Transcript The Information and Services Economy a.k.a. Business

The Information and Services Economy
a.k.a.
Business Architecture and Services Science
IS210, Week 6
Profs Bob Glushko & Anno Saxenian
UC Berkeley School of Information
Fall 2006
A new dominant logic for marketing
 Marketing in the goods economy: financial
optimization and the 4 P’s
 Product
 Price
 Placement
 Promotion
 Marketing in the services economy: communication
across organizational boundaries
 An ongoing social and economic process
 Knowledge is fundamental source of competitive advantage
 Inherently customer-oriented and relational
 Goods as distribution/delivery mechanisms for services
Emerging services-centered logic
Intangible resources are key
 Service provision, not goods, is fundamental to economic exchange
 Specialized competences (skills and knowledge) or services are
primary goal of exchange;
 Goods are intermediate, not end, products that transmit knowledge
and are used by consumers in value-creation process;
Customers co-create value
 Customers always co-producers of services via relational exchange;
 Value is perceived & determined by consumer;
Role of the enterprise
 The enterprise can only make value propositions;
 Wealth is obtained through application and exchange of specialized
knowledge and skill.
A services economy curriculum
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Marketing strategy: competences and capabilities in creation
of value, resource advantage theory
Management of cross-functional business processes to
support development of capabilities & competences for
market-driven organization
Integrated marketing communication
Consumer behavior: relational
Pricing: building and maintaining value propositions,
management of long-term customer equity
Marketing channels: coordinating marketing networks and
systems
Supply chain mgmt: management of value constellations and
service flows
The core competence of the corporation
“Competitiveness in long run derives from ability to build,
at lower cost and faster than competitors, the core
competencies that spawn unanticipated products.”
 Core competences are collective learning in the
organization—particularly how to coordinate diverse
production skills & integrate multiple technology streams
Sony’s miniaturization capabilities
Citicorp’s operating system for 24/7 operation
 Core competence is communication, involvement, and
deep commitment to working across organizational
boundaries: need to blend deeply specialized and
different types of expertise
Core competence of the corporation II
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Core competence does not diminish with use, but needs
to be nurtured & protected, serve as engines for new
business development
3M sticky tape competence => “post-it” notes, coated
abrasives, magnetic tape, photo film, pressuresensitive tape… (substrates, adhesives, coatings.. .)
Tests for identifying core competencies
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Provides access to variety of markets
Makes significant contribution to perceived customer benefit of
end product
Difficult for competitors to imitate
From core competences to core products
 Core products are the tangible link between core
competences and end products – the components or
subassemblies that contribute value to end products (e.g.
Canon’s desktop laser printer “engines.”)
 To sustain core competence companies seek to maximize
world manufacturing share in core products: producing for
both external and internal customers provides market
feedback as well as revenue that insures maintenance of
core competencies.
 A dominant share in core products allows company to
shape the evolution of applications and end markets.
From SBU model to core competencies
 SBU model of the corporation sees company as
portfolio of autonomous businesses.
 Unit of analysis is discrete businesses with related products
 Resources get trapped (imprisoned) in business units
 Innovation is bounded by immediate opportunities; hinders
hybrid opportunities for innovation
 View company as portfolio of core competencies,
core products, and market-focused core businesses.
 Unit of analysis is businesses and core competencies
 Top management enunciates strategic architecture, builds
competencies for long term
 Strategic architecture makes resource allocation priorities
transparent; provides template for allocation decisions,
forces organization to identify and commit to technical and
business linkages across businesses that will provide
competitive advantage
The challenge: learning v. monitoring
What do modern economic organizations need to do?
Motivate talent, encourage initiative, innovation,
development of core competencies
Coordinate/monitor activities of/between internal
and external units
Organizational options: Devolve decision-making authority and
access to relevant information within corporation, focus on
core competences/products
Governance options:
Maintain ownership of assets but decentralize internally;
Spin-off units to market, focus assets on core competences;
Result is less a hierarchy than a federation or network
Learning by monitoring
Governance options in a network
Arms-length, market relationships between units–
discrete transactions, maximizes autonomy, no trust
Hybrid relationships of co-production, co-design—
”learning by monitoring” with “studied trust”
Institutionalization of continuous, joint conversation about
common goals as well as apportionment of gains and
losses => mutual experimentation and definition of roles
Ownership relationships between units— blind trust,
maximizes control
Business processes, collaborations, and
transactions
“The model of business organization shapes need to
exchange information across organizational
boundaries.” Bob Glushko, Document Engineering
 Business processes are synchronized by loosely
coupled information exchanges using documents
Business process
Business process
transaction
transaction
transaction
transaction
COLLABORATIONS
transaction
transaction
transaction
transaction
Enterprise Boundary
New directions in the social sciences
 W. Brian Arthur “Complexity and the Economy”
Science, 1999
 Duncan J. Watts Six Degrees: The Science of a
Connected Age, 2002
“The story of the sciences in the twentieth Century
in one of a steady loss of certainty. Much of what
was real and machine-like and objective and
determinate at the start of the century, by midcentury was a phantom, unpredictable, subjective,
and indeterminate.”
W. Brian Arthur “The End of Certainty in Economics” Einstein
Meets Magritte Conference, 1994
The end of certainty in economics
 What defined science at start of century?
 The power to predict
 The clear distinction between subject & object
 What does the loss of predictive power in sciences
mean for economics? Other social sciences?
 Economics claims to be a science: a body of wellreasoned knowledge; has maintained “certainty”
 But is the economy like a gigantic machine?
Origins of modern economics
English and Scottish enlightenment, 18th c.
All nature is but Art* unknown to Thee
All Chance, Direction, which thou canst not see
All Discord, Harmony, not understood
All partial Evil, universal Good:
And, spite of Pride, in erring Reason’s spite
One truth is clear, “Whatever IS, is RIGHT”
Alexander Pope An Essay on Man, 1733
*Art: artifice, technique, or mechanism
The search for a grand theory
 Hidden simplicity behind traffickings of traders and
manufactories and butchers and bakers…the
“invisible hand”
 Economy as a gigantic machine; if we understood
the working of its parts we could predict the whole.
 Goal: Grand Unified Theory of economics
 Theory of the consumer, rational human behavior + theory
of the firm = microeconomics
 Aggregate theory of the economy = macroeconomics
 Economics as predictive science becomes
mathematics (e.g. models of rational expectations)
But there were problems . . .
1.
Human beings: not orderly machine components—
they have foibles, caprices, emotions.
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Finessed with “economic man”: perfectly rational being who
reasons perfectly deductively on well defined problems
Technology: destroys the orderly machine by changing
the entire economy.
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Couldn’t be finessed so technology either ignored or treated as
exogenous by economics.
Economic man (subject) needs to operate on welldefined Problems (object) to make orderly, predictive
theory possible. And well defined Problems should
have well-defined Solutions. The solutions are building
blocks for next aggregated level of theory.
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Works for simple problems with one decision maker….
Economics and indeterminacy
 Once you acknowledge that people don’t have complete
information and well defined, predetermined preferences
you encounter problems of logical indeterminacy.
 People create world that forms their expectations, but don’t
(can’t) do so in a perfectly logical deductive way;
 Our ideas and preferences co-create the world that our forecasts
attempt to predict, and problems are indeterminate.
 Impossibility of separating subjects of the economy (the
people that form it) from the object (the economy itself)
creates large areas of indeterminism.
 Examples: Crashes and bubbles
Economy constructed by its agents
 Economy emerges from our subjective beliefs, which in
aggregate structure the micro economy, shape financial
markets, direct flows of capital and govern strategic
behavior and negotiations.
 These subjective beliefs are not determinate in advance:
they co-evolve, arise, decay, change, mutually reinforce
and mutually negate.
 Subject and object cannot be neatly separated.
 Creates possibility of “studied trust” rather than either
opportunism or “blind trust”
Complexity and the economy
Complexity economics as non-equilibrium theory
(vs. standard economics seeks static patterns in
behavioral equilibrium) with nonlinearities and
positive feedbacks: multiple equilibria, increasing
returns, importance of small events.
 Complex systems with multiple elements adapting or
reacting to patterns created by the elements;
 In natural sciences: elements (cells in immune system,
ions in a spin glass) co-create; systems evolve
 Application to economics: human agents become the
elements in the systems (bankers, consumers, firms,
investors) but they do have strategic intent, behavior
The economy as a complex system
The El Farol Bar Problem
 Agents cannot assume or rationally deduce
expectations; must discover them over time
 Failure of beliefs, expectations to converge over time as
predicted by standard economic models; rather divergent
beliefs that exhibit mutually reinforcing expectations
among sub-populations
 Alternating periods of high and low volatility (comparable
to the bubbles and crashes in financial markets)
Out-of-equilibrium theory of the economy: economy as
process-dependent, organic, always evolving
Six degrees: science of a connected age
 Why does a large complex connected systems behave
differently than a dissociated collection of components?
 Small disease outbreak => epidemic
 Crickets chirping => synchronization
 Single genes => genetic traits
 How does individual behavior aggregate to collective
behavior? Parts don’t sum up in a simple fashion, but
interact to generate “bewildering” emergent behavior
 The “science of networks” recognizes that “what
happens and how it happens depends upon the
network” which itself has evolved historically.
Emergent effects
 Complex systems are self-constituting and
coherent systems driven by interaction of
equals, without any central authority or control.
 Need to understand dynamics of the network
and dynamics on the network.
 Importance of phase transitions in different
spheres, from social to chemical to physical.