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Service Science as a Science of the Artificial. Josephine Cheng, IBM Almaden Research Center, Jim Spohrer, IBM Research December 8, 2008. Support from IBM and NSF grant IIS-0527770 2006-09 is gratefully acknowledged. Outline & Thesis. Service Worlds That Compute Value

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Service science as a science of the artificial l.jpg

Service Science as a Science of the Artificial

Josephine Cheng, IBM Almaden Research Center,

Jim Spohrer, IBM Research

December 8, 2008

Support from IBM and NSF grant IIS-0527770 2006-09 is gratefully acknowledged.


Outline thesis l.jpg

Outline & Thesis

  • Service Worlds That Compute Value

  • Sciences of the Artificial

  • Service Science

Progress, or successful universal structural change in artificial worlds, is characterized by higher density value-cocreation interactions (service) between entities that are capable of judging, or computing the relative merits of, alternative possible future artificial worlds. Today, we are entities in one possible artificial world with money (“universal exchange medium”), rights (“universal rule of law”), and literacy (“universal education”) as three examples of progress. Money, rights and literacy are judged as progress because they support higher density value-cocreation interactions between entities. Service science calls these entities, whether people, businesses, or nations, service system entities. They interact via knowledge-based value-propositions, both formal and informal, connected into large service system networks and part of a global service system ecology.

Service science studies artificial worlds, service worlds that compute value.

Physics, chemistry, biology, etc. study natural worlds.


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Outline of next section

  • Service Worlds That Compute Value*,**

    • Economics & social science

    • Operations, marketing & management

    • Computing, software & information

    • Systems, networks & engineering

    • Psychology & experience design

  • Sciences of the Artificial

  • Service Science

* = All of these service worlds matter to IBM

** = Service phenomena are value-cocreation phenomena


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Service Worlds: Economics and Social ScienceGlobal change in what people do and how value is created

Ten Nations

Total 50% of World Wide Labor

A = Agriculture, G = Goods, S = Services

US Employment History & Trends

2005

1980-2005

PC Age

United States

(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 largest labor force migration in human history is underway, driven by global communications, business and technology growth, urbanization and low cost labor

International Labor Organization


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Service Worlds: Economics and Social ScienceInformation services is where recent growth is

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

The Origin

of Wealth

by Eric D.

Beinhocker

2M years as hunting clans/bands

10K years as farm families

200 years as factory workers

60 years (so far) as knowledge

workers in organizations

and now digital networks

The Pursuit of Organizational Intelligence,

By James G.

March

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


Service worlds economic and social science knowledge intensive service activities is growing most l.jpg

Service Worlds: Economic and Social ScienceKnowledge-intensive service activities is growing most

US Gross Domestic Product

Products

Services

Material

11%

30%

Information

& Organization

9%

50%

  • Based on Uday Karmarkar, UCLA

  • (Apte & Karmarkar, 2006)


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Service Worlds: Economics and Social ScienceHistorical cross-over point recently achieved

In 2006 the service sector’s share of global employment overtook agriculture for the first time, increasing from 39.5% to 40%. Agriculture decreased from 39.7% to 38.7%. The industry sector accounted for 21.3% of total employment.

- International Labour Organization

http://www.ilo.org/public/english/region/asro/bangkok/public/releases/yr2007/pr07_02sa.htm


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“…America’s service sector had a $3.7 billion trade surplus with China...”

“China is now the ninth largest purchaser of American services.”

Service Worlds: Economics and Social SciencePractical consequences found in trade statistics

Wall Street Journal Oct 30th 2007


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Service Worlds: Operations, Marketing, and Management A classification of services

Teboul, J. (2006). Service is Front Stage: Positioning Services for Value Advantage, Palgrave.


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Service Worlds: Operations, Marketing, and Management Front stage and back stage

Teboul, J. (2006). Service is Front Stage: Positioning Services for Value Advantage, Palgrave.


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Service Worlds: Operations, Marketing, and Management The service-profit chain

The service-profit chain establishes the link between profitability, customer satisfaction, and employee satisfaction.

Heskett, J. L., Jones, T. O., Loveman, G. O., Sasser, W. E., Schlesinger, L. A. (1994). Putting the service profit chain to work. Harvard Business Review, 72, 164 – 174.


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Service Worlds: Operations, Marketing, and ManagementCustomer input is critical & major source of process variation

Sampson, S. E. (2001). Understanding service businesses: Applying principles of the unified services theory (2nd ed.). New York: John Wiley & Sons.


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Service Worlds: Operations, Marketing, and Management Scaling and learning curves are different in service operations

IBM Revenue and Profit Mix (2005):

Scaling & learning curves are different for IT manufacturing and IT services

Service Innovation: How to invest to create, improve, and scale up services?


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Service Worlds: Operations, Marketing, and Management Scaling service operations

Spohrer, J., Maglio, P. P., Bailey, J. & Gruhl, D. (2007). Steps toward a science of service systems. Computer, 40, 71-77.


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Reaching the Goal: How Managers Improve a Services Business Using Goldratt’s Theory of Constraints

John Arthur Ricketts, IBM

Service Worlds: Operations, Marketing, and Management Service innovation deals with creating, improving, and scaling

  • “Theory of Constraints (TOC) gets its name from the fact that all enterprises are constrained by something. If they weren’t they could grow as large and as fast as they wanted… So the first step in applying TOC is to figure out precisely where the constraints are….”

  • Three types of constraints:

    • Internal

    • External

    • Interface


Service worlds computing software information web services l.jpg

WSDL Structure

Service

Port

(e.g. http://host/svc)

Port

Binding

(e.g. SOAP)

Binding

Abstract interface

portType

operation(s)

inMesage

outMessage

Service Worlds: Computing, Software & Information Web Services


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Service Worlds: Computing, Software & Information Service Oriented Architecture (SOA)


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New Hybrid Compute & Information Services Appear in the Cloud

Service Worlds: Computing, Software & Information Cloud and IT Service Management – ITIL v3


Service worlds computing software information tim chou s model seven book business models l.jpg

1

Traditional

2

Open Source

3

Outsourcing

4

Hybrid

5

Hybrid+

6

SaaS

7

Internet

$4000/user

(one time)

$0/user

$4000/user

(one time)

$4000/user

(one time)

$300/user/

month

<$100/user/

month

Ads

Transactions

Embedded

(< $10/user/

Month)

SW

Support

Management

$800/user/

year

$1600/user/

year

$800/user/

year

$800/user/

year

Bid

<1300/user

/month

$150/user/

month

@H

@C

@H

@C

@H

@C

RedHat

MySQL…

IBM

EDS…

ORCL

Blackbaud..

Callidus…

Webex

Salesforce

WoW..

eBay

Google

Amazon…

Service Worlds: Computing, Software & Information Tim Chou’s “Model Seven” Book – Business Models

From Tim Chou’s Model Seven


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Value networks andservice ecosystems

Service Worlds: Systems, Networks, and Engineering Ecology of service system entities that interact


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IBM Systems Journal

Service Worlds: Systems, Networks, and Engineering Conceptual model of service value network

Rouse and Basol (2008)


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20th

21st

Century

Century

Service Worlds: Systems, Networks, and Engineering IBM’s evolution to a globally integrated enterprise (GIE)

A globally integrated enterprise -- business in a connected world

The international era -- exporting

The multinational era -- replicating

  • IBM is formally established in 1924 ($11M in revenue; 3384 employees) with sales operations in Canada, Latin America, Europe & Asia; 3 manufacturing facilities completed in Europe by end of decade

  • “Mini” IBM sales companies established in all major countries of operation, each with full-blown back-office functions e.g., HR, Finance, Marketing, Procurement

  • Seeded mfg in select countries to temper risk of nationalization

  • Over 200,000 employees Services Delivery (incl. ISC) across 50 delivery centers in 21 countries

  • 12 Global Shared Services Units

  • Nearly 2/3 of revenue outside US


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Optimization

Service Worlds: Systems, Networks, and Engineering Supply chain and workforce optimizations


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Service Worlds: Psychology & Experience DesignBehavioral science for better service design


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Service Worlds: Psychology & Experience Design The Psychology of Waiting Lines


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Peer Insights

Service Innovation by Design

Service Worlds: Psychology & Experience Design Service Innovation by Design

From Peer Insights “Seizing the Whitespace”


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Summary of last section

  • Service Worlds That Compute Value*

    • Economics & social science

    • Operation, marketing & management

    • Computing, software & information

    • Systems, networks & engineering

    • Psychology & experience design

  • Sciences of the Artificial

  • Service Science

* = All of these service worlds matter to IBM


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Outline of next section

  • Service Worlds That Compute Value

  • Sciences of the Artificial

    • Natural and Artificial Worlds

    • Economic Rationality: Adaptive Artifice

    • Psychology & Learning

    • Design

    • Social Planning

    • Complexity

  • Service Science


Sciences of the artificial natural and artificial worlds l.jpg

Sciences of the Artificial: Natural and Artificial Worlds

  • The world we live in today is much more a man-made, or artificial, world than a natural world.

  • Four indicia that distinguish the artificial from the natural:

    • Artificial things are synthesized (though not always or usually with full forethought) by human beings.

    • Artificial things may imitate appearances in natural things while lacking, in one or more respects, the reality of the latter.

    • Artificial things can be characterized in terms of functions, goals, adaptation.

    • Artificial things are often discussed, particularly when they are being designed, in terms of imperatives (“ought to”) as well as descriptives.

  • The computer is a member of an important family of artifacts called symbol systems, or more explicitly, physical symbol systems. Physical symbol systems can often substitute for things in the natural world and each other.


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Sciences of the Artificial:Economic Rationality: Adaptive Artifice

  • Economics exhibits in purest form the artificial component in human behavior, in individual actors, business firms, markets, and the entire economy.

  • We can interpret this bare-bones theory of the firm either positively (as describing how business firms behave) or normatively (as advising how to maximize profits).

  • Today several branches of applied science assist the firm to achieve procedural rationality. One of them is operations research (OR); another is artificial intelligence (AI). Mathematics and heuristic search are important tools for rational actors.

  • Game theory’s most valuable contribution has been to show that rationality is effectively undefinable when competitive actors have unlimited computational capabilities for outguessing each other, but that problem does not arise acutely in a world, like the real world, of bounded rationality.

  • Each species in the ecosystem is adapting to an environment of other species evolving simultaneously with it. The evolution and the future of such systems can only be understood from a knowledge of their histories.


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Sciences of the Artificial:Psychology and Learning

  • Human beings, viewed as behaving systems, are quite simple. The apparent complexity of our behavior over time is largely a reflection of the complexity of the environment in which we find ourselves.

  • …behavior is adapted to goals, hence is artificial, hence reveals only those characteristics of the behaving system that limit the adaptation.

  • The adaptiveness of the human organism… makes it an elusive and fascinating target of our scientific inquiries – and the very prototype of the artificial.

  • Computers have transported physical symbol systems from the platonic heaven of ideas to the empirical world of actual processes carried out by machines or brains, or by the two of them working together.


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Sciences of the Artificial:Design

  • In the past much, if not most, of what we knew about design was intellectually soft, intuitive, informal, and cook-booky.

  • The artificial world is centered precisely on this interface between the inner and the outer environments; it is concerned with attaining goals by adapting the former to the latter. The proper study of those who are concerned with the artificial is the way in which that adaptation of means to environments is brought about – and central to the process of design itself.

  • In substantial part, design theory is aimed at broadening the capabilities of computers to aid design…

  • Design is a process of search for alternatives in a space of possible worlds.


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Sciences of the Artificial:Social Planning

  • As to the founding fathers it is instructive to examine their own views of their goals, reflected in The Federalist… What is striking about these documents is their practical sense and awareness they exude of the limits of foresight about large human affairs.

  • As we look back on such design efforts and their implementation, and we contemplate the tasks of design that are posed in the world today, our feelings are mixed.

    • We are energized by the great power our technological knowledge bestows on us.

    • We are intimidated by the magnitude of the problem it creates or alerts us to.

    • We are sobered by the very limited success – and some disastrous failure – of past efforts to to design on the scale of whole societies.

  • Data about the future – predictions – are commonly the weakest points in the armor of fact.

  • Who is the client? It may seem peculiar to ask, “Who is the client?” when speaking of the design of large social systems.


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Science of the Artificial:Complexity

  • Roughly, by complex system I mean one made up of a large number of parts that have many interactions.

    • …in such systems the whole is more than the sum of the parts in the weak but important pragmatic sense that, given the properties of the parts and the laws of their interactions, it is not trivial to infer the properties of the whole.

  • Business firms, governments, and universities all have a clearly visible parts-within-parts structure.

    • But formal organizations are not the only, or even the most common, kind of social hierarchy. Almost all societies have elementary units, called families, which may be grouped into villages or tribes, and these into larger groupings, and so on.

  • Information theory explains organized complexity in terms of the reduction of entropy (disorder) that is achieved when systems (organisms, for example) absorb energy from external sources and convert it to pattern or structure.

  • Feedback controls shows how a system can work towards goals and adapt to a changing environment, thereby removing mystery from teleology.

  • The notion of substituting a process description for a state description of nature has played a central role in the development of modern science. Dynamics laws… provided the clue for the simple description of the complex.


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Summary of last section

  • Service Worlds That Compute Value

  • Sciences of the Artificial

    • Natural and Artificial Worlds

    • Economic Rationality: Adaptive Artifice

    • Psychology & Learning

    • Design

    • Social Planning

    • Complexity

  • Service Science


Outline of next section36 l.jpg

Outline of next section

  • Service Worlds That Compute Value

  • Sciences of the Artificial

  • Service Science

    • Stages of scientific maturity

    • Grand challenge problem

    • First small steps


Service science stages of scientific maturity collect and classify phenomena l.jpg

Service Science: Stages of Scientific MaturityCollect and classify phenomena

Early Stage

Collect and Classify

(Biology)

Carl Linnaeus,

the father of modern

taxonomy and ecology,

and a pioneer of the

science of biology

Mature Stage

Unify and Mathematize

(Electro-Magnetism)


Service science stages of scientific maturity service system entities are diverse and complex l.jpg

A. Informal Service Systems

B. Formal Service Systems

1. Social Systems

Human Systems/Sociotechnical Systems

Human Cultures

2. Political Systems

Governed Systems

Value Systems

3. Economics Systems

Markets and Organizations

Firms or Hierarchies

Economic Institutions

Gray Markets

4. Legal Systems

Legislative, Judicial, Executive Separation

5. Organizational Systems

Managed Systems

Open Source Communities

6. Information Systems

Linguistic Systems

Mathematical Systems

Physical Symbol Systems

7. Engineered Systems

Technological Systems

Designed Systems

8. Ecological Systems

Evolved Systems

Nature’s Services

Service Science: Stages of Scientific MaturityService system entities are diverse and complex

A.

1.

2.

8.

3.

B.

7.

4.

6.

5.

“The goal of science is to make the wonderful and complex understandable and simple – but not less wonderful.” – Herb Simon, The Sciences of the Artificial


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CBM: Component Business Model

WBM and RUP: Work Practices & Processes

SOA: Technical Service-Oriented Architecture

Key Performance Indicators (KPIs)

IBM IBV: Component Business Models

Service Science: Stages of Scientific MaturityIBM has begun to systematically map and classify diverse service systemsindustry by industry, component by component, measure by measure…

IEEE Computer, Jan 2007


Service science stages of scientific maturity component business modeling cbm l.jpg

Service Science: Stages of Scientific MaturityComponent business modeling (CBM)

  • Component Business Modeling is a framework for analyzing and modeling a business

    • for organizing and grouping business activities into components

  • In a component business map: activities are grouped along two coordinates:

    • business competencies (columns) and accountability levels (rows)

Cherbakov, L. Galambos, G, Harishankar, R., Kalyana, S. & Rackham, G. (2005). Impact of service orientation at the business level. IBM Systems Journal, 44, 653 – 658.


Service science stages of scientific maturity component business modeling cbm41 l.jpg

Service Science: Stages of Scientific MaturityComponent business modeling (CBM)

  • Component Business Modeling is a framework for analyzing and modeling a business

    • for organizing and grouping business activities into components

  • In a component business map: activities are grouped along two coordinates:

    • business competencies (columns) and accountability levels (rows)

Cherbakov, L. Galambos, G, Harishankar, R., Kalyana, S. & Rackham, G. (2005). Impact of service orientation at the business level. IBM Systems Journal, 44, 653 – 658.


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Component Business Model to Help Decompose Your BusinessExperience and Know-how from Thousands of Client Engagements

Component Business Modeling tool 2.0

  • 70+ maps supporting 17 industries

  • 23 enhanced with key performance indicators (KPI)

  • Over 2,000 trained CBM specialists armed with the CBM tool

  • 30 CBM patents filed

  • CBM tool license available to clients

Integrates with WebSphere Business Modeler

Presentation to Gartner in October 2007, by R. Leblanc


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Integrating Component Business Models with Industry Process Models

+

=

Component Business Models (CBM) and Tool

Industry Process Models in WBM, built by BPM CoE, leveraging APQC’s Process Classification Framework

Result: business transformation engagements delivered more quickly, through more industry-specific insights and more powerful CBM Tool

IBM is bringing together its Business Process Management Center of Excellence (BPM CoE), IBM Research, and the Global Business Solution Center (GBSC) to map Component Business Models (CBM) to Industry Process Models

Presentation to Forrester in November 2007, by T. Rosamilia


Service science stages of scientific maturity mechanisms of economic evolution l.jpg

Standard operating procedures are passed down from one generation to the next

Successful processes can be copied, though transfer is not costless

Learning curves

Patent protection

Evolution of firms … best understood through an examination of history

Service Science: Stages of Scientific MaturityMechanisms of economic evolution

“If the adaptation of both the business firm and

biological species to their respective

environments are instances of heuristic search…

we will still have to account for the mechanisms

that bring the adaptation about. In biology the

mechanism is located in the genes and their

success reproducing themselves. What is the

gene’s counterpart in the business firm?

Nelson and Winter suggest that business firms

accomplish most of their work through

standard operating procedures – algorithms for

making daily decisions that become routinized and

are handed down from one generation of

executives and employees to the next.”

- Herb Simon, Sciences of the Artificial


Service science stages of scientific maturity mechanisms of economic evolution need for a tool l.jpg

Service Science: Stages of Scientific MaturityMechanisms of economic evolution – need for a tool

  • Every decade both HPC and PC platforms increase

  • complex simulation capabilities by 1000x.

  • - HPC: (2000 106), (2010 109), (2020 1012), (2030 1015) …

  • - PC: (2000 103), (2010 106), (2020 109), (2030 1012) …

CBM-based Industry Simulations - 2013?

15

12

Heart Simulation

Log Entities

9

Universe Simulation

Brain Simulation

Projected

Simulation Capability

6

Earth Simulator

2030

2000

2010

2020


Service science grand challenge problem discover a moore s law for service system improvement l.jpg

Service Science: Grand Challenge ProblemDiscover a Moore’s Law for service system improvement

Service System/Network

1. People

2. Technology

3. Shared Information

4. Organizationsconnected by value propositions

Computational System

More win-win interactions, more value

Requires investment roadmap

More transistors, more powerful

Requires investment roadmap


Service science grand challenge problem towards a moore s law a smarter planet l.jpg

Service Science: Grand Challenge Problem Towards a Moore’s Law – “A Smarter Planet”

  • Computational power doubles at a predictable rate.

  • Are there analogous capability-doubling laws that apply in services?

  • Suppose that traces of human activity in particular service systems double at some rate, and that these human activity data lead to specific opportunities for improved or increased service productivity or quality.

  • Consider Amazon.com: The quality of recommendations depends on accurate statistics – the more purchases made, the better the statistics for recommendations.

  • Three improvement “laws” that might be applicable in services:

    • The more an activity is performed (time period doubling, demand doubling), the more opportunities to improve.

    • The better an activity can be measured (sensor deployment doubling, sensor precision doubling, relevant measurement variables doubling) and modeled, the more opportunities to improve.

    • The more activities that depend on a common sub-step or process (doubling potential demand points), the more likely investment can be raised to improve the sub-step.


Service science grand challenge problem towards a moore s law accelerating adoption l.jpg

Supply:Knowledgecreation rate

Demand:Customeradoption rate

Servicesystem/networkgrowth

Howtoinvest?

100

Television

Electricity

Telephone

Radio

Automobile

VCR

50

PC

% Adoption

Cellular

Internet

0

25

50

75

100

125

150

Years

Service Science: Grand Challenge Problem Towards a Moore’s Law – accelerating adoption


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Service Science is emerging as a distinct field. Its vision is to discover the underlying logic of complex service systems and to establish a common language and shared frameworks for service innovation. To this end, an interdisciplinary approach should be adopted for research and education on service systems.

Service Science: Grand Challenge Problem Towards a Moore’s Law – “Succeeding through Service Innovation”

  • For education: Enable graduates from various disciplines to become T-shaped professionals or adaptive innovators; promote SSME education programmes and qualifications; develop a modular template-based SSME curriculum in higher education and extend to other levels of education; explore new teaching methods for SSME education.

  • For research: Develop an interdisciplinary and intercultural approach to service research; build bridges between disciplines through grand research challenges; establish service system and value proposition as foundational concepts; work with practitioners to create data sets to understand the nature and behaviour of service systems create modelling and simulation tools for service systems.

  • For business: Establish employment policies and career paths for T-shaped professionals; review existing approaches to service innovation and provide grand challenges for service systems research; provide funding for service systems research; develop appropriate organisational arrangements to enhance industry-academic collaboration; work with stakeholders to include sustainability measures.

  • For government: Promote service innovation and provide funding for SSME education and research; demonstrate the value of Service Science to government agencies; develop relevant measurements and reliable data on knowledge- intensive service activities; make public service systems more comprehensive and citizen-responsive; encourage public hearings, workshops and briefings with other stakeholders to develop service innovation roadmaps.

http://www.ifm.eng.cam.ac.uk/ssme/


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Service Science: Grand Challenge Problem Towards a Moore’s Law – Call to create Service Innovation Roadmaps (SIR) reports

5. Call for actions

1. Emerging demand

2. Define the domain

3. Vision and gaps

4. Bridge the gaps

Service Innovation

Growth in service GDP and jobs

Service quality

& productivity

Environmental friendly & sustainable

Urbanisation &

aging population

Globalisation & technology drivers

Opportunities for businesses, governments and individuals

Service

Systems

Customer-provider interactions that enable value cocreation

Dynamic configurations of resources: people, technologies, organisations and information

Increasing scale, complexity and connectedness of service systems

B2B, B2C, C2C, B2G, G2C, G2G service networks

Stakeholder

Priorities

Education

Research

Business

Government

The white paper offers a starting point to -

Service

Science

To discover the underlying principles of complex service systems

Systematically create, scale and improve systems

Foundations laid by existing

disciplines

Progress in academic studies and practical tools

Gaps in knowledge and skills

Develop programmes & qualifications

Skills

& Mindset

Encourage an interdisciplinary approach

Knowledge

& Tools

Develop and improve service innovation roadmaps, leading to a doubling of investment in service education and research by 2015

Employment

& Collaboration

Policies

& Investment

Glossary of definitions, history and outlook of service research, global trends, and ongoing debate

“Succeeding through Service Innovation” Whitepaper: A Framework for Progress

(http://www.ifm.eng.cam.ac.uk/ssme/)


Service science first small steps discipline classification system for service worlds l.jpg

Service Science: First Small StepsDiscipline classification system for service worlds

General

Service Science Education

Research in Service Science

Service Science Policy

History of Services

Case Studies

Miscellaneous

Service Foundations

Service Theory

Service Philosophy

Economics of Services

Theoretical Models of Services

Mathematical Models of Services

Service Complexity Theory

Service Innovation Theory

Service Foundations Education

Service Engineering

Service Engineering Theory

Service Operations

Service Standards

Service Optimization

Service Systems Engineering

Service Supply Chains

Service Engineering Management

Service Systems Performance

Service Quality Engineering

New Services Engineering

Computer Services

Information Technology Services

Service Engineering Education

Service Management

Service Marketing

Service Operations

Service Management

Service Lifecycle

Service Innovation Management

Service Quality

Human Resources Management

Customer Relationship Management

Services Sourcing

Services Law

Globalization of Services

Service Business Education

Human Aspects of Services

Service Systems Evolution

Behavioral Models of Services

Decision Making in Services

People in Service Systems

Organizational Change in Services

Social Aspects of Services

Cognitive Aspects of Services

Customer Psychology

Education in Human Aspects of Services

Service Design

Service Design Theory

Service Design Methodology

Service Representation

Aesthetics of Services

Service Design Education

  • Service Arts

    • Service Arts Theory

    • Traditional Service Arts

    • Performance Arts

    • History of Service Arts

    • Service Arts Education

  • Service Industries*

    • The Service Industry

    • Utilities

    • Wholesale Trade

    • Retail Trade

    • Transportation and Warehousing

    • Information Services

    • Finance and Insurance

    • Real Estate and Rental

    • Professional and Technical Services

    • Management Services

    • Administrative and Support Services

    • Educational Services

    • Health Care and Social Assistance

    • Arts, Entertainment, and Recreation

    • Accommodation and Food Services

    • Public Administration Services

    • Other Service Industries

Claudio Pinhanez & Paul Kontogiorgis, “A proposal for a service science discipline classification systems,”

Presented at Frontiers in Service Conference, October 2008


Service science first small steps the u s national innovation investment act legislator interest l.jpg

US House and Senate voted to approve on August 2nd,, 2007; President has signed.

SEC. 1106. STUDY OF SERVICE SCIENCE.

(a) Sense of Congress- It is the sense of Congress that, in order to strengthen the competitiveness of United States enterprises and institutions and to prepare the people of the United States for high-wage, high-skill employment, the Federal Government should better understand and respond strategically to the emerging management and learning discipline known as service science.

(b) Study- Not later than 270 days after the date of enactment of this Act, the Director of the Office of Science and Technology Policy, through the National Academy of Sciences, shall conduct a study and report to Congress regarding how the Federal Government should support, through research, education, and training, the emerging management and learning discipline known as service science.

(c) Outside Resources- In conducting the study under subsection (b), the National Academy of Sciences shall consult with leaders from 2- and 4-year institutions of higher education, as defined in section 101(a) of the Higher Education Act of 1965 (20 U.S.C. 1001(a)), leaders from corporations, and other relevant parties.

(d) Service Science Defined- In this section, the term `service science' means curricula, training, and research programs that are designed to teach individuals to apply scientific, engineering, and management disciplines that integrate elements of computer science, operations research, industrial engineering, business strategy, management sciences, and social and legal sciences, in order to encourage innovation in how organizations create value for customers and shareholders that could not be achieved through such disciplines working in isolation.

Service Science: First Small StepsThe U.S. National Innovation Investment Act – Legislator interest


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ENVIRONMENTAL ENGINEERING

It's a growing field, and engineers are needed to clean up existing pollution problems and prevent future ones.

SERVICE SCIENCE, MANAGEMENT, AND ENGINEERING (SSME)

This emerging discipline is getting a big push from industry, including IBM and Hewlett-Packard. SSME combines engineering, computer science, economics, and management to improve the service sector.

Service Science: First Small StepsUS News – Smart Choices Graduate Engineering

http://www.usnews.com/usnews/edu/grad/articles/brief/gbeng_brief_2.php

http://www3.brookings.edu/metro/pubs/20070904_gleiecosystem.pdf


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Service Science: First Small StepsProgress Toward Service Science…

  • Education

    • 200+ courses, programs, or degrees established in 50+ countries

    • 12 centers, seminars, or groups established

  • Government

    • 11+ programs for service research and education in 11 countries

    • $500M+ committed worldwide

  • Industry

    • SRII established to promote service research and innovation agenda, with sponsorship from IBM, Oracle, Xerox, Microsoft and others

  • Association Service SIGs

    • AIS, INFORMS, AMA, etc.


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Service Science: First Small Steps

http://www.ibm.com/university/ssme


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We welcome ideas to accelerate the development of service science

Visit us in

San Jose, CA USA

IBM Almaden

Research Center

One of eight main

IBM Research labs

worldwide

Email: [email protected]

Blog: http://forums.thesrii.org/blog?blog.id=main_blog

Service Research: http://www.almaden.ibm.com/asr/

Service Innovation: http://www.ifm.eng.cam.ac.uk/ssme/


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Herbert A. Simon – Gets our vote as the first service scientist

The Sciences of the Artificial by Herbert A. Simon

  • http://en.wikipedia.org/wiki/Herbert_Simon

  • “Herbert Simon (1916-2001), in the course of a long and distinguished career in the social and behavioral sciences, made lasting contributions to many disciplines, including economics, psychology, computer science, and artificial intelligence. In 1978 he was awarded the Nobel Prize in economics for his research into the decision-making process within economic organizations. His well-known book The Sciences of the Artificial addresses the implications of the decision-making and problem-solving processes for the social sciences. “

Models of a Man :

Essays in Memory of Herbert A. Simonby Mie Augier (Editor), James G. March (Editor)


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People as Service System Entities

  • “All the information workers observed experienced a high level of fragmentation in the execution of their activities. People averaged about three minutes on a task and about two minutes on any electronic device or paper document before switching tasks.”

    • Gloria Mark and Victor M. Gonzalez, authors of “Research on Multi-tasking in the Workplace”


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Families as Service System Entities

  • "The family is the natural and fundamental group unit of society and is entitled to protection by society and the State".

    • Article 16(3) of the Universal Declaration of Human Rights

  • “Developing a Family Mission Statement”

    • Stephen R. Covey, author of The 7 Habits of Highly Effective Families

  • “In the agricultural age, work-life-and-family blended seamlessly.”

    • IBM GIO 1.0


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Cities as Service System Entities

  • “Cities are the defining artifacts of civilisation. All the achievements and failings of humanity are here… We shape the city, and then it shapes us. Today, almost half the global population lives in cities.”

    • John Reader, author of Cities

  • IBM Releases ``IBM and the Future of our Cities'' Podcast

    • IBM Press Release 2005


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Nations as Service System Entities

  • “Understanding economic change including everything from the rise of the Western world to the demise of the Soviet Union requires that we cast a net much broader than purely economic change because it is a result of changes in (1) the quantity and quality of human beings; (2) in the stock of human knowledge particularly as applied to human command over nature; and (3) the institutional framework that defines the deliberate incentive structure of a society.”

    • Douglass C. North, author of Understanding the Process of Economic Change


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Businesses as Service System Entities

  • “…of the 100 entities with the largest Gross National Product (GNP), about half were multi-national corporations (MNCs)… The MNCs do not exist on traditional maps.”

    • Alfred Chandler and Bruce Mazlish, authors of Leviathans

  • “The corporation has evolved constantly during its long history. The MNC of the late twentieth century … were very different from the great trading enterprises of the 1700s. The type of business organization that is now emerging -- the globally integrated enterprise -- marks just as big a leap. “

    • Sam Palmisano, CEO IBM in Foreign Affairs


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Universities as Service System Entities

  • “The contemporary American university is in fact a knowledge conglomerate in its extensive activities, and this role is costly to sustain.”

    • Roger L. Geiger, author of Knowledge and Money: Research Universities and the Paradox of the Marketplace


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Hospitals as Service System Entities

  • “Modern medicine is one of those incredible works of reason: an elaborate system of specialized knowledge, technical procedures, and rules of behavior.”

    • Paul Starr, author of The Social Transformation of American Medicine


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Call Centers as Service System Entities

  • “Call Centers For Dummies helps put a value on customer relations efforts undertaken in call centers and helps managers implement new strategies for continual improvement of customer service.”

    • Réal Bergevin, author of Call Centers For Dummies


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Data Centers as Service System Entities

  • “All data centers are unique, but they all share the same mission: to protect your company’s valuable information.”

    • Douglas Alger, author of Build the Best Data Center Facility for Your Business


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Building tools & organizations – accelerating growth of capabilities

Global Brain: The Evolution of

Mass Mind from the Big Bang

to the 21st Centuryby Howard Bloom

Nonzero : The Logic

of Human Destiny

by Robert Wright


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Progression of phenomena: Emergence of Complex Systems

Physical System

Physics

Culture

People with

mental models

Language

Trust

Tools &

Technology

Organizations

And

Institutions

Value Co-Creation

(Service)

Chemical System

Chemistry

h

Biological System

Biology

Human System

Anthropology

Service System

Service Science

Artificial worlds are

built upon

Natural worlds

Things That Make Us Smart by Donald A. Norman


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“Here is the thesis in a nutshell. All social creatures face a fundamental dilemma – what’s good for the individual is not always what’s good for the group. Humans evolved two distinct new ways to cope with this dilemma. Morals go back to our human origins, and work best in small groups. Markets work best at large scale, and their rise 200 years ago ushered in the modern world.”

Service Worlds: Economics and Social ScienceMorals and Markets: An Evolutionary Account


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Service is a subset of:

Types of entities

Types of interactions

Types of outcomes

Service is:

Service system entities

Value-cocreation interactions(normatively)

Value-cocreation outcomes(normatively)

Competitor Provider Customer Authority

A

S

P

C

(substitute)

OO

OO

LC

LC

SA

SA

PA

PA

value-proposition

change-experience

dynamic-configurations

time

service = value-cocreation

B2B

B2C

B2G

G2C

G2B

G2G

C2C

C2B

C2G

***

provider resources

Owned Outright

Leased/Contract

Shared Access

Privileged Access

customer resources

Owned Outright

Leased/Contract

Shared Access

Privileged Access

Service = Value-Cocreation


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Criminals

Government

Agencies

Users

Insurance

Agents

Competitors

Intermediaries

Consultants

Web Communities

Customers

Managers

Third Parties

Shareholders

Engineers

Banks

eBusinesses

Suppliers

Contractors

Employees

PEOPLE

ORGANIZATIONS

Needs

Experience

Aspirations

AS-IS

Target & Context

TO-BE

Target &

Context

Benefits

OUTCOME

Target &

Context

IF-REDONE

Target &

Context

Learning

Wants

Relationships

Gaps

SERVICE

Side Effects

Goals

Constraints

Sacrifices

Disputes

Responsibilities

Unintended Consequences

Expectations

Insights

SHARED

INFORMATION

TECHNOLOGY

Rational Choices

Procedures

Regulations

Policies

Hardware

Buildings

Plans

Flowcharts

Vehicles

Applications

Diagrams

/ Schematics

Equipment

Rules

Instructions

Tools

Templates

Software

Infrastructure

Schedules

Prices


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