LEADER 06504nam 22006252 450 001 9910795883603321 005 20230224105124.0 010 $a1-78330-522-3 010 $a1-78330-480-4 035 $a(MiAaPQ)EBC6680099 035 $a(Au-PeEL)EBL6680099 035 $a(CKB)21672950600041 035 $a(UkCbUP)CR9781783304806 035 $a(EXLCZ)9921672950600041 100 $a20220722d2022|||| uy| 0 101 0 $aeng 135 $aur||||||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aData-driven decisions $ea practical toolkit for librarians and information professionals /$fAmy Stubbing$b[electronic resource] 210 1$aLondon :$cFacet,$d2022. 215 $a1 online resource (xvi, 180 pages) $cdigital, PDF file(s) 300 $aTitle from publisher's bibliographic system (viewed on 04 Aug 2022). 311 08$aPrint version: Stubbing, Amy Data-Driven Decisions London : Facet Publishing,c2022 9781783304790 320 $aIncludes bibliographical references and index. 327 $aCover -- Praise for Data-Driven Decisions -- Title Page -- Copyright -- Dedication -- Contents -- Figures and Tables -- Contributors -- Acknowledgements -- Part 1: Background -- 1 Introduction -- About the author -- The wider context -- The what, the why and the where of the data-driven decision process -- The toolkit? -- Going further -- What will you get from this book? -- 2 Using the Toolkit -- Getting started -- Book layout -- The model -- A circular approach -- Part 2: The Toolkit -- 3 Step 1: Identify -- Introduction -- Data needs -- Data queries -- Data sources -- Time to practise -- Summary -- 4 Step 2: Collect -- Introduction -- Choosing your data -- Data collection methods -- Summary -- 5 Step 3: Map -- Introduction -- What is mapping? -- Making data comparable (normalising) -- Visualisation -- Creating a map of your data -- Summary -- 6 Step 4: Analyse -- Introduction -- What is analysis? -- Understand context -- Conclusions -- Summary -- 7 Step 5: Act -- Introduction -- What is the action step? -- Sharing data -- Planning actions -- Summary -- 8 Step 6: Review -- Introduction -- Why do we review? -- What do we review? -- How to review and questions to explore -- Make the changes -- What next? -- Part 3: Going Further -- 9 Moving from a Transactional to a Transformational Service Using Data -- Introduction -- Why lead with data? -- Transactional vs transformational work -- Data-led culture -- Data with compassion -- Case study -- 10 Collection Mapping for Collection Management -- Introduction -- Understanding your collection as a concept -- Collection mapping -- Conclusion -- 11 User Experience and Qualitative Data -- Introduction -- What is UX? -- Undertaking UX research in a library -- The UX techniques -- Ethics of research -- Recruiting participants -- Analysis -- Now write it up! -- What next? -- Words of caution. 327 $aThis is the beginning -- 12 Alternative Data Sources: Using Digital and Social Media to Inform Management Decisions in Your Library -- Introduction -- Libraries and social media -- Social media terminology and background -- What sort of data are we talking about? -- Data from social media marketing activity -- User engagement data and dialogue (outcomes measurement and evaluation) -- Service improvements and customer services -- Altmetrics -- Web-based analytics -- Summary -- 13 Starting from Scratch: Building a Data Culture at the University of Westminster -- Background -- Overnight opening case study -- Lessons learned and reflection -- 14 Back to the Drawing Board: How Data Visualisation Techniques Informed Service Delivery during the COVID-19 Pandemic -- Setting the scene -- Background -- Piktochart -- Power BI -- Case study: the pandemic -- Final thoughts -- Appendix -- Bibliography -- Index. 330 $aData-Driven Decisions: A Practical Toolkit for Library and Information Professionals is a simple, jargon-free guide to using data for decision making in library services. The book walks readers step-by-step through each stage of implementing, reviewing and embedding data-driven decisions in their organisation, providing accessible visualisations, top tips and downloadable tools to support readers on their data journey. Starting with the absolute basics of using data, the author creates a framework for building skills and knowledge slowly until the reader is comfortable with even complex uses of data.

The book begins with an exploration of the foundations of data-driven decisions in libraries including a look at the impact of the current financial climate on resources, theoretical foundations of data collection and analysis, and how this book can be used in practice. The next section takes readers through the data-driven decisions model, providing a guide for understanding and a manual for implementation of the model. Finally, the book provides further perspectives and reading surrounding analysis and implementation of data-driven decisions. This section aims to give supplementary and focused information on different areas of data-driven decisions which can be included in processes once the reader understands the foundation of the book from earlier chapters.

Highly practical and written in an accessible style, this book is an essential resource for librarians and information professionals who increasingly need to justify decisions on programmes and services through quantifiable data. 606 $aLibrary administration$xDecision making 606 $aInformation resources management$xDecision making 606 $aQuantitative research 606 $aData mining 606 $alibrary$9eng$2EUROVOC 606 $atext and data mining$9eng$2EUROVOC 606 $adecision-making$9eng$2EUROVOC 606 $adata processing$9eng$2EUROVOC 606 $adigital technology$9eng$2EUROVOC 615 0$aLibrary administration$xDecision making. 615 0$aInformation resources management$xDecision making. 615 0$aQuantitative research. 615 0$aData mining. 615 7$alibrary. 615 7$atext and data mining. 615 7$adecision-making. 615 7$adata processing. 615 7$adigital technology. 676 $a025.1 700 $aStubbing$b Amy$01530333 801 0$bUkCbUP 801 1$bUkCbUP 906 $aBOOK 912 $a9910795883603321 996 $aData-driven decisions$93775365 997 $aUNINA