Parallel Universes: Decision Analysis and Data Science

Music City Center 

In data science, we identify patterns in data and discover what useful, interesting information we can extract. In decision analysis, we utilize that information to make informed choices. Data science primarily functions as a producer of information, while decision analysis serves as a consumer. By leveraging facilitation and decision analysis skills, we broaden our horizons to engage in project framing and collaborate with our colleagues, domain experts, and organization leaders to support their decision-making processes.

Understanding how our identities and beliefs shape our perspective on a problem is quite challenging. However, we can align conflicting sides on a decision by agreeing on the problem framework, establishing values and objectives, determining the data and model that will guide us, generating alternatives, and considering the trade-offs.

It can be challenging to step outside our own beliefs and biases. It is humbling to listen to other sides openly, but this will make us fuller and more effective statistical and data scientists.

decision analysis

structured decision-making

collaboration 

Section on Statistical Consulting