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Can (John) Saygin, Ph.D. Assistant Vice President for Sponsored Project Administration Office of the Vice President for Research Professor, College of.

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Presentation on theme: "Can (John) Saygin, Ph.D. Assistant Vice President for Sponsored Project Administration Office of the Vice President for Research Professor, College of."— Presentation transcript:

1 Can (John) Saygin, Ph.D. Assistant Vice President for Sponsored Project Administration Office of the Vice President for Research Professor, College of Engineering Center for Advanced Manufacturing and Lean Systems Phone: 210.458.5194 can.saygin@utsa.edu Metrics: The Good, The Bad, and The Ugly

2 Outline Lean: What does it mean? IOM 2013 Report From Data to Metrics Success Stories of Lean We want to hear from you

3 LEAN

4 LEAN: SEE WASTE and ELIMINATE IT Waste (Non-Value Added): Anything that adds cost, time, effort without adding value Waiting Over-Production Defects Motion Wastes Inventory Transport Under- Utilization of Human Talent Over-Processing DEFINE VALUE!!!

5 HOW DO YOU MEASURE WASTE? Metric: a standard of measurement Performance Metric: Standards of measurement by which efficiency, performance, progress, or quality of a plan, process, or product can be assessed. Deviation  |Actual| - |Target|

6 LEAN METRICS Lean Metrics – the appropriate measurements and goals for the Lean Improvement activities Commonly used Time-based Lean Metrics Individual Cycle Time Total Cycle Time Queue Time Total non-time based metrics, such as: cost, customer satisfaction, on-time delivery, and quality. And many more…

7 TRAP… “averages”

8 "If you can't describe what you are doing as a process, you don't know what you are doing." PROCESS… FLOW - W. Edwards Deming

9 DEFINE-MEASURE-ANALYZE-IMPROVE-CONTROL DMAIC must be a “continuous process” Define the system, the voice of the customer and their requirements, and the project goals, specifically. Measure key aspects of the current process and collect relevant data, including controllable and uncontrollable factors. Analyze the data to investigate and verify cause-and-effect relationships. Determine what the relationships are, and attempt to ensure that all factors have been considered. Seek out root cause of the defect under investigation. Improve the current process based upon data analysis using techniques: Future process Control the future state process to ensure that any deviations from target are corrected before they result in defects. Implement control systems and continuously monitor the process. METRICS

10 To successfully use lean metrics: – Standardize measurements Make sure the results are accurate and consistent – Metrics should be easy to collect Gather data where it is most useful – Make the Lean Metric Visual Make information accessible Goal: Predictable Output – Stable Output is more important than spikes of outstanding performance 10 Success with Lean Metrics

11 Process Design & Improvement Process Flow Validation Process Flow Automation Do the Right Thing Do it Right Do it Better EFFECTIVENESS (Performance directly linked to Desired Outcomes) EFFICIENCY (Rate of Desired Outcomes) WHATHOW Continuous Improvement: A Mindset 11 Operational Performance Metrics Programmatic Performance Metrics

12 Eliminate Whenever Possible 12 PoliciesFunctionsProcesses Laws, Regulations, Rules at various levels 5 Why’s… Do not target the symptoms Get to the Root-Cause

13 INSTITUTE OF MEDICINE 2013 Report

14 IOM Report (2013)

15 Mission, Vision, Goals

16 Complexity, Inconsistency, Cost

17 “Learning Health Care System” Continuous Improvement CTSA 2.0 Additional Complexity: Network (12 sites in 2006 to 61 sites in 2013)

18 Lack of… Metrics

19 IOM 2013 Report – Page 8

20 Learning Healthcare System

21 Lean Enterprise

22 Are they different?

23 Where to Start?

24 Lean in IOM 2013 – Page 67

25 Evaluation -- Page 81

26 Evaluation Individual CTSAs (pp.82-83)

27 15 Metrics (Page 84)

28 June 2013 Meeting

29 Programmatic Performance Metrics Operational Performance Metrics

30 FROM DATA TO METRICS

31 “In God we trust… All others, bring data.” W. Edwards Deming

32 Reference: "Data, Information, Knowledge, and Wisdom" by Gene Bellinger, Durval Castro, Anthony Mills Data represents a fact or statement of event without relation to other things. Information embodies the understanding of a relationship of some sort, possibly cause and effect. Knowledge represents a pattern that connects and generally provides a high level of predictability as to what is described or what will happen next. A) It is raining. B) The temperature dropped 15 degrees and then it started raining. C) If the humidity is very high and the temperature drops substantially the atmospheres is often unlikely to be able to hold the moisture so it rains.

33 The Big Picture Reference: "Data, Information, Knowledge, and Wisdom" by Gene Bellinger, Durval Castro, Anthony Mills

34 Where to focus when determining metrics…

35 Actionable Information… Not just data

36 Tools: Data Collection, Analysis,…

37 Job by itself…

38 Myopic Nature: Single Metric!!!

39 Interpretation leads to action…

40 Stakeholders

41 Simple

42 Source: Source -- http://www.juiceanalytics.com/writing/choosing-right-metric/http://www.juiceanalytics.com/writing/choosing-right-metric/

43 An Example from UTSA Human Resources… SUCCESS STORIES OF LEAN An Example from UTSA Human Resources…

44 http://camls.utsa.edu/

45 HR at UTSA Background Human Resource (HR) managing “On-Boarding Process” of new hires – Orientation, tax and insurance paperwork, computer and email accounts, requests for keys, telephone line, parking, etc. Problems: – New hires often take 2 weeks to be truly “on-board” – HR team spends hours on missing data & error corrections everyday – Lots of “waiting” among offices You are hired!

46 Objectives: Shorten new hire time Improve work readiness Increase compliance Methodology: Lean training for entire office Value stream mapping and implementation planning The Improvement Project HR at UTSA

47 Root Causes Disconnected operations Isolated resources Ineffective (error prone) paperwork process Solutions Redesigned workflow (new “value stream map”) Partners with OIT, ID Card Office, Parking, etc. Standardized web forms The Findings HR at UTSA

48 New process provides integrated resources at the Orientation for New Employees New hires are ready on Day 2 versus 2 Weeks 100% accuracy of I-9’s $231,319 net savings in 1 st year The Results HR at UTSA

49 IT IS TIME TO HEAR FROM YOU…

50 Think of processes or functions that you perform… Write on a piece of paper: The Good: You are comfortable with it. You do it well. The Bad: You are not comfortable with it. However, you work so hard and you get it done. The Ugly: You are not comfortable with it. Your performance varies when doing it. Do it yourself

51 Discuss as a team and compile your notes on a large sticky paper Do it as a team… Good Bad Ugly

52 Can (John) Saygin, Ph.D. Assistant Vice President for Sponsored Project Administration Office of the Vice President for Research Professor, College of Engineering Center for Advanced Manufacturing and Lean Systems Phone: 210.458.5194 can.saygin@utsa.edu Any questions, comments

53

54 As an Engineer…


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