This isn't _incorrect,_ but I'd say it's insufficient, or at least it lacks a sufficient treatment of what technical debt is and what is important about it.
Technical debt is known technical problems that are affecting or will affect your velocity or the business as a whole. When considering technical debt, you need to know:
- the estimated amount of time required to correct the problem - the ongoing penalty you're paying by not correcting it, if any - the hard cutoff by when the problem must be correct, if any - the consequences for not correcting the problem by the hard deadline
Three examples to demonstrate:
1) You have a User god-model that is thousands of lines of code long. It is incredibly hard to work with, and any change that interacts with it takes, on average, 5x as long as a change that doesn't. It would take appx. four weeks to refactor sufficient methods out of this model to make it as easy to work with as the rest of the code, but there is no hard cutoff by when this problem must be solved.
2) You're only able to clear your job queues on the weekend, and the job queue time has been growing steadily for the past few months. By mid-week, the average queue time is appx. 10 minutes and by end-of-week, it's nearly 30. If this problem is not solved in one month's time, the end-of-week queue time is likely to be over an hour, and in two month's time, the mid-week queue time is, too. We can add extra capacity to our job runner pool in an hour or so, at a cost of $x/month.
3) The new account creation script is a mess of spaghetti code, a real eyesore. Changing it requires about 10-20x as much effort as any other part of the system. It would take appx. 2 weeks to untangle. However, there is no hard cutoff by when this problem must be solved, and in fact, this code is rarely ever touched anyway, only twice in the last year and only small changes were required.
These three cases fall roughly into the three categories suggested by OP (1 -> preventing from doing stuff now, 2 -> preventing from doing stuff later, 3 -> might prevent you from doing stuff later), but you have sufficient information to make informed, better decisions that the simpler model would miss. For example, under the simple mode, the job queue problem would be classified as "try to focus on", but the User god-model takes priority ("minimize" "stuff now" problems). But 2 seems much simpler to fix (provided you can afford it), and the consequences to deprioritizing it in favour of the god-model fix could be catastrophic to user confidence.
And in both systems, we're most likely going to ignore problem #3, but if we know that a larger change to new account creation is coming up, one that you would expect to take 2+ days in another other part of the system, you now can expect that it would instead take 20-40 days in the spaghetti code, but that refactoring it would be appx. 16+2 = 18 days, a net win.