research review network economies innovators
DESCRIPTION
Research Review on Network Economies. Includes an overview of the research agenda for CFB and explanation of innovation.TRANSCRIPT
Center for Future Banking
Network Economies
Research Review
November 10th, 2008
Confidential
1057 blogs 2007 French Presidential Election
Video links:
MS future vision on retail banking
ING Living Tomorrow - Retail Banking
2015 Banking Retrospective
Presentation by: Ray Garcia
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Agenda
Innovators Alignment
Research Plan
Research Approach
Network Economies
2015 Outlook
Closing Remarks
2004 Oil Money contributions
to political campaigns
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Innovators Alignment
Innovators alignment
Roles and Interaction
1924 Radial Org Char
showing concentration of power
Innovator Alignment | Research Plan | Research Approach | Network Economies | 2015 Outlook
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The Research Innovators
Your Role
Create a vision and give voice to the future of banking
Develop and embody the grand challenges
Inform your business innovation through research
Foster an innovation culture
Charter research activities in collaboration with CFB
Find the opportunities to apply the research findings
Innovate associates, product, and markets
Think BIG and create entire new lines of business
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Research Innovator Interaction
How we’ll interact
Speculate the innovation
Spot what remains to be known
Identify research that needs to be pursued
CFB finds who is working on the big problem already
Sponsor the research with CFB
Joint innovation and Research report to Executive Advisory Committee
Map of They Rule Corp Boards
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The Innovators Challenge
Visioning that does not exist today and may be difficult to describe what will be tomorrow
Overcoming the fear of failure
Measuring risk and calculating when it too much or not enough
Treating ideas as a commodity, let them go, work on the ones that keep coming back
Making the vision real and executing through the challenges
Getting allies to see what your are imaging
Learning from the past and not repeating the same mistake twice
Knowing when to stop and not getting so committed to a failed path that you don’t change it
Finding the essence of the problem or the guiding principles at work
What is the framework or mental model being used, how can be to used to reframe the ideas
Getting a sense of the timing and pacing for the innovation
When it is good enough
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Research Plan
Information Value chain
Behavioral Economies
Identity, Trust, Privacy, Security
Network Economies
Social Responsibility
Mapping Pigeon flight
Innovator Alignment | Research Plan | Research Approach | Network Economies | 2015 Outlook
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Research Macro Themes Described
Macro Theme Description
Information Value chain
Information flow is the signal versus and noise of information science. The value is an increase or decrease in signal. Information is the lowest atomic unit of measure for our research. The flows form interdependent chains or graph of relationships. The flows of value are not exclusive to money and include any convertible value.
Behavioral Economics
Includes any behaviors that happen before and after the decision of a consumer or producer. Behavior is observed, modeled, anticipated, projected, predicted as well as all the vagaries of the human condition. The unit of measure is at human scale and includes many uncontrolled factors.
Identity, Trust Privacy, Security
Identity includes concepts of privacy or public disclosure. Trust implies the concepts of gradations of security or no security if full trust is granted. Both included measures of credibility and honesty or value systems that are human. The concepts span system processes and human interaction.
NetworkEconomies
Networks are the systems that connect and the people acting in social interactions. Information flows, social behavior, identity and trust are aggregated into economic interactions within a network.
Social Responsibility
Includes individual actions representing corporations as well their household and raises questions of ethics. This aggregates the network economies into defined groups that care for direct and indirect impact and consequences of decisions.
* joined by a team of colleagues, researchers, students, support staff, bank line of business, committee
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CFB Research Plan
Macro Trend
Questions Asked
Research Topics
Information Value chain
How do we empower people to use information?
How will the next generation of information clouds emerge?
How do we de-mystify financial management?
Living Lab / Flagship store
Retail Banking Analytics
Sensing Stores / Speechome Video
Ambient Intelligence / Surface Computing/ Siftables /Word play
Affective Computing
Information flow is the signal versus and noise of information science. The value is an increase or decrease in signal. Information is the lowest atomic unit of measure for our research. The flows form interdependent chains or graph of relationships. The flows of value are not exclusive to money and include any convertible value.
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CFB Research Plan
Macro Trend
Questions Asked
Research Topics
Behavioral Economics
How do customers respond to “life events?”
How we predict what customers want?
How do we enable people to make rational decisions?
Behavioral Economics
Prediction Markets
Affective-Cognitive Predicting Customer Purchase Decisions
Includes any behaviors that happen before and after the decision of a consumer or producer. Behavioral is observed, modeled, anticipated, projected, predicted as well as all the vagaries of the human condition. The unit of measure is at human scale and includes many uncontrolled factors.
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CFB Research Plan
Macro Trend
Questions Asked
Research Topics
Identity, Trust, Privacy, Security
What will be the new deal for data and privacy?
What are the new platforms to manage risk?
What are the new economic models for trust and security?
Living Labs / New deal for Data
Identity and Identification Models
Personalized Customer Service
Trusted Investment Advisor
Face Reader for affective responsive computing
Identity includes concepts of privacy or public disclosure or fabricated personas which are both public and private. Trust implies the concepts of gradations of security or no security if full trust is granted. Both included measures of credibility and honesty or value systems that are human. The concepts span system processes and human interaction.
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CFB Research Plan
Macro Trend
Questions Asked
Research Topics
Network Economies
How will hyper-connected mobility and locality change banking?
How do we enable frictionless interactions to customers?
How will networks change the way we live//transact?
Mobile Commerce / Physical interaction / Living Lab
Future Consumption / Living Lab
Social Network Risk models
ATM & Mobile Phone interactions
Understanding Associates interaction – peers /managers/customers
Networks are the systems that connect and the people acting in social interactions. Information flows, social behavior, identity and trust are aggregated into economic interactions within a network.
Webiste map
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CFB Research Plan
Macro Trend
Questions Asked
Research Topics
Social Responsibility
How can we enable people to live better?
How do we transform the image of banking?
How do we foster consumer financial health?
Volunteerism and activism
Civic Media and Voice of the Community
Financial Life Time household Literacy and decision making
Account Ability and sensible consumerism
Next Billion in our Neighborhood / Living Labs
Includes individual actions representing corporations as well their household and raises questions of ethics. This aggregates the network economies into defined groups that care for direct and indirect impact and consequences of decisions.
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Research Theory and Impact
Macro Theme Consumer Impact * Theory Basis Research Unit
Information Value chain
Usability
Sensing Store
Communications
Signal/Noise
Bits/Bytes
Numbers/Time
Behavioral Economics
Consumer
Buying Decision
Individual
Choice Theory
Psychology
Mind/Emotion
Identity, Trust Privacy, Security
Consumer
Confidence
Risk Containment
Chaos Theory
Safe
Systems
NetworkEconomies
Connected
Consumption
Complexity/Game/
Graph Theory
Societal
Knowledge
Social Responsibility
Consumer
LiteracyPhilosophy
Values
Ethics/Law
*sampling of research projects summarized
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Research Approach
What is it?
How does it work?
Converting research to commerce.
Zaha Hadid Architect 3d Nurbs
Innovator Alignment | Research Plan | Research Approach | Network Economies | 2015 Outlook
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“if you always do what you always did, you always get what you always got”
- Einstein
What is observed
learn
What they say Market OpeningWhat they offer What we offer
Customer needs (discovered)
Proprietary VOC
and market research
Opportunities
identified (size, growth, profitability)
Comprehensive
review, financials and market share, etc.
Leader and innovator
in banking product and distribution
Customer needs (observed)
Customer needs (told)
Market opportunities
Competitor driven
Product driven
New worldviewProduct centric Customer centric
Banking Design CFB
Consumer Banking TransformationTraditional Model
CFB Approach: ‘Real-world’ connection
Academic
Research
Methods
Consumer insightMarket research
Ethnography
Corporate and University
collaboration on research
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CFB Approach: Future Created
What we can observe / learn
(discovered)Customer needs
Customer Banking Design
Consumer Banking Transformation
Available thru cutting-edge
research
What we can observe / learn
Customer needs (discovered)
Customer needs (observed)
New worldviewCustomer centric
Customer Banking Design
Center for Future Banking
Consumer Banking Transformation
Banking TransformationNew Markets Created
Blue Ocean Strategy
Value the customer could not imagine.
This is the voice of the future.
Market value innovations developed using strategic investments in emerging lines of
business and ventures.
Requires service innovation culture, informed by research and creative open visionary
leadership.
Sustained Competition
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CFB Approach: Design Research and Business Model Development
InformationValue chain
Network Economies
Customer Needs Observed (IDEO & Design Research)
BehavioralEconomics
Identity/TrustPrivacy/Security
Social Responsibility
TANGIBLE COMMON SENSE CLARITY•help people grasp the bigger financial picture•Go beyond a menu to a recipe; “I need expert financial guidance”•Make financial information more understandable and tangible instead of using abstract concepts.
WISDOM OF CROWDS•Enable people to use collective knowledge of fellow customers•Foster reassurance by connecting like-minded customers
CULTURE OF ACHIEVING•Create moments of pride and mementos of achievement. “Account alerts are embarrassing – they make me feel poor” •Set an atmosphere of encouragement
MY PACE, MY ROUTINE•Infer preferences: “Amazon knows me better than my bank” •Know and accommodate people’s schedules and daily patterns.
TransformativeBusiness Model
-------------------------Outside-In
Customer Analysis / Research
Inside-Out Competitive Analysis
Compelling Offer
Finance ModelDISTRUST•Trust is difficult to attain, fragile, and can be easily eroded. When trust is broken, we are often the last to know.
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Existing Innovation Ecosystem informed by Macro Theme Research
Commercialization:New Product Introduction (NPI) & Product Enhancement (PMI)
Product Management
Ide
as
TG0
Define Measure Analyze Improve Control
Strategic Planning
Idea Generation
Stabilized Stabilized Products / Products / ServicesServices
Ide
as
Ide
as
Ide
as
Process Management & Initiative Governance
Approved Approved ConceptsConcepts
Strategic Themes / Strategic Themes / OpportunitiesOpportunities
Intellectual Property
Inte
llec
tua
l Pro
pe
rty
Review IPlandscape
Evaluate ideasfor IP value
Patent corefeatures
Limit exposurefrom existing
external patents
Patent additional key features
Review/revisePatent app
Monitor forIP opportunities
Concept Development
Idea Management
RapidPrototyping
CFB Macro Themes ResearchMedia Lab concept Prototypes
CBT Market Research
New LOB Formation
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CFB Approach: Understanding Research
“The Media Lab may have lots of useful artifacts or techniques
that may be re-purposed in completely different ways than
they would expected… ”
“Build first…ask questions later”“Break what is fixed””
“action oriented inquiry”
“Academia can be very useful when applied to Bank data and
may help uncover new understanding that would
otherwise not be available to the Bank”
What is foundational Research?
A process of continuous inquiry. An examination of a subject from many points of view.
Pursuit of what works, what does not work and why
Uncovering a theoretical proof or essential truth.
The construction of knowledge for the public good.
A systematic experimentation of observable phenomenon.
Creating Innovations!
Information gatheringScenario analysisProduct developmentMarketing research Collecting VOCBusiness development
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CFB Approach: Doing collaborative Research
“Triple Helix; Industry, Academia, Government”
1. Identify and create tectonic shifts in the global socio-economic landscape
a. Experimental Research on what may impact the way people live, work and thrive.
b. Long-term partnership with collaboration between academia, industry and the civic bodies
is the only way to identify potential mass adoption of new standards, behaviors and
business frameworks
2. Research to Predict, build, and test future drivers of business models
a. Agreed on a rapid extreme experimentation approach in live environments
b. Macro Themes generate emerging concepts to research real scenarios
c. Inform existing product innovation by pipelining the experimental research findings,
techniques, and artifacts into the enterprise to create a sense of ownership and urgency
to formulate or seize these emerging business models
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CFB Research Outcomes Categories
“All outcomes need to be converted to products before they are useful”
Artifacts
Research results with tangible embodiments that demonstrate what is possible
Early indicators of physical interfaces afforded interaction designers
Example: Patties Maes, Siftables devices
Techniques and methods
The invention of new techniques for analysis of experimental data.
Example: Deb Roy, Speechome fish lens and video processing
Observations
Speculative insights based on observations that inform hypothesis for experimentation
Example: Dan Ariely Behavioral Economies patterns
Understandings
Theories that challenge the prevailing beliefs. Intangible experimental demonstration
Example: Sandy Pentland, Sociometer discovery of Honest Signals
Philosophy
Radical thinking that breakthrough common practice
Example: Stallwart, Free Software Foundation, Open Source Software
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Converting Research into Business
“Finding and creating new billion dollar markets”
Company creates the innovations
Leadership provides the Vision for the Future
Prioritizes innovation as part of its Hoisin planning
Associates engaged in innovation are trained to think creatively by working with CFB
Creates service concepts from marketing research and ethnographic studies
Generated insights from its own data repositories with superior quants and tools
Product Innovation teams collaborate across the company
Product Teams create new IP and acquires IP to secure it position
Engage its strategic partners to help create breakthrough products and services
Uses the investment fund to fuel new market innovations
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CFB Informing Business Innovation through Research
“Inform innovation through world class research engagements”
CFB Through engagement with Academia
Engages with researcher to influence their focus areas
Spots interesting research outcomes
Keeps a focus on the future horizon
Informs the product innovation teams
Provides creative context and inspiration to market innovations
Assist leadership in realizing long term vision for Banking futures
Trains the top talent in creating the future through Executive in Residence rotation
May directly conduct research where gaps in conceptual knowledge are present
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Research Conceptual Structure
Value
Creation
TACTICS TODAYNow – 12 months
STRATEGIC HORIZON1 – 3 years
RESEARCH FUTURES+3 to 10 years
VALUE CREATION
SERVICE SCIENCE
RESEARCH
Data
Human Interaction
Economic Models
Information Behavior
System Dynamic Knowledge
NetworkRelationships
Financial Ecology
TECTONIC SHIFT
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Network Economiesdefinition: any complex system where value is stored and exchanged
Why it matters!
Grand Challenges
What is it?
How does it work?
Impact
CFB Examples
Ethnography study map
Visualization link: World Growth in PC and Cell Phone Adoption
Innovator Alignment | Research Plan | Research Approach | Network Economies | 2015 Outlook
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Network Economies – Why it Matters!
Conceptual inclusions into Network Economies All matching and routing systems
All computing and communications systems
Human and Biological systems
The connected planet Estimated 1 billion bank accounts worldwide, 2 Billion Cell phones and growing rapidly
Network economies are responsible for entire country and regions economic development
Network economies are integral to globalization
Financial/Banking systems are wholly dependent on network economies
Range of Network Economies dependencies Trade systems of various types
Reputation systems
Supply and Demand chain dynamics
Electric Power Grids
Modern Food and Health delivery are not possible without Network Economies
Transportation systems use network economies
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Grand Business Challenges
Market Discovery
What techniques can be used to uncover hidden insights and unmet needs from the voice of the customer as captured in a social network application?
Can we identify and unlock the commercial potential of social capital inherent in communities?
How do we evaluate ways of fostering user generated content and a free exchange of expertise within the community?
Network Economic Models
How can a social networks extend beyond a communication vehicle to have more relevancy in managing a business effectively?
Can labor be shared, cost spread, profit pooled?
Can a network be used to manage business risk?
Could it be used as a source of capital?
Can the network aggregate its purchasing power?
What is the balance between competition and cooperation within a network?Tsunami
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Grand Research Questions
Networks converging physical and virtual spaces
How do networks emerge and scale? How are physical and virtual different?
What is the inherent value system and constraints under which they form?
How is knowledge shared and problems solved within social networks.
Do SmartMobs behave predictably? Can they be controlled?
How would augmented reality retail emerge with social networks?
Network Economic Models
What are the micro-economic forces at play?
How do new currencies impact group decisions?
New currencies could be coupons, loyalty point systems, barter systems, time trading systems, money within games, micro/nano payments, one time use codes, media capture and exchanges, peer to peer value exchanges.
How do networks behave in physical spaces when using mobile Location based services and can form spontaneous connections?
Strange Attractor
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Network Economies – What is it?
What are Network Economies Value exchanges based on relationships that transcend a single transaction Frictionless matching of producers and consumers, freescale growth Communities of Practice with convertible social capital Rebalancing of power asymmetries and disequilibrium
Enablers of Network Economies Internet and ICT Mobility, cell phones, laptops Software that affords self organizing activities
US Industry Examples using Social Networking Google, EBay, Amazon, Paypal, Skype, Joost Intuit Small Business Community Facebook - Visa Business Network Facebook - Fiserv MyMoney program Prosper Peer to Peer Lending
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Network Economies – How does it work? a research history
6 (5.5 – 6.6) Degrees of separation
In 1960’s S. Milgram (psychologist) demonstrates 6 degrees using US postal mail
In 1973 M. Granovetter (sociologist) theory “Strength of Weak Ties” spread of info in networks
In 1994 R. Reynolds paper on Cultural Algorithms using computational models
Online 3 degrees of separation is more likely
A. Barabasi (physics) demonstrates preferential attachment model, nodes with lots of links have higher probability of acquiring more links.
Yahoo research discovers growth in members and connections are needed for healthy networks to thrive. If either stall the network dies.
R. Dunbar (anthropologist) argues a maximum of 150 social relationships can be maintained which is the historical size of farming villages.
The world is highly clustered geographically and socially, enabling short paths traversals within networks and across groups
Social Contagion, diffusion of innovation, people imitate each other 0 1 2 effect where the probability of imitation is great once 2 friends have done something
Jared Diamond posits a theory for Societal Collapse inferring social networking theory
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Network Economies – How does it work? Current research finding Nov. ‘08
mathematical model “hidden metric space”
may explain the “small-world phenomenon”
relates to man-made and natural networks
human language to gene regulation
neural networks connecting neurons to organs and muscles within our bodies.
Natural world routing only uses local knowledge and not global knowledge of the network which is how communications routing works today.
Natural networks transmit information very efficiently without any single node having knowledge of the structure of the entire network
Many complex networks share similar shapes that maximize their communications
Implications range from cancer research on gene therapy to more efficient routing on the internet.
How the hidden metric space guides communication. If node A wants to reach node F, it checks the hidden distances between F and its two neighbors B and C. Distance CF (green dashed line) is smaller than BF (red dashed line), therefore A forwards information to C. Node C then performs similar calculations and selects its neighbor D as the next hop on the path to F. Node D is directly connected to F. The result is path ACDF shown by green edges in the observable topology.
Source: CAIDA, UC San Diego Supercomputer Center
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Network Economies – What are the numbers?
Simple Math explains the net effect Potential number of interactions within a Social Network may be expressed as
n ( n -1 ) / 2 where n is the number of people in the network
Given a starting social network of 100 people with 100% growth rate to 200 people
The number of potential connections grows from 4,950 to 19,900 or 302%
d-2 probability of being friends decreases exponentially as the distance/dissimilarity increases
What this produces? Facebook example: Post money Valuation of 15 Billion as of June 08
130+ Million unique visitors in June 08, comscore avg. internet Ads spend $132/user
Technical statistics
10 Million request/second (500,000 to database tier)
1+ Terabyte/day of data volume and growing
Visa & Fiserv on Facebook to access growing installed user base.
Thousands of custom applications with a rate of innovation accelerating
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Network Economies – It is not New, and has a Global Impact
Globalization
Thriving interdependent Social Networks
Silicon Value/Alley, Boston, Austin
Hsinchu-Taipei, Bangalore, Tel Aviv, Singapore
Local Social Networks
Cambridge, Helsinki, Sophia Antipolis, Stockholm, Munich
Silicon Valley Innovation example
Three large network facilitate new entrepreneurs
Firms, R&D Labs, Universities
VC’s, Investment Bankers, Law Firms
Suppliers and Customers
They all rely on reputation and trust to make decisions
They are highly purposeful and dynamic with adhoc communities of practice
The networks are highly diverse and global
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Network Economies – Consequences of not taking it seriously
Global Salafi Jihad
Most complex systems are not random and present similar topologies
Properties like:
small-world = high clustering, low path length
scale free properties = self-organizing, preferential attachment.
Robust against random failure but vulnerable to targeted attacks.
Same pattern for:Meth WorldGang NetworksDark Web
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Network Economies
Center for Future Banking
Media Lab Examples
Related projects
China Globalization Map
Innovator Alignment | Research Plan | Research Approach | Network Economies | 2015 Outlook
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Network Economies – CFB MIT projects examples
Catching up with today
Situated Mobile Commerce a Living Lab
Future Consumption Network
Call Center and the Socio-meter
Corp Social Media
Related Projects
Future Proof the Company
Information Economics
Silicon Valley Network
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Network Economies – Future Consumption Network / Living Labs
Inquiry – What is the value of Hyper-Connected Social Mobile Networking at the Convergence of Virtual and Physical Spaces?
Inputs – Mobile and Telecom Infrastructure, Social Networking Capabilities
Outputs – Idea Market connecting consumers, merchants, product manufactures, and financial services, as well as Small Business Mobile Living Lab
Academic Team
Faculty - Sandy Pentland, Andy Lippman, David Reid
Students - Kwan Lee, Dawei Shen, Aithne Pao, Anmol Madan, Taemie Kim,
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Network Economies – Future Consumption Network
Connected Consumption Mobile-informed consumer through open
contribution
Reverse auction environment
Collaborative shopping
Rewarded for participation
Bank products offered as participation incentive
Sensing consumer short-term/long-term interests
Future Consumption Network Intelligent, on-demand network that brings
together loosely integrated entities in an efficient and highly integrated manner
Open transaction network
Socially responsible network that rewards savings & investment
Dis-intermediating payment network
CFB Exec: Hans Schumacher
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Network Economies – Future Consumption Network
Budget Envelope Card
Restrict spending behavior while being rewarded/incented for staying within predefined budget by category
Budget surplus dynamically invested
Real-time expenditure tracking
Compete with peer groups
Concrete Budgeting
Actively manage short to long-term financial goals and evaluate purchase decisions on-demand to attain a “concrete” financial future
Comparisons to peer group
CFB Exec: Hans Schumacher
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Network Economies – Call Center Social Analysis
Inquiry – Examination of associate interactions with peers, managers and customers, and activity analysis for predicting group behavior by including all available communications traces.
Inputs – Frontline call center interaction, work flows, email and phone data, including socio-meter instrumentation.
Outputs - group behavior analytics, models for successful interactions across multiple channels, define behavioral characteristics that are critical to driving success.
Academic Team
Faculty - Sandy Pentland
Students - Ben Waber, Coco Krumme, Anmol Madan, Iolanthe Chronis
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Network Economies – Call Center Social Analysis
Predicting Associate Interactions
Predict the outcome of an associate/customer interaction after seconds of listening?
Discover patterns of activity that usually go unobserved in organizations/call centers?
Track and evaluate the unconscious human behavior with the collaborative and social side?
Honest Signals hidden in Human communications
People have 2 distinct “channels” of communication –
verbal rational channel, which information flows linguistically
nonlinguistic channel, often ignored, but carries as much information.
Human behavior can predicted accurately by capturing thin slices of what people do.
We need instrumentation since people can’t observe others objectively.
Cannot manage what is not measured.
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Network Economies – Call Center Social Analysis
Experimental Proposal
Test Social/Human Behavior in Contact Center
Outfit 80 agents (4 teams), their managers, and Unit managers with wearable sensors.
Track and record conversational and physical interactions between associates, team and unit managers.
Capture email, instant message and telephone records for the duration to contribute to the analysis.
Duration to last 30 days.
Impact
.004% shrinkage
(80 agents @ 15 minutes)
Hawthorne Effect
CFB Exec: David Price
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Network Economies – Corp Social Media
CFB will utilize an external blog to … Promote dialogue with innovators, competitors, MIT & Academia, BAC Associates
Communicate activities of the Center, disinformation to competitors;
Position Bank of America as a progressive innovative leader;
Learn in a lower risk environment strategies to utilize Social Media to engage key constituents.
Experimental Analytics Implemented Coremetrics, I2A tags, and collect Cluster Map data.
iCrossing has included a reporting tool that CFB Team can access on-demand
Post Launch SLA for detailed reporting work with Supply Chain
iCrossing will provide a detailed 6 & 12 month summary post-launch summary
Team CFB Exec’s, Legal, Social Media, PR, Marketing Communications
CFB Team with Jeff Carter
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Network Economies – Related Projects
Initiated by innovators in collaboration with CFB
Oct 21st Design Charette, 70 people, Faculty, Students, BAC, City of Boston, guest speakers
Event stimulated research possibilities not previously considered
Video Documentaries available for Leadership Learning.
Highlights of Projects Initiated:
Living Labs project initiated with Mobile Initiative, Sandy Pentland
City of Boston engaged with CFB, MIT, BAC in Living Labs project
SBOC Data analysis – discovery of internal competencies in data and text analysis prior to engaging MIT students.
SBOC used in the EpiCenter project – connecting the virtual with the physical for richer engagement with customers.
Peer to Peer Lending Analysis – pattern recognition class doing analysis, possible academic paper with significant finding pending. Ray Garcia with Dawei Shen and Hyungil Ahn
Information as a Product
Community Change Card, Jon Ramer, City of Boston
Merry Miser project Charlie DeTar
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Network Economies
Future Proofing the Company with
Information Economics of Network Knowledge
Innovator Alignment | Research Plan | Research Approach | Network Economies | 2015 Outlook
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Team and Inquiry – Information Economics of Network Knowledge
Bank Strategic Champions – Laurie Readhead and Lance Drummond
Business Tactical Leaders – Margaret Weichert, Ross Feldman, Beverly Ladley, Indur Koul
Innovators Committee – CFB - Hans Schumacher, Todd Inskeep; BAC - Marc Keller, Matt Calman
Quant Committee – David Joffe and David Joa
Audience – Quant doing Informatics and business leaders needing to understand information economics, network and emergence theory.
Business Inquiry –
How might data and information captured within Bank systems be converted to knowledge that informs a Financial Ecology and Network Relationships such that they can be leveraged as residual products.
How would the Economics of Information assess value or reveal insights to be discovered to inform service innovations, generate revenue, reduce risk, or improve operations?
How does value emerge from a network and how would Quants use Informatics to continuously discover emerging opportunities and threats given the severe challenges of data quality management.
Research Inquiry –
How do personal, social, commercial, knowledge networks emerge?
What is the inherent value system and constraints under which networks form?
How does using information economics to show how fairness contributes to efficiency and innovation?
How is knowledge elicited, assessed, shared and problems solved within networks?
What are the micro-economic forces within information intensive service businesses?
What experimental methods are used to model, simulate, predict, inform, improve, knowledge products?
What are the learning models, cognitive models, and affective models that influence knowledge economies?
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Research Design - Information Economics of Network Knowledge
Theoretical Basis – Information Economics, Social Science, Computation, Information Science, Ontology
Business Basis – Financial Ecology, Human Dynamics, Knowledge Management, Social Media
Methods – Qualitative Research methods, quantitative analysis, ethnographies
Techniques - data processing, statistical analysis, pattern recognition, text processing, machine learning
Business Inputs – Bank transaction data, data from information network experimentation, marketing research databases, external market data sources, financial data feeds, expert annotation
Research Inputs – MIT prototypes in; common sense knowledge, social media, cognitive/affective markets, knowledge markets
Experimental Platform – communications market borrowing from several MIT projects and creating a system for on-going long term research.
Informatics Toolkit – an assembly of open source, or low cost, tools used in the analysis and visualizations of data.
Key Outputs –
Valuation of latent Network Knowledge factoring system dynamics, content, membership, relations between nodes.
Knowledge elicitation, discovery, and dissemination, modeling, simulation and prediction of human systems including cultural algorithms which inform market dynamics.
A formulation of the research discipline in Service Science merging techniques from Qualitative and Quantitative research borrowing from various practices. This Service Science would determine how to convert research findings into innovative services that can be formulated, tested, disseminated within a large scale global company.
The Network Knowledge and information economics would include a synergistic co-generated service innovation between consumers and producers. This may include a communications marketplace that is both internal and external and reconciles the need for knowledge elicitation and dissemination.
Quant tools, techniques, and methods for applied information economics against bank data.
Academic Team (proposed)
Research Scientist – Marshall Van Alstyne (Sloan School), Kelly Hewett (BAC Market Researcher)
Phd Candidates – Dawei Shen, Hyungil Ahn, Polychronis Ypodimatopoulos, Ankur Mani
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Related Research to Information Economics of Network Knowledge
Economic Choice Theory and Group Decision Making
Problem Statement – How do people learn to make important economic decisions that impact their personal finances and/or company value from the social engagements and information sources they have available? What are the cultural forces at work? What methods could be used to experiment, model, simulate, predict, inform, improve, group decision making within tribes, co-workers, and communities of practice? How does economic literacy impact other important decisions such as health, home, children, work, and consumer behavior? How does economic literacy change throughout ones life and how is it inter-generational? How is economic literacy taught and learned. What are the educational psychological models and cognitive models that help inform personal and group decisions and how do social values systems influence the choices and expectations.
Scaling the Service Innovation Process to create breakthrough new products (Cooperative Collective Intelligence Elicitation and Dissemination)
Problem Statement – Service companies lack the experimental research activities that are prevalent in product companies and therefore do not have a science of service to create and build a body of knowledge. The research methods and process for converting research findings into innovative services requires a discipline to be formulated, tested, and disseminated to be effective within a large scale global company. Can these service innovations be co-generated between the consumer and producer such that they evolve into a synergistic relationship? Using Social Media to elicit knowledge and applying methods for evolving the knowledge into innovations while opening communications to a free exchange of ideas between consumer and producers is a challenge for industries where confidentiality and proprietary information is consider a risk to the business and therefore all communications is controlled. How to balance the economic benefits of a free communications with the desire for control requires research in the economics of information to devise techniques to resolve these conflicting goals.
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Candidate Research Collaboration
Academia
Sloan School Center for Digital Business
CSAIL
Auto-ID Lab
Corporate
IBM Center for Social Software
Rueters and Bloomberg
Appforge
Selectminds
Government
Fed Reserve
City of Boston
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IP Generation
Technology disclosure with MIT
Personal Augmented Reality in a Retail Environment
Inventors: Ray Garcia and Stephen Miles
An intelligent personalized agent running on a mobile wireless connected device that monitors and advises a user in recommendation-making process in a retail setting through both private and public information services, whereby the identification of the mobile device and rfid transponder impacts both the personal display and the public display
Conceptual Ideas under development
Multi-function card associate with a mobile device that acts as a dual factor authentication using a transparent card, embedded image that is reveal through matching with the display on the phone. The card is anonymous with no markers. The information on the card includes dual magstripes, barcode, optical storage, contactless rfid with a coil.
Communications market which is a hyper network of knowledge and affective associations of constructed information amongst a large group of participants. The knowledge is hyper connect to the people, context of situation and circumstance, and has a financial ecology that expands in a free market with minimal regulatory rules. Small world scale free networks of efficient information economies are allowed to emerge.
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Pattern Recognition Analysis of Peer to Peer Lending data from Prosper
From Sergio, Rahul, and Aithne, they are exploring the effects of social capital:
1. Social profile Friend: number of 1st-degree friends, number of 2nd-degree friends Endorsement: Endorsement number Group: Group leader reward rate, Group Rating, Group Size
2. Social Interaction - Bids from friends and group members
3. Classifiers were built to determine whether a list could turn into a loan.
4. Social factors are not determinant, but they do increase the chance of getting a loan when all other financial features are similar. This is demonstrated clearly by using clustering.
5. Users do not have time to maintain many social profiles, it's beneficial to use existing social networks as a foundation.
From Charlie, Matt, Ernesto, and Coco:
1. A Bayes belief network and a decision tree are formulated for classification. The unique benefit of Bayes network and decision tree is that it graphically presents some good practice for users if they try to increase their odds to get a loan.
2. Textual information, such as words used in endorsement, description, etc. is analyzed and proved to be very influential.
3. A risk assessment model built on Hidden Markov Model is formulated, and works very well. It can effectively predict a loan carrier's financial health, and predict potential delinquency.
4. Coco starts some interesting games with the image posted by users.
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Sloan Research to leverage in experimental design
Research Scientist Marshall Van Alstyne
Correlation of speed of Information Diffussion via social networks with productivity
Internal knowledge markets - Information economics applied to quantifying the effects of knowledge management using price theory, information asymmetry, and network theory. The goal is to discover information behaviors that predict success.
Anti-spam & Malware Research - A formal proof of information economics impact on eliminating spam without using a filter.
Open Platforms & innovation
The social efficiency of fairness
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MIT Concepts prototypes to monitor
PolyQuest: It’s your data, your connections
Team: Polychronis K
Problem Description: A next generation social network that is distributed and provides users complete ownership over their data and social connections. Contrary to centralized social networking systems like facebook, each user maintains their personal information and their list of friends on their own private web space. The list of their friends are pointers to other web spaces, while public key infrastructure is used to provide different levels of access to different friends, while providing minimum or no information to strangers.
Experience Sharing Market for Forecasting Marketplace Success
Team: Hyungil Ahn
Problem Description: We develop a novel market game that harnesses people's collective perceptions and experience sharing to forecast the success or failure of new items (products / services / UI designs, etc). Companies can register their new items on this market (as a test bed) to ask people's collective opinion. In each trial session, a participant makes his or her own best prediction on other people's overall opinion about the new items to get incentives (e.g., real opportunities to experience the items) and have fun in gambling-like games. As a participants guess (or portfolio) approaches the collective guess of all participants, he or she has a greater chance of winning an incentive. Participants improve the accuracy of their next prediction by sharing their experiences. As participants have more trial sessions, their collective prediction converges into one common opinion (forecasting the success or failure of new items).
Funk 2
Team: Bo Morgan
Problem Description: Funk2 is a novel process description language that keeps track of everything that it does. Remembering these causal execution traces allows parallel threads to reflect, recognize, and react to the history and status of other threads. Novel forms of complex, adaptive, nonlinear control algorithms can be written in the Funk2 programming language. Currently, Funk2 is implemented to take advantage of distributed grid processors consisting of a heterogeneous network of computers, so that hundreds of thousands of parallel threads can be run concurrently, each using many gigabytes of memory. Funk2 is inspired by Marvin Minsky's Critic-Selector theory of human cognitive reflection, and is the foundation for the Neural Models of Mind project.
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MIT Projects to License for use in future research
Selectricity
Team: Chris Csikszentmihalyi, Alyssa Wright, Benjamin Mako Hill
Problem Description: Selectricity is a web-based voting system that supports anonymous and voter-verifiable balloting, and includes an election-methods library that implements a variety of election techniques, includeing several preferential systems. Unlike most voting projects, Selectricity does not attempt to address the issues raised in mainstream political elections. Instead, it provides a simple set of tools that small groups and organizations can use to incorporate computationally complex decision-making into new areas, and for purposes where they ordinarily would find such decision-making into new areas, and for purposes where they ordinarily would find such decision-making prohibitively complex. By supporting a variety of election methods, it provides a way for users to explore and compare the effects of different voting systems and, ultimately, come to better decisions.
Common Sense Reasoning
Team: Henry Leiberman, Catherine Havasi, Robert Spear, Dustin Smith, Jayant Krishnamurthy
Collecting Common Sense – the open mind common sense project, acquiring knowledge from untrained people through the use of on-line interfaces and games.
Common Sense Recommendations – that are more user friendly than collaborative filtering systems. Uses tools to build intelligent recommendation agents and effective product exploration tools
Not-So-Common Sense – infusing data sets with common sense
Perspective Space – discovering distinct communities of people with jargon and belief structures from simple ratings
Analogy Space
Common Sense Investing
Common consensus: a game for collecting commonsense goals
ConceptNet
Divisi: Reasoning over Semantic Relationships
E-Commerce When Things Go Wrong
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MIT Project techniques to re-build in future research for new inquiry
Behavior Capture from Thousands of People On-line
Team: Jeff Orkin, Deb Roy
Restaurant game simulation of patron to host interaction to capture dialogs and sequences of common actions. The analysis is statistical and produces dialog that mimics frequent occurrences of phrases.
New Media Medicine
Team: Frank Moss, John More
Collaborhythm – collaborative decision making between doctor and patient
Collective Discovery – a massive collection of “everyday experiments”
HealthMap – real-time disease outbreak tracking and visualization system
I’m Listening – pre-visit interviews to help categorize patient symptoms for efficient diagnosis.
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Tentative Research Milestone Plan
Network Economies Defined Dec-08
Grant Draft based on initial research design Jan-09
Grant submittal and review Feb-09
Stakeholder commitment, Biz Relevancy, Funding, BAC staffing secured Mar-09
Research PI commitment and plan Apr-09
Executive Course in Information Economics to support research created Jun-09
Experimental Instrument created Jul-09
Initial Research execution and Analysis Dec-09
Research Paper Submittal to peer review conference Jan-10
Trial adoption of tools, methods, techniques, by quants for internal use Feb-10
Quant discovery of major revenue impact in network effect Apr-10
Journal Article submittal Jun-10
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Network EconomiesAnalyst Future Outlook
2015 Context Aware Computing source: Gartner ITExpo 2008, William Clark
Analogous to MIT Sandy Pentland vision of an
Aware Society of Tribes in a Living Lab
Champion Alignment | Research Plan | Research Approach | Network Economies | 2015 Outlook
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Situation and Context Aware Tribes
What is Context Aware Computing
Emerging context-enriched services will use location, presence, social attributes, and other environmental information to anticipate an end-user's immediate needs, offering more-sophisticated, situation-aware and usable functions.
By 2012 estimates:
More than 7.3 billion networked devices worldwide
298 million subscribers of location-based services
>75% of new search installations will include social search element
• $150 billion of $1.8 trillion global telecom spending will shift from services to applications
• Global market potential that context-aware computing can impact: $215 billion
MVE algorithm plot on citywide activitySource: Sense Networks
source: Gartner ITExpo 2008, William Clark
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Context-Aware Society in 2015
SocializationPersonal Services
Personal Commerce
Context Agents
Context Brokers
Fine-grained, anticipatory search
Context-Enriched Services
Identity
Knowledge Collaboration
Community
Environment
Process
me
Sensors
Universalgeo-fencing, hyper-optimized processes
A way to manage identity, reputation, and privacy
Virtualized worlds, avatars, persona-bots
Consistency across channels
Auto-tagging,
anticipatory
search
source: Gartner ITExpo 2008, William Clark
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Socialization
Challenges in Context-Aware Society
PersonalServices
Personal Commerce
Context
Brokers
Fine-grained, anticipatory search
Context-Enriched Services
Identity
Knowledge Collaboration
Community
Environment
Process
me
Sensors
Universalgeo-fencing, hyper-optimized processes
A way to manage identity, reputation, and privacy
Virtualized worlds, avatars, persona-bots
Consistency across channels
Auto-tagging,
anticipatory search
Shared Shared TrustTrust InformationInformation
FederationFederation
Context Context SwitchingSwitching
Cross- Cross- Endpoint Endpoint
ExperienceExperience
Cross- Cross- Personna Personna
ExperienceExperience
Cross-Session Cross-Session ExperienceExperience
Agent Agent ProvisioningProvisioning
Sensor Sensor OverloadOverload
Real-TimeReal-TimeContext DeliveryContext Delivery
Cross- Cross- Application Application ExperienceExperience
Context Agents
source: Gartner ITExpo 2008, William Clark
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Real-World, 2009: Context-Enriched Services in Mobile and E-Commerce
IdentityCommunity
Environment
Process
User-Defined Rules
System-Defined Rules
Reference
History
Network Capability
Endpoint Capability
Location
Presence
Groups
Tagging
Links
Bookmarks
CalendarPIM
Role
Security
Privacy
Reputation Tolerances
Trust
Journal
Calendar Tasks ContactsReputation
TolerancesTrust
Reference
HistoryWhat information do vendors and comparison sites provide?
What is my history with the various sites?
Are the network I'm on and my current device capable of supporting streaming video on the product at this moment?
Do I choose to share the fact I have just arrived at the store whose Web site I have been using for comparison shopping?
Can I easily validate the level of trust and security of the vendors I'm accessing on my smartphone?
Is the salesperson who I am working with available physically or online at this moment?
What are the tips from others making similar purchasing choices?
How much information do I expose to a vendor or a community? How do I repair my reputation if damaged?
What are my tolerances for m-commerce/e-commerce from an expense and usability standpoint?
Context
Brokers
source: Gartner ITExpo 2008, William Clark
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Figuring all this out – Navigating through large scale complexity
Assuming
A desire to create the future
Triple Helix Strategy – Industry, Academia, Government
Experimental design
Quality data and its meta descriptions
Best research team
Best methods and techniques for analysis
Business willingness and patience to discovery the unknown
A new understanding of information economics
Then, how will you comprehend it all?
So that you make the best decisions based on evidence, analysis and intuition
Using transparency and access to complexity in a form that can be understood
We need to provide the methods for our top executives to fly through the complexity
Using new computational models, simulations, and interfaces
These interfaces would use Visualization, Sonification, and Kinesthetic navigation
One example of a new interface: G-Speak Overview
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Suggested Next Steps for discussion
Grand challenges revised
Detail reviews of CFB project with each Executive in Residence
Detail review of Information Economics research proposal
Assessment on analysis and visualization techniques and methods applied to bank data
Presentation of MIT project assets to source innovations from
Consideration of grants to direct new research
Line up of innovation team within each LOB to work with research track
Alignment of marketing research, innovation team, and CFB research to spot Billion dollar opportunities
Advisory Board communication on effort to inspire the rest of the company
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Big Company (statements heard in my first 90 days at BAC)
STAGNANT “We own the market we are just that big!”CYNICAL “It will never happen!”CONFUSED “What is going on in the market?”TOO LATE “How did that happen?”
Future Proof Company (why I am here)
THINK “Service as a Science”LISTEN “Co-create the future with the consumer”SERVE “Mass preference and configuration”SCALE “Human dynamics scale”ADAPT “Grow, split, shift, evolve”
Closing Remark
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References and Suggested Reading list
CFB Research Macro Themes and research reviews posted on CFB website
CFB website for Network Economies blog posting by Ray Garcia
Hsinchun Chen and J. Xu The topology of dark networks: ACM Oct. 08
Bill Howard Analyzing Online Social Networks: ACM Nov. 08
Suggested Book List:
•Born Digital
•Honest Signals
•The Long Tail
•Crowdsourcing
•Network Power
•We are smarter than Me
•The Big Switch
•The Cluetrain Manifesto
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For questions on this presentation contact:
Ray GarciaVisiting ScientistCenter for Future Banking at MIT Media Lab
[email protected]://www.linkedin.com/in/alterwork