Obtaining System Knowledge Early to Build Cost and Schedule Estimating Confidence

When Government space-based system engineering manufacturing development (EMD) programs are less than 15% spent of estimated program costs, traditionally almost 80% of design costs are committed! (Figure 1) Furthermore, programs entering the EMD program phase with less than U.S. Government Accountability Office (GAO) recommended knowledge are likely to have lower technology maturities, systemic vulnerabilities, requirements volatility and validation uncertainty resulting in lower-than-expected performance, significant cost growth and schedule delays. This has been demonstrated across multiple programs highlighted in the GAO Annual Report on Selected Weapon Systems. For example, the 2019 GAO report found that of 51 programs reviewed, there was an average cost growth of $569B (51%) [BY$19] and 27-month (35
^%
) schedule delays since the first full estimates (generally established at development start). For 2020 reporting, the trends continued with another two percent cost growth, and additional schedule delays from those original approved program baselines. This trend continues as programs still enter EMD with less than the recommended knowledge. The GAO, in their Knowledge Point (KP) assessment, indicated that growth was directly attributable to less system knowledge than that recommended adding significant risk to the programs. Furthermore, the 2020 report found a correlation between attaining specific knowledge at key acquisition points using recommended best practices improved cost and schedule performance. Discussing these practices further to support our proposed tool set we demonstrate effective implementations. Now, with an urgent need to field advanced systems earlier, novel approaches to implementing best practices that obtain knowledge earlier in development are needed. Integrating tools such as System Readiness Level (SRL) method (a function of technology readiness and integration maturity) and Model Based System Engineering (MBSE) is one approach. When these methods are applied in the concept and development lifecycle phases it enables early critical system knowledge to be obtained. Results of using these methods provide analysts enriched data for making informed forecasts of cost and schedule against technical capabilities that can show sensitivities and drivers that become part of the initial program estimates. In this paper, we demonstrate how to obtain technical, cost and schedule knowledge using integrated tools, identify gaps and where to focus resources. Through detailed assessment using SRL and MBSE methods, we highlight how to reveal and reduce risks to programs by fleshing out system (and system of systems) maturity, missing knowledge, weaknesses, requirement and validation mismatches that will result in and cost risk opportunities to keep programs on track throughout the lifecycle. Last, we discuss future research to support emerging programs and tool maturity.