Assesing Vulnerabilities in Model-Centric Acquisition Programs Using Cause-Effect Mapping
Abstract
Assessing Vulnerabilities in Model-Centric Acquisition Programs Using Cause-Effect Mapping Principal Investigator: Dr. Donna H. Rhodes, Massachusetts Institute of Technology This research will be led by Dr. Donna H. Rhodes, Massachusetts Institute of Technology. Acquisition programs increasingly use model-centric approaches, generating and using digital assets throughout the lifecycle. Recent research supports new model-centric practices, yet in spite of sound practices there are uncertainties that may impact programs over time. The emergent uncertainties (policy change, budget cuts, disruptive technologies, threats, changing demographics, etc.) and related programmatic decisions (e.g., staff cuts, reduced training hours) may lead to cascading vulnerabilities within model-centric acquisition programs, potentially jeopardizing program success. The research objectives include: (1) investigate uncertainties and related decisions that may lead to potential vulnerabilities in model-centric acquisition programs; (2) generate a generic model for aiding program managers in detecting and assessing vulnerabilities as related to the program’s model-centric practices and environment; and (3) define a step-wise process for applying the generic model in assessing and mitigating model- centric vulnerabilities. This research seeks to provide program managers with the means to identify model-centric program vulnerabilities and determine where interventions can most effectively be taken. The technical approach for the research begins with literature review and gathering results of past research studies of relevance, including studies of model-centric environments and transformations from traditional to model-centric engineering paradigm (sometimes referred to as the digital engineering paradigm), recent workshop findings, and related work on vulnerability assessment that may have implications for this work. Cause-Effect Mapping, a technique developed at MIT, will be employed to examine cascading effects between emerging uncertainties and terminal outcomes. Using the results, a CEM is generated and used for discussion with subject matter experts, and information on uncertainties and leading indicators will be collected. Analysis is performed to consider the cascading vulnerabilities and potential intervention options. The results are used to refine the CEM and analytic approach to develop a generic model for vulnerability assessment of model-centric programs. Usability of the resulting model is tested with selected research stakeholders. This research aims to contribute a useful approach for assessing, detecting and mitigating vulnerabilities in acquisition programs, specifically related to the use of model-centric practices and environments. The approach is compatible with existing DoD vulnerability assessment practices and frameworks. Anticipated results are empirically-grounded vulnerabilities of model- centric programs and a CEM generic model for identifying vulnerabilities and interventions. The anticipated outcome is a step-wise process that program managers can apply on their programs using the generic model to assess, prioritized and mitigate model-centric vulnerabilities.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Feb 10, 2017
- Source ID
- N002441710011
Entities
People
- Donna H. Rhodes
Organizations
- Harvard University