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.
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.
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