Please use this identifier to cite or link to this item:
https://dair.nps.edu/handle/123456789/4443
Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Donna H. Rhodes | - |
dc.contributor.author | Eric Rebentisch | - |
dc.contributor.author | Allen Moulton | - |
dc.date.accessioned | 2021-05-19T23:42:23Z | - |
dc.date.available | 2021-05-19T23:42:23Z | - |
dc.date.issued | 2021-05-19 | - |
dc.identifier.citation | Published--Unlimited Distribution | en_US |
dc.identifier.uri | https://dair.nps.edu/handle/123456789/4443 | - |
dc.description | Acquisition Management / Defense Acquisition Community Contributor | en_US |
dc.description.abstract | Digital engineering transformation changes the practice of systems engineering, and drives the need to re-examine how engineering effectiveness is measured and assessed. Early engineering metrics were primarily lagging measures. More recently leading indicators have emerged that draw on trend information to allow for more predictive analysis of technical and programmatic performance of the engineering effort. By analyzing trends (e.g., requirements volatility) in context of the program’s environment and known factors, predictions can be forecast on the outcomes of certain activities (e.g., probability of successfully passing a milestone review), thereby enabling preventative or corrective action during the program. This paper discusses continuing research on the adaptation of existing systems engineering leading indicators (developed under the assumptions of document-based engineering) for digital (model-based) engineering. Model-based implications identified in the research are discussed in support of the use of existing leading indicators in digital engineering programs. An illustrative example describes how measurement data can be extracted from a digital system model and composed into indicators. The importance of visualization and interactivity is discussed, especially the potential role of visual analytics and interactive dashboards. Several recommendations for future research are proposed based on interim research findings. | en_US |
dc.description.sponsorship | Acquisition Research Program | en_US |
dc.language.iso | en_US | en_US |
dc.publisher | Acquisition Research Program | en_US |
dc.relation.ispartofseries | Acquisition Management;SYM-AM-21-136 | - |
dc.subject | Systems Engineering | en_US |
dc.subject | Digital Engineering | - |
dc.subject | Management Paradigm | - |
dc.title | Investigation of Leading Indicators for Systems Engineering Effectiveness in Model-Centric Programs | en_US |
dc.type | Presentation | en_US |
Appears in Collections: | Annual Acquisition Research Symposium Proceedings & Presentations |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
SYM-AM-21-136.pdf | Presentation PDF | 1.58 MB | Adobe PDF | View/Open |
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.