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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 http://guides.lib.usf.edu/informedstaffing

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Informed Desk Staffing with Quantified Reference StatisticsUsing Electronic Data Collection to Re-Envision Reference Services at the USF Tampa Libraries

ALA 2011 Annual Conference PresentationRUSA MARS Top TrendsJune 25, 2011http://guides.lib.usf.edu/informedstaffing

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Lily Todorinova, University of South Florida

Andy Huse, University of South Florida

Barbara Lewis, University of South Florida

Matt Torrence, University of South Florida

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University of South Florida

Campuses: Tampa, St. Petersburg, Sarasota, LakelandStudent Population: (Tampa): approx. 40,000Profile: Urban, Undergraduate, High Research Activity

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The Libraries

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Re-Envisioning Public Services

• Context for the project: 2010, Inter-departmental

• History of the Learning Commons

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Assessment

• Tally sheets and/or "clickers"o Sample days throughout the semester

• Experimentation & anecdotal information

• Aeon

• Desktracker

 

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Recommendations

• 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

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Virtual Reference: The Solution

• Started with email in 1999

• Moved to, from, and back to collaborative serviceso TBLC Statewide

• Chat and text serviceso Supplement, or replacement?

• The future...?

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Management Decision-making

• Decision-making literature

• Structured interviewso Past, present, & future data collections

What? How? Why?

o Decision-making process What types of decisions? How was it done? How do you want to do it? What type of data do you need?

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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.

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Results in Academic Services

• Changes in daily schedulingo Down to one librarian/GA for slower timeso Modifications to evening coverage (TBLC chat help)o On-call hours

• Changes to weekend schedulingo Librarian shift moved to Sunday evenings (4-8pm)o Email and chat coverage on Saturdays

• Increased focus on consultationso Workshopso Research Rescueo Individual sessions

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Conclusions and the Future

• Knowledge Tracker

• Systematized referral process

• Cross-informational training between service points

http://guides.lib.usf.edu/informedstaffing