Here's my experience from the trenches. I work as a data scientist at a big Canadian bank and have been pushing R for over a year. I started using R as a data analyst, looking for a way out of Excel hell. One of the larger pieces of work our team was doing was an annual process that required a lots of iterations, a lot of (ever-updating) data, regular outputs often in graphical format, and a fast turnaround. If only there were a tool that perfectly aligned to all of those needs.
Well, that tool was forever Excel. When I joined the team I pushed hard to use R. It was initially met with a lot of resistance. The VP called it a 'black box', never mind that I could show him the exact code that produced the exact output. I started posting on our internal social networking site about the dangers in using Excel, and about how other tools, ahem, might be better suited to certain tasks. It gained a lot of traction internally. I kept posting about R, until I became known as the R guy.
My VP was still resistant, so I had a strategy for him. He wanted Excel outputs so he could fiddle with numbers, so I used R to output to Excel, while also giving him the benefits of the real things he wanted: charts, fast turnaround, accuracy, better insights. Eventually, I noticed he wasn't even looking at the Excel files I'd send him, but only at the PDFs and slides I created in Markdown.
That small success led to people approaching me, asking how they too could use R. I started with small training sessions with my team, and later expanded that to 30+ people attending regular bootcamps. I'd teach tidyverse first, and skip base R as much as possible, as recommended by David Robinson and found that worked well.
Next I started following some of the tips for internal R packages, following examples from Airbnb, to create an internal package that does things like sets up our proxies and standardizes visual identity. Around the same time I published an in-house style guide. I started creating more posts showing the power of R using relatively public internal data, such as how we can identify communities and cliques by looking at who follows who on our internal social network. I put up pretty graphs and people went wow.
I've started traveling to other offices, on a different continent, to continue to spread the gospel of R. I do presentations to our students, as well as at internal talks. I recently did one on visualization using R and Shiny and it was really well received. My favourite line from the talk was talking about how my boss loves Python and I love being right. It's a slow process, but there is progress.
Personally, I use ProjectTemplate for all the work I do, but I haven't forced it (or anything) on anyone. I don't have that kind of clout, and resistance is so high here I have found that the carrot seems to work better than the stick.
One anecdote, I had a colleague who loved analysis and so I thought he would love R. I showed him all the things I could and he said "I could do that in Excel, and in half the time." I tried to push R, but he resisted. I left that team 5 months ago. Looks like he's missed me, because recently he's come to a boot camp, and was excited to show me all the neat tricks he's learned in R. He just recently moved to a new team and was excited to show them the things he's learned.
That's how I did it and I'm by no means done. I'm still trying to build adoption across the organization. It's easy to build it on my team, I'm a team of one. Our larger team of data scientists are also easy to convince, they are all using either R or Python. It's the rest of the org that is tied to Excel that is slow to convert. What I've learned is persistence will pay off, and that little victories are sometimes all you can hope for. There's no replacing the power of teaching people in a boot-camp style session. Half the people tend to fade out, but the other half seem to be incredibly engaged. Find ways to show the good work you can do. Make life easier. Reduce the friction for getting started as much as possible. There's no point teaching Shiny before they've seen how easy it is to clean and automate rudimentary tasks.
I don't know if I've answered your questions, but there's my experience for what it's worth.