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What is it?
Predictive Analytics is the ability of A.I. technology to predict outcomes based on previous experience data (Litsey & Mauldin, 2018). Static data is the type of data that is stored within the computer on spreadsheets for future analysis and is generally automatically generated by the system. If an A.I. were able to use predictive analytics to analyze this type of data, such as circulation data generated by a library’s ILS system, then the A.I. would be able to supervise all materials being circulated, predict patron behavior, and automatically order materials as necessary (Litsey & Mauldin, 2018).
Use Case: Texas Tech University Libraries
The Automated Library Information Exchange Network (ALIEN) is the first system of its kind to be developed for such a purpose, and is still in development. Systems like ALIEN hold the potential to improve patron services by predicting the books that will be requested in the future, and ordering them ahead of time to have them on the shelf before the patron wants or asks for them. This type of system would require an immense amount of metadata linking it with publisher’s records, popular book lists, and collected circulation behavior data in order to work accurately.
References
Litsey, & Mauldin, W. (2018). Knowing What the Patron Wants: Using Predictive Analytics to Transform Library Decision Making. The Journal of Academic Librarianship, 44(1), 140–144. https://doi.org/10.1016/j.acalib.2017.09.004
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