Technical Metrics for Identifying Key Processor Components for Acquisition in Open System Architectures and Non-Proprietary Infrastructures

Due to the mandate by the Department of Defense that all new architecture programs shall be open system architectures (OSA) and the rapid expansion of non-proprietary infrastructures (NPI) in the form of cloud computing, the need for finding metrics and methods to identify key component technologies for potential acquisition has become essential. Once a component of the architecture has been identified as a potentially key technology, there are many business analysis methods to evaluate the value to the organization such as return on investment, return of equity, and cost-benefit analyses. Yet, technical analysis metrics and methods are required first in order to identify the key processor component technologies for potential acquisition within open system architectures or non-proprietary infrastructures. This technical analysis step is often overlooked by business analysis methods and is required before any business analysis can be conducted. Organizations, such as the Department of Defense, need to have a list of candidate technologies for contract acquisition prior to business case analysis so that they can understand which technologies are worthy of purchasing the technical data rights or licenses. The purpose of this research is to review the literature to determine technical metrics and methods for identifying key processor component technologies for potential acquisition. The research methodology for finding these metrics and methods consists first of a qualitative thematic analysis of the metrics and methods to place them into categories followed by a quantitative correlation study of these metrics and methods. The sample set for this research is then a meta-analysis of seventy-seven scholarly and peer reviewed empirical studies which yielded a consistent set of metrics and a method found to have statistically significant positive correlations with the baseline sample set. This research also yielded that simulation was the analytical method most often utilized as the primary means of empirical study and the reasons for its use. These metrics and the analytical method of simulation found in this research form a useful framework for identifying key processor components of the open system architecture. This research outlines the timing and data required from the competing contractors in order to effectively utilize this framework of metrics and the simulation method. Finally, the framework utilizing the metrics and methodologies found in this research are capable of being extended to any organization (government or commercial) that uses a structured and standardized acquisition process for open system architectures or non-proprietary infrastructures.