1. Chris Lehman - calehman@illinois.edu University of Illinois at Urbana-Champaign This project looked at whether an effective usability makeover of an enterprise analytics interface was possible in under two months through the use of low-cost methods, with an eye towards identifying best practices that could be distilled from the results. Introduction Objective 1. Performed cognitive walkthroughs Task-based method that identified “low hanging fruit” without need for user studies Used hypothetical but realistic stand-ins known as personas in place of users Walked through tasks on 3 competitor’s “campus profile” sites to generate ideas Process 2. Conducted user studies 3. Sketched paper mock-ups 4. Created prototypes Results Best Practices Identified Strategies for user studies involving executive-level users Start off with an easy task to build the user’s confidence and help them relax Continually stress that this is not a “test” Make overly complex tasks “time-permitting” Rapid Redesign of an Enterprise Analytics Interface The usability of simple non-interactive websites have been studied extensively, but less attention has been paid to enterprise analytics interfaces. These systems are powerful and data rich, but they frequently suffer from an overstuffed user interface. The field of User Experience Design (UXD) offers low-cost methods, both in terms of money and time, to identify and resolve user interface issues in these systems. Background The specific enterprise analytics system studied was the Campus Profile at the University of Illinois. The Campus Profile provides interactive 10-year snapshots going all the way back to 1989 that contain over 700 quantitative indicators across more than 300 departments summarized at 4 different administrative levels. Conducted dry run study with “pilot” user to solidify task wording and check timing Performed studies with target audiences: 2 with dean’s assistants, 1 with department head Identified issues through task analysis and prioritized with simple table (see above) Created sketches that try to move beyond the current interface rather than “fix” it Ideas guided by user studies and competitor site cognitive walkthroughs Paper was used rather than computer to prevent technology from stifling innovation Created multiple prototypes by modifying screenshots of original interface with Paint.NET Primary focus of prototypes was implementing fixes identified in user studies Secondary focus of prototypes was incorporating ideas sketched in paper mock-ups 1 st Prototype 2 nd Prototype Idea “A” Idea “B” Final Prototype Interface changes that go beyond “fixes” 1.Replaced horizontal navigation bars with tabbed navigation 2.Created login functionality to default to home unit data and allow report saving 3.Created footer to provide visible contact information and “frame” main content Elements added that infuse appeal and improve ease-of-use 1.Added dropdown menus with built-in search to minimize scrolling (see below) 2.Added instant graph functionality to save user from having to use Excel (see below) 3.Enlarged Excel and Print buttons and moved them closer to the data table 4.Changed navigation bars and table header colors to match colors in header Wording/labeling issues addressed 1.Added word “Items” to qualify Standard, Expanded, and Strategic navigation tabs 2.Added word “Reporting” to qualify meaning of Custom navigation tab 3.Added word “Profile” to qualify meaning of Change Year 4.Removed abbreviations in item descriptions wherever possible 5.Simplified data table header by removing dash and additional year from display Through the use of low-cost high-impact methods, we showed how significant gains in usability can be achieved in a very short period of time, even for a complex Enterprise Analytics interface. Conclusion Users ignore abbreviations and are drawn instead to spelled out words If abbreviations must be used, use them sparingly and consistently Users do not read text in pop-up windows Use modeless feedback instead – “ask for forgiveness, not permission” Users ignore generic “Help” buttons Use context-sensitive help and FAQs instead; also provide Glossary Users don’t understand format of numbers just by looking at them Clearly label numbers: percentages with %, thousands with “k”, millions with “M” Users have difficulty with complex keyboard interactions Stick to mouse-based interaction wherever possible due to Mac/PC keyboard differences and also due to minimal keyboard support in many mobile devices Note: These can be applied to other types of users as well High-frequency interface issues and suggested solutions