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Title: Technical Data as a Service (TDaaS) and the Valuation of Data Options
Authors: George E Thompson; Michael McGrath
Keywords: Technical Data
Technical Data Package
Technical Data Set
Intellectual Property
Real Options
Technical Data as a Service
Digital Engineering
Product Life-Cycle Management
Digital Thread
Digital Twin
Issue Date: 20-Jun-2019
Publisher: Acquisition Research Program
Citation: Published--Unlimited Distribution
Series/Report no.: Product Lifecycle Management
Abstract: Technical data allow the Department of Defense to sustain the systems it acquires and provide flexibility for future acquisitions; however, acquiring these data is challenging. Current DoD policy requires program managers (PMs) to consider procuring technical data and associated data rights during acquisition, and current practice is to negotiate for and acquire a complete Technical Data Package (TDP) in anticipation of future unspecified needs. However, because those needs are uncertain, it is difficult to determine a fair and reasonable price. Some data that are eventually needed may not be acquired, and some data that are acquired may never be used. New digital data technologies can overcome these challenges, but only if paired with new acquisition approaches. Today's data management systems make it possible to define and manage digital subsets of the Technical Data Sets (TDSs) that are tailored to the Government specific data needs, or use cases. The ability to contract for optional delivery of TDSs as needs arise will require valuation methods that allow PMs to negotiate pricing under conditions of uncertainty. To help meet these challenges, this research develops and demonstrates a new approach to the valuation of technical data, based on the application of real options theory. A key objective is to show how this approach, together with the application of technical data use cases and the capability of new data management tools, allows DoD PMs to hedge against uncertainty and acquire technical data on more favorable terms. The results include an algorithm for implementing the approach under a wide range of circumstances, and an example that shows how that algorithm can be used to answer practical questions that the PM faces when acquiring technical data (for example, Which data, if any, should be acquired now? Should the government negotiate options to access certain data downstream? If so, how should industry and government arrive at a mutually acceptable price?) Finally, the paper shows how this approach supports the development of a powerful new business model Technical Data as a Service (TDaaS). The methods, tools, and frameworks developed herein provide several benefits. First, they help DoD purchase only the data that are needed, when they are needed, and for how long they are needed, thus enabling significant potential savings in system life-cycle costs. Second, they allow DoD to respond to unanticipated needs by preserving options for future data access and/or ownership. Third, they help industry and Government arrive at a fair and reasonable price by allowing both parties to more accurately assess data value and risk from their own unique perspectives. Fourth, they are consistent with, and help to achieve the benefits of, related DoD initiatives in acquisition and digital engineering. These indirect benefits include not only acquisition cost savings but also improved trade space exploration and reduced acquisition cycle time. Finally, it should be noted that the results of this research can be directly incorporated into upcoming DoD pilot programs aimed at implementing Congressionally-directed improvements in technical data acquisition and intellectual property valuation.
Description: Logistics Management / Grant-funded Research
Appears in Collections:Sponsored Acquisition Research & Technical Reports

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