ISM 270 Service Engineering and Management Lecture 3: 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 Technology Technology

Technology Technology

Customer Customer ServerServer

Server 

Server 

Server

CustomerCustomer

Customer

D. Technology-MediatedService Encounter

E. Technology-GeneratedService Encounter

A. Technology-FreeService Encounter

B. Technology-AssistedService Encounter

C. Technology-FacilitatedService 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)

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

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)

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)

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 Electronic interface

Physical environment

Payment Credit card Cash or check

Differentiation Convenience Personalization

Privacy Anonymity Social interaction

Grocery Shopping Comparison

On-lineShopping

TraditionalShopping

Advantages ConvenienceSaves timeLess impulsebuying

See new itemsMemory triggerProduct samplingSocial interaction

Disadvantages Forget itemsLess controlNeed computerDelivery fee

Time consumingWaiting linesCarry groceriesImpulse buying

Economics of ScalabilityDimensions High Scalability Low

E-commerce continuum

Sellinginformation(E-service)

Selling value-added service

Sellingservices 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. Does the 7-Eleven Japan distribution system exhibit scalability economics?

2. How does the 7-Eleven example of B2C e-commerce in Japan illustrate the impact of culture on service system design?

3. 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 InnovationRadical Innovations

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 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

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

People

Technology Systems

Product

Full Launch Development

Design Analysis

Org

aniz

atio

nal

Con

text Team

s

Tools

Enablers

• Formulation of new services objective / strategy• Idea generation and screening• Concept development and testing

• Business analysis• Project

authorization

• Full-scale launch• Post-launch

review

• Service design and testing• Process and system design and testing• Marketing program design and testing• Personnel training• Service testing and pilot run• Test marketing

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

No Reservations

Self-seating. Menu on BlackboardEliminate

Customer Fills Out Form

Pre-prepared: No Choice

Limit to Four Choices

Sundae Bar: Self-service

Coffee, Tea, Milk onlyServe Salad & Entree Together:

Bill and Beverage Together

Cash only: Pay when Leaving

TAKE RESERVATIONSEAT GUESTS, GIVE MENUSSERVE WATER AND BREAD

TAKE ORDERSPREPARE ORDERS

Salad (4 choices)

Entree (15 choices)

Dessert (6 choices)

Beverage (6 choices)SERVE ORDERS

COLLECT PAYMENT

Specific Table SelectionRecite Menu: Describe Entrees & SpecialsAssortment of Hot Breads and Hors D’oeuvresAt table. Taken Personally by Maltre d’

Individually Prepared at table

Expand to 20 Choices: Add Flaming Dishes;Bone Fish at Table; Prepare Sauces at TableExpand to 12 Choices

Add Exotic Coffees; Sherbet betweenCourses; Hand Grind Pepper

Choice of Payment. Including House Accounts:Serve Mints

LOWER COMPLEXITY/DIVERGENCE CURRENT PROCESS HIGHER COMPLEXITY/DIVERGENCE

Taxonomy of Service Processes Low divergence High divergence (standardized service) (customized service)

Processing Processing Processing Processing Processing Processing of goods Information of people of goods Information of people

Dry Check Auto repair Computer No Cleaning processing Tailoring a programming Customer Restocking Billing for a suit Designing a Contact a vending credit card building machine

Ordering Supervision Indirect groceries of a landing customer from a home by an air contact computer controller No Operating Withdrawing Operating Sampling Documenting Driving a customer- a vending cash from an elevator food at a medical rental car service machine an ATM Riding an buffet dinner history Using a worker Assembling escalator Bagging of health club interaction premade groceries Searching for facility (self- furniture information

service) in a libraryDirectCustomer Food Giving a Providing Home Portrait HaircuttingContact service service in a lecture public carpet painting Performing worker restaurant Handling transport- cleaning Counseling a surgical interaction Hand car routine bank ation Landscaping operation washing transactions Providing service mass vaccination

Generic Approaches to Service Design

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

erviceuiringtheSCostsofAcqPrice

lityProcessQuaducedResultsPro

Value

Amazon.com

Discussion: What were / are the key drivers of success? What role has technology played?

Discussion

Name1. An existing service that could be improved

by new technology

2. A new service that could be introduced if new technology were developed

3. 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

Traveling Salesman-type problems very common in services

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 Standard problem is very difficult to solve (NP –

complete) We will use the Clarke-Wright Algorithm (page 499 of

text) C-W algorithm intuition:

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 locationsYou are given the distance between any two locations

1. Calculate the ‘savings’ from adding a link between two locations instead of returning to base in between

2. Order the savings links from to bottom3. Create the schedule by

1. Starting with a schedule that goes from base to each location and back2. Add feasible links from the savings list in order of savings

4. Stop when no savings can be made, or all links are on one cycle

Managing Service Inventory

Factory Wholesaler Distributor Retailer Customer

Replenishment order

Replenishment order

Replenishment order

Customer order

Production Delay

WholesalerInventory

Shipping Delay

Shipping Delay

DistributorInventory

RetailerInventory

Item Withdrawn

McGraw-Hill/Irwin

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 lead time

Constraints and relevant costs

18-46

Relevant Inventory Costs Ordering costs

Receiving and inspections costs

Holding 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 Economic Order Quantity (EOQ) Special Inventory Models

With Quantity DiscountsPlanned Shortages

Demand Uncertainty - Safety Stocks Inventory Control Systems

Continuous-Review (Q,r)Periodic-Review (order-up-to)

Single Period Inventory Model

18-49

Inventory Levels For EOQ Model

0

Un

its o

n H

an

d

Q

Q

D

Time

18-50

Annual Costs For EOQ Model

18-51

EOQ Formula Notation

D = demand in units per yearH = holding cost in dollars/unit/yearS = cost of placing an order in dollarsQ = order quantity in units

Total Annual Cost for Purchase Lots

EOQ TCp S D Q H Q ( / ) ( / )2

EOQDS

H

2

18-52

Annual Costs for Quantity Discount Model

0 100 200 300 400 500 600 700

22,000

21000

20000

2000

1000

C = $20.00 C = $19.50 C = $18.75

Order quantity, Q

Ann

ual C

ost,

$

18-53

Inventory Levels For Planned Shortages Model

Q

Q-K

0

-KT1 T2

TIME

T

18-54

Formulas for Special Models Quantity Discount Total Cost Model Model with Planned Shortages

TC CD S D Q I CQqd ( / ) ( / )2

TC SD

QH

Q K

QBK

Qb

( )2 2

2 2

QDS

H

H B

B*

2

K QH

H B* *

18-55

Values for Q* and K* as AFunction of Backorder Cost

B Q* K* Inventory Levels

B

0 B

B 0

2DS

H

2DS

H

H B

B

undefined

QH

H B*

Q*

00

0

0

18-56

Safety Stock (SS) Demand During Lead Time (LT) has

Normal Distribution with

SS with r% service level

Reorder Point

Mean d LTL( ) ( )

Std Dev LTL. .( )

SS z LTr

ROP SS dL

18-57

Continuous Review System (Q,r)

Average lead time usage, dL

Reorder point, ROP

Safety stock, SS

Inventory on hand

Ord

er q

uant

ity, E

OQ

EOQ

EOQ

d1 d2

d3

Amount used during first lead time

First leadtime, LT1

Order 1 placed

LT2 LT3

Order 2 placed Order 3 placed

Shipment 1 received Shipment 2 received Shipment 3 received

Time

18-58

Periodic Review System(order-up-to)

RP RP RP

Review period

First order quantity, Q1

d1

Q2Q3

d2

d3

Target inventory level, TIL

Amount used duringfirst lead time

Safety stock, SS First lead time, LT1 LT2 LT3

Order 1 placed Order 2 placed Order 3 placed

Shipment 1 received Shipment 2 received Shipment 3 received

Time

Inventory on Hand

18-59

Inventory Control Systems Continuous Review System

Periodic Review System

EOQDS

HROP SS LT

SS z LTr

2

RP EOQ

TIL SS RP LT

SS z RP LTr

/

( )

18-60

ABC Classification of Inventory Items

0102030405060708090

100110

Percentage of inventory items (SKUs)

Per

cen

tag

e o

f d

oll

ar v

olu

me

A B C

18-61

Inventory Items Listed in Descending Order of Dollar Volume

Monthly Percent of Unit cost Sales Dollar Dollar Percent of Inventory Item ($) (units) Volume ($) Volume SKUs Class

Home Theater 5000 30 150,000 74 20 AComputers 2500 30 75,000

Television sets 400 60 24,000Refrigerators 1000 15 15,000 16 30 BDisplays 250 40 10,000

Speakers 150 60 9,000Cameras 200 40 8,000Software 50 100 5,000 10 50 CThumb drives 5 1000 5,000CDs 10 400 4,000

Totals 305,000 100 100

18-62

Single Period Inventory ModelNewsvendor 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

Stock Qp(D) D 6 7 8 9 10

.028 2 4 2 0 -2 -4

.055 3 12 10 8 6 4

.083 4 20 18 16 14 12

.111 5 28 26 24 22 20

.139 6 36 34 32 30 28

.167 7 36 42 40 38 36

.139 8 36 42 48 46 44

.111 9 36 42 48 54 52

.083 10 36 42 48 54 60

.055 11 36 42 48 54 60

.028 12 36 42 48 54 60

Expected Profit $31.54 $34.43 $35.77 $35.99 $35.33

18-64

Single Period Inventory Model Incremental Analysis

E (revenue on last sale) E (loss on last sale)

P ( revenue) (unit revenue) P (loss) (unit loss)

P D Q C P D Q Cu o( ) ( )

1 P D Q C P D Q Cu o( ) ( )

P D QC

C Cu

u o

( )

(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

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14

Newspaper demand, Q

Pro

bab

ilit

y

P(D<Q)(Co applies)

P(D>Q)(Cu applies)

0.722

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 revenueS – D = D(PNY)

)1( PNY

SD

18-67

Statistics Review

Statistics Review

Probability and Random Events

Distribution Functions

Central 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 Quality

Geoff Ryder