IBM Research – Almaden Services Research
Why the world needs more systems thinkers
focused 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, (spohrer@us.ibm.com)
Director, Almaden Services Research
ISSS 2005, 49th Annual Meeting, Cancun, Mexico | July 4th, 2005
Service Innovations & Service Science
Today’s Talk
 The world needs more multidisciplinary systems thinkers
Accelerating 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 design
Government, 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 ebusiness and business performance transformation services require new ratio of
specialists to systems thinkers (service scientists)
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IBM Research
© 2005 IBM Corporation
Service Innovations & Service Science
Problem
Need more
system thinkers
•
The Systems View
of the World:
A Holistic Vision
for Our Time
by: Ervin Laszlo
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IBM Research
How We Got Here :
A Slightly Irreverent History
of Technology and Markets
by Andy Kessler
© 2005 IBM Corporation
Service Innovations & Service Science
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:
• governed by feedback, nonlinear, history
Dynamic, tightly coupled,
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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IBM Research
© 2005 IBM Corporation
Service Innovations & Service Science
Q: How do people invest their time?
A: Building and using tools and relationships (organizations) to achieve goals.
(human activities change over time as we develop and use new capabilities)
Humans as Informavore (George A. Miller, 1983)
Source: Pirolli (2002)
Information
Energy
George
Max
5
[
Energy
Time
IBM Research
]
[
]
Useful info
Max
Time
© 2005 IBM Corporation
Service Innovations & Service Science
Building tools & organizations – accelerating growth of capabilities
Billion Years Ago
Natural Processes
Generations Ago
Human Processes
12
Big Bang (EMST)
100,000
Speech
11.5
Milky Way (Atoms)
750
Agriculture
8
Sun (Energy)
500
Writing
4.5
Earth (Molecules)
400
Libraries
3.5
Bacteria (Cell)
40
Universities
2.5
Sponge (Body)
24
Printing
0.7
Clams (Nerves)
16
Accurate Clocks
0.5
Trilobites (Brains)
5
Telephone
0.2
Bees (Swarms)
4
Radio
0.065
Mass Extinctions
3
Television
0.002
Humans
Tools & Clans
Coevolution
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
6
IBM Research
Nonzero : The Logic
of Human Destiny
by Robert Wright
© 2005 IBM Corporation
Service Innovations & Service Science
Coevolution of Institutions, Disciplines, Professions, Application
(governance, exploration, exploitation, diffusion of innovation)
System Evolution
Systems
Layer
Evolution
System Design = Knowledge Value
Laws &
Institutions
Disciplines
& Research
Professions
& Jobs
Technology &
Organizations
Governance
(.gov)
Exploration
(.edu)
Exploitation
(.com)
(Application)
Diffusion of Innovation
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
Sociotech
Systems
HunterGatherers
2M years ago
(15-150 people)
imperial,
chief, priest
Anthropology
Hunter
Fire, Clothing,
Knife, Spear
10K-5K years
(5 million people)
ruler, king,
scribe
History, Law
or
Agricultural
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-Form
Business Org.
Info
Services
50 years ago
(now 6 billion)
politician,
vote
Computer &
Organization
Sciences
Computer
Scientist
Computer,
Search Engine
Natural
Systems
Human
Systems
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© 2005 IBM Corporation
Service Innovations & Service Science
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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IBM Research
© 2005 IBM Corporation
Service Innovations & Service Science
Human Activities: Sociotechnical System Evolution
Estimated world (pre-1800) and then U.S. Labor Percentages by Sector
120
100
Services (Info)
Services (Other)
Industry (Goods)
Agriculture
Hunter-Gatherer
80
60
40
20
20
50
20
00
19
50
19
00
18
50
18
00
20
00
00
0
20 YA
00
0
10 YA
00
0
Y
20 A
00
YA
0
Estimations based on Porat, M. (1977) Info Economy: Definitions and Measurement
The Company of
Strangers : A Natural
History of Economic
Life
by Paul Seabright
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IBM Research
The Pursuit of
Organizational
Intelligence,
by James G. March
Exploitation vs exploration
© 2005 IBM Corporation
Service Innovations & Service Science
Human Population: Sociotechnical System Evolution
“Ethnosphere. sum total of all
the thoughts, beliefs, myths, and
institutions brought into being by the
human imagination”
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IBM Research
Rise of the modern managerial firm
Effects of Agriculture,
Colonial Expansion & Economics,
Scientific Method, Industrialization
& Politics, Education, Healthcare &
Information Technologies, etc.
Shadows in the Sun,
by Wade Davis
The Visible Hand: The
Managerial Revolution in
American Business
by Alfred Dupont Chandler
© 2005 IBM Corporation
Service Innovations & Service Science
Systematic Innovation: Invest & Get Predictable Results
 Moore’s Law – Scaling down helped propel Computer Science
Scale-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 Science
Scale-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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© 2005 IBM Corporation
Service Innovations & Service Science
Approach
Focus on
service systems
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© 2005 IBM Corporation
Service Innovations & Service Science
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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© 2005 IBM Corporation
Service Innovations & Service Science
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.
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
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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.
IBM Research
© 2005 IBM Corporation
Service Innovations & Service Science
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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© 2005 IBM Corporation
Service Innovations & Service Science
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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© 2005 IBM Corporation
Service Innovations & Service Science
IBM Research Worldwide
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IBM Research
© 2005 IBM Corporation
Service Innovations & Service Science
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 Research
© 2005 IBM Corporation
Service Innovations & Service Science
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 11/2004
183.5 teraflops on 3/2004
(Linpack benchmark)
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IBM Research
© 2005 IBM Corporation
Service Innovations & Service Science
What you may not know… IBM helped start computer
science; not out of altruism, but to meet a business need
Now IBM is working with
academics and government
to 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 new
organizational structure, and the benefits from these
Investments are realized over a long period of time.”
Eric Brynjolfsson, “Beyond the Productivity Paradox”
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© 2005 IBM Corporation
Service Innovations & Service Science
Service Science: Why Now? IBM’s perspective
100
90
80
70
60
50
40
30
20
10
0
1982
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IBM Research
Services
Software
Hardware
Other
1988
1994
1998
2003
© 2005 IBM Corporation
Service Innovations & Service Science
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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IBM Research
© 2005 IBM Corporation
Service Innovations & Service Science
Multidisciplinary Nature of
PhDs 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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IBM Research
© 2005 IBM Corporation
Service Innovations & Service Science
Need for service scientists in Research
PhDs in IBM’s Research Division (US)
Engineering and Natural Sciences
Social Sciences
Business and Management
Liberal Arts and Humanities
Other
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IBM Research
© 2005 IBM Corporation
Service Innovations & Service Science
Problem: Motivation & Definitions
 Motivation
Need 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 Definitions
Services: 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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© 2005 IBM Corporation
Service Innovations & Service Science
Why Now?
The world is becoming a service system.
Top Ten Nations by Labor Force Size
(about 50% of world labor in just 10 nations)
A = Agriculture, G = Goods, S = Services
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
>50% (S) services, >33% (S) services
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IBM Research
2004
2004
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 urbanization,
global communications,
low cost labor, business growth
and technology innovation.
© 2005 IBM Corporation
Why Now?: US GNP Today and in the Future
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
Products
Material
Information
Services
11%
30%
9%
50%
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© USK/Sep’04
SI&GIE/27
Service Innovations & Service Science
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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© 2005 IBM Corporation
Service Innovations & Service Science
So, services are…
Pay for performance in which client and provider coproduce value
 High talent performance
Knowledge-intensive business services (business performance transformation
services) (e.g., chef’s, concert musicians)
 High support performance
Environment 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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© 2005 IBM Corporation
Service Innovations & Service Science
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 clientside 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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IBM Research
© 2005 IBM Corporation
Service Innovations & Service Science
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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IBM Research
© 2005 IBM Corporation
Service Innovations & Service Science
High talent performance is on the rise in the US economy
95% of all scientists are alive today.
Type of work
system
1979
Example
1996
All
Services
Goods
Tightly
Constrained
6%
5%
4%
10%
Call center,
Fast food
Unrationalized
Labor
Intensive
25%
25%
26%
15%
Maid, child
care
SemiAutonomous
35%
30%
30%
35%
Admin.,
Manager
High-skill
Autonomous
34%
40%
40%
40%
Executive,
Engineer
From Herzenberg, Alic, Wial (1998)
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IBM Research
© 2005 IBM Corporation
Service Innovations & Service Science
Tip of the hat to Henry Chesbrough, a pioneer.
Henry Chesbrough, IBM Faculty Award, Services Science Pioneer
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IBM Research
© 2005 IBM Corporation
Service Innovations & Service Science
Why Service Science?
New knowledge drives the process of systematic innovation…
Knowledge sources driving service innovations…
Science & Engineering
(Study phenomena Technology
and create new
Innovation
knowledge)
Social-Organizational
Social Sciences
Innovation
(Study phenomena
and create new
knowledge)
Business
Innovation
Business Administration
and Management
(Study phenomena
and create new
knowledge)
Demand
Innovation
Global Economy
& Markets
(Emergence of
new knowledge in
practice!)
SSME = Service Sciences, Management, and Engineering
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IBM Research
© 2005 IBM Corporation
Service Innovations & Service Science
Berkeley’s new ORMS undergraduate major
Rhonda Righter, IBM Faculty Award
http://www.ieor.berkeley.edu/AcademicPrograms/Ugrad/ORMS.pdf
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IBM Research
© 2005 IBM Corporation
Service Innovations & Service Science
Evolution &
Revision
School of
Management
Marketing
Service Marketing
Operations
Service Operations
Accounting
Service Accounting
(Activity-Based Costing)
Contracts & Negotiations
Service Sourcing
(eSourcing)
Management Science
Service Management
Management of
Technology
Management of
Innovation
Operations Research
Service Operations
Industrial & Systems
Engineering
Service Engineering
Computer Science
Service Computing, Web
Services, SOA
Economics
Institutional Economics
Experimental Economics
Psychology
Labor Psychology
(Human Capital Mgmt)
Anthropology
Business Anthropology
School of Engineering
and Science
School of Social Sciences
Organization Theory
Professional Schools
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Medical School, Law School, Education School, Hotel
& Restaurant School, Media & Communications, etc.
IBM Research
Selection &
Aggregation
Transformation
& Integration
Services Sciences, Management, and Engineering
(SSME) and Solutions Engineering
Discipline
Service & Solutions Excellence Centers
(Information Science & Technology Management)
School
© 2005 IBM Corporation
Service Innovations & Service Science
Relationship of Service Science to Existing Academic Areas:
The center balances three key factors: business value, IT process, organizational culture
1. Service Engineering
1990-2004
1900-1960 14. Computer &
Information Sciences
Process: Information Technology
2. Service Operations
15. Management of
Innovation
3. Service Management
4. Service Marketing
6. Agent-based computational economics
17. Operations Research
18. Systems Engineering
28
7. Computational
Organization Theory
21 18
1 11
10
5
13
7
2 17
3
6
4
8 12
15
16 27
22
9 25
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
37
16. Organization Theory
14
5. Social Complexity
People:
Organizational
Culture
1960-1990
IBM Research
23
26
19
20
19. Management Science
20. Game Theory
21. Industrial Engineering
22. Marketing
23. Managerial
Psychology
24
Capital:
Business
Decisions
24. Business
Administration (MBA)
25. Economics
26. Law
27. Sociology
Before 1900 28. Education
© 2005 IBM Corporation
Service Innovations & Service Science
Networked Information Systems
ORGANIZATIONS
TECHNOLOGY
NETWORKED
INFORMATION
SYSTEMS
MANAGEMENT
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IBM Research
© 2005 IBM Corporation
Service Innovations & Service Science
Services Related Programs (small sampling)
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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
IBM Research
© 2005 IBM Corporation
Service Innovations & Service Science
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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IBM Research
© 2005 IBM Corporation
Service Innovations & Service Science
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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IBM Research
© 2005 IBM Corporation
Service Innovations & Service Science
One Policy
Challenge:
Beyond Technology
Patents… Patenting
Business, SocialOrganizational,
Demand Innovations
Source:
Robert M. Hunt
“You can patent that?
Are patents on software and
business models good for
the new economy?”
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IBM Research
© 2005 IBM Corporation
Service Innovations & Service Science
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 Emergent
Khalil, 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.
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IBM Research
© 2005 IBM Corporation
Service Innovations & Service Science
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?
Human
System
Help me
by doing some
of it for me
(custom)
Help me
by doing all
of it for me
(standard)
Tool
System
Collaborate
Augment
(incentives)
(tool)
1
Z
2
Delegate
Automate
(outsource)
(self-service)
3
4
The choice to
change work practices
requires answering
four key questions:
- Should we? (Value)
- Can we? (Technology)
- May we? (Governance)
- Will we? (Priorities)
Organize People Harness Nature
(Socio-economic models with intentional agents) (Techno-scientific models with stochastic parts)
Example: Call Centers
Collaborate
(1970)
Experts: High skill people on phones
44
Augment
(1980)
Tools: Less skill with FAQ tools
IBM Research
Delegate
(2000)
Market: Lower cost geography (India)
Automate
(2010)
Technology: Voice response system
© 2005 IBM Corporation
Service Innovations & Service Science
Example Model:
Oliva & Sterman (2001) Quality Erosion in Service Industry
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IBM Research
© 2005 IBM Corporation
Service Innovations & Service Science
Model of service business
Profitability 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 measures
Relationship & Sales Excellence
Operations & Delivery Excellence
Value Chain & Partnership Excellence
Client-provider negotiations
1. value creation
2. differentiation
3. cost cutting
4. compliance
5. market insights
Internal to service provider
1. providers resources
2. investments & incentives
3. quality & productivity
4. innovation & growth
5. life cycle management
External to service provider
1. clients resources
2. suppliers resources
3. complementors resources
4. substitutors resources
5. academic, government, etc.
13
service
organizations
12
people
11
products
10
assets
9
methods
8
service
organizations
7
people
6
products
5
assets
4
methods
3
offerings
(solutions)
2
engagements &
renegotiation
proposals &
negotiation
clients
1
14
Governance & Management Excellence
Geographies, Industry Sectors, Solutions
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IBM Research
© 2005 IBM Corporation
Service Innovations & Service Science
Towards Service Arts & Science…
Science
(Knowledge of
what can be validated)
Arts
(Knowledge of
what can be imagined)
Technology
Engineering
(Control)
(Design of Possible)
Service
System
Evolution
Policy
Management
(Governance)
(Design of Possible)
(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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IBM Research
© 2005 IBM Corporation
Service Innovations & Service Science
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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IBM Research
© 2005 IBM Corporation
Service Innovations & Service Science
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.
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IBM Research
© 2005 IBM Corporation
IBM Research – Almaden Services Research
REST IS BACKUP
ISSS 2005, 49th Annual Meeting, Cancun, Mexico | July 4th, 2005
Service Innovations & Service Science
Services
 Services include government, security, healthcare, education, financial,
insurance, retail, wholesale, leisure, entertainment, information,
communication, transportation, utilities, professional, and business
services
 Characteristics of service systems
Service 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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IBM Research
© 2005 IBM Corporation
Service Innovations & Service Science
Why Service Science?
The world needs more service innovation & systematic
approaches to service innovation must be interdisciplinary
Technology Innovation
Science &
Engineering
Business Innovation
Business
Management
&Administration
Service
Science
Social-Organizational
Innovation
Social
Sciences
Global
Economy
& Markets
Demand
Innovation
SSEM = Service Sciences, Engineering, and Management
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IBM Research
© 2005 IBM Corporation
IBM Research
Having a vision is not enough …
Bob Sutton, IBM Faculty Award, pro-Service Innovations
Skills +
Incentives +
Resources +
Action Plan
= Change
Skills +
Incentives +
Resources +
Action Plan
= Confusion
Incentives +
Resources +
Action Plan
= Anxiety
Resources +
Vision +
Vision +
Skills +
Incentives +
Vision +
Skills +
Incentives +
Vision +
Skills +
Action Plan
= Frustration
Action Plan
= Slow change
Structure
Resources +
= False starts
Strategy
53
IBM Confidential
Implement
Process
People
Tools
Culture
Vision +
Operations
© Copyright IBM Corporation 2004
Service Innovations & Service Science
Trend 1: Rise of the Service Economy
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
Top Ten Labor Forces by Size
(WW 50% Agriculture., 10% Goods, 40% Services)
% US Labor Force by Sector
(S) Services:
Value from enhancing,
protecting, distributing,
understanding, and
customizing
(G) Goods:
things
Value from
making products
(A) Agriculture:
Value from
harvesting nature
IT spend contributes to rapid growth of
productivity (GDP/Jobs) as well
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IBM Research
© 2005 IBM Corporation
Service Innovations & Service Science
Trend 2: Rise and Shift in Service Research
Academic 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.
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 reengineering, 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)
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.
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IBM Research
“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 new
process, rebuilding their staff or designing a new
organizational structure, and the benefits from these
Investments are realized over a long period of time.”
Eric Brynjolfsson, “Beyond the Productivity Paradox”
Part 3: Managing Service Operations
Chapter 10. Forecasting Demand for Services
Chapter 11. Managing Waiting Lines
Chapter 12. Queuing Models and Capacity Planning
Chapter 13. Managing Capacity and Demand
(Excerpt from Fitzsimmons & Fitzsimmons)
BPTS = Business Process Transformation Services
© 2005 IBM Corporation
Service Innovations & Service Science
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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IBM Research
© 2005 IBM Corporation
Service Innovations & Service Science
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 Life
by Paul Seabright
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© 2005 IBM Corporation