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We develop an evolutionary model and theory of software technical debt accumulation to facilitate a rigorous and balanced analysis of its benefits and costs in the context of a large commercial enterprise software package. Our theory focuses on the optimization problem involved in managing technical debt, and illustrates the different tradeoff patterns between software quality and customer satisfaction under early and late adopter scenarios at different lifecycle stages of the software package. We empirically verify our theory utilizing a ten year longitudinal data set drawn from 69 customer installations of the software package. We then utilize the empirical results to develop actionable policies for managing technical debt in enterprise software product adoption.