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Copyright 2009 John Wiley & Sons, Inc. Beni Asllani University of Tennessee at Chattanooga Service Design Operations Management - 6 th Edition Chapter.

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Presentation on theme: "Copyright 2009 John Wiley & Sons, Inc. Beni Asllani University of Tennessee at Chattanooga Service Design Operations Management - 6 th Edition Chapter."— Presentation transcript:

1 Copyright 2009 John Wiley & Sons, Inc. Beni Asllani University of Tennessee at Chattanooga Service Design Operations Management - 6 th Edition Chapter 5 Roberta Russell & Bernard W. Taylor, III

2 Copyright 2009 John Wiley & Sons, Inc.5-2 Lecture Outline   Service Economy   Characteristics of Services   Service Design Process   Tools for Service Design   Waiting Line Analysis for Service Improvement

3 Copyright 2009 John Wiley & Sons, Inc.5-3 Service Economy Source: U.S. Bureau of Labor Statistics, IBM Almaden Research Center

4 Copyright 2009 John Wiley & Sons, Inc.5-4

5 Copyright 2009 John Wiley & Sons, Inc.5-5 Characteristics of Services  Services acts, deeds, or performances acts, deeds, or performances  Goods tangible objects tangible objects  Facilitating services accompany almost all purchases of goods accompany almost all purchases of goods  Facilitating goods accompany almost all service purchases accompany almost all service purchases

6 Copyright 2009 John Wiley & Sons, Inc.5-6 Continuum from Goods to Services Source: Adapted from Earl W. Sasser, R.P. Olsen, and D. Daryl Wyckoff, Management of Service Operations (Boston: Allyn Bacon, 1978), p.11.

7 Copyright 2009 John Wiley & Sons, Inc.5-7 Characteristics of Services (cont.)  Services are intangible  Service output is variable  Services have higher customer contact  Services are perishable  Service inseparable from delivery  Services tend to be decentralized and dispersed  Services are consumed more often than products  Services can be easily emulated

8 Copyright 2009 John Wiley & Sons, Inc.5-8 Service Design Process

9 Copyright 2009 John Wiley & Sons, Inc.5-9   Service concept purpose of a service; it defines target market and customer experience   Service package mixture of physical items, sensual benefits, and psychological benefits   Service specifications performance specifications design specifications delivery specifications Service Design Process (cont.)

10 Copyright 2009 John Wiley & Sons, Inc.5-10 Service Process Matrix

11 Copyright 2009 John Wiley & Sons, Inc.5-11 Design Decision High-Contact ServiceLow-Contact Service High v. Low Contact Services   Facility location   Convenient to customer   Near labor or transportation source Source: Adapted from R. Chase, N. Aquilano, and R. Jacobs, Operations Management for Compensative Advantage (New York:McGraw-Hill, 2001), p. 210   Facility layout   Must look presentable, accommodate customer needs, and facilitate interaction with customer   Designed for efficiency

12 Copyright 2009 John Wiley & Sons, Inc.5-12 Design Decision High-Contact ServiceLow-Contact Service   Quality control   More variable since customer is involved in process; customer expectations and perceptions of quality may differ; customer present when defects occur   Measured against established standards; testing and rework possible to correct defects Source: Adapted from R. Chase, N. Aquilano, and R. Jacobs, Operations Management for Compensative Advantage (New York:McGraw-Hill, 2001), p. 210   Capacity   Excess capacity required to handle peaks in demand   Planned for average demand High v. Low Contact Services (cont.)

13 Copyright 2009 John Wiley & Sons, Inc.5-13 Design Decision High-Contact ServiceLow-Contact Service   Worker skills   Must be able to interact well with customers and use judgment in decision making   Technical skills Source: Adapted from R. Chase, N. Aquilano, and R. Jacobs, Operations Management for Compensative Advantage (New York:McGraw-Hill, 2001), p. 210   Scheduling   Must accommodate customer schedule   Customer concerned only with completion date High v. Low Contact Services (cont.)

14 Copyright 2009 John Wiley & Sons, Inc.5-14 Design Decision High-Contact ServiceLow-Contact Service High v. Low Contact Services (cont.)   Service process   Mostly front-room activities; service may change during delivery in response to customer   Mostly back- room activities; planned and executed with minimal interference Source: Adapted from R. Chase, N. Aquilano, and R. Jacobs, Operations Management for Compensative Advantage (New York:McGraw-Hill, 2001), p. 210   Service package   Varies with customer; includes environment as well as actual service   Fixed, less extensive

15 Copyright 2009 John Wiley & Sons, Inc.5-15 Tools for Service Design  Service blueprinting line of influence line of influence line of interaction line of interaction line of visibility line of visibility line of support line of support  Front-office/Back- office activities  Servicescapes space and function space and function ambient conditions ambient conditions signs, symbols, and artifacts signs, symbols, and artifacts  Quantitative techniques

16 Copyright 2009 John Wiley & Sons, Inc.5-16 Service Blueprinting

17 Copyright 2009 John Wiley & Sons, Inc.5-17 Service Blueprinting (Con’t)

18 Copyright 2009 John Wiley & Sons, Inc.5-18 Elements of Waiting Line Analysis  Operating characteristics average values for characteristics that describe performance of waiting line system average values for characteristics that describe performance of waiting line system  Queue a single waiting line a single waiting line  Waiting line system consists of arrivals, servers, and waiting line structure consists of arrivals, servers, and waiting line structure  Calling population source of customers; infinite or finite source of customers; infinite or finite

19 Copyright 2009 John Wiley & Sons, Inc.5-19

20 Copyright 2009 John Wiley & Sons, Inc.5-20 Elements of Waiting Line Analysis (cont.)  Arrival rate (λ) frequency at which customers arrive at a waiting line according to a probability distribution, usually Poisson frequency at which customers arrive at a waiting line according to a probability distribution, usually Poisson  Service time (μ) time required to serve a customer, usually described by negative exponential distribution time required to serve a customer, usually described by negative exponential distribution  Service rate must be shorter than arrival rate (λ < μ)  Queue discipline order in which customers are served order in which customers are served  Infinite queue can be of any length; length of a finite queue is limited can be of any length; length of a finite queue is limited

21 Copyright 2009 John Wiley & Sons, Inc.5-21 Elements of Waiting Line Analysis (cont.)  Channels number of parallel servers for servicing customers number of parallel servers for servicing customers  Phases number of servers in sequence a customer must go through number of servers in sequence a customer must go through

22 Copyright 2009 John Wiley & Sons, Inc.5-22 Operating Characteristics  Operating characteristics are assumed to approach a steady state

23 Copyright 2009 John Wiley & Sons, Inc.5-23 Traditional Cost Relationships  as service improves, cost increases

24 Copyright 2009 John Wiley & Sons, Inc.5-24 Psychology of Waiting  Waiting rooms magazines and newspapers magazines and newspapers televisions televisions  Bank of America mirrors mirrors  Supermarkets magazines magazines “impulse purchases” “impulse purchases”  Disney costumed characters costumed characters mobile vendors mobile vendors accurate wait times accurate wait times special passes special passes

25 Copyright 2009 John Wiley & Sons, Inc.5-25 Psychology of Waiting (cont.)  Preferential treatment Grocery stores: express lanes for customers with few purchases Grocery stores: express lanes for customers with few purchases Airlines/Car rental agencies: special cards available to frequent-users or for an additional fee Airlines/Car rental agencies: special cards available to frequent-users or for an additional fee Phone retailers: route calls to more or less experienced salespeople based on customer’s sales history Phone retailers: route calls to more or less experienced salespeople based on customer’s sales history  Critical service providers services of police department, fire department, etc. services of police department, fire department, etc. waiting is unacceptable; cost is not important waiting is unacceptable; cost is not important

26 Copyright 2009 John Wiley & Sons, Inc.5-26 Waiting Line Models  Single-server model simplest, most basic waiting line structure simplest, most basic waiting line structure  Frequent variations (all with Poisson arrival rate) exponential service times exponential service times general (unknown) distribution of service times general (unknown) distribution of service times constant service times constant service times exponential service times with finite queue exponential service times with finite queue exponential service times with finite calling population exponential service times with finite calling population

27 Copyright 2009 John Wiley & Sons, Inc.5-27 Basic Single-Server Model  Assumptions Poisson arrival rate Poisson arrival rate exponential service times exponential service times first-come, first- served queue discipline first-come, first- served queue discipline infinite queue length infinite queue length infinite calling population infinite calling population  Computations λ = mean arrival rate λ = mean arrival rate μ = mean service rate μ = mean service rate n = number of customers in line n = number of customers in line

28 Copyright 2009 John Wiley & Sons, Inc.5-28 Basic Single-Server Model (cont.)  probability that no customers are in queuing system  probability of n customers in queuing system  average number of customers in queuing system  average number of customers in waiting line ( ) P 0 = 1 – λμ ( ) ( )( ) P n = ∙ P 0 = 1 – λ n λ n λ μ μ μ L =L =L =L = λ μ – λ Lq =Lq =Lq =Lq = λ 2 λ 2 μ (μ – λ)

29 Copyright 2009 John Wiley & Sons, Inc.5-29 Basic Single-Server Model (cont.)  average time customer spends in queuing system  average time customer spends waiting in line  probability that server is busy and a customer has to wait (utilization factor)  probability that server is idle and customer can be served 1 L 1 L μ – λ λ W = = λ μ (μ – λ) Wq =Wq =Wq =Wq = λμ ρ =ρ =ρ =ρ = I = 1 – ρ = 1 – = P 0 = 1 – = P 0λμ

30 Copyright 2009 John Wiley & Sons, Inc.5-30 Basic Single-Server Model Example

31 Copyright 2009 John Wiley & Sons, Inc.5-31 Basic Single-Server Model Example (cont.)

32 Copyright 2009 John Wiley & Sons, Inc.5-32 Service Improvement Analysis  waiting time (8 min.) is too long hire assistant for cashier? hire assistant for cashier? increased service rate increased service rate hire another cashier? hire another cashier? reduced arrival rate reduced arrival rate  Is improved service worth the cost?

33 Copyright 2009 John Wiley & Sons, Inc.5-33 Basic Single-Server Model Example: Excel

34 Copyright 2009 John Wiley & Sons, Inc.5-34 Advanced Single-Server Models  Constant service times occur most often when automated equipment or machinery performs service occur most often when automated equipment or machinery performs service  Finite queue lengths occur when there is a physical limitation to length of waiting line occur when there is a physical limitation to length of waiting line  Finite calling population number of “customers” that can arrive is limited number of “customers” that can arrive is limited

35 Copyright 2009 John Wiley & Sons, Inc.5-35 Advanced Single-Server Models (cont.)

36 Copyright 2009 John Wiley & Sons, Inc.5-36 Basic Multiple-Server Model  single waiting line and service facility with several independent servers in parallel  same assumptions as single-server model  sμ > λ s = number of servers s = number of servers servers must be able to serve customers faster than they arrive servers must be able to serve customers faster than they arrive

37 Copyright 2009 John Wiley & Sons, Inc.5-37 1 λ n s!s n – s μ P 0, for n ≤ s 1 λ n n! μ ( ) { P 0, for n > s P n =  probability that there are no customers in system  probability of n customers in system 1 λ n 1 λ s sμ n! μ s! μ sμ - λ ( ) ( )( ) n = s – 1 n = 0 1 P 0 = ∑ + Basic Multiple-Server Model (cont.)

38 Copyright 2009 John Wiley & Sons, Inc.5-38 Basic Multiple-Server Model (cont.)  probability that customer must wait ( ) 1 λ s sμ 1 λ s sμ s! μ sμ – λ P w = P 0 λμ (λ/μ) s λ λμ (λ/μ) s λ (s – 1)! (sμ – λ) 2 μ L = P 0 + Lλ W =W =W =W = L q = L – λμ 1 L q μ λ W q = W – = ρ =ρ =ρ =ρ = λ λ λsμsμ λ λsμsμ

39 Copyright 2009 John Wiley & Sons, Inc.5-39 Basic Multiple-Server Model Example

40 Copyright 2009 John Wiley & Sons, Inc.5-40 Basic Multiple-Server Model Example (cont.)

41 Copyright 2009 John Wiley & Sons, Inc.5-41 Basic Multiple-Server Model Example (cont.)

42 Copyright 2009 John Wiley & Sons, Inc.5-42 Basic Multiple-Server Model Example (cont.)

43 Copyright 2009 John Wiley & Sons, Inc.5-43 Basic Multiple-Server Model Example (cont.)

44 Copyright 2009 John Wiley & Sons, Inc.5-44 Basic Multiple-Server Model Example (cont.)  To cut wait time, add another service representative now, s = 4 now, s = 4  Therefore:

45 Copyright 2009 John Wiley & Sons, Inc.5-45 Multiple-Server Waiting Line in Excel

46 Copyright 2009 John Wiley & Sons, Inc.5-46 Copyright 2009 John Wiley & Sons, Inc. All rights reserved. Reproduction or translation of this work beyond that permitted in section 117 of the 1976 United States Copyright Act without express permission of the copyright owner is unlawful. Request for further information should be addressed to the Permission Department, John Wiley & Sons, Inc. The purchaser may make back-up copies for his/her own use only and not for distribution or resale. The Publisher assumes no responsibility for errors, omissions, or damages caused by the use of these programs or from the use of the information herein.


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