This paper proposes lazy group sifting for dynamic variable reordering during state traversal. The proposed method relaxes the idea of pairwise grouping of present state variables and their corresponding next state variables. This is done to produce better variable orderings during image computation without causing BDD size blowup in the substitution of next state variables with present state variables at the end of image computation. Experimental results show that our approach is more robust in state traversal than the approaches that either unconditionally group variable pairs or never group them.