Relative effects (ratios) alone don’t provide enough information for judging the importance of the difference between the two groups. They also may give the impression that a difference is more important than it actually is.
For example, if an intervention (such as using a seed treatment) cuts the likelihood of getting a crop disease in half and the baseline risk of the crop becoming infected is 2 in 100, using the intervention may be worthwhile, even if it also has side-effects (e.g. reducing the yield in healthy crops). If, however, the risk of getting the disease is 2 in 10,000, then using the intervention may not be worthwhile even though the relative effect is the same. The absolute effect of an intervention (the difference) is likely to vary where there is a different baseline risk.