Assessment of Evidence Typology
A framework for categorizing evidence and matching it with appropriate analytical methods to extract decision-guiding insights. It links transactional data, empirical research, norms and standards, and expert judgment to probabilistic, thematic, summarization, and pooling analyses.
THE IDEA
A framework needs enough detail for people to use it. This evidence typology connects categories of evidence with methods for turning them into information that can guide a decision. The categories appear in [Figure 7.2], and the analytical approaches in [Figure 7.3]; the diagrams are not included in this excerpt.
The proposed mapping is:
- Probabilistic analyses for transactional, communication, and other recorded data. These methods help assess patterns and uncertainty in data that may be varied and voluminous.
- Thematic analyses for identifying and synthesizing relevant findings across empirical research studies, including studies that reconcile results on the same topic.
- Summarization for bringing together applicable industry norms, organizational norms, and standards.
- Pooling for combining expert opinions and forecasts.
The category helps identify a starting approach. Differences within each category may require several analytical techniques.
When to use it
A business strategist evaluating market data, competitor research, and industry standards to decide on a new product launch.
A policy analyst combining expert forecasts, empirical studies, and organizational norms to draft a climate action plan.
A project manager assessing transactional data, team feedback (expert judgment), and industry best practices to improve workflow efficiency.
FROM THEORY TO EVERYDAY LIFE
In practice
Transactional Data Analysis
A company analyzing sales transactions to identify purchasing patterns uses probabilistic analysis to predict future buying behavior and inform inventory decisions.
Research Synthesis for Policy
A public health agency reviews studies on vaccination policy. It uses thematic analysis to identify recurring findings and explain differences in context, alongside the studies’ quantitative estimates of effectiveness.
A MOMENT TO REFLECT
Put it to work.
Think of a recent decision you made that relied on multiple types of evidence. Which analytical approaches did you implicitly use, and how could this typology have improved your process?
Consider an instance where a compelling idea lacked operational details. How did that affect its implementation? What would the evidence typology prescribe?
Identify a situation where you had to combine experiential evidence (like expert opinions) with empirical data. How would you apply pooling and thematic analysis together?
CONTINUE THE CONVERSATION
Source texts
- Evidence-Based Decision-Making How to Leverage Available Data and Avoid Cognitive Biases (Andrew D. Banasiewicz)