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Title: Integrated Decision Technology for Acquisition and Contracting
Authors: Roy Garrison
Daniel Dolk
Albert Barreto
Keywords: Simplified Acquisition Procedures; Decision Technology
Decision-Support System (DSS)
DSS Generator
Integrated Decision Technology Environment (IDTE)
Issue Date: 1-Apr-2008
Publisher: Acquisition Research Program
Citation: Published--Unlimited Distribution
Series/Report no.: Simplified Acquisition Procedures (SAP)
Abstract: Decision technologies in the form of decision-oriented software systems have proliferated dramatically over the past two decades. Most of these systems tend to be stand-alone systems which are focused on a relatively narrow set of analytical techniques for solving quite specific problems. Many applications, however, require a combination of these technologies to address complex decision-making problems. What is missing in the DSS landscape is an environment in which to create a DSS Generator that integrates requisite technologies flexibly and quickly to construct a robust application. We discuss the notion of an integrated decision technology environment (IDTE) in the context of Federal acquisition and contracting. Specifically, we show how the application of existing decision support technologies can assist Federal Government contracting personnel in determining which vendor proposal offers the best overall value to the customer in competitive solicitations. The intent is to establish a model that, when implemented, will ensure that contracting personnel evaluate proposals both consistently and fairly for simplified acquisition procedures (SAP). The proposed system, Source Selection Support System (S4), integrates several decision support technologies including a weight-based ranking model, a multi-criteria decision analysis software system, an expert system, data mining, and a data warehouse. We describe the data, model, knowledge, and user interface components of S4, present a use case, and show how virtualization technology can facilitate the implementation of this DSS. We conclude by discussing how this approach can be generalized to embrace a fuller portfolio of decision technologies which can, in turn, address a wider array of more complex contracting applications.
Description: Contract Management / NPS Faculty Research
Appears in Collections:Sponsored Acquisition Research & Technical Reports

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