Designing a Graphical Decision Support Tool to Improve System Acquisition Decisions
Abstract
System acquisition decision makers are frequently charged with choosing a single system from a set of feasible possibilities that could best fulfill the needs of their organizations. While numerous rules and regulations are already in place for both commercial and government acquisitions to ensure the acquisitions are conducted fairly, decision makers need greater support than rules and regulations alone can provide. The acquisition decision is a complex data analysis problem, where the decision maker must analyze multiple candidate systems on a number of performance and cost metrics. To understand this multivariate environment, decision makers must analyze the system data at multiple levels of reasoning. This research proposes a decision support tool that best supports system acquisition decision makers by providing them with graphical representations displaying how well candidate systems fulfill their organizations? needs. System acquisition decisions require support of three basic levels of reasoning (Data Processing, Information Aggregation, and Knowledge Synthesis) in order to perform system trade-offs on relevant system metrics. To test how well decision support tools could support system acquisition decision makers, two graphical decision support tools were designed: a traditional separable display and a new configural display named Fan Visualization (FanVis). To compare the effectiveness of FanVis against a traditional separable display, an experiment was conducted where participants answered a series of system acquisition questions across the three levels of reasoning. Analysis of the experimental results indicate that FanVis and the separable displays support a system acquisition decision maker, but to different degrees across the three levels of reasoning. Comparatively, participants tended to have higher performance on Knowledge Synthesis tasks us
Document Details
- Document Type
- Technical Report
- Publication Date
- Jun 01, 2009
- Accession Number
- ADA530936
Entities
People
- Anna E. Massie
Organizations
- Massachusetts Institute of Technology