Well, a lot of people "abuse" existing tools because they don't have time to learn 100 different tools, also. It's not "lazy" to realize that there is a finite amount of time available in a day (or a project) and to cope accordingly. If my employer allowed me time to get up to speed on all the "most appropriate" tools for any given project, I would be learning different tools all the time instead of doing my actual job :-) because I don't do just one kind of work day-in and day-out.
So there is an actual engineering tradeoff in the tools space: learning a few very flexible tools in-depth, and using them for most tasks...or learning lots of different, specific, focused tools superficially. I suspect most people are somewhere in the middle.
@ antedeluvian the use of Excel in Electronic Engineering
There was a time I did not know how to use Excel, then I needed to calculate PCB dimensions for impedance control of broadside-coupled differential stripline. The textbook equation was a real pig, but learned how to use the Excel goal-seek function to automatically iterate guesses until it found the right one. The prototype boards measured within 2% of the target.
Well yes, a lot of people abuse existing tools due to inertia or just plan laziness. That's a bit of a shame, but our work ethic isn't what it once was.
I myself stumbled upon R in a search for a good math package. I had used Octave a bit, and mostly liked it, but being a fan of Lisp, I was immediately drawn to R's simiarly to the Scheme language. Specifically I needed to do some curve fitting to linearize the response of a sensor, and come up with coefficients to embed in firmware. R made short work of it, and it made so much sense, that I've been hooked ever since. I've since written an entire suite of instrument control software with it, so I go straight from lab equipment into data structures in R, complete with graphing if needed.
And I don't have to fight with Windows to use it. ;)
A lot of people use Excel (or an equivalent; I use the name generically, like 'Xerox") for the type of curve fitting I needed to do that day, or other related stuff, and if that tool works for them, that's great. The R approach better matches the way my mind works, and the productivity boost has been great for both myself and those who depend on my work. It's not for everyone, but give it a try, you might like it. The learning curve is steep, like any other complex tool, but it's worth it.