The practices of systems engineering are believed to have high value in the development of complex systems. Heuristic wisdom is that an increase in the quantity and quality of systems engineering (SE) can reduce project schedule while increasing product quality. This paper explores recent theoretical and statistical information concerning this heuristic value of SE. It explores the underlying theoretical relationships among project cost and schedule, technical value, technical size, technical complexity, and technical quality, summarizing prior work by the author. It then identifies and summarizes six prior statistical studies with conclusions that relate to the value of SE. Finally, the paper provides final results of a statistical study by the INCOSE Systems Engineering Center of Excellence (SECOE) that presents evident correlations supporting the heuristics. The results indicate that optimal SE effort is approximately 15–20% of the total project effort.

This paper presents quantitative results on the return on investment of systems engineering (SE-ROI) from an analysis of the 161 software projects in the COCOMO II database. The analysis shows that, after normalizing for the effects of other cost drivers, the cost difference between projects doing a minimal job of software systems engineering-as measured by the thoroughness of its architecture definition and risk resolution-and projects doing a very thorough job was 18% for small projects and 92% for very large software projects as measured in lines of code. The paper also presents applications of these results to project experience in determining "how much up front systems engineering is enough" for baseline versions of smaller and larger software projects, for both ROI-driven internal projects and schedule-driven outsourced systems of systems projects.

Research work continues into Systems Engineering Return on Investment (SE-ROI) following prior work on Value of Systems Engineering and Systems Engineering Effectiveness. This paper presents major results in the form of statistically proven relationships between systems engineering (SE) activities and the technical, schedule and cost success of programs. It has been found that all defined SE activities correlate positively with program success as measured in three of four success metrics used (cost overrun, schedule overrun and perceptive success). When the effect of program characterization parameters is included, the correlation is strong with optimum levels of SE activities as much as 25% of a program cost. The paper presents quantified values for the relationships, indicating appropriate levels of each SE activity that correlate to optimum levels of success. Results show a surprising lack of correlation between SE activities and the technical quality of the product system, for which some possible explanations are provided.

Past analysis has shown that there is a quantifiable correlation between the amount, types and quality of systems engineering efforts used during a program and the success of the program. For any given program, an amount, type and quality of systems engineering effort can be selected from the quantified correlations. The optimal nature of these selections, however, has not yet been explored. An ongoing project, Systems Engineering Return on Investment (SE‐ROI), aims to quantify the correlations by gathering data on current and completed programs. This paper describes the practical program of research being used in the SE‐ROI project and the current state of that development. The research program involves defining categorization sufficient to explore the correlations, implementing that categorization onto data sheets, gathering data from real programs through a personal interview process with the program leaders, and then performing statistical work to reveal the correlations. The project expects to achieve practical results in the form of (a) statistical correlation of SE methods with project success, to understand how much of each SE method is appropriate under what conditions, (b) leading indicators that can be used during a project to assess the project's expected future success and risks, and (c) identification of good SE practices that are appropriate to generate success under different conditions.1

A goal of systems development is to produce enduringly valuable product systems-i.e., systems that are valuable when delivered to their users and which continue to be attractive to their stakeholders over time. However, quantifying the life-cycle value (LCV) provided by a system has proven elusive. In this paper, we propose an approach to quantifying a system's LCV based on the key parameters that have perceived value to the system's stakeholders. For this, we draw upon insights from the management, marketing, product development, value engineering, and systems engineering literature. We then demonstrate our proposed approach with an example of a cellular telephone system. By designing systems for maximum LCV, systems architects and engineers will provide dramatically increased value to their organizations and other stakeholders. However, to provide maximum LCV, a system may need to be designed to facilitate adaptability to changing circumstances and stakeholder preferences. We conclude the paper with discussions of some of the major difficulties in measuring LCV and some of the opportunities for further research in this area.