achieved within an acceptable level of risk. The use of the Continuous Risk Management Program results in a set of actionable risks that can be assessed with regard to the probability and consequences of occurrence. This information could be used to plan mitigation measures indicating that all risks have been reduced to acceptable levels by the projected launch date, to inform cost–benefit analyses and prioritization efforts, and to help NASA obtain adequate resources (funding, time, expertise) to carry out these measures. Representation of BR risks in this format, in addition to the current formats, may be an effective supplemental way of communicating the elements of the BR throughout the organization.
To enhance effective communication of the content of the BR, the committee recommends that the BR be designed and utilized as a dynamic database of information relative to risk definition and assessment, from which a document or set of alternative documents can be derived at any time and incorporated into a risk management program.
The period of time over which the Design Reference Missions will be planned and executed is decades. Thus, it is fundamentally important that configuration control methods be established and implemented for keeping the BR up-to-date as new knowledge and technologies develop. In this regard, the committee observed that new literature relative to risks in the BR that became available over the course of committee deliberations has not yet been incorporated into the BR. A mechanism is needed for periodic searches of the literature for information related to risks—including research conducted in space or in analog environments—as well as literature on the status of validation of existing countermeasures. This process can be facilitated by identifying an “owner and manager” within NASA for each set of related BR risks and establishing a regular review cycle. Given the rate of publication of new literature, it seems prudent to conduct reviews for updating not less than once annually.
Where there is a desire to combine published research data with “expert opinion” from stakeholders, methods such as computer modeling (White et al., 2003), Bayesian updating, and elicitation of expert opinion are available (see Appendix E for a description of the Bayesian update pro-