Evolutionary success requires strategic allocation of scarce resources. Considering a single growth rate, more than 3.4 million biochemical pathways were identified using a metabolic model of the bacterium Escherichia coli. Each pathway represents a unique combination of enzymes and a unique resource investment strategy. Analogous to classical factory design principles, E. coli metabolic pathways demonstrate a converse relationship between investment costs (pathway enzyme synthesis requirements) and operating costs (pathway substrate yield). The optimal resolution of the metabolic trade-off between pathway investment costs and pathway operating costs was determined through multidimensional analysis of parameters like growth rate and the availability of anabolic and catabolic resources. Experimental enzyme data for catabolite-limited chemostat growth are consistent with ‘high investment cost-low operating cost' strategies while experimental enzyme data for environmental stress and resource starvation are consistent with ‘low investment cost-high operating cost' strategies. The network cost analysis also permits calculation of the metabolic trade-off between high affinity enzyme systems and the investment of limiting resources.