Transcript Technology in services

ISM 270
Service Engineering and
Management
Lecture 3: Technology in Services
Announcements
 Homework
1 due next week
 Homework 2 due following week
Today’s Lecture
 Role
of Technology in Services
 New Service Development
 Facility location problems
 Inventory Management
 Statistics and Probability Review
Technology in Service
Discussion
Name an Internet site you believe will be
successful in the long run - explain why.
IT Significance
Information Technology can change the way that an
organization (business or public sector) competes.
• As the foundation for organizational renewal.
• As a necessary investment that should help
achieve and sustain strategic objectives.
• As an increasingly important communication
network among employees and with customers,
suppliers, business partners and even
competitors.
Strategic Roles
of Information Systems
Specific Examples:
 Lower Costs
 Differentiate
 Innovate
 Promote Growth
 Develop Alliances
 Improve Quality and Efficiency
 Build an IT Platform
 Support (enable) other
Strategies
Role of Technology in the Service Encounter
Technology
Customer
Technology
Server
A. Technology-Free
Service Encounter
Customer
Technology
Server
B. Technology-Assisted
Service Encounter
Technology
Customer
Customer
C. Technology-Facilitated
Service Encounter
Technology
Server
D. Technology-Mediated
Service Encounter
Customer
Server
Server
E. Technology-Generated
Service Encounter
Technology has led to the Evolution of
Self-service
Service
Industry
Human
Contact
Machine Assisted
Service
Electronic Service
Banking
Teller
ATM
Online banking
Grocery
Checkout clerk
Self-checkout station
Online order/
pickup
Airlines
Ticket agent
Check-in kiosk
Print boarding pass
Restaurants
Wait person
Vending machine
Online order/
delivery
Movie theater
Ticket sale
Kiosk ticketing
Pay-for-view
Book store
Information
clerk
Stock-availability
terminal
Online shopping
Education
Teacher
Computer tutorial
Distance learning
Gambling
Poker dealer
Computer poker
Online poker
Self-service Technologies (SST)
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Does customer adoption of self-service follow a
predictable pattern?
How do we measure self-service quality (e.g.,
ease of use, enjoyment, and/or control)?
What is the optimal mix of SST and personal
service for a service delivery system?
How do we achieve continuous improvement
when using SST?
What are the limits of self-service given the loss
of human interaction?
Self-Service examples
 Airline
industry
 Banking
Technology has led to
service automation
 Fixed-sequence
(F) - parking lot gate
 Variable-sequence (V) - ATM
 Playback (P) - answering machine
 Numerical controlled (N) - animation
 Intelligent (I) - autopilot
 Expert system (E) - medical diagnosis
 Totally automated system (T) - EFT
Technology has led to a variety of
services available via the web
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
A retail channel (Amazon.com)
Supplemental channel (Barnes & Nobel)
Technical support (Dell Computer)
Embellish existing service (HBS Press)
Order processing (Delta Airline)
Convey information (Kelly Blue Book)
Organization membership (POMS.org)
Games (Treeloot.com)
Several technologies needed to
converge to bring E-Business

Internet
 Global telephone system
 Communications standard TCP/IP
(Transfer Control Protocol/Internet Protocol)
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
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
Addressing system of URLs
Personal computers and cable TV
Customer databases
Sound and graphics
User-friendly free browser
E-Business has led to multiple
business models
(Weill & Vitale, Place to Space, HBS Press, 2001)
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Content Provider: Reuters
Direct to Customer: Dell
Full-Service Provider: GE Supply Co.
Intermediary: eBay
Shared Infrastructure: SABRE
Value Net Integrator: 7-Eleven Japan
Virtual Community: Monster.com
Whole-of-Enterprise: Government
Economics of E-Business

Sources of Revenue:
- Transaction fees
- Information and advice
- Fees for services and commissions
- Advertising and listing fees

Ownership
- Customer relationship
- Customer data
- Customer transaction
Electronic vs. Traditional Services
Features
Electronic
Traditional
Encounter
Screen-to-face
Face-to-face
Availability
Anytime
Working hours
Access
From anywhere
Travel to location
Market Area
Worldwide
Local
Ambiance
Payment
Electronic
interface
Credit card
Physical
environment
Cash or check
Differentiation
Convenience
Personalization
Privacy
Anonymity
Social interaction
Grocery Shopping Comparison
On-line
Shopping
Advantages
Convenience
Saves time
Less impulse
buying
Disadvantages Forget items
Less control
Need computer
Delivery fee
Traditional
Shopping
See new items
Memory trigger
Product sampling
Social interaction
Time consuming
Waiting lines
Carry groceries
Impulse buying
Economics of Scalability
Dimensions
High
Scalability
Low
E-commerce
continuum
Selling
information
(E-service)
Selling valueadded service
Selling
services with
goods
Selling goods
(E-commerce)
Information vs.
Goods Content
Information
dominates
Information with
some service
Goods with support
services
Goods dominate
Degree of Customer
Content
Self-service
Call center backup
Call center support
Call center order
processing
Standardization vs.
Customization
Mass distribution
Some
personalization
Limited
customization
Fill individual orders
Shipping and
Handling Costs
Digital asset
Mailing
Shipping
Shipping, order
fulfillment, and
warehousing
After-sales service
None
Answer questions
Remote maintenance
Returns possible
Example Service
Used car prices
Online travel agent
Computer support
Online retailer
Example Firm
Kbb.com
Biztravel.com
Everdream.com
Amazon.com
E-Business Supply Chain
(Network) Elements

Major entities including firm of interest and its
customers, suppliers, and allies
 Major flows of product, information, and money
 Revenues and other benefits each participant
receives
 Critical aspects: participants, relationships, and
flows
Example: 7-Eleven Japan
Japanese 7-Eleven
 Read

case in text
(p 109, 7th edition, p103, 6th edition, p122 5th
edition)
Evolution of B2C E-Commerce in
Japan
1.
2.
3.
Does the 7-Eleven Japan distribution system
exhibit scalability economics?
How does the 7-Eleven example of B2C ecommerce in Japan illustrate the impact of
culture on service system design?
Will the 7-Eleven “Konbini and Mobile” system
be adopted in the United States?
Video
New Service Development
Service innovation
 How
do I come up with a ‘new’ idea?
 Do I start with a customer need?

A technology?
Levels of Service Innovation
Radical Innovations
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Major Innovation: new service driven by information and
computer based technology
Start-up Business: new service for existing market
New Services for the Market Presently Served: new
services to customers of an organization
Incremental Innovations
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Service Line Extensions: augmentation of existing service
line (e.g. new menu items)
Service Improvements: changes in features of currently
offered service
Style Changes: modest visible changes in appearances
Technology Driven Service Innovation
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Power/energy - International flights with jet
aircraft
Physical design - Enclosed sports stadiums
Materials - Astroturf
Methods - JIT and TQM
Information - E-commerce using the Internet
Service Design
Elements

Structural
- Delivery system
- Facility design
- Location
- Capacity planning
 Managerial
- Service encounter
- Quality
- Managing capacity and demand
- Information
New Service Development Cycle
• Full-scale launch
• Post-launch review
Full Launch
Development
Enablers
• Formulation
of new services
objective / strategy
• Idea generation
and screening
• Concept
development and
testing
People
• Service design
and testing
• Process and system
design and testing
• Marketing program
design and testing
• Personnel training
• Service testing and
pilot run
• Test marketing
Design
Product
Technology
Systems
Tools
Analysis
• Business analysis
• Project authorization
Service Blueprint of Luxury Hotel
Video
Strategic Positioning
Through Process Structure
Degree of Complexity: Measured by the
number of steps in the service blueprint.
For example a clinic is less complex than
a general hospital.
Degree of Divergence: Amount of
discretion permitted the server to
customize the service. For example the
activities of an attorney contrasted with
those of a paralegal.
Structural Alternatives for a Restaurant
LOWER COMPLEXITY/DIVERGENCE
CURRENT PROCESS
No Reservations
Self-seating. Menu on Blackboard
Eliminate
Customer Fills Out Form
TAKE RESERVATION
SEAT GUESTS, GIVE MENUS
SERVE WATER AND BREAD
TAKE ORDERS
PREPARE ORDERS
Pre-prepared: No Choice
Salad (4 choices)
Limit to Four Choices
Entree (15 choices)
Sundae Bar: Self-service
Dessert (6 choices)
Coffee, Tea, Milk only
Serve Salad & Entree Together:
Bill and Beverage Together
Cash only: Pay when Leaving
Beverage (6 choices)
SERVE ORDERS
COLLECT PAYMENT
HIGHER COMPLEXITY/DIVERGENCE
Specific Table Selection
Recite Menu: Describe Entrees & Specials
Assortment of Hot Breads and Hors D’oeuvres
At table. Taken Personally by Maltre d’
Individually Prepared at table
Expand to 20 Choices: Add Flaming Dishes;
Bone Fish at Table; Prepare Sauces at Table
Expand to 12 Choices
Add Exotic Coffees; Sherbet between
Courses; Hand Grind Pepper
Choice of Payment. Including House Accounts:
Serve Mints
Taxonomy of Service Processes
Low divergence
(standardized service)
No
Customer
Contact
Processing
of goods
Processing
Information
Dry
Cleaning
Restocking
a vending
machine
Check
processing
Billing for a
credit card
Processing
of people
Processing
of goods
Processing
Information
Auto repair
Tailoring a
suit
Computer
programming
Designing a
building
Ordering
groceries
from a home
computer
Indirect
customer
contact
No
customerservice
worker
interaction
(selfservice)
Direct
Customer
Contact
High divergence
(customized service)
Food
service
worker
interaction
Operating
a vending
machine
Assembling
premade
furniture
Giving a
service in a
restaurant
Hand car
washing
Withdrawing
cash from
an ATM
Providing
lecture
Handling
routine bank
transactions
Processing
of people
Supervision
of a landing
by an air
controller
Operating
an elevator
Riding an
escalator
Home
public
transportation
Providing
mass
vaccination
Sampling
food at a
buffet dinner
Bagging of
groceries
Documenting
medical
history
Portrait
carpet
cleaning
Landscaping
service
Haircutting
painting
Counseling
Searching for
information
in a library
Driving a
rental car
Using a
health club
facility
Performing
a surgical
operation
Generic Approaches to Service Design
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Production-line
• Limit Discretion of Personnel
• Division of Labor
• Substitute Technology for People
• Standardize the Service
Customer as Coproducer
• Self Service
• Smoothing Service Demand
Customer Contact
• Degree of Customer Contact
• Separation of High and Low Contact Operations
Information Empowerment
• Employee
• Customer
Customer Value Equation

ResultsPro duced   ProcessQua lity 
Value 
Price   CostsofAcq uiringtheS ervice 
Amazon.com
 Discussion:


What were / are the key drivers of success?
What role has technology played?
Discussion
Name

1.
2.
3.
An existing service that could be improved
by new technology
A new service that could be introduced if
new technology were developed
A technology that hasn’t yet converged to a
service
Transportation and Location
Problems
 Appear
frequently in service design
 Homework
2 has an example
Clarke-Wright for homework 2
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Traveling Salesman-type problems very
common in services
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Delivery of goods
Mail routes
Sales tour
Standard problem:

Given the distance between each city pair, visit all N
cities in some order, ending back at the base
• Objective: Minimize total distance traveled
Traveling salesman
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Standard problem is very difficult to solve (NP –
complete)
We will use the Clarke-Wright Algorithm (page 499 of
text)
C-W algorithm intuition:
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Start with the path that returns to base between every node
Add links between nodes instead of returning in order of distance
gained
Stop when no gain can be made
Note: This is a good heuristic

Performs well in practice, but not guaranteed to find the best
solution.
Clark-Wright Algorithm
Objective: Find the shortest-path sequence for visiting N locations
You are given the distance between any two locations
1.
2.
3.
Calculate the ‘savings’ from adding a link between two
locations instead of returning to base in between
Order the savings links from to bottom
Create the schedule by
1.
2.
4.
Starting with a schedule that goes from base to each location and back
Add feasible links from the savings list in order of savings
Stop when no savings can be made, or all links are on one
cycle
Managing Service
Inventory
Replenishment
order
Factory
Production
Delay
Replenishment Replenishment
order
order
Wholesaler
Shipping
Delay
Wholesaler
Inventory
McGraw-Hill/Irwin
Distributor
Retailer
Shipping
Delay
Distributor
Inventory
Customer
order
Customer
Item Withdrawn
Retailer
Inventory
Role of Inventory in Services
 Decoupling
inventories
 Seasonal inventories
 Speculative inventories
 Cyclical inventories
 In-transit inventories
 Safety stocks
18-45
Considerations in Inventory
Systems
 Type
of customer demand
 Planning
time horizon
 Replenishment
 Constraints
lead time
and relevant costs
18-46
Relevant Inventory Costs
 Ordering
costs
 Receiving
 Holding
and inspections costs
or carrying costs
 Shortage
costs
18-47
Inventory Management
Questions
 What
should be the order quantity (Q)?
 When should an order be placed, called a
reorder point (ROP)?
 How much safety stock (SS) should be
maintained?
18-48
Inventory Models
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Economic Order Quantity (EOQ)
Special Inventory Models
With Quantity Discounts
Planned Shortages
Demand Uncertainty - Safety Stocks
Inventory Control Systems
Continuous-Review (Q,r)
Periodic-Review (order-up-to)
Single Period Inventory Model
18-49
Units on Hand
Inventory Levels For EOQ Model
Q
0
Q
D
Time
18-50
Annual Costs For EOQ Model
18-51
EOQ Formula

Notation
D = demand in units per year
H = holding cost in dollars/unit/year
S = cost of placing an order in dollars
Q = order quantity in units
 Total Annual Cost for Purchase Lots

EOQ
TCp  S ( D / Q)  H (Q / 2)
2 DS
EOQ 
H
18-52
Annual Costs for Quantity
Discount Model
22,000
C = $20.00
C = $19.50
C = $18.75
21000
20000
2000
1000
0
100
200
300
400
Order quantity, Q
500
600
700
18-53
Inventory Levels For Planned
Shortages Model
Q-K
Q
TIME
0
-K
T1
T2
T
18-54
Formulas for Special Models
 Quantity
Discount Total Cost Model
 Model with Planned Shortages
TCqd  CD  S ( D / Q)  I (CQ / 2)
D
(Q  K ) 2
K2
TCb  S  H
B
Q
2Q
2Q
2 DS  H  B 
Q 



H
B 
*
 H 
K Q 

 H  B
*
*
18-55
Values for Q* and K* as A
Function of Backorder Cost
B
Q*
B 
2DS
H
0 B 
2DS  H  B 


H  B 
B 0
undefined
K*
0
 H 
Q*
 H  B 
Q*
Inventory Levels
0
0
0
18-56
Safety Stock (SS)
 Demand
During Lead Time (LT) has
Normal Distribution with
Mean(d L )   ( LT )
Std . Dev.( L )   LT
 SS with r% service level
SS  zr LT
 Reorder Point
ROP  SS  d L
18-57
Continuous Review System (Q,r)
Amount used during first lead time
Inventory on hand
EOQ
Reorder point, ROP
d3
Average lead time usage, dL
Safety stock, SS
d1
d2 EOQ
First lead
time, LT1
LT2
LT3
Time
Order 1 placed
Order 2 placed
Shipment 1 received
Order 3 placed
Shipment 2 received
Shipment 3 received
18-58
Periodic Review System
(order-up-to)
Inventory on Hand
Target inventory level, TIL
Review period
RP
RP
RP
First order quantity, Q1
Q3
Q2
d3
d1
Amount used during
first lead time
d2
Safety stock, SS
First lead time, LT1
LT2
LT3
Time
Order 1 placed
Order 2 placed
Shipment 1 received
Order 3 placed
Shipment 2 received Shipment 3 received
18-59
Inventory Control Systems
 Continuous
Review System
2 DS
EOQ 
H
ROP  SS   LT
SS  zr
 Periodic
LT
Review System
RP  EOQ / 
TIL  SS   ( RP  LT )
SS  zr RP  LT
18-60
Percentage of dollar volume
ABC Classification of
Inventory Items
110
100
90
80
70
60
50
40
30
20
10
0
A
B
C
Percentage of inventory items (SKUs)
18-61
Inventory Items Listed in
Descending Order of Dollar Volume
Inventory Item
Unit cost
($)
Monthly
Sales
(units)
Dollar
Volume ($)
Home Theater
Computers
5000
2500
30
30
150,000
75,000
Television sets
Refrigerators
Displays
400
1000
250
60
15
40
24,000
15,000
10,000
Speakers
Cameras
Software
Thumb drives
CDs
150
200
50
5
10
60
40
100
1000
400
9,000
8,000
5,000
5,000
4,000
Totals
305,000
Percent of
Dollar
Volume
Percent of
SKUs
Class
74
20
A
16
30
B
10
50
C
100
100
18-62
Single Period Inventory Model
Newsvendor Problem Example
D = newspapers demanded
p(D) = probability of demand
Q = newspapers stocked
P = selling price of newspaper, $10
C = cost of newspaper, $4
S = salvage value of newspaper, $2
Cu = unit contribution: P-C = $6
Co = unit loss: C-S = $2
18-63
Single Period Inventory Model
Expected Value Analysis
p(D)
D
6
7
Stock Q
8
.028
.055
.083
.111
.139
.167
.139
.111
.083
.055
.028
2
3
4
5
6
7
8
9
10
11
12
4
12
20
28
36
36
36
36
36
36
36
2
10
18
26
34
42
42
42
42
42
42
0
8
16
24
32
40
48
48
48
48
48
-2
6
14
22
30
38
46
54
54
54
54
-4
4
12
20
28
36
44
52
60
60
60
$31.54
$34.43
$35.77
$35.99
$35.33
Expected Profit
9
10
18-64
Single Period Inventory Model
Incremental Analysis

E (revenue on last sale)
P ( revenue) (unit revenue)

E (loss on last sale)
P (loss) (unit loss)
P( D  Q)Cu  P( D  Q)Co
1 P( D  Q)C
u
 P( D  Q)Co
Cu
P ( D  Q) 
Cu  Co
(Critical Fractile)
where:
Cu = unit contribution from newspaper sale ( opportunity cost of underestimating demand)
Co = unit loss from not selling newspaper (cost of overestimating demand)
D = demand
Q = newspaper stocked
18-65
Critical Fractile for the
Newsvendor Problem
P(D<Q)
(Co applies)
Probability
P(D>Q)
(Cu applies)
0.722
0
1
2
3
4
5
6
7
8
9 10 11 12 13 14
Newspaper demand, Q
18-66
Retail Discounting Model





S = current selling price
D = discount price
P = profit margin on cost (% markup as decimal)
Y = average number of years to sell entire stock of “dogs” at
current price (total years to clear stock divided by 2)
N = inventory turns (number of times stock turns in one year)
Loss per item = Gain from revenue
S – D = D(PNY)
S
D
(1  PNY )
18-67
Statistics Review
Statistics Review
 Probability
and Random Events
 Distribution
 Central
Functions
Limit Theorem
Probability
 In
a random event problem where all
events are equally likely
 P [condition A] =
# Events satisfying A / # possible events
Density functions
 PDF
= probability density function
= probability of random variable equal to each
value
 CDF
= cumulative distribution function
= probability of random variable being less
than or equal to each value
= integral of PDF up to that value
Conditional Probability
P
[Event1|Event2] =
Prob[Both Events]/Prob[Event2]
 Conditional

PDF
f(x|y) = f(x,y) / f(y)
Next Week
 Service
 Geoff
Quality
Ryder