Adapting Venture Capital Concepts to Enterprise System Acquisitions Renee Stevens, Principal Investigator Problems:
Federal acquisition confronts long-standing, well-publicized challenges. Enterprise systems, characterized by evolving requirements, complex linkages across boundaries, and political, organizational and economic issues, introduce additional challenges. These challenges are being recognized and there is a growing interest in tailoring the acquisition process to deal with the complexity and uncertainty inherent in enterprise systems.
Objectives:
The goal of this research is to contribute a strategic, forward-looking view of enterprise systems acquisition. Specifically, the research objectives are to explore venture capital (VC) approaches and determine whether and how they can be used to improve the acquisition of enterprise systems in the federal arena, and to develop and pilot elements or an enterprise systems acquisition model.
Activities:
Research activities will be organized into three overlapping phases. Phase I entails inventorying VC and federal acquisition methods, developing a VC-derived enterprise acquisition model, and identifying opportunities for early pilots. Phase II will validate and refine the model features. Phase III will leverage early pilots to apply the proposed approach to a government program.
Impact:
The research will develop within MITRE a rich understanding of enterprise systems acquisition as a complement to the evolving discipline of enterprise systems engineering. It will foster a rich dialogue across the federal acquisition community, including policy makers, practitioners, and academicians, and develop the basis for an alternative set of processes for the acquisition of enterprise systems.
Approved for Public Release: 07-0282 Presentation [PDF]
Data Protection Services Modernization Steven Sesar , Principal Investigator
Datacenter Consolidation Using VMWare Virtualization John Robinson, Principal Investigator
Enterprise Dynamics: An Architecture-Based, Decision-Driven Approach Ken Hoffman, Principal Investigator Problems:
Large complex systems acquisition programs have high failure rates attributable to various systemic factors. The national challenges addressed in these acquisitions require multiple agents working in a heavily networked environment at both technical and organizational levels. Improved quantitative and qualitative methods are needed to resolve the performance, organizational, and information dynamics of enterprises and improve acquisition processes and the transition to effective operations.
Objectives:
We will describe, model, and analyze the interactions within an enterprise, stakeholders, and the external environment, as large-scale systems acquisition programs are undertaken. Research will focus on strategies and governance policies in general use and on alternative fast track strategies for heavily networked enterprises that involve organizational interoperability among agencies, as well as sharing of services, data, and technical infrastructure.
Activities:
This collaborative project with MIT's Engineering Systems Division will integrate qualitative and quantitative factors. We will develop a framework and a model that covers all aspects of enterprise architecture and the decisions that drive its evolution and implementations. We will analyze the dynamics of acquisition policies and strategies, enterprise transformation attributes and metrics, and collaborate with research on complex adaptive systems, enterprise systems engineering (ESE), and other MITRE resources.
Impact:
Enterprise dynamics will provide a foundation discipline for ESE that incorporates enterprise architectures and decision theory. The research will provide insights into critical success factors in the acquisition of large-scale systems in complex operational environments. Specific recommendations will be developed for improved management and governance policies that are sensitive to the operational patterns and the dimensions of the system to be implemented.
Approved for Public Release: 05-1235 Presentation [PDF]
Real Options Applications for Public Sector Investment and Acquisitions Felipe Moreno-Hines, Principal Investigator Problems:
Government agencies face dynamic acquisition and investment environments, yet they rely on decision-making methods and tools that force inflexible, fixed commitments to risky, long-term projects. Standard benefit-cost analysis methods consistently undervalue project benefits by ignoring flexibility and the organization's ability to adapt to new information as the system matures.
Objectives:
We will apply a real options approach to the design and valuation of a federal acquisition in order to demonstrate the value of the framework and develop real options analysis as a corporate competence in this dynamic public sector environment.
Activities:
We will investigate best practices in real options analysis and assess the benefit of flexible design in complex systems. We will apply this framework to the design and valuation of a federal acquisition, using enabling decision support software. We will work with project managers and decision makers to identify sources of uncertainty and design system and implementation contingency strategies (i.e., options).
Impact:
The research will produce a framework for system design and investment planning that enables decision makers to account for the value of system flexibility. This framework will support better use of public funds by reducing the cost and schedule overruns that result from long-term, fixed predictions about system performance that are typically made early in the design stages.
Approved for Public Release: 07-0104 Presentation [PDF]
Risk Model for Dynamic Aviation Security Alfred Anderegg, Principal Investigator Problems:
The DHS second strategic review concluded that mitigation measures should be dynamically applied in proportion to the risk of terrorist actions. The review also mandated using an algorithm-based risk assessment. The problem is the absence of a clear model of aviation security risk suitable to inform decision makers.
Objectives:
The game theory and artificial intelligence communities agree that traditional algorithms can at best only minimize a worst case scenario. The ultimate goal is a dynamic decision model, reflecting both friendly and adversarial options, to better provide decision makers with actionable insights.
Activities:
We will prototype a model of vulnerability (our perspective) and threat (adversary perspective) together as an algorithm to gauge risk, and generate scenarios that allow decision makers to determine what types of decisions models might realistically support. We will identify the most significant parameters for modeling risk and the decision makers who might be the best audience for algorithm-based risk assessments.
Impact:
A prototype model will position MITRE within two years of a technology transfer of decision support tools for algorithm-based risk-driven decision making. The prototype and associated papers will focus on syntax for defining threats and risks, methods for generating threat vector cases, ways to quantify combined payoff (feasibility and consequences), the level of decisions that can be informed, and terminology for describing risk algorithms.
Approved for Public Release: 07-0105 Presentation [PDF]
Selecting Services for a Service Oriented Architecture Marc Halley, Principal Investigator Problems:
As agencies move to service oriented architectures (SOA), the major concern is selecting the highest value services for the enterprise. Much is know about SOA technology, but very little is known about which services should be created. What services are desired? What services are possible? In what priority order should services be developed? Can an easy method be devised?
Objectives:
The objective is to develop a general method and decision tool that agencies can use to create a service portfolio. By selecting services from two large IRS cases, we will develop a general method applicable to other agencies. These agencies will then be able to select services from legacy applications that will be used throughout the enterprise.
Activities:
Phase 1 will select a set of test cases with IRS domain owners. Phase 2 will analyze these cases for legacy assets, possible services, and priority lists of services, and will produce two service portfolios. Phase 3 will generalize the selection method for use in other situations and cases.
Impact:
This IR&D project will develop service portfolios for two very large IRS systems (the Account Management System and the Integrated Data Retrieval System), along with a general methodology for selecting services for other IRS systems. The project will also generalize the method for Treasury applications, with potential application to any agency.
Approved for Public Release: 07-0350 Presentation [PDF]
System Complexity, the "ilities," and Robustness John Dahlgren, Principal Investigator Problems:
As systems become more complex, systems engineers need to understand the design tenets that have enabled historical systems to be flexible, adaptable, upgradeable, and robust. Concurrently, program managers need objective methods of pricing future investment options to invest in those attributes that ensure a positive return on investment. This combination is needed to support effective spiral development of systems.
Objectives:
The research will develop definitions of positive performance in the "ilities" (systemic properties), identify systems that have historically performed well in the ilities and the key attributes that enabled this performance, determine the cost of including these attributes in the sample systems, and develop a methodology to price a future option to include these attributes during system design, development and spiral development.
Activities:
The team will query the systems engineering community to find example historical systems, research the design tenets that enabled positive performance, and determine the incremental cost of including the ilities in the original system design. The team will also research comparison systems that failed to perform well in the ilities and will then apply these concepts to current-day systems.
Impact:
This research will aid program managers to make wise short-term and long-term decisions, extend the operational lifetime of future systems as a result of adding the ilities related design tenets, and decrease initial and lifetime system costs. This research will apply to both government and commercial systems.
Approved for Public Release: 05-1485 Presentation [PDF]
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