When trying to find the optimal size and placement for an element, I can model the utility using Fitt's law. Of course, using this law by itself will just tell me that everything should be massive and infinitely close.
So we need some way of determining the cost of creating an object of some size & placement. My initial thought was to model it as an opportunity cost, and say:
Let p be the probability that the object will be used, and F(d,s) be Fitt's equation for a distance d and size s. Then the utility
U(p,d,s) = p × F(d,s) - (1-p) × F(d,s)
Where the term
p * F(d,s) indicates the utility if the object is used, and the term
(1-p)*F(d,s) indicates the (negative) utility if the object is not used.
This has the obvious result: if p > .5, make it infinitely large; if p < .5, make it infinitely small.
I think what I really want is to add an entry to my "lottery" with some utility assigned to blank space. But I'm not really sure what that utility would be.
I'm sure this must be heavily studied. Can anyone point me to some resources to help clear up my confusion?
EDIT: Let's take a simple example. I can put all the actions they need under a menu. I can duplicate some of these actions as "quick buttons" to make it quicker for them to get to these actions. What is the optimal number of quick buttons?
Some basic observations:
- If there are one or two actions which are used way more than the others, the ideal is to show only those one or two. Adding the infrequently used items isn't worth the cost of the clutter.
- Even if all items are used with equal frequency, you don't want to put every single action as a quick button, because then you're just duplicating the menu
Can we formalize these observations?