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Assuming price sensitive demand, a recent paper presents a model for a reseller's response to a supplier's temporary price reduction over an interval. However, the paper proposes rather complicated computational procedures for obtaining the optimal solutions to the model. We show that effective use of Excel Solver can simplify the solution procedure for the practicing mangers. Thus, our work should help improve the likelihood of actual use of the model in practice. Secondly, we identify an inconsistency in the optimal strategies recommended by that model for the two situations of temporary price reductions it addresses. We show that the inconsistency originates in an unnecessarily restrictive assumption. Using a less restrictive assumption, we present a modified model. Because we do not even try to establish the existence of local optimality, our approach must be labeled as 'a heuristic.' However, our model and solution procedure not only produces internally consistent results, it also yields a higher profit for the reseller. In short, we present a model that is less restrictive, more profitable, and easier for practicing managers to actually use. Finally, based on the analysis in this paper, we suggest that instead of oversimplifying a situation just to be able to establish local or global optimality of the resulting solution, operations researchers should develop models that truly represent the particular situations they are modeling. Then, if necessary, they may want to use heuristic approaches to solve those models even if those approaches may not provide a guarantee for local or global optimality of the solution.