Data-Driven Decision Making: An Holistic Approach to Assessment in Special Collections Repositories

Abstract

Objective – In an environment of shrinking budgets and reduced staffing, this study seeks to identify a comprehensive, integrated assessment strategy to better focus diminished resources within special collections repositories.

Methods – This article presents the results of a single case study conducted in the Special and Digital Collections department at a university library. The department created an holistic assessment model, taking into account both public and technical services, to explore inter-related questions affecting both day-to-day operations as well as long-term, strategic priorities.

Results – Data from a variety of assessment activities positively impacted the department’s practices, informing decisions made about staff skill sets, training, and scheduling; outreach activities; and prioritizing technical services. The results provide a comprehensive view of both patron and department needs, allowing for a wide variety of improvements and changes in staffing practices, all driven by data rather than anecdotal evidence.

Conclusion – Although the data generated for this study is institutionally specific, the methodology is applicable to special collections departments at other institutions. A systemic, holistic approach to assessment in special collections departments enables the implementation of operational efficiencies. It also provides data that allows the department to document its value to university-wide stakeholders.