Spring 2006  

21st Century Knowledge:
Priorities of the Knowledge Economy

Secure On-line Registration Online Registration in Advance is Required

March 3, 2006 8:00am - 5:00pm

preferred

Time	Interaction	Speaker
07:30 - 08:30	Continental Breakfast & Registration	Staff
08:30 - 9:30	Markets and Exchanges Preference Markets	Ely Dahan Assistant Professor of Marketing
9:30 - 11:00	Complexity and Complex Systems Network Strategies for Managing Complexity: Organizational and Value Network Analysis	Verna Allee
11:00 - 11:30	Participant Introductions Morning Break	All
11:30 - 1:00	Value Webs and Networks Value Network Dynamics: Building Internal and External Value Networks	Verna Allee
1:00 - 2:00	Hosted Luncheon	All
2:00-3:30	Value Webs and Networks Value Network Tools and Methods: GenIsis	Verna Allee
3:30 - 4:00	Afternoon Refreshments	All
4:00 - 5:00	Social Media, Tools and Networks Enterprise Wikis Use: Engagement, Participation, and Co-Generation	Ann Majchrzak Professor Marshall School of Business
5:00	Spring 2006 Southern California Adjournment

21st Century Knowledge
Priorities of the Knowledge Economy

Event Themes

Prediction Markets

Also known as information markets, decision markets, idea futures, and virtual markets, prediction markets are speculative markets created for the purpose of making predictions. Assets are created whose final cash value is tied to a particular event, outcome or parameter (e.g., total sales next quarter). The current market prices can then be interpreted as predictions of the probability of the event or the expected value of the parameter.

People who buy low and sell high are rewarded for improving the market prediction, while those who buy high and sell low are punished for degrading the market prediction. Evidence so far suggests that prediction markets are at least as accurate as other institutions predicting the same events with a similar pool of participants.
 
One of the oldest and most famous is the University of Iowa's Iowa Electronic Market. It has been predicting the results of American presidential elections since 1988 with greater accuracy than polling companies. Prediction markets were championed in James Surowiecki's 2004 book The Wisdom of Crowds. Prediction markets are speculated to be useful decision support tools for corporations. (Wikipedia)

Who uses Prediction Markets?

The list of companies using prediction markets to tap internal, future-focused knowledge is impressive. Microsoft, Google, Yahoo!, Ely Lily, HP and other top, knowledge-based leaders are achieving fundamental advancements in KM with these potent market technologies.


"...the idea of markets working within companies has started to seep out into some of the nation's largest corporations. Companies from Microsoft to Eli Lilly and Hewlett-Packard are bringing the market inside, with workers trading futures contracts on such "commodities" as sales, product success and supplier behavior. The concept: a work force contains vast amounts of untapped, useful knowledge that a market can unlock. "Markets are likely to revolutionize corporate forecasting and decision making," says Robin Hanson, an economist at George Mason University, in Virginia, who has researched and developed markets. "Strategic decisions, such as mergers, product introductions, regional expansions and changing CEOs, could be effectively delegated to people far down the corporate hierarchy, people not selected by or even known to top management." (Time Magazine)
 
More resources: http://kmblogs.com/public/item/106758

Complex Systems

Complex adaptive systems, are a special case of complex systems. They are complex in that they are diverse and made up of multiple interconnected elements and adaptive in that they have the capacity to change and learn from experience. The term complex adaptive systems was coined at the interdisciplinary Santa Fe Institute (SFI), by John H. Holland, Murray Gell-Mann and others. John H. Holland is one of the inventors of evolutionary computation and genetic algorithms. Nobel Prize laureate Murray Gell-Mann discovered quarks.

The term complex adaptive systems (or complexity science) is often used to describe the loosely organized academic field that has grown up around the study of such systems. Complexity science is not a single theory— it encompasses more than one theoretical framework and is highly interdisciplinary, seeking the answers to some fundamental questions about living, adaptable, changeable systems.

Examples of complex adaptive systems include the stock market, social insect and ant colonies, the biosphere and the ecosystem, the brain and the immune system, the cell and the developing embryo, manufacturing businesses and any human social group-based endeavor in a cultural and social system such as political parties or communities. There are close relationships between the field of CAS and artificial life. In both areas the principles emergence and self-organization are very important. (Wikipedia)

Value Network Analysis

Value network analysis is an essential and critical knowledge leadership priority. All contemporary process analysis disciplines are heavily transactional in focus. They fail in complex, boundary-spanning knowledge-based environments. Social network analysis (SNA) offers a good description of relationships and flows, but does not show the business model. Only value network analysis bridges these disciplines offering a complete, systems-level view of your knowledge-based business ecologies.     
 

Value Network Analysis
 

Value network analysis is a natural and common-sense way to elaborate and improve business productivity, expand innovation and retire/reduce costly, inefficient processes. It is a boundary-spanning, holistic method. Value network analysis elaborates the intangibles that account for 90% or more of revenue and earnings in your knowledge-based businesses.
 

Value Network Tools and Methods

Tangibles are goods, services and revenues. Intangibles are relationships, brand, experiences, social networks, knowledge markets and other key enterprise assets. Intangibles create most of the wealth in today's knowledge economy. Intangibles are central to innovation, cost savings and productivity growth. Yet, organizations don't know how to elaborate or measure intangibles. Sometimes, they try to apply 20th Century transactional or manufacturing methods like 6-Sigma or TQM. This efforts always fail.

Organizations now have new, superior methods for understanding, visualizing and leading their intangibles. Collectively, these methods are known as value networks (VN) and value networks analysis (VNA). Equipped with these techniques, organizations can articulate, optimize and master intangibles. The outcomes are improved resource utilization, productivity, innovation and sharply improved performance overall.

The leading toolkit for intangibles is GenIsis. It is part of the ValueNet Works offerings. The illustration below outlines some of these integrated, easy-to-use offerings.

Genesis Application Portfolio