Weighted A* is the most popular satisficing algorithm for heuristic search. Although there is no formal guarantee that increasing the weight on the heuristic cost-to-go estimate will decrease search time, it is commonly assumed that increas- ing the weight leads to faster searches, and that greedy search will provide the fastest search of all. As we show, however, in some domains, increasing the weight slows down the search. This has an important consequence on the scaling behavior of Weighted A*: increasing the weight ad infinitum will only speed up the search if greedy search is effective. We examine several plausible hypotheses as to why greedy search would sometimes expand more nodes than A* and show that each of the simple explanations has flaws. Our contribution is to show that greedy search is fast if and only if there is a strong correlation between h(n) and d∗(n), the true distance-to-go, or if the heuristic is extremely accurate.