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Wilson Confidence, Skills, And Accepting that Good Enough is Good Enough

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This presentation was provided by Frankie Wilson of the Bodleian Library, University of Oxford, during the NISO Webinar, Using Analytics to Extract Value from the Library's Data, Part Two, held on September 19, 2018.

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Wilson Confidence, Skills, And Accepting that Good Enough is Good Enough

  1. 1. Getting started Confidence, skills, and accepting that good enough is good enough Frankie Wilson Head of Assessment & Secretariat
  2. 2. Presentation outline • Barriers to action • Skills needed • What success looks like • Get loud!
  3. 3. Barriers to action • Paralysis of perfection • Tools • Skills • Confidence • Time • Money
  4. 4. Paralysis of perfection • “Assessment Guru” • No such thing as perfect data • “Lies, damned lies and statistics” • Everything has a human element
  5. 5. Tools • Excel • Word • Survey tool (e.g. SurveyMonkey) • Post it notes • Paper and pens/pencils • A ‘critical friend’ • Questioning mind
  6. 6. Skills • Data cleaning • Graphs • Write questions • Ask “why?”
  7. 7. Time and Money • Does take time • Planning • Doing • Analysing • Thinking • Writing • Get’s quicker with practice • You can go a long way on $50
  8. 8. Skills: Data Cleaning • Are these numbers correct? • Apply your knowledge Branch Number of book loans Main Library 3758649 Law Library 2456 Medical Library 786910 History Library 643859 Psychology Library 424800 English Library 786910
  9. 9. Skills: Graphs • Pie chart
  10. 10. Skills: Graphs • Bar chart (always start at 0)
  11. 11. Skills: Graphs • Compound bar chart
  12. 12. Skills: Graphs • Component bar chart
  13. 13. Skills: Graphs • Line graph
  14. 14. Skills: Write questions • Find a book on how to write good questions (social science research methods). • Follow it.
  15. 15. Skills: Ask “why?” • Read responses to interviews / focus groups / free text questions. • Note things that strike you as interesting / surprising / odd. • Group data (tag / categorise) • Summarise the responses in each category. • Ask “why?” • Go back round again …
  16. 16. What success looks like • Good enough is good enough • Data analysis: • Purposeful • Useful • Actioned • What do you want to know? • Trustworthy
  17. 17. A note on terminology • Inputs – staff FTE • Processes – speed of re-shelving • Outputs – # e-journals • Customer satisfaction -    • Impact – effect of IS session on quality of referencing • Outcome – University score in REF • Return on Investment – £ economic benefit for every £ input • Value – support for learning • Worth – contribution to international reach of University • Quality -
  18. 18. “Everything that can be counted does not necessarily count; everything that counts cannot necessarily be counted” Albert Einstein
  19. 19. Trustworthy • Clear, unambigous question • Appropriate approach • How many? How often? When? Quantitative • Why? How? How do they feel? Qualitative • Appropriate data gathering method • Documented analysis
  20. 20. Get Loud! • Communicate results for action • Write with audience in mind • Close the loop • What action taken • Document learning • Improve with practice
  21. 21. Questions? • frankie.wilson@bodleian.ox.ac.uk • Out soon: “Putting Library Assessment Data to Work” Killick & Wilson (Facet) • @qualitydog

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