AALL Spectrum

AALL Spectrum / September/October 2018 / Volume 23, Number 1

AALL Spectrum / Published by American Association of Law Libraries

Issue link: http://epubs.aallnet.org/i/1016225

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SEPTEMBER/OCTOBER 2018 | AALL SPECTRUM 21 Data analytics offer benefits for all law libraries by providing both broad and detailed views of operations and areas where productivity has grown or lagged. The challenge is finding a system that tracks work, provides useful measurements for managers, and is easy to use (i.e., a system that does almost everything that we need). There are many ways to track the number of questions your library receives (including those paper tick marks), but today's sophisticated online tracking systems provide so much more. The trick to selecting the right system is to first identify your needs and then prioritize them. This determines the data you should collect and will help you select a system that will meet most of those needs. What Is a Reference Tracking System? Reference tracking systems are usu- ally web-based systems that manage and store research requests in a single location. A requestor simply sends an email to the library request address and the tracking system automatically creates a request ticket (phone calls and in-person requests may be manu- ally added). Depending on the request, one or more researchers can add them- selves to the ticket as the assignee(s). The assignee then responds to the request from within the system, includ- ing acknowledging the request, asking for more information, or sending the research results to the requestor. Ideally, the system records all interac- tions related to the ticket, including the requestor's and assignee's names, the date of the request, the comple- tion date, and the time worked, and it stores or links to the work product. These systems also provide preset reports, graphs, and other data visu- alizations that help with analyzing the data on the back end. Some systems also allow you to create custom reports for more flexibility. However, almost all systems allow you to export the data into other formats for use in spread- sheets and data visualization tools, such as Tableau. How Can Reference Data Be Used? Reference tracking systems can improve management of workload by produc- ing meaningful data about user needs, FIGURE 1: NUMBER OF RESEARCH REQUESTS (2014-2017). 2014 2015 2016 2017 which can then be analyzed to identify trends and patterns. They also serve as a repository of easily accessible, completed requests. Here are just a few examples of how we use our ref- erence tracking systems to help with decision-making: To ensure adequate staffing: At Sidley's library, we discovered spikes in the number of requests during the last 10 minutes of the workday in each time zone, which explained why we had some difficulty providing adequate staffing in the late after- noons. Based on this data, we created an extra shift to help cover this time period, which has greatly improved our ability to manage our late after- noon work. To better understand how our work has changed: At Sidley, the number of research requests has steadily risen over the last four years (see Figure 1). We also receive increasingly compli- cated requests, as indicated by the number of hours spent per request and the type of requests received. This data gave us a much more holis- tic view of the work we do (especially when compared to a simple count of the number of requests received). To pinpoint inefficiencies: At the University of California, Irvine (UCI) School of Law Library, we use our tracking system to identify projects we should delegate to lower-cost employ- ees, such as faculty research assistants. For example, we are currently track- ing the frequency of and time spent on 50-state survey requests. To identify training opportunities: The bubble graph image on the fol- lowing page (Figure 2) displays the requests handled by three different researchers. The color of each bubble represents a different type of request, such as document delivery, case law research, company profiles, securities research, etc. The size of each bubble represents the number of requests taken. Depending on the overall

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