Data Intelligence, Business Analytics
Well, I seem to be having trouble understanding your math!Let's see if my Math would work easier ~
Taking your example -
ROI is the return on Investment,
ROI = (Revenue - Cost)/Cost
For the first example, 10,000% ROI = (Revenue - $1)/$1 or Profit = 10,000%*$1 = $100
Same for the second, 1% ROI = (Revenue - $10000)/$10000 or Profit = 1%*$10,000 = $100
So, the profits in both the cases = $100 (not $99 as you had calculated).
Instead, what needs to be considered is the initial costs/capital required to generate these profits. The way I would use ROI is to think like this -
If I can generate 10,000% ROI on my investment, I'd start to invest heavily into that medium, rather than a medium that can yield only 1%!
Be warned though, that this comparison is only possible if Investment costs are comparable and ceterus paribus! Which is generally not the case... Also, if a $1 yielded such a high ROI, there's something to suspect and definitely expect a much lower return with increasing investment!
I'd like to hear your counter views on this...
I didn't know that piece on Optimizing Profit & ROI by Chinese & Americans respectively! Well, wouldn't both be invalid without a conditioning on Investment, yes, ROI will be useless, but so would Profit. On your note that maximizing profits doesn't need a conditioning variable, what if I found out that maximizing my profit would be to maximize my cost? Would that be a good direction to take? I don't think so..
It's better to optimize, and by that, it involves both elements Revenue & Cost - so be it Profit or ROI, we should get the same results in different scales!
I don't know if any one metric would ever work, but if it's optimizing you're talking about, more factors will factor in, and hence that would work best.
And to me, the ROI is a neat metric that conditions your profits on the cost, which scales down to show you the relative scenario and not absolute numbers!
I'd love to hear other views....