Measure Up! Data Analytics and Libraries Alan Safer CSU Long Beach Alan.Safer@csulb.edu. Lesley Farmer CSU Long Beach Lesley.Farmer@csulb.edu 1 2 Does this sound familiar? I can’t get the articles I need! The catalog says the book is there, but I can’t find it. What does it take to get a new book on the shelf before it becomes old? No one uses our self-check out system. Should we subscribe to ebooks? Why isn’t online reference service used? 3 What data do you collect? 4 What data do you collect? Circulation figures Patron usage Facilities usage Computer usage Internet usage Reference consultations and fill Library guides/bibliographies use Instructional sessions Website hits (including tutorials) Database usage vs cost ILL processing and turnaround time Ordering, processing, cataloging, preservation, weeding workflow and time Ebook usage vs cost Library software usage vs cost Staff scheduling Equipment maintenance and repairs 5 What tools do you use to collect data? 6 What tools do you use to collect data? Surveys Web statistics Circulation statistics Interviews and interviews Observation LibQual / PibPAS Flowfinity Document collecting 7 What do you DO with that data? Descriptive statistics Analyze workflow for efficiency Reveal trends Benchmark efforts Control quality Do cost-benefit analysis Analyze student learning Optimize scheduling Optimize queuing 8 Techniques Correlation analysis (for relationship between continuous variables) Multiple Regression(continuous response variable), Logistic Regression(categorical response variable) Decision Trees Principle Components, Factor Analysis Hypothesis testing (paired tests, two sample tests, ANOVA) Chi-Square tests of independence (for relationship between categorical variables) 9 Graphs Box Plots Stem and Leaf Plots Histograms/Bar Graphs Pareto Charts Pie Charts Time Series Plot Outlier assessment 10 How do the data connect with your library’s goals? The Answer May Be Data Analytics >> Decisions Y= f (X) To get results, should we focus our behavior on the Y or X ? • • • • • • • Y Dependent Output Effect Symptom Monitor Response • • • • • • • X1 . . . XN Independent Input-Process Cause Problem Control Factor Why should we test or inspect Y, if we know this relationship? Basic Implementation Roadmap Identify Customer Requirements Understand and Define Entire Value Streams Vision (Strategic Business Plan) Deploy Key Business Objectives - Measure and target (metrics) - Align and involve all employees - Develop and motivate Continuous Improvement (DMAIC) Define, Measure, Analyze, Improve Identify root causes, prioritize, eliminate waste, make things flow and pulled by customers Control -Sustain Improvement -Drive Towards Perfection 13 14 Case Study: Arizona State University Study ILL article borrowing process Why: improve service to meet increased demand Drivers: customer expectations, cost reduction, leverage technology Personnel: leadership, staff involvement Voyles, J. F., Dols, L., & Knight, E. (2009). Interlibrary Loan Meets Six Sigma: The University of Arizona Library's Success Applying Process Improvement. Journal Of Interlibrary Loan, Document Delivery & Electronic Reserves, 19(1), 75-94. 15 Define Phase Reduce costs Focus on articles (many processes possible) ID customer expectations relative to turnaround time, scan quality, priority value Fill 80% of article requests within 3 days Premise: no additional staff or $ 16 Measure Phase Current process capabilities through flow charts, performance matrixes, data collection sheets 17 18 Analyze Phase ID root causes of problems in order to eliminate or reduce them Tools: fishbone diagram, histogram, Pareto chart, XmR chart 19 20 21 Improve Phase Cause: variations and delays in searching and delivery on evenings/weekends Cause: lack of lender staff evenings/weekends Cause: Choosing right ISSN Lags in searching difficult requests Pilot/evaluate cost, support solutions based on impact, 23 Implemented Solutions Use downtime of other evening/weekend staff Replace student workers with FT/temp staff Add staff hours on evenings/weekends Train Schedule search requests Encourage other libraries to increase evening/weekend staff, and use ODYSSEY 24 Control Phase New quality standards Responsibility/timeline for implementation Method to measure user satisfaction Methods to measure process control and capability Progress reports 25 26 Lessons Learned Increased cost for document supplier wasn’t worth it Saved $2/request (even with more requests) Use ILL system that tracks detailed data including processing steps Get monthly data summary 27 Over to You… Areas for improvement? Ways to incorporate data analytics? And who are good data analytics partners? Readings 28 Agrawal, P. (2011). Application of ‘Six Sigma' in libraries for enhancing service quality. Intl. Journal of Information Dissemination & Technology, 1(4). Bentley, W. (2010). Lean six sigma secrets for the CIO. Boca Raton, FL: CRC Press. Biranvand, A., & Khasseh, A. (2013). Evaluating the service quality in the Regional Information Center for Science and Technology using the Six Sigma methodology. Library Management, 34(1/2), 56-67. Chapman, J., & Lown, C. (2010). Practical ways to promote and support collaborative data analysis projects. Code4lib, 12, 12-21. Delaware Division of Libraries. (2006). Library success: A celebration of library innovation, adaptation & problem solving, 149-153. Dong-Suk, K. (2006). A study on introducing six sigma theory in the library for service competitiveness enhancement. IFLA Conference Proceedings, 1-16. Huber, J. (2011). Lean library management. New York: Neal-Schuman. Jain, M. (2009). Delivering successful projects with TSP and Six Sigma. Boca Raton, FL: CRC Press. Jankowski, J. (2013). Successful Implementation of Six Sigma to Schedule Student Staffing for Circulation Service Desks. Journal Of Access Services, 10(4), 197-216. Kastelic, M., & Peer, P. (2012). Managing IT services: Aligning best practice with a quality method. Organizacija, 45(1), 31-37. Kumi, S., & Morrow, J. (2006). Improving self service the Six Sigma way at Newcastle University Library. Program: Electronic Library & Information Systems, 40(2), 123-136. Kucsak, M. (2012). Bringing Six Sigma to the Library. Library Faculty Presentations & Publications (2012). http://works.bepress.com/michael_kucsak/7/ Lientz, B., & Rea, K. (2002). Achieve lasting process improvement:.New York: Academic Press. Murphy, S. (2009). Leveraging Lean Six Sigma to culture, nurture, and sustain assessment and change in the academic library environment. College & Research Libraries, 70(3), 215-225. Voyles, J. , Dols, L., & Knight, E. (2009). Interlibrary Loan Meets Six Sigma: The University of Arizona Library's Success Applying Process Improvement. Journal Of Interlibrary Loan, Document Delivery & Electronic Reserves, 19(1), 75-94. 29 Sample Data Analytics Tools 30 SIPOC chart 31 Balanced Scorecard 32 33 Decision Tree 34 Process Capacity Quality Control, 7th Edition by Douglas C. Montgomery. Copyright (c) 2012 John Wiley & Sons, Inc. Chapter 7 Actions taken to improve a process 35 Quality Control, 7th Edition by Douglas C. Montgomery. Copyright (c) 2012 John Wiley & Sons, Inc. Chapter 5 Control Chart Examples 1. 2. 3. 4. 5. 6. 7. Histogram or stem-and-leaf plot Check sheet Pareto chart Cause-and-effect diagram Defect concentration diagram Scatter diagram Control chart 36 37 Stem-and-Leaf Plot 38 Scatter Diagram 39 Defect Concentration Diagram 40 Failure Analysis Quality Control, 7th Edition by Douglas C. Montgomery. Copyright (c) 2012 John Wiley & Sons, Inc. Chapter 1 41 42 DMADV: for new projects Define design goals (client demands, library goals) Measure and identify CTQs (characteristics that are Critical To Quality): product capabilities, production process capability, risks Analyze to develop and design alternatives Design details (and optimize) Verify the design 43 Next Steps Let’s work together! Lesley.Farmer@csulb.edu Alan.Safer@csulb.edu Operational Excellence Methodology Plan Execute Identify Problem • • • • • • Strategic Link to Business Plan defined in Project Selection Process Defined Business Impact with Op Ex Champion support Structured Brainstorming at all organizational levels Cause and Effect Diagrams identifying critical factors Primary and Secondary Metrics defined and charted Multi-Level Pareto Charts to confirm project focus Practical Problem • • • • • • Develop a focused Problem Statement and Objective Develop a Process Map and/or FMEA Develop a Current State Map Identify the response variable(s) and how to measure them Analyze measurement system capability Assess the specification (Is one in place? Is it the right one?) Problem Definition • Characterize the response, look at the raw data • Abnormal? Other Clues? Mean or Variance problem? • Time Observation • Spaghetti Diagram • Takt Time • Future State Maps • Percent Loading • Standard Work Combination • Use Graphical Analysis, Multi-Vari, ANOVA and basic statistical tools to identify the likely families of variability Problem Solution • • • • • • • • • • • Problem Control Execute Plan Identify the likely X’s 5S • Set Up Time Reduction (SMED) Material Replenishment Systems Level Loading / Line Leveling Cell Design • Visual Controls Use Design of Experiments to find the critical few X’s Move the distribution; Shrink the spread; Confirm the results Mistake Proof the process (Poka-Yoke) Tolerance the process Measure the final capability Place appropriate process controls on the critical X’s • Document the effort and results • Standard Work • TPM Problem Solving What do you want to know? How do you want to see what it is that you need to know? What type of tool will generate what it is that you need to see? What type of data is required of the selected tool? Where can you get the required type of data? Based in part on Six Sigma Methodology developed by GE Medical Systems and Six Sigma Academy, Inc. Crane Co. Op. Ex. Methodology Originated by MBBs; D. Braasch, J. Davis, R. Duggins, J. O’Callaghan, R. Underwood, I. Wilson