Keywords: Storytelling, insight, decision making, visualization
Data scientists use sophisticated technologies to extract insight from big data; when the insights do not result in an action, data scientists miss precious opportunities in making their largest possible impact. In practice, a lot of data science results are not implemented. To better convert insights into actions, data scientists need to leverage the art of data storytelling and need to understand the process of how people make decisions. In this presentation, I am going to talk about two aspects of data storytelling, presentation hierarchy and visual hierarchy, to demonstrate two simple steps that can consistently improve insight-to-action conversion. One is to put insights directly on the top of presentation hierarchy; two is to make bold statements on the top of visual hierarchy. In addition to the two hierarchies, data storytelling power can be further enhanced through leveraging business decision-making processes. I am going to discuss three archetypes of decision-making and their characteristics in relation to data science: strategic decisions, operational decisions and managerial decisions. Insight is one essential out of data work; because data scientists typically hand over insight to other professionals for action, data scientists should optimize their data storytelling to keep the insight-to-action conversation as successful as possible.