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Service quality

Service quality. Unit 11 & Chapter 6. Ever wonder what 99.9% meant?. Is a goal of 99.9% good enough? 1 hour of unsafe drinking water every month 2 unsafe plane landings per day at O’Hare Airport in Chicago 16,000 pieces of mail lost by the U.S. Post Office every hour.

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Service quality

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  1. Service quality Unit 11 & Chapter 6

  2. Ever wonder what 99.9% meant? Is a goal of 99.9% good enough? 1 hour of unsafe drinking water every month 2 unsafe plane landings per day at O’Hare Airport in Chicago 16,000 pieces of mail lost by the U.S. Post Office every hour.

  3. Ever wonder what 99.9% meant? 20,000 incorrect prescriptions every year 500 incorrect operations each week 50 babies dropped at birth every day 22,000 checks deducted from the wrong bank account each hour 32,000 missed heart beats per person each year

  4. What is Service Quality? • Identify a “quality” service • Discuss why it is high quality

  5. Garvin’s 8 Dimensions of Quality • Performance • features • Reliability • Conformance • Durability • Serviceability • Aesthetics • Perceived Quality

  6. Schonberger’s Additional 4 Dimensions of Quality • Quick Response • Quick change expertise • Humanity • Value

  7. Quality toolbox (no shortage of topics for MGT 667) 1992 Baldrige winner’s Texas Instruments DSEG (now Raytheon TI Systems)

  8. Quality Management Tool Box Complexity Process Mapping, Design for Manufacturability & assembly, Root cause analysis, FMEA, Fault trees, Quality Function Deployment, Focused factories, Group technology, Smart simple design, 5s, visual systems Culture Quality awareness, Teams, Autonomous work groups, Baldrige quality award, ISO 9000, Deming, PDCA, Policy Deployment (Hoshin Kanri), Supplier Mgt & certification, Six sigma, Metrics/scorecards/ dashboards, Benchmarking, JIT/Lean mfg. Corrective action program, Kaizen events, Total Productive Maintenance (TPM), cost of quality, zero defects, ISO1400, EMS, Servqual (gap analysis) VariationSPC (control charts), Process capability (Cpk), Design of Experiments, Taguchi, acceptance sampling, Gauge R&R, other statistical tools Mistakes mistake-proofing (poka-yoke), Just culture, Standardization Ergonomics, Human factors engineering

  9. Mistake-proofing tool flowchart

  10. Best thinking on Service Quality:

  11. Service Quality Model • Financial Services -- focus group based • A.K.A. Gap Analysis, SERVQUAL • Compares customer perceptions with customer expectations (Gap #5) • Gap #5 = function of Gaps #1, #2, #3, #4 Here’s how the looks...

  12. Word-of-mouth communications Personal needs Past Experience Expected service Gap #5 Perceived Service provider Gap #4 External Communication to Customers Service Delivery Gap #3 Gap #1 Service Quality Specifications Gap #2 Management Perceptions of Customer Expectations customer

  13. GAPS #1 and #2 Gap #1: Lack of market research Inadequate upward communication Too many levels of management Gap #2: Inadequate management communication of service quality Perception of infeasibility Inadequate task standardization Absence of goal setting

  14. GAPS #3 and #4 Gap #3: 1) Role ambiguity and conflict 2) Poor employee or technology job fit 3) inappropriate control systems 4) Lack of perceived control 5) Lack of teamwork Gap #4: 1) Inadequate horizontal communication 2) Propensity to overpromise

  15. Change the design by mistake-proofing Mistake-proofing is the use of process design features to facilitate correct actions, prevent simple errors, or mitigate the negative impact of errors.

  16. Change the design by mistake-proofing

  17. If it is worthwhile to mistake-proof yo-yos… …What else would it be worth mistake-proofing?

  18. Exercise: Can you think of examples of mistake-proofing in your car?

  19. 1998, John R. Grout Applications to Services • Server and customer errors impact service quality and must be managed • Focus on “front-office” customer interaction • “Back-office” important but more similar to manufacturing Source: make your service fail-safe. Chase, R. B., And D. M. Stewart. 1994. Sloan management review (spring): 35-44. 1/3 of customer complaints relate to problems caused by the customer themselves

  20. Server Poka-yokes Task Treatment Tangibles • Task poka-yokes: • Doing work incorrectly, not requested, wrong order, too slowly • Treatment poka-yokes: • Lack of courteous, professional behavior • Tangible poka-yokes: • Errors in physical elements of service

  21. Examples Task Treatment Tangibles • Task poka-yokes: • Cash register buttons labeled by item (instead of price) • Tags to indicate order of arrival • Treatment poka-yokes: • Bell on shop door • Record eye color on bank transaction form (insure eye contact) • Tangible poka-yokes: • Paper strips around towels (indicate clean linens) • Envelope windows

  22. Preparation Encounter Resolution Customer Poka-yokes • Preparation poka-yokes: • Failure to bring necessary materials, understand role, or engage correct service • Encounter poka-yokes: • Inattention, misunderstanding, or memory lapses • Resolution poka-yokes: • Failure to signal service failure, provide feedback, learn what to expect

  23. Examples Preparation Encounter • Preparation poka-yokes: • Appointment reminder calls • Student degree requirement checklist • Encounter poka-yokes: • Height bar in amusement park • ATM using card swipe instead of insertion • Resolution poka-yokes: • Provide premium for completed survey Resolution

  24. Have you ever… • Shot a rifle? • Played darts? • Shot a round of golf? • Played basketball? Emmett Jake Who is the better shot?

  25. Even very rare outcomes are possible (probability > 0) Even very rare outcomes are possible (probability > 0) Fewer in the “tails” (upper) Fewer in the “tails” (lower) Most outcomes occur in the middle Variability The world tends to be bell-shaped

  26. Variability Here is why: Even outcomes that are equally likely (like dice), when you add them up, become bell shaped

  27. “Normal” bell shaped curve Add up about 30 of most things and you start to be “normal” Normal distributions are divide up into 3 standard deviations on each side of the mean Once your that, you know a lot about what is going on ? And that is what a standard deviation is good for

  28. Setting up control charts:Calculating the limits • Find A2 on table (A2 times R estimates 3σ) • Use formula to find limits for x-bar chart: • Use formulas to find limits for R chart:

  29. Lots of other charts exist

  30. Limits • Process and Control limits: • Statistical • Process limits are used for individual items • Control limits are used with averages • Limits = μ ± 3σ • Define usual (common causes) & unusual (special causes) • Specification limits: • Engineered • Limits = target ± tolerance • Define acceptable & unacceptable

  31. Process capability (Cpk) Good quality: defects are rare (Cpk>1) μ target Poor quality: defects are common (Cpk<1) μ target Cpk measures “Process Capability” If process limits and control limits are at the same location, Cpk = 1. Cpk≥ 2 is exceptional.

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