ISM 270 Service Engineering and Management ISM

ISM 270 Service Engineering and Management

ISM 270: Service Engineering and Management Focus on Operations Decisions in the Service Industry Ø Open to students with an undergraduate engineering/science degree Ø Learn analytical tools and software for decision making Ø Featuring guest lectures from industry practitioners Ø Text: Fitzsimmons & Fitzsimmons Ø ‘Service Management’ Operations, Strategy, Information Technology

Topics covered The nature of service enterprises Ø Strategy for new service development Technology in services Ø Quality in service encounters Ø Forecasting demand Ø Managing service capacity Ø Supply chains in services Ø Globalization and outsourcing Ø

Skills / Tools Learned Programming Tools • SAS Enterprise Miner • Spreadsheet Programming • Optimization Solvers • Web Programming in a Browser • Littlefield Team-Based Management Simulation Analytical Methods • Linear Programming • Data Envelopment Analysis • Statistics for Forecasting • Capacity Management and Queueing Theory • Project Management Under Uncertainty • Theory of Service Supply Chains

Sample Project Utilizing statistics for web service development

ISM 270: Details Ø 6 – 9 pm, Tuesday evenings Ø January 10 – March 13 (Winter) 2007 Ø UCSC Silicon Valley Center Ø Instructor: Kevin Ross l kross@soe. ucsc. edu Ø Teaching Assistant: Geoff Ryder l gryder@gmail. com

Who is here? Ø My background Ø Brief introductions, student survey

Logistics Ø Class website Ø Readings Ø Text book Ø Office hours l 5 -6 pm before class, or by appointment Ø Fee for Simulation Game

Class Plan Ø Allotted class time = 3 hours Ø Average adult attention span = 20 minutes Ø… Ø Lecture / visitor / lab / split

Computer issues Ø Who has a laptop? Ø Web access Ø Finding research papers Ø Excel, solver, …

Please… Ø Bring: l l Paper, pen, laptop, … Opinions Questions Interesting articles, stories, anecdotes Ø Provide feedback!!! Ø Make every effort to keep up with readings etc.

Schedule Class Date Topic 1 Jan 10 The nature of Data envelopment analysis of service productivity service linear programming enterprises 2 Jan 17 Strategy for new service development 3 Jan 24 Lab Activity Web programming: access the Google Maps API using Java. Script to display data for a service facility location problem Technology in Web programming: aggregate and process services Guest Speaker Reading Assessm ent Vargo, S. L. & Lusch, R. F (2004). HW 1 due Paul Maglio Senior Manager IBM Research TBA business data using XML and My. SQL. Web project assignment. 4 Jan 31 Quality in service encounters Statistical service process control problem. 5 Feb 7 Project Management Statistics review homework Christoph Heitz as preparation forecasting demand section. Project management exercise. Frank Tung HW 2 due

Schedule Class Date Topic Lab Activity Guest Speaker 6 Feb 14 Forecasting demand Analyze real call center arrival data to predict future traffic levels. Maximilien 7 Feb 21 Managing service capacity Apply principles from queueing theory to service capacity planning problems. TBA 8 Feb 28 Service Managemen t Game Challenge Competitive team-based Littlefield service management Challenge simulation challenge 9 Mar 6 Supply chains in services Continue Littlefield management challenge 10 Mar 13 Globalizatio n and outsourcing Project presentations Charles Ng Reading Assessm ent HW 3 due Bring Laptop Homewor k 4 due Homewor k 5 due Final Project Report due

Assessment Value Date Homework 50% Weekly Littlefield Project Final Project 10% Feb 28 40% March 13

Homework 1: Applying the Excel solver tool for data envelopment analysis (DEA)

Homework 2: use AJAX calls to build a mashup with the Google Maps API

Homework 3: learn to use SAS Enterprise Miner

Put in some lab time and learn other useful SAS features. . .

Project Ø More details later… Ø Focus on new service development Ø Written and Verbal Presentation at final class March 13

Questions and Break

Remaining in Lecture 1 Ø Services in the Economy Ø Data Envelopment Analysis l l Linear Programming Excel

Perspective Ø World-wide trends Ø Personalization trends

Text Chapter 1: Role of Services in an Economy Service Management Professor James Fitzsimmons University of Texas at Austin

Quiz Question Ø Name the top 10 USA companies by revenue in 2007 Ø How many would you describe as service companies?

Top 10 1. Wal-Mart Stores. 2. Exxon Mobil 3. General 4. Chevron 5. Conoco. Phillips 6. General Electric 7. Ford Motor 8. Citigroup 9. Bank of America 10. American Intl. Group

Definitions Ø What are services? Ø Service enterprises?

Service Definitions Intangible goods? Services are deeds, processes, and performances. Valarie Zeithaml & Mary Jo Bitner A service is a time-perishable, intangible experience performed for a customer acting in the role of a co-producer. James Fitzsimmons Folks doing things for folks for Money Paul Magio

Definition of Service Firms Service enterprises are organizations that facilitate the production and distribution of goods, support other firms in meeting their goals, and add value to our personal lives. James Fitzsimmons

Services Science, Management and Engineering …the application of science, management, and engineering disciplines to tasks that one organization beneficially performs for and with another • (Wikipedia)

Role of Services in an Economy

Percent Service Employment for Selected Nations Country 1980 1987 1993 United States 67. 1 71. 0 74. 3 Canada 67. 2 70. 8 74. 8 Israel 63. 3 66. 0 68. 0 Japan 54. 5 58. 8 59. 9 France 56. 9 63. 6 66. 4 Italy 48. 7 57. 7 60. 2 Brazil 46. 2 50. 0 51. 9 China 13. 1 17. 8 21. 2 2000 74. 2 74. 1 73. 9 72. 7 70. 8 62. 8 56. 5 40. 6

Trends in U. S. Employment by Sector

Stages of Economic Development Pre. Use of dominant human Society Game activity labor Standard Unit of of living social life measure Structure Technology Pre- Against Agriculture Raw Extended Sub- Routine Simple hand Industrial Nature Mining muscle household sistence Traditional tools power Authoritative Industrial Against Goods Machine Individual Quantity Bureaucratic Machines fabricated production tending of goods Hierarchical nature Post- Among Services Artistic Community Quality of Inter- Information industrial Persons Creative life in terms dependent Intellectual of health, Global education, recreation

The New Experience Economy

The Four Realms of an Experience

Experience Design Principles Ø Theme the Experience (Forum shops) Ø Harmonize Impressions with Positive Cues (O’Hare airport parking garage) Ø Eliminate Negative Cues (Cinemark talking trash containers) Ø Mix in Memorabilia (Hard Rock T-shirts) Ø Engage all Five Senses (Mist in Rainforest)

Source of Service Sector Growth Ø Innovation Push theory (e. g. Post-it) l Ø Product looking for a problem Pull theory (e. g. Cash Management) l Need drives innovation Services derived from products (Video Rental) Information driven services Difficulty of testing service prototypes Ø Social Trends Aging of the population Two-income families Growth in number of single people Home as sanctuary Ø

Question: What has engineering got to do with all of this?

Discussion Topics Ø Describe the work that you do from a service perspective Ø Illustrate how the type of work you do influences a person’s lifestyle.

Example Service Innovation: Disney World Ø Link

Lessons from Disney

Data Envelopment Analysis (DEA) Ø Method for evaluating efficiency of similar venues/products Ø Incorporates inputs and outputs – not just one dimensional Ø Uses LINEAR PROGRAMMING (LP)

Sample LP: Product Mix Problem Ø How much beer and ale to produce from three scarce resources: l l l 480 pounds of corn 160 ounces of hops 1190 pounds of malt A barrel of ale consumes 5 pounds of corn, 4 ounces of hops, 35 pounds of malt Ø A barrel of beer consumes 15 pounds of corn, 4 ounces of hops and 20 pounds of malt Ø Profits are $13 per barrel of ale, $23 for beer Ø

Sample LP: Transportation Problem A firm produces computers in Singapore and Hoboken. Ø Distribution Centers are in Oakland, Hong Kong and Istanbul Ø Supply, demand costs summary: Ø Singapore Hohboken Demand Oakland Hong Kong 85 37 53 189 350 250 Istanbul Supply 119 94 200 500 300

Other LP examples Ø Blending problem Ø Diet problem Ø Assignment problem

Key terms of LP Ø Variables Ø Parameters Ø Objective function Ø Constraints

Standard Form (according to Hillier and Lieberman) Concise version: A is an m by n matrix: n variables, m constraints

Geometry of LP Ø Consider the plot of solutions to a LP

Data Envelopment Analysis (DEA) Ø Method for evaluating efficiency of similar venues/products l l Ø Incorporates inputs and outputs – not just one dimensional Uses LINEAR PROGRAMMING (LP) KEY IDEA: l l l Weight the inputs and outputs to make one unit as efficient as possible, relative to all others If this is 100% efficient, then the unit is on the frontier of efficiency; If less than 100%, there are other units that could utilize the SAME inputs for MORE outputs

DEA Example from Text: Burger Palace Ø Small, artificial example for illustration! Ø Page 68 of 5 th edition, text Ø Burger chain has six units in several cities l l Each unit uses different combination of labor hours and dollars to produce meals Which units use their resources most efficiently?

Productivity of Burger Palace Service Units Service Unit 1 Meals Sold Labor Hours 100 2 Dollars 2 100 4 150 3 100 4 100 6 100 5 100 8 80 6 100 10 50 200

DEA summary of terms Ø Define variables l l l Ø E_k = efficiency of unit k u_j= coefficient for output j (relative decrease in efficiency per unit reduction of output value) v_i = coefficient for input i (relative increase in efficiency per unit decrease of input value) O_jk = observed ouput j units generated by service unit k during one time period I_ik = no. units input used by service unit k during one period Note: l l l k=1. . K = service unit counter j=1. . M = output counter i=1. . N = input counter

DEA Objective and constraints Evaluating unit e Trick = Rescaling to get linear equations

Homework: Week 1 Ø Link

Next Week Ø Paul Maglio Ø Strategy in Services