Prediction+Markets+Article+VA,+JA

WORKING DRAFT- WORK IN PROGRESS INSIDE KNOWLEDGE ARTICLE
Victoria G. Axelrod and Jenny Ambrozek

Prediction Markets- Deadline February 1
Title candidate:

="Prediction Markets: Co-creating an organization's future".=


 * Overview**

Prediction is the nirvana for business. Every business leader wants to reduce risk and uncertainty in decision making. Prediction markets hold the allure of optimizing decisions on new products and services to launch. They are not without issues. Wisdom of Crowds author James Surowiecki whose book popularized the notion that "the many are smarter than the few" is the first to admit **"prediction markets aren’t a crystal ball, but they are almost always better than any existing forecasting method". (**Jed Christiansen Notes from the European Prediction Markets Summit)http://kmblogs.com/public/blog/186847

It is nearly two decades since the first enterprise prediction market was installed by Robin Hanson, George Mason University associate professor of economics, yet lack of widespread adoption points to the issues surrounding successful implementation. More recently, Andrew McAfee, social technology advocate, Harvard academic and creator of Enterprise 2.0 framework which includes prediction markets suggests adoption will grow and companies cannot ignore the inherent benefits of collaboration tools. http://blog.hbs.edu/faculty/amcafee/index.php/faculty_amcafee_v3/how_to_hit_the_enterprise_20_bullseye/

Improved business forecasting in highly competitive markets, knowledge sharing and collaboration are driving adoption growth and interest as evidenced in the recent Google study findings and media coverage of Bet2give market forecasts that predicted the Boeing 787 delivery delay. This article defines prediction markets, the potential value through case examples of organizations that have had success using prediction markets, the variety of situations in which to use and not use, criteria for establishing, a short list of some of the software tool companies and recent academic research on lessons learned.

Jed Cristiansen quote

co creating the grass roots knowledge of organization the most informed and where it is located not always the expected people

//... quants are becoming more highly prized because the "easy" profit in many industries is gone. As an industry matures, it needs more information and better analysis to keep profitability, thus the need for quants. I think this is certainly the case for prediction markets. The only problem with prediction markets is that people in general mis-understand probabilities. When binary markets are traded, people could become disillusioned when the underdog wins. (This is not the case when index markets are used, and the market output can be directly compared to the standard forecast.)//


 * Why organizations want prediction markets**

Organizations historically have a difficult time of getting at the “truth” about what their employees think about critical business questions. What is the likelihood a product or service will get to market on time, be a success in the market, be sold in large enough quantity to generate hoped for revenue, be met with customer praise or even meet their companies key performance indicators (goals). The list goes on.

Communication both up and down as well as between collaborating divisions is not always optimal in spite of cross-functional teams, project management processes, and open feedback systems to ensure forthright information flows. Overconfidence, optimism, Wall Street pressures, sales quotas, pleasing the “boss”, fear of failure, risk aversion, shooting the messenger bearing bad news all conspire to reduce the “truth” – the product or service will make or miss the mark.

The business press regularly reports stories about information shortages and sharing failures catching senior executives off guard at the worst possible times. Boeing's recent failure to meet it's 787 delivery schedule is the latest example and Chairman and Chief Executive Jim McNerney's statement tells all.

//The company has sent manufacturing and procurement experts numbering "in the hundreds" to suppliers' factories after discovering problems with the first 787 delivered to Boeing's final assembly line. Those problems, including a serious lack of documentation on the work remaining to complete the first airplanes, drove the company's decision this month to delay the first 787 deliveries for six months and to replace the head of the plane's development efforts. Noting that// **//Boeing was "surprised on the physical reality"//** //of the condition of the first plane, Mr. McNerney said officials "realized we really need to work with [suppliers] to make sure we have better visibility" on the manufacturing process. "//**//We need that data transparency across all of the build in order to execute the plan that we've laid out.//**//"// //[|Wall Street Journal]//

This is just the beginning for Boeing as the depth and magnitude of the problem continues to unfold the delays keep mounting along with customer concern – who wants to fly in a 787. But tapping into the collective intelligence of the employees, suppliers, and leadership connected with the Dreamliner production may have saved Boeing both financial repercussions as well as market confidence in the brand performance. The public Bet2Give prediction market stock in whether or not Boeing would meet its May 2008 delivery target had been trading way below 50%, mostly between 20-30% in October of 2007, months before the missed delivery date announcement. https://bet2give.com/b2g/market/linear/market.html?symbol=Boeing787on...
 * (Emile Servan-Schreiber Newsfutures Prediction Markets Google Group post extracted 2007-01-26**
 * http://groups.google.com/group/Prediction-Markets/browse_thread/thread/c9cfa4d8e0ea27e7#**

David Perry, cofounder of Consensuspoint notes "Yes, markets are early warning systems for many things, they give you a sense of what your people know and do not know." Top managers at Boeing certainly would have benefited from the knowledge employees had that delivery dates were going to be missed but knowledge alone does not bridge the "doing" something about it gap. Often the knowledge is just a precursor to more systemic issues. In any event early information can lead to course corrections.


 * What is a prediction market?**

//A place where information is aggregated via market (or other) mechanisms for the primary purpose of forecasting events, or the probability that an event will occur (Kirtland 2007) Alex Kirtland - UsableMarkets 25 March 2007 power point presentation//

A market is just that - a means for buying, selling and trading shares for a price. Markets by their nature are dynamic and take place over time allowing for prices to fluctuate depending on confidence of the traders. And Emile

Jed Christiansen of Mecury Consulting short You Tube overviews prediction markets http://blog.mercury-rac.com/what-is-a-prediction-market-video/

Aggregation is the key word. What is being aggregated and is there potential for biases?

//(Q: Is below extracted from the Consensus Point notes?? And the second list?? )// Experience of leading prediction market thinkers and pioneers suggests the following essential ingredients for conducting efficient markets that allow the Wisdom of the Crowds to emerge. - **Diversity of knowledge.** Not everyone should know the same things about the topic they’re trying to predict. - **Diversity of beliefs.** Not only should the group know different things, they should also have different beliefs (Republican, Democrat, Moonie, Christian, Free Marketer, etc.). - **Diversity of expertise.** This refers not to knowledge specific to the question at hand, but to the lifetime of knowledge people have accumulated and has shaped their world-views. James Surowiecki
 * **diversity**—having access to a lot of different perspectives, sources of information and sets of knowledge is more valuable than individual IQ or expertise;
 * **independence of opinion**—if individuals can deliver their decisions simultaneously and blind to everyone else’s choices, you get real knowledge and superior decisions untouched by groupthink, peer pressure and other group dynamics; and
 * **a method of aggregating information**—here is where technology and system design come in.


 * Brief history of Prediction Markets**

began with an idea Robin Hanson had in the


 * Why is a Prediction Market a useful decision making tool?**

Prediction markets expand people’s connections in organizations. Through market participation employees from disparate parts of organizations discover unknown people with similar interests and unexpected talents. Market activity becomes a thread in employee conversations. Previously unrecognized expertise emerges through successful trading and listing on leader boards.

Smart companies are exploring use and adopting prediction markets to connect intelligences and improve decision-making and forecasting. But doing so demands leadership that is not threatened by discovering what the collective wisdom can tell them, especially when the information shared is not what they want to hear. Organizations are notoriously resistant to processes which upset traditional power and control structures. Individuals hired for their expertise may be threatened that they are not the sole source of information.


 * Successful Prediction Market Adoption: What does it take?**

1. 3R's of Participation
Pioneering prediction market platform provider Newsfutures CEO Emile Servan-Schreiber focuses on the importance of participation. (Phone interview 2008-01-25) that starts with participant belief in the wise counsel of people who make final decisions based on the market outcomes. His 3 R’s for participation include:

Rewards—any kind of material prize e.g. weekend holiday, cash prize

Recognition.. how much the company will recognize participants for good forecasts

Relevance. how much my participation is going to help me do my job.

Experience with a pharmaceutical industry market engaging doctors to forecast volume of prescriptons that will be written for different drugs reveals the 3R's are at work. Participating in the market is relevant, because it informs their day-to-work. They are rewarded by increased and timely industry knowledge. Being invited to participate recognizes their professional standing.

Note: Jed Christiansen
===At the same time, too high an incentive (particularly monetary) can provide perverse incentives, where an individual could benefit through sabotage of a company project. (For example, they bet against a project's success, then work to undermine the project.) But a well-thought out and designed incentive structure will ensure maximum participation with no perverse inventives.===

Based on exerience with his clients, David Perry, CEO of prediction market platform provider Consensus Point focuses on......

(Victoria, can you please pitch in essence based on David conversation?)

2. Keep it Simple
Experience is teaching that not everybody will be an enthusiastic prediction market participant. Even at Google, a company known for hiring quantitative talent, participation was skewed towards IT people? (Check paper.) For trading newcomers prediction market participation can be challenging. Platform providers are developing new models that simplify the process.

Include token example.

3. Promote Geographic Trader Spread
A key research finding from investigating use of prediction markets within Google was the impact of close physical proximity in influencing trading decisions.

4. Pay Close Attention to your Regulatory Environment
Its clear Google is not alone in using prediction markets but few companies seem willing to openly reveal their initiatives. Prediction Markets Cluster founder John Maloney explains that regulation is the "elephant in the room". Especially in highly regulated industries and for companies operating under compliance legislation like Sarbanes-Oxley, corporate legal departments are protective and careful. A real business issue to address with management in proposing any prediction market initiative.

5. Match **Type of market to business problem**


 * 6. Markets may not be efficient**

7. Design to Avoid Biases

8. Integrate Prediction Market Projects to your Collaboration Ecosystem
For companies ranging from Google, to etc etc prediction markets are proving an invaluable business intelligence tool.

Still, they are just one tool and in planning projects ensure learning gained here is distributed and integrated with other initiatves.

9. Strategically Use Prediction Markets to Engage Stakeholders
As a knowledge share tool prediction markets provide an opportunity to capture insights in, across and between organizations. Markets can engage employees in markets operating only within the organizations as Google does. But companies like Corning have used prediction markets to tap partner and supplier knowledge to predict LCD screen adoption. http://hanson.gmu.edu/PAM/press/NYT-3-11-06.htm (Note Corning a Newsfutures client. Follow up with Emile to get update.Are they still using? What did they learn?)

10. Integrate Ways to Tap the Thinking Processes Too
Experience with the Long Bet: project reveals that it's also important to capture what leads to thinking so if the bet comes true that the thinking behind it also visible. Include in the prediction market project management means of promoting and capturing dialogue around the prediction market. Gold lies in the trader's thought processes, not just the outcome.

Final Note
Prediction markets like any of the social media tools or enterprise 2.0 tools are only as good as the organizational cultures using them. Even with the data generated from an open system tool leaders need to be able to execute and implement – the data may tell you that employees are not confident in meeting a goal but only effective management skills will enable a change of course.

ADD: Reiterate "//prediction markets as a tool for co-creating an organization's//" future

jed Christiansen- http://groups.google.com/group/Prediction-Markets/browse_thread/thread/bcd79bd39bd1bba2 NOTE : Fortune Elkins- Misys Fortune is very passionate both about prediction markets and her company, Misys. In her company, as in most others, "uncertainty costs money." Fortune has been successfully testing prediction markets at Misys, and has found that they have been working quite well. She's also had some interesting results, where the person that made massive winnings by (correctly) betting against the crowd was an outsider to the project in question, but someone with extensive knowledge of the company itself. It shows that anyone can be successful in a market, so long as they use the knowledge, experience and resources they have within the company.

Long bets. Favorite field.
 * RAW MATERIAL- IDEAS

What’s been before and why it is or is not like a prediction market.

What are the benefits?**

A little around the technology and algorithms.


 * The practical applications.

Whose using and what for.

What are criteria for wanting to use a prediction market?

How do we get it started? Costs. When not to use.

Not like electronic trading and no human being playing around. Algorithm making decisions. e.g. prediction market taking data from a balanced scorecard.

How does that relate to prediction markets? And maybe it’s a piece to be inserted?**

JA Themes.**

John Maloney the elephant in the room – regulatory issues.

Increasingly quantitative nature of business.

How proximity impacts predictions. Human bias based on real world geographic proximity that transcended social closeness.

Co-horts of predictions based on time in the business. Newcomers more optimistic. Irrational exuberance v hard learned lessons of the experienced.

What it takes to make prediction markets work in organizations.