BASIC DEFINITION OF QUALITY IN SERVICES:
Excellent quality = you would highly recommend this service
Good quality = you would recommend this service
Poor quality = you would not recommend using this service
Very poor quality = you would recommend against using this service
SERVICE SITUATIONS:
|
Auto brake job |
American Express Card |
One-day training seminar |
|
Executive search firm |
Catered wedding |
City police department |
|
Financial planning |
Computer repair |
Rock concert |
|
Used car sales |
Theme park |
Travel agent |
|
Landscaping |
U.S. Postal Service |
Interior decorating |
|
Federal Express |
State auto license bureau |
Car wash |
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Temporary office help agency |
Movie theater |
Airline |
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Public utility (elec. or gas) |
Nursing care |
Defense attorney |
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Trash pickup-city or private |
Dome stadium |
Dry cleaner |
|
U.S. Army combat unit |
Pre-school |
Accounting firm |
|
Pet grooming |
Gambling casino |
Bank checking account |
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Hospital emergency room |
Barber/beauty shop |
Mexican restaurant |
|
Purchasing dept. in mfg. firm |
Security service |
Newspaper |
|
Information systems department |
Photo developing |
Student copy service |
SPECIFIC SERVICE CHOSEN
EXPLAIN ALL OF YOUR ANSWERS — “YES” OR “NO” IS NOT ACCEPTABLE.
1. Is there a physical product involved? Which is dominant, the product or the service?
2. How unique or how standardized is the product and/or service from the same company from one time to the next?
3. Give three specific examples of characteristics of the product and/or service that would determine how well the quality of the service is rated.
4. Is the customer involved in the production and delivery of the service? How?
5. What is an example of (a) a critical defect, (b) a major defect, and (c) a minor defect?
6. Give two or more examples of the cost(s) of a defect for the company?
7. After the service is delivered, is corrective action possible? Is restitution possible?
8. Is service quality most affected by the contact employee, by technology, or by management? Explain your choice.
9. Is service quality the same as customer satisfaction?
What is SQC?
Statistical Quality Control (SQC)
The term used to describe the set of statistical tools used by quality professionals to evaluate organizational quality.
Statistical Quality Control (SQC)
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3 Categories of SQC
Statistical process control (SPC) inspecting a random sample of an output from process, within range and functioning properly
Descriptive statistics the mean, standard deviation, and range
Involve inspecting the output from a process
Quality characteristics are measured and charted
Helps identify in-process variations
Acceptance sampling used to randomly inspect a batch of goods to determine acceptance/rejection
Does not help to catch in-process problems
Statistical Quality Control (SQC)
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Sources of Variation
Variation exists in all processes.
Variation can be categorized as either:
Common or Random causes of variation
Random causes that we cannot identify
Unavoidable, i.e.; slight differences in process variables like diameter, weight, service time, temperature
Assignable causes of variation
Causes can be identified
Eliminate cause i.e.; poor employee training, worn tool, machine needing repair
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Descriptive Statistics
The Mean- measure of central tendency
The Range- difference between largest/smallest observations in a set of data
Standard Deviation measures the amount of data dispersion around mean
Distribution of Data shape
Normal or bell shaped or
Skewed
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Distribution of Data
Normal distributions
Skewed distribution
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SPC Methods-Developing Control Charts
Control Charts (aka process or QC charts) show sample data plotted on a graph with CL, UCL, and LCL
Control chart for variables are used to monitor characteristics that can be measured, e.g. length, weight, diameter, time
Control charts for attributes are used to monitor characteristics that have discrete values and can be counted, e.g. % defective, # of flaws in a shirt, etc.
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Setting Control Limits
Percentage of values under normal curve
Control limits balance risks like Type I error
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7
Control Charts for Variables
Use x-Bar and R-bar charts together
Used to monitor different variables
x-Bar and R-bar charts reveal different problems
What is the statistical control difference from one chart to the next?
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Control Charts for Variables
Use x-Bar charts to monitor the changes in the mean of a process (central tendencies)
Use R-bar charts to monitor the dispersion or variability of the process
System can show acceptable central tendencies but unacceptable variability
System can show acceptable variability but unacceptable central tendencies
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Constructing an x-Bar Chart: A quality control inspector at the Cocoa Fizz soft drink company has taken three samples with four observations each of the volume of bottles filled. If the standard deviation of the bottling operation is .2 ounces, use the below data to develop control charts with limits of 3 standard deviations for the 16 oz. bottling operation.
| Time 1 | Time 2 | Time 3 | |
| Observation 1 | 15.8 | 16.1 | 16.0 |
| Observation 2 | 16.0 | 16.0 | 15.9 |
| Observation 3 | 15.8 | 15.8 | 15.9 |
| Observation 4 | 15.9 | 15.9 | 15.8 |
| Sample means (X-bar) | 15.875 | 15.975 | 15.9 |
| Sample ranges (R) | 0.2 | 0.3 | 0.2 |
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Center line and control limit formulas
Solution and x-Bar Control Chart
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Control limits for±3σ limits:
Center line (x-double bar):
x-Bar Control Chart
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Control Chart for Range (R)
Center Line and Control Limit formulas:
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Factors for three sigma control limits
Factor for x-Chart
A2
D3
D4
2
1.88
0.00
3.27
3
1.02
0.00
2.57
4
0.73
0.00
2.28
5
0.58
0.00
2.11
6
0.48
0.00
2.00
7
0.42
0.08
1.92
8
0.37
0.14
1.86
9
0.34
0.18
1.82
10
0.31
0.22
1.78
11
0.29
0.26
1.74
12
0.27
0.28
1.72
13
0.25
0.31
1.69
14
0.24
0.33
1.67
15
0.22
0.35
1.65
Factors for R-Chart
Sample Size
(n)
R-Bar Control Chart
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Second Method for the x-Bar Chart Using R-bar & A2 Factor
Use this method, Control limits solution, when sigma for the process distribution is not known:
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Control Charts for Attributes –
P-Charts & C-Charts
Attributes are discrete events: yes/no or pass/fail
Use P-Charts for quality characteristics that are discrete and involve yes/no or good/bad decisions
Number of leaking caulking tubes in a box of 48
Number of broken eggs in a carton
Use C-Charts for discrete defects when there can be more than one defect per unit
Number of flaws or stains in a carpet sample cut from a production run
Number of complaints per customer at a hotel
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P-Chart Example: A production manager for a tire company has inspected the number of defective tires in five random samples with 20 tires in each sample. The table below shows the number of defective tires in each sample of 20 tires. Calculate the control limits.
| Sample | Number of Defective Tires | Number of Tires in each Sample | Proportion Defective |
| 1 | 3 | 20 | .15 |
| 2 | 2 | 20 | .10 |
| 3 | 1 | 20 | .05 |
| 4 | 2 | 20 | .10 |
| 5 | 2 | 20 | .05 |
| Total | 9 | 100 | .09 |
Solution:
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P-Charts are used when both the total sample size
and the number of defects can be computed
P- Control Chart
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C-Chart Example: The number of weekly customer complaints are monitored in a large hotel using a c-chart. Develop three sigma control limits using the data table below.
| Week | Number of Complaints |
| 1 | 3 |
| 2 | 2 |
| 3 | 3 |
| 4 | 1 |
| 5 | 3 |
| 6 | 3 |
| 7 | 2 |
| 8 | 1 |
| 9 | 3 |
| 10 | 1 |
| Total | 22 |
Solution:
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C-Charts are used when you can compute only
the number of defects but not the proportion
that is defective
C- Control Chart
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Process Capability
Product Specifications
Preset product or service dimensions, tolerances: bottle fill might be 16 oz. ±.2 oz. (15.8oz.-16.2oz.)
Based on how product is to be used or what the customer expects
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±6 Sigma versus ± 3 Sigma
In 1980’s, Motorola coined “six-sigma” to describe their higher quality efforts
Six-sigma quality standard is now a benchmark in many industries
Before design, marketing ensures customer product characteristics
Operations ensures that product design characteristics can be met by controlling materials and processes to 6σ levels
Other functions like finance and accounting use 6σ concepts to control all of their processes
PPM Defective for ±3σ versus ±6σ quality
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Acceptance Sampling
Defined: the third branch of SQC refers to the process of randomly inspecting a certain number of items from a lot or batch in order to decide whether to accept or reject the entire batch
Different from SPC because acceptance sampling is performed either before or after the process rather than during
Sampling before typically is done to supplier material
Sampling after involves sampling finished items before shipment or finished components prior to assembly
Used where inspection is expensive, volume is high, or inspection is destructive
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Acceptance Sampling Plans
Goal of Acceptance Sampling plans is to determine the criteria for acceptance or rejection based on:
Size of the lot (N)
Size of the sample (n)
Number of defects above which a lot will be rejected (c)
Level of confidence we wish to attain
There are single, double, and multiple sampling plans
Which one to use is based on cost involved, time consumed, and cost of passing on a defective item
Can be used on either variable or attribute measures, but more commonly used for attributes
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Implications for Managers
How much and how often to inspect?
Consider product cost and product volume
Consider process stability
Consider lot size
Where to inspect?
Inbound materials
Finished products
Prior to costly processing
Which tools to use?
Control charts are best used for in-process production
Acceptance sampling is best used for inbound/outbound; attribute measures
Control charts are easier to use for variable measures
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SQC in Services
Service Organizations have lagged behind manufacturers in the use of statistical quality control
Statistical measurements are required and it is more difficult to measure the quality of a service
Services produce more intangible products
Perceptions of quality are highly subjective
A way to deal with service quality is to devise quantifiable measurements of the service element
Check-in time at a hotel
Number of complaints received per month at a restaurant
Number of telephone rings before a call is answered
Acceptable control limits can be developed and charted
Statistical Quality Control (SQC)
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Defining Quality
Definition of quality is dependent on the people defining it
There is no single, universal definition of quality
“performance to standards”, “meeting customer’s needs”, “satisfying the customer”
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Defining Quality – 5 Definitions
1. Conformance to specifications
How well a product/service meet targets and tolerances defined by its designers.
2. Fitness for use
Evaluates performance for intended use
3. Value for price paid
Evaluation of usefulness vs. price paid
4. Support services
Quality of support after sale
5. Psychological
Ambiance, prestige, friendly staff
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Manufacturing Quality vs. Service Quality
Manufacturing focuses on tangible product features (can be seen, touched, directly managed)
Conformance
Performance
Reliability
Features
Durability
Serviceability
Service produce intangible products that must be experienced (cannot be seen or touched)
Intangible factors
Consistency
Responsiveness
Courtesy, friendliness
Promptness, timeliness
Atmosphere
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Cost of Quality
Quality affects all aspects of the organization
Quality has dramatic cost implications of:
Quality control costs (to achieve high quality)
Prevention costs
Appraisal costs
Quality failure costs (consequences of poor quality)
Internal failure costs
External failure costs
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Cost of Quality – 4 Categories
Early detection/prevention is less costly
(Could be by a factor of 10)
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Evolution of TQM – New Focus
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Reactive
Proactive
Quality Gurus
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TQM Philosophy
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TQM focuses on identifying quality problem root causes
Encompasses the entire organization
Involves the technical as well as people
Relies on seven basic concepts of
Customer focus
Continuous improvement
Employee empowerment
Use of quality tools
Product design
Process management
Managing supplier quality
TQM Philosophy Concepts
Focus on Customer
Identify and meet customer needs
Stay tuned to changing needs, e.g. fashion styles
Continuous Improvement
Continuous learning and problem solving, e.g. Kaizen, 6 sigma
Plan-Do-Study-Act (PDSA)
Benchmarking
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Ways of Improving Quality
Plan-Do-Study-Act Cycle (PDSA)
Also called the Deming Wheel after originator
Circular, never ending problem solving process or continuous improvement process
Seven Tools of Quality Control
Tools typically taught to problem solving teams
Quality Function Deployment (QFD)
Used to translate customer preferences to design
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PDSA Details
Plan
Evaluate current process
Collect procedures, data, identify problems
Develop an improvement plan, performance objectives
Do
Implement the plan – trial basis
Study
Collect data and evaluate against objectives
Act
Communicate the results from trial
If successful, implement new process
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PDSA Details – cont’d
Cycle is repeated
After act phase, start planning and repeat process
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TQM Philosophy Concepts – cont’d
Employee Empowerment
Empower all employees; external and internal customers
Team Approach
Teams formed around processes; 8-10 people
Meet weekly to analyze and solve problems
Use of Quality Tools
Ongoing training on analysis, assessment, and correction, & implementation tools
Studying practices at “best in class” companies
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Seven Tools of Quality Control
Cause-and-Effect Diagrams
Flowcharts
Checklists
Control Charts
Pareto Analysis
Histograms
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1. Cause-and-Effect Diagrams
Called Fishbone Diagram
Focused on solving identified quality problem
Used by quality control teams; brainstorming
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2. Flowcharts
Schematic diagram
Used to document the detailed steps in a process
Often the first step in Process Re-Engineering
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3. Checklist
Simple data check-off sheet
Designed to identify type of quality problems at each work station; per shift, per machine, per operator
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4. Control Charts
The UCL and LCL are calculated limits used to show when a process is in or out of control i.e.; weight, width, or volume
Key tool used in Statistical Process Control – Chap. 6
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5. Scatter Diagrams
A graph showing how two variables are related to one another
The greater the degree of correlation, the more linear are the observations
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6. Pareto Analysis
Technique that displays the degree of importance for each element
Named after the 19th century Italian economist; often called the 80-20 Rule
Principle is that quality problems are the result of only a few problems i.e.; 80% of problems are caused by 20% of causes
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7. Histograms
A chart that shows the frequency distribution of observed values of a variable (i.e.; service time
at a bank drive-up window)
Displays whether the distribution is symmetrical (normal) or skewed
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Reliability – Critical to Quality
Reliability is the probability that the product, service or part will function as expected
No product is 100% certain to function properly
Reliability is a probability function dependent on sub-parts or components
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Reliability; Critical to Quality – cont’d
Reliability of a system is the product of component reliabilities
RS = (R1) (R2) (R3) . . . (Rn)
RS = reliability of the product or system
R1 = reliability of the components 1 thru n
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Reliability; Critical to Quality – cont’d
Increase reliability by placing components in parallel
Parallel components allow system to operate if one or the other fails
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RS = R1 + (R2* Probability of needing 2nd component)
Process Management & Managing Supplier Quality
Quality products come from quality sources
Quality must be built into the process
Quality at the source is the belief that it is better to uncover source of quality problems and correct it
TQM extends to quality of product from company’s suppliers
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Quality Awards and Standards
Malcolm Baldrige National Quality Award (MBNQA)
The Deming Prize
ISO 9000 Certification
ISO 14000 Standards
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MBNQA- What Is It?
Award named after the former Secretary of Commerce – Regan Administration
Intended to reward and stimulate quality initiatives
Given to no more that two companies in each of three categories; manufacturing, service, and small business
Past winners; Motorola Corp., Xerox, FedEx, 3M, IBM, Ritz-Carlton
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MBNQA- Criteria
| # | Categories | Points |
| 1 | Leadership | 120 |
| 2 | Strategic Planning | 85 |
| 3 | Customer and Market Focus | 85 |
| 4 | Information and Analysis | 90 |
| 5 | Human Resource Focus | 85 |
| 6 | Process Management | 85 |
| 7 | Business Results | 450 |
| TOTAL POINTS | 1000 |
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Criteria represents Quality belongs to everyone!
And criteria promotes “continuous improvement”.
The Deming Prize
Given by the Union of Japanese Scientists and Engineers since 1951
Named after W. Edwards Deming who worked to improve Japanese quality after WWII
Not open to foreign companies until 1984
1989 – Florida P & L was first US company winner
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ISO Standards
ISO 9000 Standards: (1987)
Certification developed by International Organization for Standardization
Set of internationally recognized quality standards
Companies are periodically audited & certified
ISO 9000:2000 QMS – Fundamentals and
Standards
ISO 9001:2000 QMS – Requirements
ISO 9004:2000 QMS – Guidelines for Performance
More than 40,000 companies have been certified
ISO 14000: (1987)
Focuses on a company’s environmental responsibility
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Why TQM Efforts Fail
Lack of a genuine quality culture
Lack of top management support and commitment
Over- and under-reliance on SPC methods
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