We don’t see a lot of need for prefatory material here.

He [Rami Levy, a technologist with the Motorola's mobile devices business] says the combined revenue from product-based ideas and cost savings from internal innovations is “conservatively” 5 to 10 times TIX administration costs, which largely involve two to three dedicated employees. The cost to purchase and implement prediction-market software — called Foresight Server, from Consensus Point — was “under $100,000,” he says.

CFO.com has an extensive write-up of the customer success we’ve had with Motorola, and we are impressed with Mr. Levy’s ability to concisely identify the bottom line value that our Foresight prediction markets platform is capable of delivering to the enterprise.

Further, the article is an elegant case study of the sort of business scenario that is a perfect opportunity for the use of prediction markets, the path to implementation, and the ultimate value.

What we like best about the article, in fact, and consider a true success for Motorola’s implementation of our solution, is that the value goes beyond raw consideration of the bottom line:

But additional, softer benefits were key goals for the program, too. These have been realized through collaboration forums that allow employees to see and comment on others’ ideas, which are thus improved by the crowd’s input. The forums facilitate people from disparate regions and company organizations forming relationships, working together on ideas, and avoiding duplication of effort, Levy says. Motorola actually introduced the forums in 2005 along with the voting mechanism, but participation spiked after TIX was introduced and continues to rise.

The bottom line, says Levy: “TIX has proved to be an excellent conduit for enabling collaborative innovation and creating new value for Motorola in a fun and enjoyable way that encourages participation at a minimal cost.”

When was the last time you implemented something for the enterprise that not only created cost-effective value but was also fun?

You can read the full CFO.com article here, and you can contact us about Foresight here. We predict customer success if you do.

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.

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.

Excerpt from Michael J. Mauboussin’s Think Twice: Harnessing the Power of Counterintuition

Accurately projecting holiday sales is a crucial task for retailers.  A forecast that is too low leaves shelves bare and profits lost, while too much optimism leads to dusty inventory and pressure on profit margins.  So retailers have come up with a precise sales estimate.  To do so, most merchants rely on experts—individuals in the organization who gather information, study trends, and make predictions. 

                The stakes are especially high for consumer electronics firms because they generate so much of their revenue during the gift-giving season and the value of their inventory depreciates rapidly.  The pressure is really on the internal experts at consumer-electronics giant Best Buy, one of a multitude of retailers that rely on specialists.  So you can imagine the reaction when James Surowiecki, author of the best-selling book The Wisdom of Crowds strolled into Best Buy’s headquarters and delivered a startling message: a relatively uninformed crowd could predict better than the firm’s best seers.

                Surowiecki’s message resonated with Jeff Severt’s, an executive then running Best Buy’s gift-card business.  Severts wondered whether the idea would really work in a corporate setting, so he gave a few hundred people in the organization some basic background information and asked them to forecast February 2005 gift-card sales.  When he tallied the results in March, the average of the nearly 200 respondents was 99.5 percent accurate.  His team’s official forecast was off by five percentage points.  The crowd was better, but was it a fluke?

                Later that year, Severts set up a central location for employees to submit and update their estimates of sales from Thanksgiving through year-end.  More than three hundred employees participated and Severts kept track of the crowd’s collective guess.  When the dust settled in early 2006, he revealed that the official forecast of the internal experts was 93 percent accurate, while the presumed amateur crowd was off by only one-tenth of 1 percent. 

                Best Buy subsequently allocated additional resources to its prediction market, called TagTrade.  The market has yielded useful insights for managers through the more than two thousand employees who have made tens of thousands of trades on topics ranging from customer satisfaction scores to store openings to movie sales.  For instance, in Early 2008, TagTrade indicated that sales of a new service package for laptops would be disappointing when compared with the formal forecast.  When early results confirmed the prediction, the company pulled the offering and relaunched it in the fall.  While far from flawless, the prediction market has been more accurate than the experts a majority of the time and has provided management with information it would not have had otherwise.

On November 5 in Chicago, Dr. Robin Hanson, Chief Scientist of Consensus Point, and Rami Levy of Motorola, will be discussing the most effective applications of prediction and idea markets in business and government organizations at a lunch hosted by Consensus Point. Idea and prediction markets will become part of the internal DNA of the best organizations, as these solutions link human capital to organization results by providing leading indicators for the most important initiatives. Rami Levy of Motorola will share the business objectives and specific results of Motorola’s Thinktank Idea Exchange.  Dr. Hanson will share some specific approaches to structuring effective markets.

Robin Hanson, PhD., Associate Professor of Economics, George Mason University and Chief Scientist, Consensus Point

Rami Levy, Technical Lead and Manager, Open Source Technologies team, and distinguished member of Motorola’s technical staff, Motorola, Inc.

For more information, contact Consensus Point at info@consensuspoint.com.

Consensus Point and Our Customers, such as Best Buy and Ingenix, follow a proven enterprise methodology to yield maximum return and value from our prediction markets.  The major organizational best practices include:

1)   Define Business Problem that prediction markets solve and articulate value that could be derived with market insights; develop projected outcomes and track progress that prediction markets solve and articulate value that could be derived with market insights; develop projected outcomes and track progress  

2)    Determine Executive Sponsor and Prediction Market Leader – two different roles, Executive Sponsor guides market strategy and decision acceleration and Prediction Market Leader provides day to day leadership; incorporate prediction market reviews into existing steering committee structures

3)    Begin with a subset of participants, internal first, and validate accuracy through comparisons to baselines; run a market for minimum 90 days, then gather proof points and expand further to other employees, partners, and potentially customers

4)    Align incentives with company culture- and provide multiple rewards that include influence and career development incentives

5)    Determine mix of participants from several functional groups, with a minimum of 30-50 participants; the broader the participant base, the more liquidity for the market

6)   Be Transparent: communicate early and often about market success and decisions that are made from market insights; employee engagement will likely increase from hearing the actions being taken as a result of the market predictions

Thesis on the effectiveness of Prediction Markets as a forecasting tool 

by Kai Trepte and Rajaram Narayanaswamy
Graduate students in the Engineering Systems Division at the Massachusetts Institute of Technology

Graduate students in the Engineering Systems Division at the Massachusetts Institute of Technology studied 20 Prediction Markets at General Mills, powered by Consensus Point, in order to determine the accuracy of Prediction Markets as a forecasting tool in a corporate setting.  According to the study, “Our findings clearly show that Prediction Markets are capable of developing very accurate forecasts, effectively aggregate information from multiple participants and may be able to provide improvement for long-range forecasting.”

Click here to read the full thesis.

Prediction Market Reveals Answer Well Ahead of Results

April 28, 2009 – Ingenix.com - Ingenix Thought Leadership – When trying to determine whether a product is priced right, a project will launch on schedule or the impact proposed health reforms will have, health care entities are considering a methodology that relies less on expert opinions and more on the intelligence of hundreds of people with diverse vantage points.

To determine the results of a key question – what will the employee engagement index be? — on an employee survey, Ingenix used the Prediction Market to gauge the outcome well in advance of the survey results being published. Within one day, the Prediction Market accurately forecasted the index.  Prediction markets provides Ingenix’s clients with early and accurate quantitative data points on future events.

This methodology, known as “collective intelligence,” uses a “prediction market” to “unleash the collective wisdom of organizations and helps them gain a more accurate picture of what is going on in their organization and the industry,” according to Ron Hoffner, associate, Ingenix Consulting.

Prediction markets, defined in a recent BusinessWeek article as “bets on ideas,” ask groups of stakeholders the following question: “What do you think something is worth, and more important, what will it be worth tomorrow?”¹ The groups’ answers have proven to be accurate most of the time, the article goes on to say. “When groups of people bet on something, their combined intelligence is often remarkably prescient.”²

Hoffner agrees. “There is an old Japanese proverb that states ‘None of us is as smart as all of us,’ and we are finding more and more that this is true,” he said. Recent academic research has shown that using a market to forecast demand results in a significant improvement in forecast accuracy when compared to traditional methods.³ The result, Ingenix believes, is that health care programs can better predict which programs are the most likely to succeed.

Another area where prediction markets can add significant value is providing quantitative data on the impact proposed health reforms will have on the industry. “What we are doing is asking a variety of people with different perspectives – who traditionally have not been included in the discussion – for their input,” Hoffner said, “For really the first time, we are going to have quantitative data on the impact of these proposed health reforms that participating organizations can use for planning.”  

Prediction markets harness viewpoints, intelligence

One of the flaws of traditional forecasting is that it generally relies on historical data to make predictions about upcoming events and results. Many years ago, a wise man once said, “You can never plan the future by the past.”⁴ Indeed, Hoffner asserted, using historical data to determine the future assumes that the environment stays the same. However, the health care environment is rapidly changing and traditional methods that use historical data do not account for these changes. The result is forecasts with greater uncertainty.

“To illustrate this point,” Hoffner said, “let’s assume historical data shows two variables are related, such as gas prices and sports utility vehicle (SUV) sales. When gas prices go up, the sales of SUVs go down; conversely, when gas prices go down, SUV sales should pick up. However, they haven’t, so the forecast of SUV sales ended up being higher than the actual SUV sales results. It is clear that how variables are related in the future can change.” These changes can come from a variety of sources, such as social changes or government regulations, he explained.

Prediction markets also may be more reliable because they aggregate and consolidate data “from many individuals, often widely dispersed, each with access to small, idiosyncratic bits of relevant information.”⁵ In a prediction market, companies ask stakeholders from across the spectrum to voice their opinions about future events and milestones by buying “stock” or using points to register their “vote,” according to Hoffner.

“Let’s say a company wants to determine how many people will sign up for their four health plans and if a new wellness program will decrease absenteeism. This is their prediction market. They give stakeholders points to assign to the different questions in the market based on their own views,” he said. “If they have a lot of confidence in the issue, they will assign more points to their answer, so instead of just a  ‘yes’ or ‘no’  answer from a survey where everyone has equal influence, people with more confidence in their view have more influence by assigning more points in the market.” 

Another improvement prediction markets offer over traditional surveys is that participants are rewarded for being right. The result of answering a question right is the participant earning points. At the end of a quarter, for example, those with the highest number of points would receive an award. This results in participants seeking information on programs, which leads to increased awareness of them. 

Further, because the information derived from these diverse sources is contributed on an anonymous basis, the data collected also may be more truthful than if solicited in person. A lower-level employee with relevant exposure to an issue being carefully tracked by the company likely would not feel comfortable telling – or even be invited to tell — his or her boss’ boss about existing problems that might affect forecasts. However, that employee likely would honestly report an experience-based lack of confidence in meeting a future target date in the prediction markets setting.

“Prediction market data fills a lot of information holes, especially when there are many unknown variables, because the diversity of ‘players’ leads to different views and different perspectives that can help reduce uncertainty,” Hoffner suggested. “It lets management know how confident people are in a given forecast while still retaining control over the final decision.”

Expanding use, value of prediction markets

Ingenix believes that prediction markets can help health care entities bridge data gaps so they can “see more and do more,” Hoffner said, so it has forged an exclusive partnership with prediction market pioneer Consensus Point to offer prediction market services to Ingenix clients. These clients either pose questions to an Ingenix prediction market or consult with Ingenix experts to build or improve a prediction market of their own.

“Although collective intelligence is not new, today we are taking that intelligence to the next level, where more value can be derived from it,” Hoffner explained. Ingenix Prediction Markets will combine prospective data from employers, brokers, consultants, providers, payers and academics with longitudinal data from Ingenix’s repositories of patient claims and consumer surveys to provide industry-leading market forecasts of how trends, such as health care reform efforts, will impact the health care industry.”

Prediction markets give Ingenix “the ability to let our clients know what’s out there and what’s coming down the road – in a way that is more accurate than any other trends method – so they can better manage their business,” Hoffner concluded. “Our approach to prediction markets is that Ingenix is providing clients with real-time focus groups that we are calling a ‘living leadership forum.’ Any changes in the views of the group and the marketplace are quickly detected, which means businesses are rarely caught off guard.”

¹ Kunz, Ben, “Prediction Markets Meet Wall Street,” BusinessWeek (Oct. 14, 2008)
² Id.
³Consensus Point
⁴ Burke, Edmund (1729-1797).
⁵ Consensus Point, “What is a Prediction Market?” (Web site accessed April 1, 2009). ,” uses a “prediction market” to “unleash the collective wisdom of organizations and helps them gain a more accurate picture of what is going on in their organization and the industry,” according to Ron Hoffner, associate, Ingenix Consulting.

 License Agreement Provides Access to Successful GE Imagination Market, Comprehensive Innovation Management Process 

Nashville, TN – Consensus Point LLC, a leading provider of prediction market software and services announced the addition of Rebecca Whitehead Munn to the leadership team and a license agreement with General Electric (“GE”).   Through the GE relationship, Consensus Point customers can have access to the proven GE Imagination Market process and benefit by identifying the most promising ideas for business growth.  GE’s Imagination Markets help answer tough business questions such as “what new technology ideas should we be investing in” and “what new products should we develop”. Market participants can submit their own ideas for entry into the market, and they can buy and sell shares of any idea in the market based on how well they believe the idea will contribute to the market’s objectives. At the end of the market, the business leader has a rank-ordered list of ideas.

GE has implemented the Consensus Point solution for idea management in over 10 GE businesses since 2006. The GE Imagination Market has uncovered innovative ideas based upon a variety of business-designated criteria. By licensing and integrating the GE “Imagination Market” technology process, Consensus Point provides a proven, comprehensive design and solution leveraging the prediction market expertise of Consensus Point and the business innovation leadership of GE.  In the recent GE-wide Imagination Market, over 1,400 employees from 170 business segments representing 42 countries suggested over 220 business model innovation ideas. GE Imagination Markets provide a fun way to engage people globally in new idea generation and result in an abundance of relevant ideas that can aid in setting future strategic directions.

Rebecca Munn joined the Consensus Point team as Senior Vice President of Sales. She brings over 22 years of proven experience in strategic planning, sales and marketing leadership, business unit operations, and services delivery. At Consensus Point, Ms. Munn is leading sales, sales operations, marketing, and customer relationships. She has held leadership positions with several global service and technology companies, most recently as the Vice President of Sales Operations of Healthways.  Ms. Munn also held several leadership roles at Cisco Systems, including the former Director of the Services Division, Connected Health Vertical, and principal in the Internet Business Solutions Group. She was the co-founder of The Arbora Group, a retail and wholesale operations start-up, in 2001. Ms. Munn is a former board member of the Nashville Technology Council. She earned an executive MBA from the University of Colorado and a BBA in marketing from the University of Texas at Austin.

“Our customers now have access to GE’s global experience in innovation management and proven design for the Imagination Market, commented Linda Rebrovick, CEO, Consensus Point.  “This fully integrated solution, including the Consensus Point Foresight software and GE Imagination Market process, allows organizations to rapidly launch and realize the significant benefits of an idea and innovation market. Some of our customers have cut the time to process ideas in half through using idea markets. In addition to the GE partnership, we are pleased to announce the continued growth of our company with the addition of Rebecca Munn to our leadership team.” 

Employees use prediction markets to vote up product ideas and productivity improvements they think should be selected for development

April 27, 2009 — CIO.com — The project: Deploy a prediction market to aggregate new business ideas suggested by Motorola employees and assess their viability. A prediction market is a system for forecasting the outcome of projects or events based on how willing individuals are to buy “stock” in them. Users buy shares to vote items up. Each item is evaluated based on how much it is “worth”: the higher the value, the more popular the idea.

The business case: Motorola sought to allow any employee the opportunity to propose ideas for new products, upgrades to current products, productivity improvements or cycle-time reductions, says Rami Levy, distinguished member of Motorola’s technical staff and a member of its open-source technology team, which manages the prediction markets for the company. In 2003, Motorola had built a system to collect ideas, called ThinkTank. But when thousands of suggestions poured in, the teams that were supposed to weed through them were overwhelmed.

Using prediction market technology, Motorola could engage employees in the selection process by letting them vote for the ideas they thought had the best business potential. The most popular ideas could then be selected for further study and eventually be developed.

First steps: Levy and his team worked with a variety of director-level managers, including senior VPs, to secure buy-in for the project. “ThinkTank was already being sponsored by an SVP,” he says, but they needed support from others who would have to produce the business-case and user scenarios for new product ideas. That sponsorship was crucial to obtaining cross-organizational participation and funding for the tool.

Once Levy’s team secured management support, they integrated prediction software from Consensus Point (called ThinkTank Idea eXchange, or TIX, internally), with its existing ThinkTank application. In a six-month pilot during 2007, they experimented with market parameters, such as how long to keep ideas in play and how to finance participants’ purchases.

Today, employees submit ideas to ThinkTank, where anyone within Motorola can vote on them. Ideas that receive at least five votes are eligible for TIX, where each idea is initially valued at $10 per share. Anyone who wants to participate gets $100,000 to start with to buy the stock of the ideas they like best. As employees buy or sell shares, the value of the idea rises—or not. After 30 days, an idea review team determines which of the top-valued ideas to pursue. Winners are judged based on their stock performance, and participants who hold stock in winning ideas get a bonus.

It typically takes 18 months to develop a product at Motorola, so the first product ideas vetted through TIX are expected to come to market this year, Levy says.

What to watch out for: Market parameters that work in one circumstance won’t necessarily work in another, says Levy. You have to fine-tune your system to your environment. Motorola decided to limit an idea to a month in TIX to ensure new ideas were always entering the market. Meanwhile, even though employees find participating fun, you need to get them involved and keep them engaged. Levy’s team ran ads on the company’s intranet, conducted user satisfaction surveys and incorporated social media into the system. “Socialize the experience,” he recommends, “by integrating user comments, tagging, recommendations and links to other information.”

By Kristin Burnham © 2008 CXO Media Inc.