We compare two different approaches to parallelization of Fortran programs. The first approach is to optimize the serial code so that it runs as fast as possible on a single processor, and then optimize the parallel version. In this paper a variety of parallel programming tools is used to obtain an optimal, parallel version of an economic policy modelling application for the IBM SP1. We apply a new technique called Data Access Normalization; we use an extended ParaScope as our parallel programming environment; we use FORGE 90 as our parallelizer; and we use KAP as our optimizer. We make a number of observations about the effectiveness of these tools. Both strategies obtain a working, parallel program, but use different tools to get there. On this occasion, both KAP and Data Access Normalization lead to the same critical transformation of inverting four of the twelve loop nests in the original program. The next most important optimization is parallel I/O, one of the few transformations that had to be done by hand. Speedups are obtained on the SP1 (using MPLp communication over the High Speed Switch).