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 month2 unsafe plane landings per day at O’Hare Airport in Chicago16,000 pieces of mail lost by the U.S. Post Office every hour.

Ever wonder what 99.9% meant?

20,000 incorrect prescriptions every year 500 incorrect operations each week50 babies dropped at birth every day22,000 checks deducted from the wrong bank account each hour32,000 missed heart beats per person each year

What is Service Quality?

Identify a “quality” service Discuss why it is high quality

Garvin’s 8 Dimensions of Quality

PerformancefeaturesReliabilityConformanceDurabilityServiceabilityAestheticsPerceived Quality

Schonberger’s Additional 4 Dimensions of Quality

Quick ResponseQuick change expertiseHumanityValue

Quality toolbox Quality toolbox (no shortage of topics for MGT 667)

1992 Baldrige winner’s Texas Instruments DSEG1992 Baldrige winner’s Texas Instruments DSEG (now Raytheon TI Systems) (now Raytheon TI Systems)

Quality Management Tool Box

Variation SPC (control charts), Process capability (Cpk), Design of Experiments, Taguchi, acceptance sampling, Gauge R&R, other statistical tools

Mistakes mistake-proofing (poka-yoke), Just culture, StandardizationErgonomics, Human factors engineering

CultureQuality 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)

ComplexityProcess Mapping,Design for Manufacturability & assembly, Root cause analysis, FMEA, Fault trees, Quality Function Deployment, Focused factories, Group technology, Smart simple design, 5s, visual systems

Mistake-proofing tool flowchartMistake-proofing tool flowchart

Best thinking on Service Quality:

Service Quality Model

Financial Services -- focus group basedA.K.A. Gap Analysis, SERVQUALCompares customer perceptions with

customer expectations (Gap #5)Gap #5 = function of Gaps #1, #2, #3, #4

Here’s how the looks...

customer

Personal needs Past Experience

Expected service

Perceived Service

Service Delivery

ManagementPerceptions of

Customer Expectations

Service QualitySpecifications

External Communication

to Customers

provider

Word-of-mouthcommunications

Gap #5

Gap #3

Gap #4

Gap #2

Gap #1

Gap #1: Lack of market researchInadequate upward communicationToo many levels of management

Gap #2: Inadequate management communication of service qualityPerception of infeasibilityInadequate task standardizationAbsence of goal setting

GAPS #1 and #2

Gap #3: 1) Role ambiguity and conflict2) Poor employee or technology job fit3) inappropriate control systems4) Lack of perceived control 5) Lack of teamwork

Gap #4: 1) Inadequate horizontal communication2) Propensity to overpromise

GAPS #3 and #4

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.

Change the design by mistake-proofing

If it is worthwhile to mistake-proof yo-yos…

…What else would it be worth mistake-proofing?

Exercise:

Can you think of examples of mistake-proofing in your car?

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.

1998, John R. Grout

1/3 of customer complaints relate to problems caused by the customer themselves

Server Poka-yokes 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

Task

Treatment Tangibles

Examples

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

Task

Treatment Tangibles

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

Preparation

Resolution

Encounter

Examples

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

Preparation

Resolution

Encounter

Have you ever…

Shot a rifle?Played darts?Shot a round of golf?Played basketball?

Emmett

Jake

Who is the better shot?

Variability

The world tends to be bell-shaped

Most outcomes

occur in the middle

Fewer in the “tails”

(lower)

Fewer in the “tails” (upper)

Even very rare outcomes are

possible(probability > 0)

Even very rare outcomes are

possible(probability > 0)

Variability

Add up the dots on the dice

0

0.05

0.1

0.15

0.2

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18

Sum of dots

Pro

ba

bili

ty 1 die

2 dice

3 dice

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

“Normal” bell shaped curve

Add up about 30 of most things and you start to be “normal”

Normal distributions are divide upinto 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

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:

RAX 2

RDLCL 3 RDUCL 4

Lots of other charts exist

P chart C charts U charts Cusum & EWMA

For yes-no questions like “is it defective?” (binomial data)

For counting number defects where most items have ≥1 defects (eg. custom built houses)

Average count per unit (similar to C chart)

Advanced charts

“V” shaped or Curved control limits (calculate them by hiring a statistician)

n

ppp

)1(3

cc 3

n

uu 3

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

Process capability (Cpk)

Good quality: defects are rare (Cpk>1)

Poor quality: defects are common (Cpk<1)

Cpk measures “Process Capability”

If process limits and control limits are at the same location, Cpk = 1. Cpk ≥ 2 is exceptional.

μtarget

μtarget