Donald R. Greer, L. Black, S. Eslinger, Dan X. Houston, R. Adams
{"title":"评估大型复杂程序的可执行性","authors":"Donald R. Greer, L. Black, S. Eslinger, Dan X. Houston, R. Adams","doi":"10.1109/AERO.2009.4839718","DOIUrl":null,"url":null,"abstract":"Why is it, when we execute very large aerospace development programs according to project management best practices, we do not reliably achieve program success? Standard project management tools used on programs include static tools such as PERT charts, critical path analysis, and earned-value analysis. These tools, however, are insufficient for representing all the dependencies that exist, or for recognizing the unintended consequences that often result from actions taken to get a program “back on track.” Also, standard project management tools provide only limited visibility into emerging short-term and long-term dynamics during development that affect a program's ability to meet its requirements adequately within the expected cost and schedule constraints, i.e., a program's ability to be executable. This paper reports on research undertaken to enhance the government's capability for managing large, complex programs. This research will produce a dynamic model adaptable to multiple large space-system development programs. However, the rigor of the modeling process has underscored the need for theoretical constructs that describe management of large, complex programs. To that end, we have sought sources to support an emerging theory that can be translated into a dynamic model that adequately represents both best and actual practices in program management. This theory is developed by creating internally consistent causal relations affecting capabilities, cost, quality, and schedule and their associated accumulations, over time.","PeriodicalId":117250,"journal":{"name":"2009 IEEE Aerospace conference","volume":"7 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Assessing executability in large complex programs\",\"authors\":\"Donald R. Greer, L. Black, S. Eslinger, Dan X. Houston, R. Adams\",\"doi\":\"10.1109/AERO.2009.4839718\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Why is it, when we execute very large aerospace development programs according to project management best practices, we do not reliably achieve program success? Standard project management tools used on programs include static tools such as PERT charts, critical path analysis, and earned-value analysis. These tools, however, are insufficient for representing all the dependencies that exist, or for recognizing the unintended consequences that often result from actions taken to get a program “back on track.” Also, standard project management tools provide only limited visibility into emerging short-term and long-term dynamics during development that affect a program's ability to meet its requirements adequately within the expected cost and schedule constraints, i.e., a program's ability to be executable. This paper reports on research undertaken to enhance the government's capability for managing large, complex programs. This research will produce a dynamic model adaptable to multiple large space-system development programs. However, the rigor of the modeling process has underscored the need for theoretical constructs that describe management of large, complex programs. To that end, we have sought sources to support an emerging theory that can be translated into a dynamic model that adequately represents both best and actual practices in program management. This theory is developed by creating internally consistent causal relations affecting capabilities, cost, quality, and schedule and their associated accumulations, over time.\",\"PeriodicalId\":117250,\"journal\":{\"name\":\"2009 IEEE Aerospace conference\",\"volume\":\"7 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-03-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 IEEE Aerospace conference\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/AERO.2009.4839718\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 IEEE Aerospace conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/AERO.2009.4839718","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Why is it, when we execute very large aerospace development programs according to project management best practices, we do not reliably achieve program success? Standard project management tools used on programs include static tools such as PERT charts, critical path analysis, and earned-value analysis. These tools, however, are insufficient for representing all the dependencies that exist, or for recognizing the unintended consequences that often result from actions taken to get a program “back on track.” Also, standard project management tools provide only limited visibility into emerging short-term and long-term dynamics during development that affect a program's ability to meet its requirements adequately within the expected cost and schedule constraints, i.e., a program's ability to be executable. This paper reports on research undertaken to enhance the government's capability for managing large, complex programs. This research will produce a dynamic model adaptable to multiple large space-system development programs. However, the rigor of the modeling process has underscored the need for theoretical constructs that describe management of large, complex programs. To that end, we have sought sources to support an emerging theory that can be translated into a dynamic model that adequately represents both best and actual practices in program management. This theory is developed by creating internally consistent causal relations affecting capabilities, cost, quality, and schedule and their associated accumulations, over time.