全球智库信息集成服务系统

Data analytic tools can help acquisition managers identify potential contractor risks indicators early on

• Statistically comparing contractor outliers relative to peers appears to be a useful way to objectively identify potential risks; this approach identifies areas for increased management attention.
• Cross-indexing public and sensitive databases through modern interfaces enables new risk indicators too time-consuming to discover manually.
• Such automated tools can help managers focus their limited resources on potential risks buried in large, diverse data and take mitigation actions based on effectiveness and program relevance.
• Identified outliers are indicators for acquisition professionals to apply their acumen, understanding of program priorities, and acceptable levels of risk to determine the relevancy and magnitude of the potential risks and what actions should be taken (if any) to mitigate them.

Some challenges remain to operationalize this capability

• Some data that are important for assessing relative contractor risks are very difficult to obtain — even for Air Force officials and federally funded research and development centers, let alone support contractors.
• Further work is necessary in developing a prototype with significant critical mass of data sources and measures to test and refine this approach. User feedback on utility and design is also needed.

Risk is a key component in any business transaction, especially transactions worth millions of dollars or more. As the Department of the Air Force acquisition professionals are aware, there are multiple kinds of risks in developing and acquiring new systems. One recurring challenge to successful acquisition program execution is poor contractor performance. When contractors are in danger of not meeting contractual performance goals, acquisition may not be fully aware of the shortfall until, for example, a schedule deadline is missed, government testing indicates poor performance, or costs exceed expectations.

The authors developed and prototyped a new way to apply data analysis on a variety of government and commercial data sources to assess the relative contractor performance risks in Air Force acquisition contracts and programs. This method produces risk indicators earlier than do current information sources and metrics by analyzing workforce, costs, financial health, influence, supply chains, past performance, and other data to assess relative risk indicators.

Such automated tools can help managers focus their limited resources on potential risks buried in large, diverse data and take mitigation actions based on program relevance and impact on desired risk levels. Identified outliers are indicators for acquisition professionals to apply their acumen, understanding of program priorities, and acceptable levels of risk to determine the relevancy and magnitude of the potential risks and what actions should be taken (if any) to mitigate them.

• Chapter One

  The Challenge: Contractor Risks in Acquisition

• Chapter Two

  Taxonomy of Relative Risks

• Chapter Three

  Relative Risk Measures and Equations

• Chapter Four

  Prototype Architecture

• Chapter Five

  Insights, Conclusions, and Next Steps

• Appendix A

  Risk Measures and Potential Data Sources