Informed Desk Staffing with Quantified Reference Statistics Using Electronic Data Collection to Re-Envision Reference Services at the USF Tampa Libraries ALA 2011 Annual Conference Presentation RUSA MARS Top Trends June 25, 2011
Lily Todorinova , University of South Florida Andy Huse , University of South Florida Barbara Lewis , University of South Florida Matt Torrence , University of South Florida
University of South Florida Campuses : Tampa, St. Petersburg, Sarasota, Lakeland Student Population: (Tampa): approx. 40,000 Profile: Urban, Undergraduate, High Research Activity
Re-Envisioning Public Services
Context for the project: 2010, Inter-departmental
History of the Learning Commons
Tally sheets and/or "clickers"
Sample days throughout the semester
Experimentation & anecdotal information
Single-staffing librarians with GAs at peak times only
Instituting a referral system between GAs (or paraprofessionals) and librarians, when desk is single-staffed
Instituting better referral between other departments and units (Special & Digital Collections, as well as Circulation, the Writing Center, and Tutoring and Learning)
Eliminating night hours and reducing weekends
Increasing reliance on virtual reference
Virtual Reference: The Solution
Started with email in 1999
Moved to, from, and back to collaborative services
Chat and text services
Supplement, or replacement?
Past, present, & future data collections
What types of decisions?
How was it done?
How do you want to do it?
What type of data do you need?
Results in Special Collections
The old backup desk model (staff/students with faculty backup) had problems: two scheduled for each hour, duplication, no benefit to patrons.
Aeon and Desk Tracker provide important data: Similar ratio (9:1) of basic informational questions to actual reference queries. Majority of patrons required "retrievals," not "consultations.”
New desk model, relatively small cadre of two staff and two students. Advantages: Frees faculty for other duties, a stable lineup of well-trained desk staff, eases schedule creation.
Statistics determined cuts in hours.
Small department, fast implementation.
Results in Academic Services
Changes in daily scheduling
Down to one librarian/GA for slower times
Modifications to evening coverage (TBLC chat help)
Changes to weekend scheduling
Librarian shift moved to Sunday evenings (4-8pm)
Email and chat coverage on Saturdays
Increased focus on consultations
Conclusions and the Future
Systematized referral process
Cross-informational training between service points