Ingenix, a Consensus Point partner, recognizes how important the power of collective intelligence can be in healthcare. With the Ingenix Prediction Market, Ingenix is helping employers optimize how healthcare dollars get spent. The end result is more profitable companies with healthier, happier employees.

Ingenix also offers a variety of solutions directly to physicians. We wouldn’t be surprised to see collective intelligence solutions from Consensus Point helping Ingenix empower doctors as well as employers.

Last week, Jonathan Bush, CEO of Athenahealth, a physician billing and practice management firm, was interviewed in the Wall Street Journal. In a wide-ranging interview covering various dimensions of healthcare policy and the ramifications from technology and innovation, this stood out to us:

Mr. Bush thinks the main benefit is the “collective intelligence” that he is starting to weave together from the 87% of American physicians who practice solo or in groups of five doctors or fewer.

Time and again the wisdom of crowds has proven valuable and most times more accurate than a single SME. Applying prediction markets in healthcare can yield benefits for policy and delivery of services.

For more on the Ingenix Prediction Market and Ingenix solutions, go to www.ingenix.com/informationis.

The Obama administration raised the innovation bar by incorporating social media into its campaign and day-to-day operations. Tales from the Technoverse’s blog post on “Technologies to Watch in 2010,” confirms that prediction markets are being successfully incorporated into government entities and will continue to be on the rise in 2010.  The Consensus Point government clients have been successful in projecting results and reducing uncertainty with prediction markets.

Excerpt from Tales from the Technoverse, “Technologies to Watch in 2010″

[Government 2.0] will also lead to greater use of 2.0 technologies to implement various versions of crowd sourcing. Where Intellipedia and Aspace are big news, internal wiki’s will become more second-nature. Pilots associated with prediction markets, using groups to predict things like project results or other public facing data, are starting to be piloted by early adopters.

Andrew McAfee shares a “teaching moment” demonstrating the real-life application of prediction markets.  McAfee’s example shows that, even in its simplest form, prediction markets are very accurate and have a wide range of uses. 

Prediction Markets: A Teaching Moment 
cross posted from the Harvard Business blog by Andrew McAfee
2:14 PM Tuesday December 1, 2009 

Nick Bostrom, Director of The Future of Humanity Institute at Oxford University, considers the impact that prediction markets could have on the creation of government policy in the UK. 

Rebooting Britain: Make policy using prediction markets

By Nick Bostrom | 01 December 2009

This article was published in the January issue of Wired UK magazine.

How do we know what to think about the future? Politicians make confident predictions. If we elect them, unemployment will allegedly go down, the economy will grow, crime will be reduced, and terrorist attacks will be prevented. If we elect their opponents, the opposite will happen. These opponents, of course, disagree. Whom should we trust?

We could listen to the media pundits, but pundits are usually given a platform because they are articulate and entertaining, not because they have a track record of being right. We could listen to academic experts, but both sides of a political dispute can usually point to some experts who support their view. Or we could try to form our own opinions; but we may not know very much about the issue at hand, and at any rate, it is unclear why we should believe that our opinions would be any more reliable than the opinions of all those millions of people who have considered the issue and embraced the opposite view.

One way of generating predictions is betting markets. If people are allowed to buy and sell bets that some hypothesis is true, then the fluctuating price of those bets can be interpreted as a probability estimate of that hypothesis. The hypothesis could be that some particular horse will win a race, or it could be that weapons of mass destruction will be found if our forces invade some particular country. The principle is the same in both cases but, as pointed out by the economist Robin Hanson, the information that could be revealed is much more valuable in the second case.

In every known head-to-head field comparison between speculative markets and other forward-looking institutions, the speculative markets have been at least as accurate. More often than not, they prevail. Orange-juice futures improve on National Weather Service forecasts, horse race markets beat horse race experts, Oscar markets beat columnists’ tips, gas demand markets beat gas demand experts, stock markets beat the official NASA panel at identifying the company responsible for the Challenger accident, election markets beat national opinion polls, and corporate sales markets beat official corporate forecasts.

Prediction markets can aggregate many small pieces of information held by large numbers of people from diverse backgrounds. Prediction markets seem to work well because they reward accuracy (rather than the ability to tell a convincing story) and punish error (rather than the voicing of politically inconvenient opinions).

No system for making predictions is going to be perfect, but so far the empirical evidence seems to quite strongly favour prediction markets compared to alternative ways of generating forecasts. Therefore, the traditional ways of forecasting uncertain political futures – pundits, academic experts, debates between leading politicians, and personal gut feelings – should be supplemented by the creation of prediction markets wherever possible. When the issue at hand is sufficiently important, such markets should be subsidised by the state as a relatively inexpensive form of intelligence gathering.

Horse-betting is selfish, but betting on policy-relevant outcomes would be public service. Pundits should be expected to put their money where their mouths are, and everybody who can afford to lose £10 or £20 should be encouraged to participate. Journalists should be asked to include information about prediction market estimates in their coverage of controversial topics. Schoolchildren should be taught applied probability theory in the classroom and given the opportunity to practice their skills in real-world settings.

This way, I think, Britain would make shrewder policy decisions. Moreover, its population would learn to think about uncertainty in a sophisticated and mature manner. In our complex modern world, that would be a winner.

Nick Bostrom is director of the Future of Humanity Institute at Oxford University.

The Consensus Point solution has proven to be an effective tool for innovation management.  Read below about an effective innovation process and how the Consensus Point idea and prediction markets have improved the innovation process for corporations.

James Gardner, Chief Technology Officer at the Department for Work and Pensions in the UK and author of the blog, Banker Vision, explains the key components of corporate innovation.  Gardner’s “tools of innovation” also are aligned with the fundamental building blocks of prediction and idea markets. 

The Tools of Innovation – excerpts from James Gardner’s BankerVision 
Our commentary in italics

A.M Mills, the author of Hell Bent on Success asks me to explain what I mean by the “tools of innovation”. It is possible to summarise, I think, because everything you need to know about doing innovation happens in four stages.

1. Futurecasting
The first is futurecasting. This is the process of working out what is likely to happen in the future so you can guide subsequent iterations of your innovation process. In the book, for example, I explain a specific futurecasting process based loosely on a scenario planning methodology, but anything that gets structured consideration of the future on the table is a good thing. Why is this important? Well, firstly, you can never ask a senior person for support on something new, especially if that new thing impacts current business or revenue, without rehearsal. They need time to think over consequences, and making them think about the future helps them do that. The second reason is that random innovation without a guide won’t always result in new things that solve the strategic problems of the firm. Out of the box thinking is all very well, but if you are not only out of the box, but out of the ballpark, it is usually not helpful.  

For example, GE has run imagination markets successfully for several years, providing a vehicle for leaders to think about the future in the context of other options. GE imagination markets resulted in higher quality ideas than traditional methods.

• 60% of ideas rated as high quality
• Gathered valuable ideas and engaged employees in a fun way

2. Ideation
Ideation is the process of collecting ideas and deciding how good they are relative to all the other ideas that you might have. The thing is, if you’re running a programme, you’ll likely have far more ideas than resources to execute them. So you have to have a way of deciding what you’re going to work on. Of course, if you’re still thinking that the answer to your innovation challenge is getting the good ideas, then you have some work to do. Ideas are everywhere, and usually all you need to do is find a good way of collecting them. Anyway, you’ll have more ideas than you know what to do with, so one of the main tools of innovation is a decent way to prioritise. Usually, people create various scoring systems to do this, but crowd based methods, such as voting and prediction markets work just as well. 

For example, Motorola launched an idea market in 2007, powered by Consensus Point, for  employees to prioritize thousands of ideas on a quarterly basis. Motorola realized the following benefits, in addition to effectively prioritizing ideas: 

• Increased number of new ideas that are pursued from 11% to 22%
• Decreased number of duplicate ideas by 50%

3. Innovate
The third stage is what I call the “innovate” stage, which is really all about the tools and processes you use to work out – in detail – the stuff that has to happen before an idea is actually fundable.  Anyway, to get to the crux of the matter here, you need to answer three questions. “Can we do this?”, which is technically, operationally, and environmentally, is the idea actually possible. “Should we do this?”, which is primarily economic, i.e. can we afford it, and if we can, will anyone want it?. And, finally, “When?”, which is mainly about the response of competitors or internal players. Answering all that means you have a case which is a candidate for funding and delivery. As you’d expect, there are lots of things you do for each of those questions to get to decent answers for as little investment as possible. 

For example, GE employees participating in the company’s “Imagination Market” trade or buy “ideas” based on how closely they believe an idea is aligned to the business objectives, how an idea compares to other alternatives, and if the idea is operationally feasible. Most often, the ideas represent new technology or new product ideas.

4. Execution
Once you have money, the final stage is execution, which is all about building the thing and getting it out in the market. Key tools here include all the things you need to do to win over users, prove you know what you’re doing from an operational perspective (remember, it’s innovation, so its new, so no one will have made it work before), and a ton of other things. But I think the most important thing is you don’t even get to the Execute stage until you’ve done a substantial amount of groundwork first.

Gardner’s “tools of innovation” are a useful guide to effective innovation management, and idea/innovation markets enable several steps in his recommended process.

Industry leaders, academicians, and business representatives leading prediction markets in enterprises recently shared their insights and innovations related to prediction markets, at the Prediction Market Cluster Summit in Chicago on November 6, 2009.

Linda Rebrovick, CEO of Consensus Point, discussed effective uses of prediction markets, based on multiple years of supporting effective enterprise prediction markets in large companies and government organizations.  She explained that effective enterprise markets require 3 key components:  a proven and expert consultant, a solution that targets key business problems, and the right customer environment and implementation plan.  Rebrovick discussed several use cases highlighting customer examples across several industries and business problems. 

Click Here to Download Presentation (PDF)

Rami Levy, Distinguished Member of the Technical Staff, Technical Lead and Manager of Motorola’s Open Source Technologies Team, explained how Motorola added the TIX Market, powered by Consensus Point, in 2007 to address the challenges of increasing idea backlog and missed opportunities. Levy explained the evolution of the TIX Market and how, over time, the prediction market has streamlined the innovation process, yielding benefits of 55% decrease in disposition days and 40% increase in idea pursue rates. 

Click here to Download Presentation (PDF)

Robin Hanson, Chief Scientist of Consensus Point, discussed the advantages of prediction markets and how to develop effective markets to efficiently yield meaningful outcomes. 

Click here to Download Presentation (PDF)

According to recent McKinsey Global Survey Results, “The heaviest users of Web 2.0 applications are also enjoying benefits such as increased knowledge sharing and more effective marketing.  These benefits often have a measurable effect on the business.” Prediction markets are one of twelve key components of Enterprise 2.0 technologies.  According to McKinsey & Company, prediction market adoption within corporations has risen from less than 1% in 2007 to 8% in 2009, as large companies are embracing Web 2.0 tools.

To read more about the McKinsey Global Survey findings and the benefits of Web 2.0, visit McKinsey.com - Business and Web 2.0: An interactive feature.  Note: Free registration required to view entire articles, and Premium membership required to access entire study.

Dawn Keller, formerly with Best Buy, evaluates ROI of prediction markets and how business leaders need to consider the “cost of not doing” and “cost of alternatives” in this equation.

 Excerpt from Dawn Keller’s blog, The Answer is in the Crowd

From what I’ve seen in the marketplace (both first and second hand), Prediction Markets frequently face the same bottom line scrutiny as any other enterprise application, tool, or resource. How much value will it generate and when? Arguably, the business case should be extra tight when evaluating something new and unconventional. And prediction markets fit the bill. They are not yet widely adopted; they stem from newfangled trends such as crowd-sourcing; and most egregiously, they challenge traditional management orthodoxies.

 Here’s what companies often say:
This seems very promising, but I’m not sure it’s worth the cost.  What kind of returns can I expect?  What is the value of this new information?

Here’s the cost-benefit equation those comments imply:
Market value = market benefit - market cost
    or …
ROI = market benefit / market cost
   where …
        cost = price of Prediction Market solution + cost of internal time & resources
        benefit = value of the information (generated by the market)
Not to get hung up on the math, but these simple equations are missing at least three variables:

1. the cost of not doing
2. the cost of alternatives
3. the multiplying factor of the company’s management “skill”

The cost of not doing

Here, I’m simply flipping around one of the original questions.  Instead of only asking what is the cost of doing something, sophisticated leaders also evaluate the cost of not doing something.  In other words, what is the risk of passing on a particular opportunity, or ignoring a particular problem?  Those risks should be considered, and considered as costs.

Read more from Dawn’s blog on the ROI of prediction markets and how prediction markets can address your business needs.

The iPredict Prediction Market, powered by Consensus Point, proves its precision in forecasting events.  Here is what’s being said about the accuracy of iPredict.

As posted on October 9^th by Eric Crampton of Offsetting Behavior.

iPredict’s forecasting performance: awesome [updated]

Matt has been doing great work over at iPredict, New Zealand’s event stock market. His latest update: iPredict’s rather good forecasting accuracy since it’s opened. On binary contracts (events that either happen or don’t), folks far too often in the iPredict forums, or even the most bombastic prediction markets blogger, say that the market has failed if its price close to closing is far away from the final price. Not so. If a stock is trading at $0.90 for a $1.00 contract, if that kind of contract doesn’t close at zero 10% of the time, the market is seriously wrong. So we want prices to follow a 45 degree line. Here’s the picture.   

A bit of underpricing around the 30-60% range, but on the whole, things are looking very good. Matt goes through a bunch of other ways of judging performance. Go read the whole thing, then start trading! At least if you’re a Kiwi.

Update: Chris Masse is right: the Olympics markets are not the kinds of events for which we would expect good prediction market performance. I just have fun poking noses. I have the underlying data for iPredict from Matt that will let me see whether we’re closer to the 45 degree line for the kinds of contracts that are more like the Olympics one as compared to the kinds of contracts that are more likely, a priori, to aggregate wisdom of crowds. Will check as soon as I’m unburied from the mountain of grading.

White paper on The Ingenix Prediction Market by Ingenix

The Ingenix Prediction Market provides a platform for understanding the psychology that drives people’s actions.

Executive Summary

If your organization offers health care benefits, understanding members’ health conditions and hidden risks is fundamental to eliminating excess spending. But you also need to know who will respond to your messages, what actions they’ll take based on the options you provide, and the timing of those actions:

Clinical Data (A) + Predicted Actions (B) = Elimination of Excess Spending

Many organizations offer clinical data. Where do you obtain the knowledge needed to predict human behavior?

Organizational decision makers in every market need to understand the psychology of their members in order to predict their actions. In the changing landscape of health care—with historical data offering few clues to the future—predicting behaviors related to health care options is the crucial challenge.

Knowledge, attitudes, and beliefs are directly related to behaviors. Understanding these factors is an issue for health care providers, researchers, insurers, pharmaceutical companies, businesses that offer health care benefits, and the employees who use health care. Fortunately, we need look no further than this diverse set of individuals to overcome the obstacles and get a clear vision of the future.

Retail organizations have successfully harnessed prediction markets to quantify the actions their employees and stakeholders will take and improve revenue forecasting as much as 70 percent over traditional forecasting methods.1 Best Buy, General Electric, and Hewlett-Packard—to name a few corporations that use prediction markets—have discovered a way to understand the behavior of their employees and stakeholders. This allows the companies to not only reduce the risk of bad decisions, but to accelerate innovation.

Now, the Ingenix Prediction Market brings this unique and reliable forecasting method to the health care sector, at exactly the moment when predicting reactions and driving innovation are desperately needed.

A More Accurate Approach to Research

A prediction market improves on traditional research methods by:

-       Providing a quantitative method to capture the attitudes and beliefs that influence behavior

-       Adjusting for respondents’ confidence and historical accuracy

-       Incentivizing respondents to reveal what they will do

-       Focusing on what groups of respondents will do rather than what an individual thinks

Predicting an Uncertain Future

A prediction market, also called a “decision market,” poses questions to a group of stakeholders, who respond with opinions of what is most likely to happen in the future. The stronger the opinion, the greater the number of points stakeholders allocate to their position. This can be done anonymously to ensure a candid response. Within a company, this means executive decision makers have access to opinions from the entire workforce, who otherwise might be reluctant or unable to share what they know.

 “The overarching problem every company faces is uncertainty,” says Ron Hoffner, Ingenix associate, “and they try a variety of ways to decrease that uncertainty.” The traditional approach is market research, using historical data, surveys, focus groups, and polls. “Each one of these methods has problems,” says Hoffner, “and the problems are accelerated in the rapidly changing world of health care. Using historical data is especially risky because the fundamental assumption is that the past will predict the future. In light of changing legislation, for instance, we cannot make that assumption.”

Focus groups, surveys, and polls present challenges, particularly within organizations, where individuals are not rewarded for delivering bad news. Multiple layers separate the people who have good information from the decision makers. A prediction market improves communication flow—within an organization or across an entire market.

Unlike polling and surveying, prediction markets are designed to predict the actions a population will take and illuminate the attitudes driving this behavior. Questions are designed in such a way that participants’ answers predict behavior; and participants are incentivized by earning points for disclosing the true attitudes of the population toward the topic. According to Hoffner, “When you want a way to summarize multiple points of view into actionable metrics, the appropriate question can gather those views and predict the likeliest outcome.”

Rev Up Your Research Engine

If you’ve done a Google search, you’ve participated in a prediction market. Based on a search of three billion possibilities, the Google search engine quickly predicts what web pages will be most useful to you. Google continuously improves its accuracy by calculating which sites are chosen most often.

Internally, Google uses prediction markets to determine whether or not product launch dates will be hit, new office openings, and other strategically important events.2 The Iowa Electronics Market (IEM) is a prediction market that was founded in 1988 as a way of predicting the outcome of political elections as measured by how individuals would vote. The IEM has proven more reliable than major national polls, even months in advance of an election. Similar markets have been created for other fields. The film industry has the Hollywood Stock Exchange, to predict Oscar winners and box-office results.

Until the Ingenix Prediction Market was unveiled, there were relatively few applications in health care. Pharmaceutical companies use them to improve awareness of project performance and for marketing. The Iowa Health Prediction Market calls on health care workers to help predict the spread of infectious diseases, such as the H1N1 flu. And now, in collaboration with Consensus Point, a leading provider of enterprise prediction markets, Ingenix has created a prediction market for the health care sector.

According to Robin Hanson, chief scientist for Consensus Point, prediction markets eliminate information bias by tapping diverse minds. Even intelligent individuals, says Hanson, are subject to the groupthink of peers. “Because we often disagree with other groups, we band together and end up agreeing too much with our own teams. No single leader can overcome such biases and data gaps to predict with certainty whether an action will succeed or fail.” Prediction markets produce forecasted behaviors that incorporate more information, run continuously, and tap the minds of those who otherwise would not provide opinions.

Collective intelligence is more reliable than any individual expert opinion. Expert or not, an individual can be wrong. In a prediction market, however, when all the responses are collected, the correct answer is remarkably close to the average of the responses. This has proven true in case after case, giving prediction markets a strong advantage over other forecasting tools.

How can a group of people have the right answer even when many individuals in the group are incorrect? In his book The Wisdom of Crowds, James Surowiecki explains: “If you ask a large enough group of diverse, independent people to make a prediction or estimate a probability and then average those estimates, the errors each of them makes in coming up with an answer will cancel each other out. Each person’s guess, you might say, has two components: information and error. Subtract the error, and you’re left with information.”

The Power of the Ingenix Prediction Market

The Ingenix Prediction Market is the first comprehensive market focused on health care. Ingenix’s strategic partner, Consensus Point, has helped a diverse array of clients improve their ability to make market-based predictions. Best Buy, CNBC, General Electric, General Mills, Motorola, and the Department of Defense have benefited from Consensus Point prediction markets that are tailored to their needs, utilizing the vast intellectual capital of employees and other stakeholders. The Ingenix Prediction Market is available online, with members of the health care sector participating and paying close attention to this constantly updated source of information. Ingenix can further customize this model to enable an organization to make market-based predictions about the actions of its unique member population.

“In the Ingenix Prediction Market, we give participants points that they can assign to the different questions based on their views,” says Hoffner. “The questions are tied to health care events and programs that may or may not be implemented. The more confidence the participant has in his or her opinion, the more points can be applied, because an individual can answer the same question multiple times.However, it costs a certain number of points to answer each time, and you can answer until you run out of points. Thus, individuals who are more confident in their view have more influence. In turn, participants are rewarded for being right by earning more points. The resulting value is a real-time indicator of the attitudes of a population, the actions they will take, and what is driving those decisions.”

Employers Use Prediction Market to Take Swift Action

Q: How will employees respond to a new health care payer?
A large research organization is switching to a new health care payer. Management needs to predict enrollment in each of the three new plans and to gauge members’ satisfaction with the new payer. Historical data and surveys can’t predict enrollment in new plans. Traditional methods take too much time, restricting the organization’s ability to take corrective action to resolve member satisfaction issues.

A: By using a customized Ingenix Prediction Market, management is able to obtain an early and accurate forecast of benefit plan enrollment numbers, and get a real-time read of employee satisfaction with the new plan.

Q: What can be done now to improve employees’ health and cut costs?
An employer needs an in-depth analysis of employees’ health needs, but also to identify what actions employees would be willing to take immediately regarding health issues such as obesity, alcohol use, and smoking.

A: Ingenix pairs a traditional survey with a Prediction Market. In four months, the survey provides an in-depth analysis of employees’ attitudes and health needs. However, in just two weeks, the Prediction Market reveals what actions employees are willing to take today to improve their health—allowing a potentially life-saving three-month jump on better health and lower costs.

For Information: 800.765.6696 | insight@ingenix.com Ingenix, Inc. | 12125 Technology Dr. | Eden Prairie, MN 55344 

Conclusion

While no one can be certain what the future of health care will look like, the need for strategic planning and sound decision making remains. The valuable information provided by Ingenix Prediction Market allows for innovative and proactive planning by policymakers, researchers, health care providers, and any organization whose business operations are affected by the issue of health care.

 “Everyone benefits by participating and sharing information,” says Hoffner. In addition to weighing in with opinions and gathering accurate, real-time information, participants in the Ingenix Prediction Market can pose their own questions. To explore how the Prediction Market works, visit www.ingenixpm.com and become a participant. If you’re interested in creating a customized prediction market for your organization, call 800-765-6089. 

About the Company

Ingenix is a global health care information, technology and consulting leader. We serve a diverse customer base within the health care community, including payers, physicians and hospitals, employers, pharmaceutical companies, consumers, property and casualty insurers, and government agencies. The number of ways that we improve health care is growing every day. Many of the most impactful innovations in health care are taking shape at Ingenix. We are applying the power of information to make the future healthier for everyone. 

Resources
www.consensuspoint.com 
1 Consensus Point Blog, April 9, 2008. Accessed July 30, 2009. Available at: www.consensuspoint.com/prediction-markets-blog/betting-to-improve-the-odds. 

Kunz, Ben, “Prediction Markets Meet Wall Street,” BusinessWeek, Oct. 14, 2008. Available at www.businessweek.com/technology/content/oct2008/tc20081013_033687.htm.

Surowiecki, James, The Wisdom of Crowds, New York: Random House, 2005.

The information in this document is subject to change without notice. This documentation contains proprietary information, which is protected by U.S. and international copyright. All rights are reserved. No part of this document may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopying and recording, without the express written permission of Ingenix, Inc. Copyright 2009 Ingenix, Inc.