I spend a lot of time thinking about my research projects. I revise and tweak the ones I'm working on, but I especially spend time planning my possible future projects, working out which ones I should most prioritise.
This is important. Choosing which projects to work on will fundamentally affect your research career, and given that a project might last months or years, spending hours or days making good choices seems pretty sensible.
I once read a suggested approach that I've come to realise has a lot of merit. Annoyingly, I can't track down the original reference (I think it may have been by Daniel Lemire or Study Hacks; even if not, you should go and read those blogs as they're very good). But the idea is this:
Identify your two best/most valuable pieces of research.
Your new project should better at least one of these.
It's a really simple approach choosing new projects, and it's kind of obvious that this should lead to good projects (provided your assessment of value is reasonable). But there's actually an interesting alternative way of describing it.
It's a hill-climbing algorithm for optimising the scientific value of your new projects over time.
Think about it. We can imagine that there is some abstract quantity, "value", associated with each of the research projects that we work on. Different people may disagree on the precise value of any given project (and even the definition), but overall we would like to be working on progressively more valuable projects. By using the above algorithm as a criterion for deciding which projects to work on, we are aiming to always increase the value of our two best pieces of research (by progressively replacing each one with something better).
Why not the best one or three projects? Well of course, it should still work if you change the number. Two is probably a good number, as having a couple of headline grabbing projects is useful for writing grants, giving talks and the like.
It occurs to me that it would be very easy to always use the same scale for assessing how good/bad a potential project will be. But by using the Top-Two algorithm, you're always pushing to do more and more valuable work. And this seems like a thoroughly good idea to me.