Title: Service Processes
1Service Processes
- Operations Management
- Dr. Ron Tibben-Lembke
2How are Services Different?
- Everyone is an expert on services
- What works well for one service provider doesnt
necessarily carry over to another - Quality of work is not quality of service
- Service package consists of tangible and
intangible components - Services are experienced, goods are consumed
- Mgmt of service involves mktg, personnel
- Service encounters mail, phone, F2F
3Degree of Customer Contact
- More customer contact, harder to standardize and
control - Customer influences
- Time of demand
- Exact nature of service
- Quality (or perceived quality) of service
43 Approaches
- Which is Best?
- Production Line
- Self-Service
- Personal attention
5What do People Want?
- Amount of friendliness and helpfulness
- Speed and convenience of delivery
- Price of the service
- Variety of services
- Quality of tangible goods involved
- Unique skills required to provide service
- Level of customization
6Service-System Design Matrix
Degree of customer/server contact
Buffered
Permeable
Reactive
core (none)
system (some)
system (much)
High
Low
Face-to-face total customization
Face-to-face loose specs
Sales Opportunity
Production Efficiency
Face-to-face tight specs
Phone Contact
Internet on-site technology
Mail contact
High
Low
7Applying Behavioral Science
- The end is more important to the lasting
impression (Colonoscopy) - Segment pleasure, but combine pain
- Let the customer control the process
- Follow norms rituals
- Compensation for failures fix bad product,
apologize for bad service
8Restaurant Tipping
- Normal Experiment
- Introduce self(Sun brunch) 15 23
- Smiling (alone in bar) 20 48
- Waitress 28 33
- Waiter (upscale lunch) 21 18
- staffing wait positions is among the most
important tasks restaurant managers perform.
9Fail-Safing
- poka-yokes Japanese for avoid mistakes
- Not possible to do things the wrong way
- Indented trays for surgeons
- ATMs beep so you dont forget your card
- Pagers at restaurants for when table ready
- Airplane bathroom locks turn on lights
- Height bars at amusement parks
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15How Much Capacity Do We Need?
16Blueprinting
- Fancy word for making a flow chart
- line of visibility separates what customers can
see from what they cant - Flow chart back office and front office
activities separately.
17Capacity greater than Average
customers arriving per hour
18Queues
- In England, they dont wait in line, they wait
on queue. - So the study of lines is called queueing theory.
19Cost-Effectiveness
- How much money do we lose from people waiting in
line for the copy machine? - Would that justify a new machine?
- How much money do we lose from bailing out
(balking)?
20We are the problem
- Customers arrive randomly.
- Time between arrivals is called the interarrival
time - Interarrival times often have the memoryless
property - On average, interarrival time is 60 sec.
- the last person came in 30 sec. ago, expected
time until next person 60 sec. - 5 minutes since last person still 60 sec.
- Variability in flow means excess capacity is
needed
21Memoryless Property
- Interarrival time time between arrivals
- Memoryless property means it doesnt matter how
long youve been waiting. - If average wait is 5 min, and youve been there
10 min, expected time until bus comes 5 min - Exponential Distribution
- Probability time is t
22Poisson Distribution
- Assumes interarrival times are exponential
- Tells the probability of a given number of
arrivals during some time period T.
23Ce n'est pas les petits poissons.
- Les poissons Les poissons
- How I love les poissons
- Love to chop And to serve little fish
- First I cut off their heads
- Then I pull out the bones
- Ah mais oui Ca c'est toujours delish
- Les poissons Les poissons
- Hee hee hee Hah hah hah
- With the cleaver I hack them in two
- I pull out what's inside
- And I serve it up fried
- God, I love little fishes
- Don't you?
24Simeon Denis Poisson
- "Researches on the probability of criminal and
civil verdicts" 1837 - looked at the form of the binomial distribution
when the number of trials was large. - He derived the cumulative Poisson distribution as
the limiting case of the binomial when the chance
of success tend to zero.
25Binomial Distribution
- The binomial distribution tells us the
probability of having - x successes in
- n trials, where
- p is the probability of success in any given
attempt.
26Binomial Distribution
- The probability of getting 8 tails in 10 coin
flips is
27Poisson Distribution
28POISSON(x,mean,cumulative)
- X is the number of events.
- Mean is the expected numeric value.
- Cumulative is a logical value that determines
the form of the probability distribution
returned. If cumulative is TRUE, POISSON returns
the cumulative Poisson probability that the
number of random events occurring will be between
zero and x inclusive if FALSE, it returns the
Poisson probability mass function that the number
of events occurring will be exactly x.
29Larger average, more normal
30Queueing Theory Equations
- Memoryless Assumptions
- Exponential arrival rate ?
- Avg. interarrival time 1/ ?
- Exponential service rate ?
- Avg service time 1/?
- Utilization ? ?/?
31Avg. in System
- Lq avg in line
- Ls avg in system
- Prob. n in system
32Average Time
- Wq avg wait in line
- Ws avg time in system
33System Structure
- The more comlicated the system, the harder it is
to model - Separate lines
- Separate tellers, etc.
34Now what?
- Simulate!
- Build a computer version of it, and try it out
- Tweak any parameters you want
- Change it as much as you want
- Try it out with zero risk
35Factors to Consider
- Arrival patterns, arrival rate
- Size of arrival units 1,2,4 at a time?
- Degree of patience
- Length line grows to
- Number of lines 1 is best
- Does anyone get priority?
36Service Time Distribution
- Deterministic each person always takes 5
minutes - Random low variability, most people take
similar amounts of time - Random high variability, large difference
between slow fast people
37Which is better, one line or two?
38Waiting Lines
- Operations Management
- Dr. Ron Tibben-Lembke
39Everyone is just waiting
40People Hate Lines
- Nobody likes waiting in line
- Entertain them, keep them occupied
- Let them be productive fill out deposit slips,
etc. (Wells Fargo) - People hate cutters / budgers
- Like to see that it is moving, see people being
waited on - Tell them how long the wait will be (Space
Mountain)
41Retail Lines
Magazines
- Things you dont need in easy reach
- Candy
- Seasonal, promotional items
- People hate waiting in line, get bored easily,
reach for magazine or book to look at while in
line
42Disney FastPass
- Wait without standing around
- Come back to ride at assigned time
- Only hold one pass at a time
- Ride other rides
- Buy souvenirs
- Do more rides per day
43Fastpasses
44Some Lucky People Get These
45In-Line Entertainment
- Set up the story
- Get more buy-in to ride
- Plus, keep from boredom
46- Slow me down before going again
- Create buzz, harvest email addresses
47False Hope
Dumbo
Peter Pan
48What did we learn?
- Human considerations very important in services
- Queueing Theory can help with simple capacity
decisions - Simulation needed for more complex ones
- People hate lines, but hate uncertainty more
- Keep them informed and amused