Today we make more decisions than ever which challenge us to locate or generate the right knowledge, at the right time, organized in a form suitable for managing technical progress. Physico-chemical modeling, when effectively implemented, improves the knowledge content of decisions and limits the risk of technology management error. Effective implementation requires four critical elements. First, a hybrid approach must be created which integrates modeling capability with empirical methods to leverage the synergy between the two for maximum value. Second, the hybrid capability must be accessible directly by technology managers, developers and practitioners to facilitate sharing of "common" knowledge. Third, the uncertainty associated with assumptions and inputs to the empirical and modeling components must be quantified to improve a user's ability to direct resources to the most "uncertain" topics and to integrate risk assessment into their decisions. Fourth, and most important, this hybrid approach must be built into the technology plan through all of its phases, from evaluation to production. A prototype structure will be described and examples of partial use of the approach in the microelectronics industry will be described. Observations of how full implementation would improve the return on investment will also be noted.