people to analyse different methods and see how well different things works to optimize further. When you spend tens of billions on engineering salaries at a data driven company you will do that.
