Toward Evidence-Based Collection Management

Crawford, S. & Syme, F. (2018). Enhancing Collection Development with Big Data Analytics. Public Library Quarterly, 37(4), 387-393. DOI: 10.1080/01616846.2018.1514922

Summary
The article looks at ways for libraries to develop their collections more efficiently by using evidence-based decision making (or EBSM, Evidence-Based Stock Management) and appropriate software to mine the structured, semi-structured and unstructured data they store on patron information behavior. If Ranganathan’s fifth law of library science holds true, it stands to reason that we speak about libraries as if they are indeed alive; we grow collections, we analyze their performance, we develop them, we lovingly weed them. To take the metaphor further, Crawford and Syme reference an interesting new metric: DOA. This term refers to the number of new items a library adds to its collection that never check out, never circulate, and are, in fact, Dead On Arrival. The authors point out the waste that this phenomenon portends in a paradigm of decreasing budgets. They argue that evidence-based selection planning using Big Data can help tackle the problem of DOA by using “predictive analytics to help staff select material that meets patron demand by consulting a number of data sources including evidence from collectionHQ (their collection management software), an author’s past performance, BISAC (Book Industry Standards and Communications) Subject performance, how an author has performed in a particular BISAC Subject Group, reviews on a title, demand, and many more” (p. 388-389). They then go into four interesting case studies to further illustrate their overall point: use of evidence-based management and selection tools keep libraries on the “right path to increased circulation, improved turnover, and enhanced customer satisfaction” (p. 392).

Commentary
I agree that evidence-based decision making is just good policy. Most libraries are not blessed with large endowments or perpetually increasing budgets, facts which therefore necessitate choices and trade-offs. Sound understandings of the patron base and ever-changing demand patterns are foundational to any decisions library staff might be called upon to make. Choosing appropriate books that will not end up DOA, and then using the data available to track, market, and measure the performance of the collection will hopefully lead libraries further down the “right path.”

Note: Crawford is Vice President and General Manager at collectionHQ and Syme is a Marketing Manager there. Not surprisingly, the article comes across with heavy bias toward the collection HQ software.

Enhancing Collection Development with Big Data Analytics

Peterson, Joy

Citation:

Crawford, S., & Syme, F. (2018). Enhancing collection development with big data analytics. Public Library Quarterly,37(4), 387-393. doi:10.1080/01616846.2018.1514922

Descriptive Summary:

Many professional organizations now use Big Data to analyze their operations and make evidence-based decisions. This article discusses the ways that libraries can use Big Data software to analyze collections and make decisions to purchase materials based on that supporting data. 

Evaluation: 

I think the use of analytics for collection development and management is an area that needs strong consideration.  While this article needs to be taken with a grain of salt, primarily because its authors are employees of the company that makes the analytical software highlighted in this study, collectionHQ, their claims are indeed valid.  

By actually tracking what is being circulated in a library system, collection managers can better anticipate the needs and interests of their patrons.  This will help increase future circulation and help eliminate what the authors call Dead on Arrival (DOA) publications, which are items that are never circulated once purchased.  The real issue here, however, is getting libraries to see the benefit of using analytics. 

Furthermore, libraries will then need to train their staff to develop analytical metrics that can be interpreted and incorporated into the collection development process.  My fear is that this kind of analytical rigor is not something that can be self-taught.  Ideally, a class in circulation analytics could be introduced into the current MS-level curriculum.  Regardless, this was a very interesting approach that I think will continue to gain traction among collection developers.

Research Data Needs from Academic Libraries: The Perspective of a Faculty Researcher

Guzman, Laura
Fall 2016

Keil, D. E. (2014). Research data needs from academic libraries: The perspective of a faculty researcher. Journal of Library Administration, 54(3), 233-240.

Summary:

In this article a faculty researcher explains what she ideally would like from a modern university library.  Keil (2014) starts the article by talking about how her work has been easier since she no longer needs to haul heavy journals to her office to do research.  She can find everything she needs for her research on the databases.  Despite this convenience, Keil says that she has come to realize that libraries are much more than just a source for books and journal subscriptions.

The rest of the article centers around the growing phenomenon of “big data.” Keil says that faculty researchers have a growing problem of managing, preserving, and sharing their data.  She would love for university libraries to assist in this process.  She encourages libraries to partner with researchers in order to deposit this raw data into manageable repositories.  More funding agencies are requiring that raw data be available via open access.  The emerging trend requires raw data to be included with the manuscript for medical journal submission.  This data can be linked in online appendices to data repositories supported by the journal or an academic library.

Kiel believes that a large part of future academic libraries should be involvement with “big data.” She urges more university libraries to “step it up” and help faculty researchers with this issue.  She says that valuable data is being left behind. 

Evaluation: 

I agree that we are moving past the era where libraries primarily collect articles and books for faculty.  "Big data" is a new area of information and it will only continue to grow as the Internet and research grows.  It would be ideal for all academic libraries to study the areas of linked data, digital repositories, and scholarly communication.