Yes. Effect size is the difference in means in proportion to the pooled standard deviation to the two treatments, and is a great measure of how large the difference is. All groups are different given large enough n. Whether that difference means anything is dependent on the effect size.

When the effect size is large you know that whatever effect you are seeing is much less likely to be chance. It's also less susceptible to large differences in variation, which the tests you are using to test significance use as an assumption (variation is equal).