Data visualization emerges a key driver of decision-making at organizational and community levels

Data visualization has emerged as a powerful tool for enabling data-driven decision-making across diverse domains, including business, medicine, and scientific research. However, no comprehensive analysis has previously addressed the types of decision-making problems supported by data visualization or how its role has evolved.

Researchers have conducted a systematic review of significant data visualization research over the past 16 years, classifying and analyzing the studies within a multidimensional decision-making framework. They determined that data visualization primarily facilitates decision-making at the organizational and community levels. Their study is published as part of the 2025 IEEE 18th Pacific Visualization Conference (PacificVis).

Although earlier efforts primarily addressed “evaluative” decision-making, recent trends indicate increasing support for a broader range of decision-making types, including “constructive” and “cognitive dominance” decision-making. Moreover, the structure of decision-making problems addressed by data visualization has expanded from “largely structured problems” to “semi-structured problems.”

The findings indicate that data visualization increasingly supports advanced decision-making by experts in fields such as business and public policy, particularly concerning semi-structured problems.

The findings of this study clarify the current scope of decision-making support provided by data visualization and offer insights to guide the development of new visualization techniques. They also highlight the need for further research into visualization methods capable of supporting individual-level decision-making and unstructured problems.