The questions that need to be answered here are, "What is an explanation?" and "What makes a good explanation?"
An explanation is generally taken to be an account that leads to greater understanding of the phenomenon, and/or its causal origins, and/or its context in, or relationship to, the world around it.
What makes a good explanation is usually addressed in the philosophy of science in terms of abductive reasoning, or inference to the best explanation. There are many versions and models of this, and a number of problems, such as, is the best explanation the most probable one, or the one that provides greatest understanding, or is the one that provides greatest understanding the most probable by implication? also, Hume's argument on the unreliability of induction, and so-on.
In practice, a few relatively simple measures can effectively rank explanations in general terms:
- How justifiable and fruitful they are, i.e. the testable implications they have, or predictions they make, and whether the results confirm them; the more varied and numerous the confirming tests and positive results, the better.
- The scope or explanatory power that they have, i.e. the diversity of phenomena of which they enable understanding, and the degree to which they unify our knowledge and understanding. Note that specificity and/or detail is important, and it is how generalisable the explanation is that gives it scope. Explanations with low specificity or detail provide correspondingly little understanding, although they may superficially apply to a wide variety of phenomena. Explanations that raise more questions than they answer, particularly if the questions are unanswerable, have no explanatory power. This doesn't mean that it is necessary to explain an infinite regress of 'why?' questions; for example, 'bad luck' is not a good explanation for a tsunami, but 'an underwater rock slide' could be. If asked to explain the rock slide, 'bad luck' is not a good explanation, but would not invalidate a rock slide as a good explanation for the tsunami.
- How simple or parsimonious they are, i.e. how few assumptions they require (application of Occam's razor).
- How conservative they are, i.e. how well they cohere with existing knowledge. This is important, but not essential; if an explanation is not conservative or contradicts existing knowledge, it needs to outperform competing explanations on the other criteria.
Given these criteria, it should not be difficult to compare the quality of 'Intelligent Design' as an explanation with its competitor(s)