Accession Number : AD1016700


Title :   Schedule Analytics


Descriptive Note : Conference Paper


Corporate Author : MITRE Corp Bedford United States


Personal Author(s) : Manring,Jennifer ; Fugate,Thomas


Full Text : http://www.dtic.mil/dtic/tr/fulltext/u2/1016700.pdf


Report Date : 30 Apr 2016


Pagination or Media Count : 32


Abstract : Program managers are becoming increasingly aware of the need for greater accuracy in schedule estimation, assessment, and risk management to control cost and Deliver on time. A Government Accountability Office (GAO) assessment of 86 programs that made up the 2012 portfolio of Major Defense Acquisition Programs (MDAPs) found that the portfolio experienced total acquisition cost growth of 38%. In addition, the average schedule delay in delivering initial capability was 27 months when measured against first full estimates (GAO, 2013), representing a 69% increase over a 12-year period.1 Most Major Automated Information Systems (MAIS) programs experienced schedule delays ranging from six months to 10 years. Clearly, schedule can pose a significant risk and drive cost growth. The purpose of this research was to help strengthen the acquisition communitys ability to produce data-driven realism in program schedules. This research effort had three main focus areas: (1) compile schedule data from programs to identify key schedule drivers and characteristics and build a data repository, (2) analyze the data from statistical and qualitative perspectives, and (3) document data collected and analysis performed, and how it can be accessed for analysis.


Descriptors :   program management , statistical analysis , risk management , life cycles , military acquisition , public policy , agile software development , cloud computing , scheduling


Distribution Statement : APPROVED FOR PUBLIC RELEASE