Case Study: Prominent Research University

• Making course content accessible to all
• Manual process of tagging PDF elements
• Desire to automate the tagging process
• Potential litigation for inaccessible online content

To make online course content accessible to all — including the visually impaired — the university manually tagged each PDF file. All headers, paragraph text, images and tables had to be tagged so they could be identified with an automated screen reader. This enabled visually impaired students  to listen to the content online. Without the tags, the information would sound like a run-on sentence — impeding the learning experience. 

While extremely important, the manual tagging process was slow and time consuming. The university's accessibility department wanted to automate as much of the process as possible to save time and reallocate staff to other value-adding tasks. Also influencing the drive to automate was the potential for litigation when online content isn't accessible to everyone.  

• Eliminated 70% to 80% of  manual steps
• Minimized litigation exposure
• Allowed staff to focus on other work
• Gained a recruitment differentiator 

By automating much of its PDF document tagging process, the university was able to eliminate 70% to 80% of its manual steps. Documents are entered into the system far quicker than before, enabling the university to deliver course content faster to the visually impaired and avoid costly potential litigation. In addition, with so much time saved, the university staff can now focus on other work central to their jobs. 

The university also gained a differentiator to share with students and parents during recruitment. This helps the university deliver on its founding principles as a social justice leader and highly inclusive higher education institution. 

• Introduced Kofax AutoStore® auto-tagging software
• Integrated auto-tagging with Ricoh MFPs
• Provided a successful proof of concept
• Integrated AutoStore into document tagging process

For several years, Ricoh had been providing the university its innovative, digital print  fleet and managed print services as well as running the on-site copy, print and scan center. Having forged a solid relationship through the years, we learned of the university's issue with manual  tagging of online content. We introduced the university to Kofax AutoStore® auto-tagging software that would allow them to remove much of manual data entry required to make documents accessible to the visually impaired. 

With AutoStore, the university could capture the information with the advanced scanning features on our MFPs, auto-tag optical character recognition (OCR) scanned content via the software, and route each document to the appropriate folder in their electronic learning management system. All headers and paragraph text could be auto-tagged, leaving only images and tables to be fine-tuned manually. 

To test the process, we installed AutoStore on five strategically placed MFP devices on campus and conducted a proof of concept with the university. After seeing the solution in action, the university enthusiastically integrated the  AutoStore solution into its document tagging process.