*All assets are the property of Stanford Graduate School of Business. This case study and prototype are used strictly for educational and instructional purposes*
SALLIE (Stanford ALL-Image Exchange) is Stanford's campus-wide system for managing and sharing digital assets. The database houses over 50,000 photos and is used by faculty, staff, and students across all departments and groups at Stanford. The database serves as a daily resource for many users but is also used as the primary digital archival system for the visual history of the University.
In this case study, I have highlighted some of the main challenges we faced. To see the entire project, please visit the links below.
1. Reduce the amount of time employees spend searching for and managing photos.
2. Centralize photos across all of Stanford University Departments and improve photo metadata.
3. Provide an organized, easy-to-use photo database that will be used by all Universty Departments.
We created a survey to discover what users thought about using Sallie. The survey results revealed that 86% of all participants (59) would not recommend Sallie to a coworker, and 65% of the participants prefer using a different photo storage database.
Additional survey results revealed what users did not like the most about using Sallie.
1. User interface (navigation and layout)
2. Time it takes to find photos
After reviewing the survey, we were able to establish several problems with the current database.
1. Search and Filter - Users were spending too much time searching and filtering photos
2. Metadata - There was a lack of centralization across campus. Many departments were independently managing photos on other storage sites
3. Usability and User Interface - The University's brand was at risk because of a diminishing image
The old search and filter functionality required the users to complete many steps by filling in description rules and reapply new rules every time they wanted to change their search. The users found the search functionality to be complicated and offering very narrowed or irrelevant search results.
Through our research, we found that users use many different search patterns when looking for a photo. If a user were looking for a specific photo, they preferred entering keys words but if the user had no idea what photo they were looking for, the user preferred browsing through a genre of photos.
The example below illustrates the flow of a user looking for a portrait of a specific faculty member by only entering her first name.
We conducted user interviews to gather insights to prioritize filter options. The filter options are designed to narrow the user's search without overly skewing the results. The filter options narrow the results by focusing on file attributes rather than subject matter.
The old database did not support a photo upload process. The task required a specialist to upload all of the photos and manually tag and categorize each image. The goal for the redesign was to allow administrators from each department to bulk upload groups of photos and through, a series of steps gradually refine the information tagged to each image.
The Bulk Upload allows the user to upload an entire photoshoot. The user can name photos by applying a series of tags and generating individual ID cutting down the time it takes to organize and upload shoots.
The user can also apply usage settings, information about the shoot, and copyright instructions.