The DoD budget request for fiscal year 2015 was $560.4B, of which $154B was set aside for Major Defense Acquisition Programs (MDAPs) in the areas of Research, Development, Test and Evaluation (RDT&E), and Procurement (Harrison, 2014). “98 MDAPs from FY2010 collectively ran $402 billion over budget and were an average of 22 months behind schedule” (Hofbaur, Sanders, Ellman, & Morrow, 2011, p. 2). Each one of these MDAPs are created by organizations commonly known as government/defense contractors that have a high level of specialized knowledge (Junkunc, 2007), advanced manufacturing practices (Boyer & Lewis, 2002), and often times engage in concurrent engineering (Haddad, 1996). There is a clear research need to examine the thresholds and complexities faced by primary contract award winners of MDAPs when engaging in traditional concurrent engineering design practices. With an increase in government spending on defense programs there has also been a massive amount of overages of cost and time for MDAPs. It is the intention of this research to better understand the convolutions that plague defense contractors during their Integrated Product & Process Design efforts via concurrent engineering (Office of Under the Secretary of Defense, 1998; The Pymatuning Group, 1988). For this goal a forecasting model that assesses Product Complexity, Program Size, Work structure, Supply Chain Embeddedness, IS/IT Systems, Governance, and the degree in which a firm is ambidextrous during its concurrent engineering processes is posited. This framework juxtaposes Integrated Product and Process Design of traditional firms (Hong et al., 2004, 2005; Koufteros et al., 2007; Hong et al., 2011; Rauniar et al., 2008; Doll et al., 2010) to that of DoD contractors through empirical analysis and case studies. By doing so, it will allow identification of systemic key differentiators that retard the MDAP Integrated Product and Process Design efforts via concurrent engineering. The assumption is that MDAPs experience greater challenges in the areas of new product realization versus non-defense firms due to product complexity and size, work structure, supplier embeddedness, IS, and governance. These variables have been stratified into three strati based on Swanson’s (1994) tri-core model, which is an adaptation of Richard Daft’s (1978) Dual-Core model for innovation within the firm. The three strati used are the Technical-Core, Administrative-Core, and IS-Core. All three strati depict the practical norms of the conjectured variables. While some variables are strictly isolated to a single stratum, there are those that belong to more than one, which can explain the cross-functional bearing of a firm/program’s operations between business units.
This research model inherently possesses significant managerial implications, both operationally and financially. The theoretical contributions of this research were validated through a mixed methods of qualitative and quantitative analysis, and showcases the differences in concurrent engineering practices of non-defense firms and that of defense firms. This research has foundations based on theories from technology management’s tri-core model (Swanson, 1994), supply chain’s grey-box vs black-box model (Koufteros, Edwin Cheng, & Lai, 2007), and operations’ capabilities, absorptive capacity and ambidexterity frameworks (Boyer, Swink, & Rosenzweig, 2005; He & Wong, 2004; Tu, Vonderembse, Ragu-nathan, & Sharkey, 2006). It also extends the concurrent engineering dialog into modern day manufacturing practices for defense contractors.