FINANCIAL VISUALIZATION SUPPORT FOR BREAKDOWN ANALYSIS A method to visualize multiple foci polyarchies by successive breaking down of visualization based on its causalities Sandeep Prabhakar Muthukumar Thirunavukkarasu Anusha Dandapani Ganesh Panchanathan

Domain information DuPont analysis –DuPont analysis is a method of analyzing the performance of a company by means of various Ratios E.g. Return on Equity, Net Income, Total Equity The data –The data consisted of the annual statements of 100 companies for the last 20 years. Each company had 180 data items. –These data items are used in calculating DuPont Ratios

What is a polyarchy? Polyarchy = multiple hierarchies

Different aspects to breakdown Breakdown based on attributes –Decomposition based on predefined formulae –E.g. Frequency = wavelength / c Frequency = R(wavelength, c) Breakdown based on values –Decomposition and grouping based on distinct values State = R(Virginia, California, ….)

What are the problems? Hierarchy + Visualization at each node? Multiple Foci –I want to see B and C siblings side by side B and C are in different hierarchies –I want to see A (ancestor) and J (a deep descendant) side by side not in each other’s context Top – Down breakdown of data sets –I want to see which sub division affects the superset causality

Our solution – Breakdown Visualization

Navigating Hierarchies

Interactions Supported Fix and move technique Brushing and linking Details on demand Drill down Comparison of two nodes not in each other’s context Visualization type can be selected that best suits the data Implicit representation of hierarchy

System Diagram MS SQL database queried with JDBC

Future Work Allow a knowledgeable user to dynamically modify and store new hierarchies Implicit hierarchy may not be suitable in all cases

Results HCI metrics: –Scale Tends to infinity as user selects the visualizations to be currently seen –User performance Every click accomplishes work! –Learning time Good –Error rate Going down the wrong path problems? Yes, Easy to recover from it –Retention time ??? –User satisfaction ???

Acknowledgements Nathan Conklin (bowls for independent study students) Dr. Chris North Dr. Raman Kumar for data access