Jim Spohrer, ([email protected]) Director, Almaden Services Research

IBM Research – Almaden Services Research

ISSS 2005, 49th Annual Meeting, Cancun, Mexico | July 4th, 2005

Why the world needs more systems thinkersfocused on service systems

--- or ---Beyond computer science: The emergence of service science

Services Sciences, Management, and Engineering (SSME)Networked Information (Systems, Services, Solutions) Sciences, Management, and Engineering (NIS 3SME)

Jim Spohrer, ([email protected])Director, Almaden Services Research

2

Service Innovations & Service Science

IBM Research © 2005 IBM Corporation

Today’s Talk

The world needs more multidisciplinary systems thinkersAccelerating rate of change and globally connected social, political, economic, business,

and technology systems

Unfortunately, without systems thinking, unintended consequences to actions all too often result

In government policy, business strategy, and academic research, what is the optimal ratio of specialists to systems thinkers in this new age of rapid change and global interconnectedness?

Focused on service systems evolution and designGovernment, business, academic collaboration ready to focus on services

Service sector dominates global economies, and the world is a big, rapidly changing, and highly interconnected service system

All stakeholders (government, business, and academics) want systematic service innovations to predictably improve productivity and quality

Why this matters to IBM? Now more than 50% services revenue, and on demand e-business and business performance transformation services require new ratio of specialists to systems thinkers (service scientists)

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Problem

Need moresystem thinkers

The Systems View of the World:

A Holistic Vision for Our Time

by: Ervin Laszlo

How We Got Here : A Slightly Irreverent History of Technology and Markets

by Andy Kessler

4



Sterman’s Business Dynamics

“Accelerating economic, technological, social, and environmental change challenge managers and policy makers to learn at increasing rates, while at the same time the complexity of the systems in which we live are growing. Many of the problems we now face arise from unanticipated side effects of our own past actions.”

Dynamic complexity arises because systems are:Dynamic, tightly coupled, governed by feedback, nonlinear, history

dependent, self organizing, adaptive, counterintuitive, policy resistant, and characterized by trade-offs

How rapid is the change and are there any patterns in how humans deal with complexity… how do people invest their time?

Business Dynamics: Systems Thinking and Modeling for a Complex World

by John Sterman

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Q: How do people invest their time?

InformationInformationEnergyEnergy

MaxUseful info

TimeMaxEnergyTime [ ][ ]

Source: Pirolli (2002)

Humans as Informavore (George A. Miller, 1983)

George

A: Building and using tools and relationships (organizations) to achieve goals. (human activities change over time as we develop and use new capabilities)

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Building tools & organizations – accelerating growth of capabilitiesBillion Years Ago Natural Processes

12 Big Bang (EMST)

11.5 Milky Way (Atoms)

8 Sun (Energy)

4.5 Earth (Molecules)

3.5 Bacteria (Cell)

2.5 Sponge (Body)

0.7 Clams (Nerves)

0.5 Trilobites (Brains)

0.2 Bees (Swarms)

0.065 Mass Extinctions

0.002 Humans Tools & Clans Coevolution

Generations Ago Human Processes

100,000 Speech

750 Agriculture

500 Writing

400 Libraries

40 Universities

24 Printing

16 Accurate Clocks

5 Telephone

4 Radio

3 Television

2 Computer

1 Internet/e-Mail

0 GPS, CD, WDM

Global Brain: The Evolution of Mass Mind from the Big Bang to the 21st Century

by Howard Bloom

Nonzero : The Logic of Human Destiny by Robert Wright

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Coevolution of Institutions, Disciplines, Professions, Application(governance, exploration, exploitation, diffusion of innovation)

System Evolution System Design = Knowledge Value

Systems Layer Evolution Laws & InstitutionsGovernance(.gov)

Disciplines& ResearchExploration(.edu)

Professions& JobsExploitation(.com)

Technology &Organizations(Application)Diffusion of Innovation

NaturalSystems

Physical 12-8B BigBang/Sun

empirical Physics Physicist Lasers, Electronics

Chemical 4.5B Earth empirical Chemistry Chemist Dyes, Plastics

Biological 3.5B Cells/DNA empirical Biology Biologist Vaccine, Corn

Neural 700M Clams… empirical Neuroscience Neurologist Cochlea Implant

SociotechSystems

or

HumanSystems

Hunter-Gatherers

2M years ago(15-150 people)

imperial, chief, priest

Anthropology Hunter Fire, Clothing, Knife, Spear

Agricult-ural

10K-5K years(5 million people)

ruler, king, scribe

History, Law Farmer,Miller,Smith, Baker

Towns, Cities, Plow, Irrigation

Industrial 250 years ago(1 billon people)

democratic,politician, vote

Engineering, Education

Engineer. Teacher

Steam Engine,Telephone, Public Education

Services 100 years ago(2 billion people)

politician, vote

MBA, Social Science

Manager M-FormBusiness Org.

InfoServices

50 years ago(now 6 billion)

politician, vote

Computer & Organization Sciences

Computer Scientist

Computer,Search Engine

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Reductionism (specialists) & Integration (systems thinkers):Plus a much prettier picture than my coevolution table!

Rita Colwell,Former Director National Science Foundation (NSF)

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Human Activities: Sociotechnical System Evolution

0

20

40

60

80

100

120

Services (Info)

Services (Other)

Industry (Goods)

Agriculture

Hunter-Gatherer

Estimations based on Porat, M. (1977) Info Economy: Definitions and Measurement

Estimated world (pre-1800) and then U.S. Labor Percentages by Sector

The Pursuit of Organizational Intelligence, by James G. March Exploitation vs exploration

The Company of Strangers : A Natural History of Economic Lifeby Paul Seabright

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Human Population: Sociotechnical System Evolution

Effects of A

griculture,C

olonial Expansion &

Econom

ics, S

cientific Method, Industrialization

& P

olitics, Education, H

ealthcare &

Information T

echnologies, etc.

The Visible Hand: The Managerial Revolution in American Businessby Alfred Dupont Chandler

Rise of the m

odern managerial

firm

Shadows in the Sun, by Wade Davis“Ethnosphere. sum total of all the thoughts, beliefs, myths, and institutions brought into being by the human imagination”

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Systematic Innovation: Invest & Get Predictable Results

Moore’s Law – Scaling down helped propel Computer ScienceScale-down of transistor size every few years results in better economics of digital

logic (faster and denser logic for computation and storage)

Algorithmic complexity theory is a well developed theory of algorithm scaling in time and space complexity

Surowiecki’s Law – Scaling up may help propel Service ScienceScale-up in number of service interactions every few years may result in better

economics of service logic (higher productivity and quality)

Wisdom of the crowds – laws of large numbers – Amazon’s recommendation system gets better with use/scale; E-bay’s reputation system; Google’s relevancy rank

The more people that use a service the easier it is to make improvements – capture experiences, analyze experience, redesign based on frequency

What is the optimal pacing to give innovators (service providers and clients) the best return on investment for participating in coproduction relationships?

The Wisdom of Crowds: Why the Many Are Smarter Than the Few and How Collective Wisdom Shapes Business, Economies, Societies and Nations

by James Surowiecki

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Approach

Focus on service systems

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Propositions

Government policy should more highly prioritize multidisciplinary services research and education centers.

Industry, academics, and government need to work more closely together to articulate the need and the potential national and global benefits.

Government needs to improve their productivity and quality of service

Businesses should be investing more to make innovation in services more systematic.

Vast quantities of service data are generated by the business world every day, and yet precious little is being leveraged by research institutions.

Businesses need to transform and improve productivity and quality of service

Academic silos should be bridged.There is an opportunity at the intersection of social sciences, business schools, science

& engineering schools (1) to create a unified theory of service system evolution, management, and design, and (2) to graduate professionals that better meet the needs of society (highly interconnected, rapidly changing).

Education needs to improve productivity and quality of service

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Definitions

Service Science, short for Services Sciences, Management, and Engineering (SSME)

Definition 1: The application of scientific, management, and engineering disciplines to tasks that one organization beneficially performs for and with another (‘services’)

Make productivity, quality, performance, compliance, growth, and learning improvements more predictable in work sharing and risk sharing (coproduction) relationships.

Science is a way to create knowledge Engineering is a way to apply knowledge and create new value Business Model is a way to apply knowledge and capture value Management improves the process of creating and capturing value.

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Terms & Definitions Service Science, short for Services Sciences, Management, and Engineering (SSME)

Definition 1: The application of scientific, management, and engineering disciplines to tasks that one organization beneficially performs for and with another (‘services’)

Make productivity, quality, performance, compliance, growth, and learning improvements more predictable in work sharing and risk sharing (coproduction) relationships.

Definition 2: The study of service systems. Evolution & Design: Services systems evolve in difficult to predict ways because of naturally

emergent and rationally designed path dependent interactions between economic entities, acting in the roles of clients and providers coproducing value.

Interactions & Value Coproduction: Service systems are made up of large numbers of interacting clients and providers coproducing value. Each economic entity is both a client and a provider. Service system dynamics are driven by the constantly shifting value of knowledge distributed among people, organizations, technological artifacts (culture), and embedded in networks or ecosystems of relationships amongst them.

Specialization & Coordination: One mechanism for creating value is specialization of clients and providers, which results in the need for coordination via markets, organizational hierarchies, and other mechanisms. Specialization creates efficiency. Efficiency creates profits and leisure. Profits and Leisure create investment (profits to innovation) and new demand (leisure to new aspirations).

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Why IBM cares about services…

Preamble: IBM Research – what you know and may not know

Problem: Motivation and Definitions

Importance: Economic Growth & Need for Service Innovations

Approach: Academic-Industry-Government Collaboration

Progress: Events, Relationships, References, Investments

Next Steps: Challenges and Obstacles

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IBM Research Worldwide

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What Physicists Do At IBM Research…This achievement is a major milestone toward creating a microscope

that can make three-dimensional images of molecules with atomic resolution

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IBM Computer Scientists build bigger, faster computers

Blue Gene, as its name suggests, is aimed at the drug-development market. Scientists hope eventually to model how proteins fold – a process that is

important in designing drugs that can block cancer cells and other diseases.

70.72 teraflops on 11/2004183.5 teraflops on 3/2004

(Linpack benchmark)

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What you may not know… IBM helped start computer science; not out of altruism, but to meet a business need

Now IBM is working withacademics and governmentto establish Service Science

The biggest costs were in changing the organization. One way to think about these changes is to treat the Organizational costs as an investment in a new asset.

Firms make investments over time in developing anew

process, rebuilding their staff or designing a neworganizational structure, and the benefits from theseInvestments are realized over a long period of time.”Eric Brynjolfsson, “Beyond the Productivity Paradox”

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Service Science: Why Now? IBM’s perspective

0102030405060708090

100

1982 1988 1994 1998 2003

Services

Software

Hardware

Other

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2004 IBM Annual Report: 2x Productivity Increase leads to 60% Gross Profit Margins for Services

source: ftp://ftp.software.ibm.com/annualreport/2004/2004_ibm_financials.pdf

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Multidisciplinary Nature ofPhDs in IBM’s Global Services Division (US)

Engineering and Natural Sciences

Social Sciences

Business and Management

Liberal Arts and Humanities

Other

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Need for service scientists in ResearchPhDs in IBM’s Research Division (US)

Engineering and Natural Sciences

Social Sciences

Business and Management

Liberal Arts and Humanities

Other

25



Problem: Motivation & Definitions

MotivationNeed better trained people: Services professionals & researchers

Need more knowledge about sustainable service innovation techniques: Innovation is the key to value creation & capture, and hence the key to sustainable business advantage

Need more systematic methods for studying and creating knowledge about service systems: Investment in science & research pays in new knowledge

Example: Computer Science (coevolution of occupation, discipline, techniques, science)

Preliminary DefinitionsServices: A client pays a service provider to transform the state of something, a person,

product, or business (e.g., enterprise transformation), in a manner mutually shaped by both.

Service Innovation: Service innovation is a change to a service system (made up of many clients and providers interacting) that creates measurable improvement in characteristics of interest, achieved via the diffusion of technical innovation, business innovation, social innovation, demand innovation, or some combination of these factors.

Service Science: Working with academics in multiple disciplines to create a definition, draft - the study of service systems (characterized by coevolving technical-business-social change) and measures of system performance (productivity, client satisfaction), growth processes (scale, scope), and learning processes (optimization-exploitation, exploration).

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Nation % WW

Labor% A

%G

%S

25 yr %delta S

China 21.0 50 15 35 191

India 17.0 60 17 23 28

U.S. 4.8 3 27 70 21

Indonesia 3.9 45 16 39 35

Brazil 3.0 23 24 53 20

Russia 2.5 12 23 65 38

Japan 2.4 5 25 70 40

Nigeria 2.2 70 10 20 30

Banglad. 2.2 63 11 26 30

Germany 1.4 3 33 64 44

Top Ten Nations by Labor Force Size(about 50% of world labor in just 10 nations)

A = Agriculture, G = Goods, S = Services

>50% (S) services, >33% (S) services

2004 2004United States

The largest labor force migrationin human history is underway,

driven by urbanization, global communications,

low cost labor, business growthand technology innovation.

(A) Agriculture:Value from

harvesting nature(G) Goods:

Value from making products

(S) Services:Value from enhancing the

capabilities of things (customizing, distributing, etc.) and interactions between things

The world is becoming a service system.Why Now?

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© USK/Sep’04 SI&GIE/27

Why Now?: US GNP Today and in the Future

Services

Material

Information

11%

9%

30%

50%

Products

From Uday Karmarkar: “Service industrialization in the global economy”Also author of HBR article: “Will you survive the services revolution?”

Uday Karmarkar, IBM Faculty Award, Pro-Service Innovation

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Definitions of Services

Deed, act, or performance (Berry, 1980) An activity or series of activities… provided as solution to customer problems

(Gronroos, 1990) All economic activity whose output is not physical product or construction

(Brian et al, 1987) Intangible and perishable… created and used simultaneously (Sasser et al,

1978) A time-perishable, intangible experience performed for a customer acting in

the role of co-producer (Fitzsimmons, 2001) A change in condition or state of an economic entity (or thing) caused by

another (Hill, 1977) Characterized by its nature (type of action and recipient), relationship with

customer (type of delivery and relationship), decisions (customization and judgment), economics (demand and capacity), mode of delivery (customer location and nature of physical or virtual space) (Lovelock, 1983)

Deeds, processes, performances (Zeithaml & Bitner, 1996)

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So, services are…

Pay for performance in which client and provider coproduce value

High talent performanceKnowledge-intensive business services (business performance transformation

services) (e.g., chef’s, concert musicians)

High support performanceEnvironment designed to allow average performer to provide a superior

performance (average cook with great cook book and kitchen; average musician with a synthesizer)

High tech performance Computational services (e-commerce, self service – client does work)

Even here… talent builds, maintains, upgrades, etc. the technology

Routine performance (sometime High Finance)This is being automated, outsourced, labor arbitrage, financial arbitrage,

migrated to high talent/value sectors, or otherwise being rationalized

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Services: Client pays provider for a performance or promise of a performance. The client and provider share responsibility for coproduction of value within the boundaries of the relationship (aspire to “win-win”).

Performance: Activities that transform the state of something.

Coproduction relationship: A relationship in which goals/work responsibilities and risks/rewards are shared, with an explicit or tacit contract defining initial/intermediate/ongoing/final states/results/effort/quality levels. External factors that might impact the relationship may or may not be enumerated. Third party partners may be involved in establishing, evaluating, and working front stage or back stage in the coproduction relationship.

Front stage activities: Sometimes called the “moments of truth” in which client and provider directly interact. Pure services are mostly front stage. Variance in the front stage is largely due to the client’s requests and actions, and provides opportunities to provide higher value services. Eliminating front stage variance can lead to standards and higher quality, but may also destroy a lot of high end value creation opportunities.

Back stage activities: Both provider-side activities that do not directly involve the client, and client-side activities that do not directly involve the provider. Pure products are mostly back stage for providers (manufacturer). Six sigma is an effective method for eliminating unnecessary variance in the backstage, which leads from custom processes to standard processes.

Services vary based on how much front-stage or back-stage activities are required, how custom or standard the activities are, and how client intensive or non-client intensive the activities are.

Provider firms orchestrate or coordinate employees, partners, and clients in the coproduction of value. Some have referred to this as creating economies of coordination – simple to complex.

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Getting systematic about service innovations

Improve back stage provider or client productivity: Applying six sigma, process re-engineering, and other transformation activities to the back stage. Function of costs of activities, including costs of unwanted variance.

Improve front stage scope: Expanding the scope of front stage services – addressing more or better the custom requests of clients, as well as exploiting more of the unique capabilities of providers. Function of value of needs, including enabling new capabilities.

Improve coordination: Standardize processes and interactions. This can boost quality (compliance) and productivity. Function of scale, complexity, and uncertainty in the system.

Improve dynamic evolution: Continuously migrate provider-client pairs to higher value creation and capture points on an on-going basis. Function of time.

Improve capabilities of people, organizations, institutions or technologies to enter into higher value creation and capture configurations. Function of systems productive capacity – innovating new capabilities (incremental, radical, and super-radical innovations).

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High talent performance is on the rise in the US economy

Type of work system

1979 1996 Example

All Services Goods

Tightly Constrained

6% 5% 4% 10% Call center, Fast food

Unrationalized Labor Intensive

25% 25% 26% 15% Maid, child care

Semi-Autonomous

35% 30% 30% 35% Admin., Manager

High-skill Autonomous

34% 40% 40% 40% Executive,Engineer

From Herzenberg, Alic, Wial (1998)

95% of all scientists are alive today.

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Tip of the hat to Henry Chesbrough, a pioneer.Henry Chesbrough, IBM Faculty Award, Services Science Pioneer

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Why Service Science? New knowledge drives the process of systematic innovation…

Science & Engineering(Study phenomena

and create newknowledge)

Business Administrationand Management

(Study phenomenaand create new

knowledge)

Social Sciences(Study phenomena

and create newknowledge)

Global Economy& Markets

(Emergence ofnew knowledge in

practice!)

BusinessInnovationTechnology

Innovation

Social-OrganizationalInnovation

DemandInnovation

SSME = Service Sciences, Management, and Engineering

Knowledge sources driving service innovations…

35



Berkeley’s new ORMS undergraduate majorRhonda Righter, IBM Faculty Awardhttp://www.ieor.berkeley.edu/AcademicPrograms/Ugrad/ORMS.pdf

36



School Discipline Evolution & Revision

Selection & Aggregation

Transformation & Integration

School ofManagement

Marketing Service Marketing

Service &

Solutions E

xcellence Centers

(Information S

cience & T

echnology Managem

ent)

Services S

ciences, Managem

ent, and Engineering (S

SM

E) and S

olutions E

ngineeringOperations Service Operations

Accounting Service Accounting (Activity-Based Costing)

Contracts & Negotiations Service Sourcing (eSourcing)

Management Science Service Management

Management of Technology

Management of Innovation

School of Engineering and Science

Operations Research Service Operations

Industrial & Systems Engineering

Service Engineering

Computer Science Service Computing, Web Services, SOA

School of Social Sciences Economics Institutional EconomicsExperimental Economics

Psychology Labor Psychology(Human Capital Mgmt)

Anthropology Business Anthropology

Organization Theory

Professional Schools Medical School, Law School, Education School, Hotel & Restaurant School, Media & Communications, etc.

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Relationship of Service Science to Existing Academic Areas:The center balances three key factors: business value, IT process, organizational culture

Process: Information Technology

Capital:BusinessDecisions

People:OrganizationalCulture

51

9 2527

14

28

10

26

24

84

1. Service Engineering

2. Service Operations

3. Service Management

4. Service Marketing

5. Social Complexity

6. Agent-based comput-ational economics

7. Computational Organization Theory

14. Computer & Information Sciences

15. Management of Innovation

16. Organization Theory

17. Operations Research

18. Systems Engineering

19. Management Science

20. Game Theory

21. Industrial Engineering

22. Marketing

23. Managerial Psychology

2367

11

12

13

1516

17

18

1920

21

22

23

1990-2004

1960-1990

1900-1960

Before 1900

8. Human Capital Management (HCM)

9. Experimental Economics

10. AI & Games

11. Management of Information Systems

12. Computer Supported Collab. Work (CSCW)

13. Human Performance Tech. & Measurement

24. Business Administration (MBA)

25. Economics

26. Law

27. Sociology

28. Education

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Networked Information SystemsNetworked Information Systems

ORGANIZATIONSORGANIZATIONS TECHNOLOGYTECHNOLOGY

MANAGEMENTMANAGEMENT

NETWORKEDNETWORKED

INFORMATIOINFORMATIONN

SYSTEMSSYSTEMS

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Services Related Programs (small sampling)

Center for Relationship Marketing and Service Management, Hanken, Finland Center for Service Leadership, Arizona State University, USA The Center for Hospitality Research, Cornell University, USA CTF, Centrum för Tjänsteforskning (Service Research Centre), University of Karlstad, Sweden Centre for Service Management, Cranfield School of Management, UK Relationship Marketing, Emory University, USA Service Management Research Programme, Nankai University, PR China Relationship Marketing, University of Auckland, New Zealand Center for Services Marketing, University of Maryland, USA School of Services Management, Nanyang Polytechnic, Singapore Fishman-Davidson Center for Service and Operations Management, Wharton, UPenn, USA Service Management, University of Buckingham, UK Service Engineering, Technion, Israel Services Management, Brigham Young University, Utah Service Management, Warwick Business School, UK Operations Management of Services, California State University, Northridge, USA Services Management & New Service Development, University of Texas, Austin, USA Service Operations Management, Universidade Federal, Rio de Janeiro, Brazil Service Operations Management, University of Calgary, Canada Management of Services, University of Western Ontario, Canada Service Operations Management, San Jose State University, CA, USA Productivity Management, City University of Hong Kong Managing Service Operations, DePaul University, USA Service Management and Strategy, London School of Business, UK

Others at http://www.servsig.org/Syllabi/Service_Operations_Management_Syllabi.pdf

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Select efforts to promote service science

Dec. 2002: Almaden Service Research established, the first IBM Research group completely dedicated to understanding service innovations from a sociotechnical systems perspective, including enterprise transformation and industry evolution(http://www.almaden.ibm.com/asr/)

March 2003: IBM-Berkeley Day: Technology… At Your Service!(http://www.eecs.berkeley.edu/IPRO/IBMday03/)

September 2003: Coevolution of Business-Technology Innovation Symposium(http://www.almaden.ibm.com/coevolution/)

April 2004: Almaden Institute: Work in the Era of the Global, Extensible Enterprise(http://www.almaden.ibm.com/institute/2004/)

May 2004: “Architecture of On Demand” Summit: Service science: A new academic discipline?(http://domino.research.ibm.com/comm/www_fs.nsf/pages/index.html)

June 2004: Paul Horn, VP IBM Research, briefs analysts on “Services as a Science”

September 2004: Chesbrough’s “A failing grade for the innovation academy” appears in the Financial Times(http://news.ft.com/cms/s/9b743b2a-0e0b-11d9-97d3-00000e2511c8,dwp_uuid=6f0b3526-07e3-11d9-9673-00000e2511c8.html)

November 2004: IBM’s GIO focuses on service sector innovations: government, healthcare, work-life balance(http://www.ibm.com/gio)

November 2004: Service Innovations for the 21st Century Workshop(http://www.almaden.ibm.com/asr/events/serviceinnovation/)

December 2004: Samuel J. Palmisano, IBM CEO, Harvard Business Review interview discusses the important role of “values” in organizational performance, “Leading Change When Business is Good”(http://harvardbusinessonline.hbsp.harvard.edu/b01/en/common/item_detail.jhtml?id=R0412C)

December 2004: IBM expands academic initiatives related to service innovations, including sponsoring Tannenbaum Institute of Enterprise Transformation at Georgia Tech.

February 2005: Chesbrough’s “Service as a Science” in Harvard Business Review Breakthrough ideas of 2005

May, June, July, etc. Oxford, Warwick, Bentley, Penn State, etc.

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Historical Example: Emergence of new academic discipline and systematic approach to innovation and wealth creation

Emergence of German dye industry, German mid-19th Century Emergence of chemistry as an academic discipline Emergence of patent protection in the new area of chemical

processes and formula Emergence of new relationships connecting firms, academic

institutions, government agencies, and clients Demonstrates needed coevolution of firms, technology, and national

institutions Took England and US over 70 years to catch up!!!

Knowledge and Competitive Advantage : The Coevolution of Firms, Technology, and National Institutions

by Johann Peter Murmann

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One Policy Challenge: Beyond Technology Patents… Patenting Business, Social-Organizational, Demand Innovations

Source:Robert M. Hunt

“You can patent that?Are patents on software and

business models good forthe new economy?”

43



Service Science – Reading List Motivation

Chesbrough (2005) Towards a new science of services. Harvard Business Review.

Chesbrough (2004) A failing grade for the innovation academy. Financial Times.

Rust (2004) A call for a wider range of services research. J. of Service Research.

Tien & Berg (2003) A case for service systems engineering. J. Sys. Science & Sys. Eng.

Rouse (2004) Embracing the enterprise. Industrial Engineer.

Karmarkar (2004) Will you survive the services revolution. Harvard Business Review. Philosophy

Vargo & Lusch (2004) Evolving a new dominant logic for marketing. J. of Marketing. Exemplar Model

Oliva & Sterman (2001) …Quality erosion in the services industry. J. of Management Science. Economics

Bryson et al (2005) Service worlds. Routledge. London, UK.

Herzenberg et al (1998) New rules for a new economy. Cornell University Press. Ithaca, NY. Technology

McAfee (2005) Will web services really transform collaboration? MIT Sloan Management Review. Textbooks

Fitzsimmons & Fitzsimmons (2001) Service management. McGraw-Hill. New York, NY.Sampson (2001) Understanding service businesses. John Wiley: New York, NY.

Evolution and Change: Managed, Designed, and EmergentKhalil, Tarek (2000) Management of Technology. McGraw-Hill, New York, NY.

Nelson (2003) On the uneven evolution of human know-how. J. of Research Policy.

Agre (2004) An anthropological problem, a complex solution. J. of Human Organization.

Baba & Mejabi (1997) Socio-Technical Systems. J. of Human Factors & Industrial Egronomics.

44



Service Science Core Questions: How do work systems reconfigure? What role does innovation play? Can integration relationships be found across different types of work system?

Collaborate(incentives)

Augment(tool)

Automate(self-service)

Delegate(outsource)

ToolSystem

HumanSystem

Help meby doing some

of it for me(custom)

Help meby doing allof it for me

(standard)

The choice tochange work practicesrequires answeringfour key questions:

- Should we? (Value)- Can we? (Technology)- May we? (Governance)- Will we? (Priorities)

Organize People(Socio-economic models with intentional agents)

Harness Nature(Techno-scientific models with stochastic parts)

43

21

Z

Collaborate(1970)

Augment(1980)

Delegate(2000)

Automate(2010)

Experts: High skill people on phones Tools: Less skill with FAQ tools Market: Lower cost geography (India) Technology: Voice response system

Example: Call Centers

45



Example Model: Oliva & Sterman (2001) Quality Erosion in Service Industry

46



Model of service businessProfitability measures for each of the 14 items below…(profits/time; time is life-span, year, quarter, month, week, day, hour, minute, second)

First level measures Second level measures Third level measuresRelationship & Sales Excellence Operations & Delivery Excellence Value Chain & Partnership Excellence

Client-provider negotiations1. value creation2. differentiation3. cost cutting4. compliance5. market insights

Internal to service provider1. providers resources2. investments & incentives3. quality & productivity4. innovation & growth5. life cycle management

External to service provider1. clients resources2. suppliers resources3. complementors resources4. substitutors resources5. academic, government, etc.

clients

proposals & negotiation

engagements &

renegotiation

offerings(solutions)

methods

assets

products

people

service organizations

methods

assets

products

people

service organizations

Governance & Management Excellence

Geographies, Industry Sectors, Solutions

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

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Towards Service Arts & Science…

Arts(Knowledge of

what can be imagined)

Science(Knowledge of

what can be validated)

Policy(Governance)

Technology(Control)

Management(Design of Possible)

Engineering(Design of Possible)

ServiceSystem

Evolution(complex adaptive systems

- Sociotechnical -with dynamics to

create and capture value- Socioeconomic -)

1. Is there a grand challenge problem worthy of both academics (a solution requires more deep knowledge and an integration across discipline silos) and businesses (a solution raises “all ships” by accelerating value creation and capture from service innovations and bestowing businesses with predictable growth advantages)?

2. Will the word “science” evolve in meaning to include methods for expanding knowledge about systems that are difficult or impossible to predict by their very nature – such as social-economic systems that invite “gaming” (as soon as the system becomes a little bit predictable competing dynamics are set in motion to both maintain the predictability and disrupt the predictability)?

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Grand Challenges (per Maglio)

1.The value of method is to enable average performers to operate like higher skill performers. But when is this possible? Under what circumstances? When is it impossible? What are tradeoffs in re-skilling people versus modifying the method? Example: An average cook might seem like an expert in a gourmet kitchen using an easy to follow cookbook.

2. What is the optimal experience-capture to method? What is the best way to go from experience to repeatable behaviors in similar but different client situations --- and with different people executing the method? What is the tradeoff of innovation versus errors in dealing with exceptional cases and differences? How does having a supervisor or mentor that checks performance help?

3. How can get an organization to change when times are good? According to Sam Palimisano in his HBR interview in December, it is easy to change when times are bad (witness IBM in the early 1990s), but how can we structure or encourage change when times are good but might be bad later?

4. What grand challenge problem is worthy of both academics and businesses? Academics need a problem whose solution requires more deep knowledge and an integration across discipline silos, and businesses need a problem whose solution raises “all ships” by accelerating value creation and capture from service innovations and bestowing businesses with predictable growth advantages.

5. Can there be a science of social-technical-economic systems, systems that by their very nature are diffciult or impossible to predict? Will the word “science” evolve in meaning to include methods for expanding knowledge about systems that are difficult or impossible to predict – such as social-economic systems that invite “gaming” (as soon as the system becomes a little bit predictable competing dynamics are set in motion to both maintain the predictability and disrupt the predictability)?

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Work items

Establish the importance of getting more systematic about service innovation for academics, business, and government

Highlight the work of the pioneers and early champions of systematic approaches to service innovation and service science

Review of components of existing degrees requirements and course elements that should be part of a service science curriculum

Define the fundamental research questions and grand challenges that the science is seeking answers to (value if answered, methodologies and tools for answering them, etc.)

Agree on conferences, journals, and other community growth initiatives Explore the role of government and industry, especially with respect to

accessing the fundamental data on which the science will be based Establish a feedback mechanism that surveys graduates who enter IGS to

see what skills they used most and the ones they wish they had learned while in school

Discuss the many roadblocks, challenges, overwhelming political obstacles, etc. to establishing the field.

IBM Research – Almaden Services Research

ISSS 2005, 49th Annual Meeting, Cancun, Mexico | July 4th, 2005

REST IS BACKUP

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Services

Services include government, security, healthcare, education, financial, insurance, retail, wholesale, leisure, entertainment, information, communication, transportation, utilities, professional, and business services

Characteristics of service systemsService systems are made up of clients and providers interacting & investing

effort to coproduce value

Clients and providers, especially businesses, care how much value is created & captures (coproduced), quality, productivity, experience

Clients can play greater (self service) or lesser roles during performance

Clients and providers as economic entities with preferences, capabilities, assets, relationships, roles, and unique histories are transformed by the nature of the service experience

The primary output of the service performance is always transformed clients and providers – assets, preferences, capabilities, relationships, roles, history

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Why Service Science? The world needs more service innovation & systematic approaches to service innovation must be interdisciplinary

Technology Innovation Business Innovation

Social-Organizational Innovation Demand

Innovation

ServiceScience

Science &Engineering

SocialSciences

SSEM = Service Sciences, Engineering, and Management

BusinessManagement

&Administration

GlobalEconomy& Markets

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Trend 1: Rise of the Service Economy Top Ten Labor Forces by Size(WW 50% Agriculture., 10% Goods, 40% Services)

% US Labor Force by Sector

(A) Agriculture:Value from harvesting nature

(S) Services:Value from enhancing, protecting, distributing, understanding, and customizing things(G) Goods:

Value from making products

Service sector has rapidly grown in US (70% of labor force)

Other nations are following the same pattern (urbanization, infrastructure, and business growth drive the shift)

Service sector buys 80% of the $2.1T IT annual spend (worldwide)

Four service industries are large and growing their IT spend rapidly to transform processes: financial and information, professional and business, retail and wholesale, and government

IT spend contributes to rapid growth of productivity (GDP/Jobs) as well

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Trend 2: Rise and Shift in Service ResearchAcademic centers have slowly increased over the past 20 years to advance the practical and theoretical knowledge of services businesses

Initially, the emphasis in service research and teaching was on B2C capacity and demand models – because underutilized capacity hurts productivity. Also demand that is simply waiting in queues may be lost or damage client satisfaction. Service places like banks, airports, hotels, etc.

Part 3: Managing Service OperationsChapter 10. Forecasting Demand for ServicesChapter 11. Managing Waiting LinesChapter 12. Queuing Models and Capacity PlanningChapter 13. Managing Capacity and Demand(Excerpt from Fitzsimmons & Fitzsimmons)

Increasingly over the past ten years, the new frontier of service research and teaching has shifted more and more towards B2B business process transformation models. Process re-engineering, IT productivity paradox, and other case studies highlight the need to constantly redesign work to improve productivity through multiple types of innovation (demand, business value, process, and organization)

“The biggest costs were in changing the organization. One way to think about these changes is to treat the Organizational costs as an investment in a new asset. Firms make investments over time in developing a newprocess, rebuilding their staff or designing a neworganizational structure, and the benefits from theseInvestments are realized over a long period of time.”Eric Brynjolfsson, “Beyond the Productivity Paradox”

Service research and practice agree that effective communication in service engagements depends on an appreciation of multiple factors: technology and process, business value and strategy, and organizational culture and people. With proper coordination between these per- spectives BPTS engagements succeed. A top adaptive work force requires people with a level of capability and familiarity in many relevant areas. BPTS = Business Process Transformation Services

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What makes us smart? How will NBIC impact this? Cognitive technologies = things that make us smart (What to measure?)

Growth of capabilities to create and achieve goals, intentionally and parsimoniously

Growth of win-win games over win-lose; higher payoffs; lower risks; lower maintenance (entropy)

Growth of capabilities to sense, communicate, decide, act; Growth of capabilities to bud and scale

Slowly: In the past 12 billion years (2 million years), evolution has been driving what has been things (humans) smarter (natural process - slow)

Atoms, Molecules, Cell, Life, Body, Nerves, Brains, Swarms, Humanity… (See next slide!)

Rapidly (Gen): In the past 200 years, organizations have been driving what has been making us smarter (human process - faster)

230 years ago it was government – rise of modern democracy (intangible - sustainable freedom)

150 years ago it was business – rise of modern managerial firm (intangible - efficient value)

Distributed intelligence - environment flooded with people!!! (Two slides away!)

Very Rapidly (Sub-Gen): In the past 50 years, technology has been driving what has been making us smarter (human process – faster still)

Only in the last fifty years with the discovery of DNA (bio), creation of digital computing technology (info), ability to manipulate matter at the atomic scale (nano), and rapid advancement of cognitive science to better understand human thought processes (cogno) has information processing in natural, social, and technological substrates been perceived as “converging” – discoveries in one area leading to advances/applications in the others

Shadows in the Sun, by Wade Davis“Ethnosphere: It's really the sum total of all the thoughts, beliefs, myths, and institutions brought into being by the human imagination. It is humanity's greatest legacy, embodying everything we have produced as a curious and amazingly adaptive species.”

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The Company of Strangers: A Natural History of Economic Life

Human beings are the only species in nature to have developed an elaborate division of labor between strangers. Even something as simple as buying a shirt depends on an astonishing web of interaction and organization that spans the world. But unlike that other uniquely human attribute, language, our ability to cooperate with strangers did not evolve gradually through our prehistory. Only 10,000 years ago--a blink of an eye in evolutionary time--humans hunted in bands, were intensely suspicious of strangers, and fought those whom they could not flee. Yet since the dawn of agriculture we have refined the division of labor to the point where, today, we live and work amid strangers and depend upon millions more. Every time we travel by rail or air we entrust our lives to individuals we do not know. What institutions have made this possible?

In The Company of Strangers, Paul Seabright provides an original evolutionary and sociological account of the emergence of those economic institutions that manage not only markets but also the world's myriad other affairs.

Drawing on insights from biology, anthropology, history, psychology, and literature, Seabright explores how our evolved ability of abstract reasoning has allowed institutions like money, markets, and cities to provide the foundation of social trust. But how long can the networks of modern life survive when we are exposed as never before to risks originating in distant parts of the globe? This lively narrative shows us the remarkable strangeness, and fragility, of our everyday lives.

The Company of Strangers : A Natural History of Economic Lifeby Paul Seabright

Jim Spohrer, ([email protected]) Director, Almaden Services Research

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Transcript of Jim Spohrer, ([email protected]) Director, Almaden Services Research