Library Improvement Through Data Analytics

Lesley S. J. Farmer
Dr. Alan M. Safer
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Item Number
978-0-8389-1425-0
Published
2016
Publisher
ALA Neal-Schuman
Pages
184
Width
6"
Height
9"
Format
Softcover
AP Categories
A
C
I
Samples

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  • Description
  • Table of Contents
  • About the authors
  • Reviews

"Show me your data!"

More than ever, funding agencies are looking for cost effectiveness. Sound data analytics is the foundation for making an evidence-based case for library programs, in addition to guiding myriad organizational decisions, from optimizing operations for efficiency to responding to community needs for customer satisfaction. Designed to be useful for novices as well as those with a background in data, this book introduces the basics of the Six Sigma framework as a model that can be applied to a variety of library settings. Helping readers make sense of data, this guide for system based, data-driven management covers such key topics as

 

  • the basics of statistical concepts;
  • recommended data sources for various library functions and processes, and guidance for using census, university, or chamber of commerce data in analysis;
  • techniques for cleaning data;
  • matching data to appropriate data analysis methods;
  • how to make descriptive statistics more powerful by spotlighting relationships;
  • 14 case studies which address such areas as digitization, e-book collection development, and reference; and
  • staffing, facilities, and instruction.

This book's clear, concise coverage will enable readers of every experience level to gain a better understanding of statistics in order to facilitate library improvement.

 

List of Tables and Figures

 

 

Part I    Overview


Chapter 1    Introduction
Chapter 2    Planning with Six Sigma

 

 

 

 

Part II        Six Sigma Steps


Chapter 3    Defining the Project
Chapter 4    Measure the Current Situation
Chapter 5    Analyze Existing Processes
Chapter 6    Improve or Introduce the Process
Chapter 7    Control the Process

 

 

 

 

Part III    A Statistics Primer


Chapter 8    Cleaning Data
Chapter 9    Getting Started with Statistics
Chapter 10    Matching Data Analytic Methods to Data
Chapter 11    Statistical and Survey Software for Libraries

 

 

 

 

Part IV    Case Studies


Chapter 12    Access and Retrieval: Case Study
Chapter 13    Benchmarking Library Standards: Case Study
Chapter 14    Data Sets: Case Study
Chapter 15    Digitization: Case Study
Chapter 16    Ebook Collection Development: Case Study
Chapter 17    Facilities: Case Study
Chapter 18    Information Audit: Case Study
Chapter 19    Instruction: Case Study
Chapter 20    Knowledge Management: Case Study
Chapter 21    Lending Devices: Case Study
Chapter 22    Marketing Virtual Reference Services: Case Study
Chapter 23    Optimizing Online Use: Case Study
Chapter 24    Reference Staffing Patterns: Case Study
Chapter 25    True Costs of Acquisitions: Case Study with Implications for Selection Practice

References
Bibliography
Other Useful Reading
About the Authors
Index

 

 

Lesley S. J. Farmer

Dr. Lesley S. J. Farmer, professor at California State University, Long Beach (CSULB), coordinates the Teacher Librarian Program and manages the CSU Information and Communication Technology (ICT) Literacy Project Literacy Project. She earned her MS in library science at the University of North Carolina, Chapel Hill, and received her doctorate in adult education from Temple University. Farmer has worked as a librarian in K–12 school settings as well as in public, special, and academic libraries. She chaired the Special Libraries Association’s Education Divisions and IFLA’s School Library Section. Farmer is a Fulbright scholar and has received national and international grants. She has also been honored with several professional association awards, including the Ken Haycock Award for Promoting Librarianship. Farmer’s research interests include ICT, media literacies, and data analytics. A frequent presenter and writer for the profession, Farmer has published three dozen professional books and more than two hundred professional book chapters and articles. She received the Special Libraries Association's 2023 Rose L. Vormelker Award, which recognizes mid-career members for teaching and mentorship.

Dr. Alan M. Safer

Dr. Alan M. Safer is a professor at California State University, Long Beach (CSULB) in the Department of Mathematics and Statistics. He received his PhD in Statistics from the University of Wyoming and his MS in Marketing Research from Southern Illinois University Edwardsville. He first came to CSULB as an assistant professor in 2000 and has been a full professor since 2010. Early in his career at the university, he created a MS degree in Applied Statistics and later a professional accelerated MS degree in Applied Statistics for industry students from companies such as Boeing, Raytheon, and Northrop Grumman. He served as the graduate advisor for 7 years, and in 2009 was awarded university advisor of the year at CSULB. Dr. Safer’s research has been very interdisciplinary; he has over 25 publications in diverse statistical areas such as finance, library science, marketing, health science, linguistics, and forensics. His primary statistical research focus is data mining and quality control. In 2012, he was appointed coordinator of a national conference on quality control sponsored by the American Statistical Association. In the last few years, Dr. Safer helped create the Orange County/Long Beach chapter of the American Statistical Association and served as its vice president.

“Farmer and Safer make the case for deliberate, rigorous use of data to evaluate library programs and procedures … While smaller libraries may not be able to use the Six Sigma Steps and Pearson correlations in their entirety, they can gain useful insight from this book on how to gather, clean, and analyze data in order to improve their processes, services, or facilities.”
— VOYA

“Data-driven decision-making is essential for effective library management in the 21st century. But the tools to develop that analysis are not readily available for library administrators. Library Improvement through Data Analytics is a practical guide with clear and detailed steps for applying Six Sigma, an effective model for targeted library improvement analysis. Applying this technique to library processes and programs can improve performance and productivity, reduce expenses and increase satisfaction of users and staff. The compelling case studies will support library administrators in deploying these important tools to make the case successfully for their libraries.”
—Susan Hildreth, Professor of Practice, UW ISchool

”Ideal for library administrators, assessment librarians, and those who are charged with communicating the library's significance. The short length and accessible language lends itself to readers with busy schedules."
— Library Journal

”Guides the reader through the world of statistics in a library-specific, nonintimidating manner. Staff members at any sized library who wish to see improvement in their processes should consider adding this volume to the collection."
— ARBA