Data Distillation: Applying Design Principles to Reporting, KPI, and Dashboards

In my career first as an analyst, then as an actuary, and now as a practicing data scientist, I have faced the challenge of communicating my stunning insights in a manner which business users could understand and from which they could take action. Executives at major broadcasting companies and at manufacturing companies raised the same objections of data not being trustworthy or numbers being twisted to say anything. Even worse was delivering major reporting tools or dashboards and having them sit unused. I have surveyed hundreds of data scientists and analysts and found that this exact issue was in every one of their top five challenges they face in their job. The solution is much simpler than I ever imagined It is a solution I have been sharing at conferences for data scientists across the United States, and a solution that is beginning to be implemented at giants in the analytics world like IBM. The solution is a process I call Data Distilling, and it revolves around applying simple design principles to the presentation of data. Data presentation is not data visualization—although that is a part of it. Data presentation is the story that you tell with the data. It includes visualizations that are appropriate and meaningful to the audience, metrics that matter, and a story to go with it. This session will focus on teaching the five basic steps of my process to attendees, and they will leave with the basic tools to help their data insights be heard, even by the nearly data deaf executive teams that we all seem to encounter.