Preliminary Observations on Program Instability

This white paper reports emerging findings at the end of Phase I of the Lean Aircraft Initiative in the Policy focus group area. Specifically, it provides details about research on program instability. Its objective is to discuss high-level findings detailing: 1) the relative contribution of different factors to a program’s overall instability; 2) the cost impact of program instability on acquisition programs; and 3) some strategies recommended by program managers for overcoming and/or mitigating the negative effects of program instability on their programs. Because this report comes as this research is underway, this is not meant to be a definitive document on the subject. Rather, is it anticipated that this research may potentially produce a number of reports on program instability-related topics. The government managers of military acquisition programs rated annual budget or production rate changes, changes in requirements, and technical difficulties as the three top contributors, respectively, to program instability. When asked to partition actual variance in their program’s planned cost and schedule to each of these factors, it was found that the combined effects of unplanned budget and requirement changes accounted for 5.2% annual cost growth and 20% total program schedule slip. At a rate of approximately 5% annual cost growth from these factors, it is easy to see that even conservative estimates of the cost benefits to be gained from acquisition reforms and process improvements can quickly be eclipsed by the added cost associated with program instability. Program management practices involving the integration of stakeholders from throughout the value chain into the decision making process were rated the most effective at avoiding program instability. The use of advanced information technologies was rated the most effective at mitigating the negative impact of program instability.

Context Interchange as a Scalable Solution to Interoperating Amongst Heterogeneous Dynamic Services

Many online services access a large number of autonomous data sources and at the same time need to meet different user requirements. It is essential for these services to achieve semantic interoperability among these information exchange entities. In the presence of an increasing number of proprietary business processes, heterogeneous data standards, and diverse user requirements, it is critical that the services are implemented using adaptable, extensible, and scalable technology. The COntext INterchange (COIN) approach, inspired by similar goals of the Semantic Web, provides a robust solution. In this paper, we describe how COIN can be used to implement dynamic online services where semantic differences are reconciled on the fly. We show that COIN is flexible and scalable by comparing it with several conventional approaches. With a given ontology, the number of conversions in COIN is quadratic to the semantic aspect that has the largest number of distinctions. These semantic aspects are modeled as modifiers in a conceptual ontology; in most cases the number of conversions is linear with the number of modifiers, which is significantly smaller than traditional hard-wiring middleware approach where the number of conversion programs is quadratic to the number of sources and data receivers. In the example scenario in the paper, the COIN approach needs only 5 conversions to be defined while traditional approaches require 20,000 to 100 million. COIN achieves this scalability by automatically composing all the comprehensive conversions from a small number of declaratively defined sub-conversions.

Context Mediation in the Semantic Web: Handling OWL Ontology and Data Disparity through Context Interchange

The COntext INterchange (COIN) strategy is an approach to solving the problem of interoperability of semantically heterogeneous data sources through context mediation. COIN has used its own notation and syntax for representing ontologies. More recently, the OWL Web Ontology Language is becoming established as the W3C recommended ontology language. We propose the use of the COIN strategy to solve context disparity and ontology interoperability problems in the emerging Semantic Web – both at the ontology level and at the data level. In conjunction with this, we propose a version of the COIN ontology model that uses OWL and the emerging rules interchange language, RuleML.

Preliminary Observations on Program Instability

This white paper reports emerging findings at the end of Phase I of the Lean Aircraft Initiative in the Policy focus group area. Specifically, it provides details about research on program instability. Its objective is to discuss high-level findings detailing: 1) the relative contribution of different factors to a program’s overall instability; 2) the cost impact of program instability on acquisition programs; and 3) some strategies recommended by program managers for overcoming and/or mitigating the negative effects of program instability on their programs. Because this report comes as this research is underway, this is not meant to be a definitive document on the subject. Rather, is it anticipated that this research may potentially produce a number of reports on program instability-related topics. The government managers of military acquisition programs rated annual budget or production rate changes, changes in requirements, and technical difficulties as the three top contributors, respectively, to program instability. When asked to partition actual variance in their program’s planned cost and schedule to each of these factors, it was found that the combined effects of unplanned budget and requirement changes accounted for 5.2% annual cost growth and 20% total program schedule slip. At a rate of approximately 5% annual cost growth from these factors, it is easy to see that even conservative estimates of the cost benefits to be gained from acquisition reforms and process improvements can quickly be eclipsed by the added cost associated with program instability. Program management practices involving the integration of stakeholders from throughout the value chain into the decision making process were rated the most effective at avoiding program instability. The use of advanced information technologies was rated the most effective at mitigating the negative impact of program instability.