OCLC Resource Sharing Conference 2019

Hear more from the panel about how statistics are making a difference in their libraries' ILL departments.

We would like to describe a method of tracking interlibrary loan transactions using the MyMap feature of Google Maps. With this tool, we will be able to apply a series of filters on the map, such as the status of a patron, custom holding groups (such as USMAI, EAST, and AJCU libraries), Rapid pods, international libraries, request type, and time of delivery. This interactive data visualization tool can be used for outreach purposes as well as internal reporting. In this presentation, we will discuss the data visualization tools, techniques, and geographic information system mapping technology. Further, we will discuss any successes and issues we encountered and what we learned through the map filters.

Background: The Access and Delivery Services and Collection Development departments at the Cushing/Whitney Medical Library have a cooperative relationship in terms of incorporating statistical ILL data into collection decisions. Budget pressures resulting in journal cancellations have made the need for data-driven decision making more acute. A question arose as to how accurately ILL statistics for journals reflect scholars’ needs in relation to library collection building. Objective: The researchers hope to determine if borrowing statistics after the cancellation of a subscribed journal reflected the same level of use compared to prior to cancellation. Methods: The researchers gathered ILL borrowing statistics for a control list of titles cancelled in fiscal year 2017/2018 and analyzed them against COUNTER JR1 statistics for the same period of time to determine if interest in a journal remained consistent post-cancellation. Results: This study’s preliminary results indicate that ILL borrowing statistics are significantly lower than anticipated based on documented usage. These results indicate that potential users are not taking additional steps to obtain articles through ILL that the library no longer subscribes to. Outcome: Statistical data with no context cannot reliably capture user behavior and librarians should consider the incomplete nature of these metrics when anticipating user need.

After 20 years of saying no to any kind of interlibrary loan sharing, how do you convince a branch library to swing the pendulum in the opposite direction and say yes to interlibrary loan requests? What sort of information do you need to demonstrate to your librarians and library staff, that sharing your resources increases the use of your collection with little to no impact on your patrons? We did it, and we can show you how we gathered statistics and other compelling information to make our case.