Systems Approach to the Development and Application of Technical Metrics to Systems Engineering Projects

摘要

Thales UK employs around 3,000 engineers, over half of which are systems engineers, delivering solutions from transport systems and secure transactions to integrated communications, naval sensors, and air defense systems. The Systems Engineering (SE) function within Thales UK seeks to minimize the impact of, or eliminate problematic SE projects. Here, problematic projects are defined as ones where the SE group on a project was expected to deliver certain characteristics against cost/time constraints arising from the problem context, however the project did not, or will not meet expectations by a significant margin. A traditional view is that the impact to the Company of problematic projects can be minimized by early detection and subsequent intervention by SE leadership. As such, Thales UK seeks to implement an approach that will alert SE staff and leadership to the presence or development of problematic projects, such that appropriate interventions can be made. Literature regarding SE technical metrics explores the development, and less frequently, the use of metrics to provide information to project teams to support judgments about current versus desirable positions. No literature has been identified that describes how SE technical metrics could be used en-masse to provide insight in to the performance of a diverse portfolio of SE projects. Thales UK has mandated the collection of a set of SE technical metrics on all SE projects, and understands that the reported data requires interpretation and relation to context. The context of each project is different and dynamic. This presents a challenge when attempting to use this data to draw conclusions regarding the health of all projects across an enterprise, and the health of the operation of an entire engineering function. This paper describes a quasi-experiment with SE leaders and project technical metrics from a range of domains within Thales UK to test whether expert judgment can determine if a project is problematic or not from metric data alone. A separate research activity is then presented which moves toward a theory of how a metrics approach could be structured for use across a diverse range of SE projects to detect characteristics of problematic projects.