Escaping the Spreadsheet: Visualizing Mental Models

Description Why must a waiter mentally translate a chronological list of orders back to a physical table? Why do Jira lists flatten a web of team dependencies into isolated, static rows? These disconnects occur because our interfaces mirror how data is stored (rows and columns) rather than how work happens (spatial and interconnected). This talk explores a critical failure in Enterprise UX: the reliance on "Spreadsheet Thinking." I will share a case study of a warehouse manager's dashboard: originally a collection of boxed widgets and static tables. While the data was accurate, it was spatially blind. To find a bottleneck, the manager had to mentally translate row numbers into physical aisle locations. The Core Idea We need to shift from designing for the database schema to designing for the user's mental model. This means moving beyond static tables to "Pervasive Analytics," visualizations that represent the topology of work, whether that is a physical floor plan or a network of task dependencies. Structure & Flow The Universal Trap: We start by identifying why the "List" is the default view for management tools, despite being poor at showing relationships. Three Vignettes of Disconnect: We will analyze three rapid examples of how "bad viz" hides reality from the decision-maker: The Physical: A warehouse manager staring at a table of "Pending Picks," unable to see that the bottleneck is physically causing a traffic jam in Aisle 4. The Spatial: A restaurant manager trying to gauge table turnover from a list of timestamps instead of a floor plan. The Abstract: A product owner using Jira lists that hide the critical web of dependencies between teams. The Pivot: We will look at how we replaced the manager's abstract tables with a live "digital twin" map. This allowed them to identify bottlenecks instantly without mental calculation. The Framework: We conclude with a practical approach to "Spatial Consistency." How do you visualize context? How do you map the relationships between data points rather than just listing them? Why This Matters This topic connects to broader conversations in data visualization about utility over aesthetics. It challenges us to see visualization not just as a reporting layer, but as the primary operating interface for complex systems. Audience & Takeaways This talk is for designers, product managers, and data practitioners working in complex domains. You will leave with a diagnostic lens to spot "Spreadsheet Thinking" in your own tools and a new vocabulary for visualizing the "topology" of work.