Optimization of Key Levers of Influence In Knowledge and Ease-of-Change Management and Addressing Variability in Design

Abstract

In large complex defense projects, a significant portion of technology and product costs are committed prior to detailed design when little is known about the product. The lack of information, knowledge and design flexibility early in the design can postpone design change decisions when it becomes more expensive and difficult to implement these changes. With adjustment to just a few key process levers, knowledge can be gained early in design and system ease-of- change increased, leading to a robust design, reduced design change costs and reduced schedule delays. The characteristics of the knowledge and ease-of-change management curves, and their levers of influence, can be described using system dynamics and statistical techniques. This paper presents an approach to optimizing these levers of influence from a cost-benefit perspective. Statistical techniques such as Monte Carlo analysis are used to predict variability in system performance attributes. Validation of this approach can be achieved through comparing the predicted effect of levers against actual performance of the management curves. The performance of the knowledge curve may be assessed using a standard knowledge management maturity assessment tool; the performance of the ease- of-change curve may be assessed through monitoring the variability of system performance attributes over the lifecycle.