Description

Book Synopsis

This book shows how to act on and make sense of data in libraries. Using a range of techniques, tools and methodologies it explains how data can be used to help inform decision making at every level.

Sound data analytics is the foundation for making an evidence-based case for libraries, in addition to guiding myriad organizational decisions, from optimizing operations for efficiency to responding to community needs. Designed to be useful for beginners as well as those with a background in data, this book introduces the basics of a six point framework that can be applied to a variety of library settings for effective system based, data-driven management.


Library Improvement Through Data Analytics

includes:

the basics of statistical concepts

recommended data sources for various library functions and processes, and guidance for using census, university, or government 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 practical case studies, covering topics such as access and retrieval, digitization, e-book collection development, staffing, facilities, and instruction.

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



Trade Review
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

Table of Contents
PART I: OVERVIEW 1. Introduction 2. Planning with Six Sigma PART II: SIX SIGMA STEPS 3. Defining the Project 4. Measure the Current Situation 5. Analyze Existing Processes 6. Improve or Introduce the Process 7. Control the Process PART III: A STATISTICS PRIMER 8. Cleaning Data 9. Getting Started with Statistics 10. Matching Data Analytic Methods to Data 11. Statistical and Survey Software for Libraries PART IV: CASE STUDIES 12. Access and Retrieval: Case Study 13. Benchmarking Library Standards: Case Study 14. Data Sets: Case Study 15. Digitization: Case Study 16. Ebook Collection Development: Case Study 17. Facilities: Case Study 18. Information Audit: Case Study 19. Instruction: Case Study 20. Knowledge Management: Case Study 21. Lending Devices: Case Study 22. Marketing Virtual Reference Services: Case Study 23. Optimizing Online Use: Case Study 24. Reference Staffing Patterns: Case Study 25. True Costs of Acquisitions: Case Study with Implications for Selection Practice

Library Improvement through Data Analytics

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    A Paperback / softback by Lesley Farmer, Alan Safer

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      View other formats and editions of Library Improvement through Data Analytics by Lesley Farmer

      Publisher: Facet Publishing
      Publication Date: Publication Date: 31/07/2016
      ISBN13: 9781783301614, 978-1783301614
      ISBN10: 1783301619

      Description

      Book Synopsis

      This book shows how to act on and make sense of data in libraries. Using a range of techniques, tools and methodologies it explains how data can be used to help inform decision making at every level.

      Sound data analytics is the foundation for making an evidence-based case for libraries, in addition to guiding myriad organizational decisions, from optimizing operations for efficiency to responding to community needs. Designed to be useful for beginners as well as those with a background in data, this book introduces the basics of a six point framework that can be applied to a variety of library settings for effective system based, data-driven management.


      Library Improvement Through Data Analytics

      includes:

      the basics of statistical concepts

      recommended data sources for various library functions and processes, and guidance for using census, university, or government 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 practical case studies, covering topics such as access and retrieval, digitization, e-book collection development, staffing, facilities, and instruction.

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



      Trade Review
      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

      Table of Contents
      PART I: OVERVIEW 1. Introduction 2. Planning with Six Sigma PART II: SIX SIGMA STEPS 3. Defining the Project 4. Measure the Current Situation 5. Analyze Existing Processes 6. Improve or Introduce the Process 7. Control the Process PART III: A STATISTICS PRIMER 8. Cleaning Data 9. Getting Started with Statistics 10. Matching Data Analytic Methods to Data 11. Statistical and Survey Software for Libraries PART IV: CASE STUDIES 12. Access and Retrieval: Case Study 13. Benchmarking Library Standards: Case Study 14. Data Sets: Case Study 15. Digitization: Case Study 16. Ebook Collection Development: Case Study 17. Facilities: Case Study 18. Information Audit: Case Study 19. Instruction: Case Study 20. Knowledge Management: Case Study 21. Lending Devices: Case Study 22. Marketing Virtual Reference Services: Case Study 23. Optimizing Online Use: Case Study 24. Reference Staffing Patterns: Case Study 25. True Costs of Acquisitions: Case Study with Implications for Selection Practice

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