Allocating Academic Library Budgets: Adapting Historical Data Models at One University Library

Dinkins, Debbi

doi:10.1080/01462679.2011.554163

Cited by 7 publications

(1 citation statement)

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“…After their analysis, the study by Lyons and Blosser 5 excluded data on academic programs, monographic circulation, electronic resources usage, interlibrary loan, and dependency on format due to various shortcomings for each category. Dinkins 6 advocated use of historical allocation and usage data only to be as effective as more complicated, time-consuming, and complex data use allocation analysis.…”

Section: Literature Reviewmentioning

confidence: 99%

Ranking Data Outliers for Collection Budget Analysis: Allocating for the Future

Brown¹,

Galbraith²,

Dixon³

et al. 2019

Proceedings of the 2018 Library Assessment Conference: Building Effective, Sustainable, Practical Assessment: December 5–7, 201

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Finding an objective and reliable means of allocating annual collection development budgets is a perennial challenge in research libraries. Many libraries tend to rely on methodologies such as applying standard inflationary increases across all or some types of funds. These methods tend to maintain and perpetuate funding priorities from year to year. Changing campus needs, including new programs and curriculum, innovations in research methodologies and teaching, and new campus-wide strategic priorities constantly challenge us to overcome the collection allocation inertia that may set in if empirical data is not used to test budgetary assumptions and then allocate resources to meet changing priorities. Faced with new campus-wide priorities, including the launch of new academic programs and campus-wide multidisciplinary initiatives, as well as fiscal pressures, such as budget cuts for library materials and annual price inflation, the Binghamton University Libraries developed a system to analyze our collection budget and evaluate our budget allocation methodology using 17 data points. Our methodology involved comparing the rankings of program funds across data points and using disparity in rankings to identify programs that are potentially over-and underfunded. We began by gathering four fiscal years of data, 2013/14-2016/17, on all library supported programs. The data was drawn from internal library and campus data, and externally created cost information for monographs and journals. Library data included costs for monographs, journals, and databases as well as circulation and interlibrary loan data. Campus data included faculty FTE, degrees granted, number of students by level (undergraduate and graduate), and course hours by department or program. External data included average monograph cost and serials cost by subject area. Once the dataset was created, each data category was ranked from highest to lowest in value. Then, library budget rankings for monographs, journals, and databases were compared to the rankings of all data points. A summary sheet was compiled to determine programs with over-and underfunded indicators. The summary sheet also indicates trends over the budget years examined. By tallying the number of times a program was labelled as either "overfunded" or "underfunded" across the ranking comparisons, we identified programs that should be examined as potentially over-and underfunded. Through this analysis and consideration of qualitative measures, such as a program's support of general education courses, interdisciplinary nature, and dependence on monographs or journals, we will be able to identify potential areas for reallocation of collections funds and better address anticipated campus curriculum and research needs. Background Founded in 1946 as a liberal arts college, Binghamton University has evolved into a highly ranked public doctoral research university. Serving 13,700 undergraduate students and 3,600 graduate students, the university boasts one of the highest retention (92% for freshmen) ...

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Section: Literature Reviewmentioning

confidence: 99%