Understanding PALT Time Frames with Big Data Analytics

Please use this identifier to cite or link to this item: https://dair.nps.edu/handle/123456789/4426

Full metadata record

DC Field	Value	Language
dc.contributor.author	David Gill	-
dc.date.accessioned	2021-05-19T21:14:19Z	-
dc.date.available	2021-05-19T21:14:19Z	-
dc.date.issued	2021-05-19	-
dc.identifier.citation	Published--Unlimited Distribution	en_US
dc.identifier.uri	https://dair.nps.edu/handle/123456789/4426	-
dc.description	Acquisition Management / Defense Acquisition Community Contributor	en_US
dc.description.abstract	Awarding federal contracts is perceived as an excessively lengthy process. The purpose of this research is threefold: (1) to understand the drivers of procurement administrative lead time (PALT), (2) to identify opportunities to reduce PALT, and (3) to predict when specific requirements are likely to be awarded. These analyses will be performed using newly available, government-wide data for over 5 million federal contracts.	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-21-119	-
dc.subject	Contracting	en_US
dc.subject	Procurement Administrative Lead Time	-
dc.subject	Big Data Analytics	-
dc.subject	PALT	-
dc.subject	Predictive Modeling	-
dc.subject	Machine Learning	-
dc.subject	Data Visualization	-
dc.subject	Time to Contract Award	-
dc.title	Understanding PALT Time Frames with Big Data Analytics	en_US
dc.type	Presentation	en_US
Appears in Collections:	Annual Acquisition Research Symposium Proceedings & Presentations

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