Introduction to Statistical Quality Control, 5th edition
Download
Report
Transcript Introduction to Statistical Quality Control, 5th edition
Measure Up!
Data Analytics
and Libraries
Alan Safer CSU Long Beach
[email protected].
Lesley Farmer CSU Long Beach
[email protected]
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!
[email protected]
[email protected]
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