Clients often ask us what level of user engagement is reasonable to expect and how that level can be sustained over time. This isn’t a challenge unique to prediction markets – it’s a challenge for all applications that depend on user-generated content. Twitter is incredibly successful, but there is a huge gulf between the number of registered Twitter users and the number of active users.

Prediction markets ask participants to give: they have to place bets, share their knowledge. The key to user engagement is to make sure that users get just as much as they give. One of our clients, a large consumer products company, has struck this balance, achieving record levels of participation. Your first assumption might be, participants are actively betting so they can win prizes — but this is not the case. In a recent user survey, only 4% of respondents said they participated because of the opportunity to win prizes.

Instead, here is what these participants “get” out of being active in the prediction market:

Share valuable information with participants. 88% of survey respondents said that one of their favorite aspects of the market was learning about the innovation opportunities being explored by the client. 55% liked that it was an opportunity to learn about others’ points of view. One comment: “It is a good way to connect product development with the marketplace. I love it!”

Demonstrate to participants that their voice is being heard. The survey also found that sharing personal insights was a key motivator of participation for 40% of respondents. One comment stated: “With this tool, I feel like a part of the company as a whole, not just a member of my specific department. I hope this tool continues to be of value to the company in the future.”

Have fun. It’s no secret that games are a great way to engage people AND teach (it’s not all fun and games). That’s why casual games, such as Farmville, have taken off. And it’s why the military uses gaming to help prepare for combat. In addition to Crowdcast, our client also uses ideation software. However, the ideation software does not have nearly the same participation levels as Crowdcast. One reason for this is because Crowdcast provides a fun, competitive game experience, whereas the ideation software doesn’t. 42% of survey respondents liked being able to see how they performed relative to other employees. One participant’s comment: “I love having a friendly competition with my colleagues – we stop by each other’s desk all the time to compare how we’re doing!”

To find out more about how Crowdcast technology works, please contact us here: info@crowdcast.com.

As the dust settles in the aftermath of the highly-anticipated Black Friday and Cyber Monday madness, retailers are gauging how successful the weekend was and what it means moving beyond this holiday season. So far, the outlook hasn’t been too sunny. Retailers rely on Black Friday and Cyber Monday to make their goals for the year and lower than expected sales can spell big trouble.

Retailers could benefit significantly from better foresight into consumer behavior and change the ultimate outcome of their most critical days of the year. Most importantly, this kind of insight would help them make better decisions for their business in terms of product stock numbers, price points, sales, discount strategies and other crucial metrics. During the holidays, new products are debuted to the public- some are swept up and instantly sell-out while others are left by the wayside, leaving stores with overstock. If retailers were able to better predict the level of sales on these days, they would have a greater chance of stocking the right stores, with the right amount of the right products.

How could they increase intelligence regarding these issues? Simple. They can leverage collective intelligence from stores, employees and buyers to understand what items are likely to be hot. Using this aggregated intelligence can help make better decisions about what to stock in stores or promote online. Bringing Crowdcast technology takes some of the guess work out of predicting product sales numbers and overall sales potential.

Prediction Markets would provide enormous insight to retailers who are desperately trying to minimize risks, ascertain realistic product quantities and gain a more reliable projection of how businesses can get the most out of the year’s most critical shopping days.

Topic: When Will Our Product REALLY Launch?
Using Collective Intelligence to de-risk new product introductions.

When: December 8^th at 11am PT.

Where: Register Today on CFO.com. It’s free to sign up.

Does your company rely on new product introductions to drive growth? A single missed launch date for a new product can impact company valuation by 5%, costing millions of dollars in market cap. With increasing consumer and investor expectations around new products and the globalization of supply chains – the risks to your company have never been higher or harder to measure.

How many products has your company launched over the years? The information you need to make better decisions and to minimize risks exists in your company, if only you had an efficient way to tap into it. Prediction markets offer a new way to identify, measure and respond to risks. By aggregating insights from across your company to evaluate and quantify risks, you have the best chance to recognize issues early and take corrective action.

In this webcast you will learn about the key problems with new product introductions, the risks they introduce, and how to use prediction markets to quickly identify, measure and respond to risks that keep new products from launching on-time.

Register Today.

I was reading a review of the new Palm Pixi on Gizmodo and I was struck by the classic new product issues that the review highlighted. First off, the product was released at $100 when its more powerful sibling the Pre is available for roughly the same price. So, Palm has likely hurt its sales more than anyone else. Second, the product appears to be riddled with quality problems. The Pixi is apparently really slow which totally misses consumer expectations for a $100 product. As a result, both Amazon and Wal-Mart are selling the Pixi for $25.

Could Palm have known? The answer is Yes. Palm invented the smart phone (remember PDAs). Do you think that Palm has some people who know about consumer preferences and behavior? Do you think that Palm has people who could have raised the alarm about the price in comparison to the already released Pre? Do you think Palm has people who could have pointed out the quality problems? You bet. So, why does this happen? Often, it is because the company has no way to listen to employees and then collect information in a way that is scalable across the company yet consumable by executives.

If Palm were to run Crowdcast solutions on a project like Pixi, then questions such as – When will the product really ship? How much will it sell for? How much will it cannibalize the Pre? and How many defects will it ship with? could have been asked. The answers to these questions would have been revealed as metrics, a date (Oct 09), a price ($25), at $25 it will hurt Pre sales by 50%, and unless we do something like fix the software before we ship it will be really slow.

It’s time that we started asking the crowd to drive new product introductions.

Universities represent our collective future. Although universities hand out diplomas to individuals, it’s our future doctors, CEOs and world leaders who toss up their hats at the end of the ceremony, right?

A recent CNET article highlighted an exercise at Singularity University’s executive program. Melanie Swan, a Silicon Valley hedge fund manager, had groups of students dream up revolutionary product ideas and also had them bet in an online prediction market on which group would get the most venture capital if their idea were real. The reporter writes:

Despite the fact that some technical problems got in the way, the point was made: prediction markets, given enough active participation, are increasingly seen as an excellent way to arrive at the answers to any number of questions, whether it’s sales figures, who will win presidential elections, or who will get the most VC funding. Indeed, the winning technology concept–a pill that could cure cancer–and team were accurately prognosticated by the market.

The university’s study is certainly forward thinking. That said, one should note that they’re not really running a prediction market – they’re running an idea market. This is an important distinction to make. When the students gear their bets towards ideas they think investors will find attractive, this means that the final outcomes of the market will be biased to the norm. We’ve discussed why idea markets are flawed and this is where Crowdcast differentiates its forecasting philosophy — gathering individual expertise to make more informed predictions around critical, quantitative metrics, rather than ideas.

Prediction markets everywhere are managing to find sure footing in uncertain times. From financial prediction markets on CFO, to the University of Iowa’s prediction markets on H1N1 virus outbreaks and vaccine levels, prediction markets are enabling us to get clarity around areas that were once opaque. Where else will we see the crowdsourced predictions put to work? The real-estate market? The struggling fashion industry?

Let’s put this very question to the wisdom of the crowds — send us your thoughts!

The anecdotes of prediction market pilots in major organizations are everywhere. Often they are tried in a small, almost clandestine manner within an isolated corner of a company by someone fairly junior. His forecasts tend to take on one of two characteristics – fun forecasts (sports, elections, etc.) or forecasts that are business related. The business-related forecasts are usually trivial and center on uninteresting metrics, or, more interestingly, they’re compelling enough that they get someone’s attention and the project is promptly killed. A junior person with an anonymous crowd can feel like a lynch mob to this middle manager who has previously ‘owned’ the forecast.

Where we have seen prediction markets thrive is where they get early senior support in the company. These executives vocally support a new way of forecasting and embrace the fact that there is knowledge that is not getting to their desks. The culture they support values and respects the opinions of their employees. They are not concerned about putting their key performance and risk indicators front-and-center for their reports to forecast and discuss openly. In these organizations, the adoption is high, sustained participation is healthy, and, yes, the forecasts are accurate. Management is able to make mid-course corrections more swiftly, and iterate product development in a more agile manner.

Prediction markets are not about ‘gotcha,’ they are about measuring and mitigating risks that are key to the business.

It is this ideal client, where the company is truly making a shift in the way they collaborate, who we look for in our engagements. This is one of the reasons we have made the decision not to employ a freemium model, offering a lower-end DIY version on our site and an enterprise-version to those who are so inclined. The inexpensive, ill-designed, and soft-pedaled implementations that result from this do a disservice to what we can really do for a company that’s all in.

Are you all in?

In the article Seeking a Shorter Path to New Drugs, Natasha Singer covers innovative methods that drug companies and researchers are using to improve drug discovery and commercialization. One of the projects she highlights is the Pharmer’s Market, our collaboration with MIT and Harvard that we announced last month. To learn more or to sign-up click here.

As we mentioned last week, Crowdcast is teaming up with Susan Scrupski and the 2.0 Adoption Council to launch a new prediction market today at the E 2.0 Conference here in San Francisco. Those attending the conference can submit their bets during the conference for chances to win prizes for the most accurate predictions.

Not at the conference? No problem. The market will be live at 3 pm PT and everyone interested in Enterprise 2.0 technology is invited to sign up here: http://surveys.crowdcast.com/adoption. To visit the market, please log in here: https://adoptionindex.crowdcast.com.

By using wisdom of the crowds, this prediction market is a new method of predicting how quickly 2.0 technologies will be adopted by enterprise businesses and will be a continuing measure of progress. The market is based on the 2.0 Adoption Council Index survey led by Scrupski and a team of market-leading professionals who are in the process of adopting 2.0 technology.

For more information click here!

The Boeing Dreamliner has been delayed 5 times and is more than 2 years behind schedule, severely denting corporate credibility and profits. Standish reports that 68% of IT projects deliver over budget, are late or missing key features, with 24% of projects being abandoned or canceled. Flyvbjerg et al. (2002) report on how public works projects are consistently over-budget by an average of 28%.

This inability to produce reliable forecasts has costs to the credibility of the organization, leads to disappointed investors and customers and makes efficient resource management next to impossible.

Why are corporate forecasts often so wrong and what can be done?

I’m writing a series of blog posts to answer this question. Each post will deal with a particular reason for bad forecasting including:

1. Over optimism
2. Strategic misrepresentation
3. Anchoring and adjusting
4. Organizational hierarchies
5. Fallacy of data

1) Optimism Bias

Optimism bias is the demonstrated systematic tendency for people to be over-optimistic about the outcome of planned actions. This includes over-estimating the likelihood of positive events and under-estimating the likelihood of negative events.

At the outset of a forecast, for example when a project plan is being put together, optimism bias can lead to unachievable timelines, underbudgeted costs and sky high sales forecasts.

This optimism bias transcends gender, age, education, and nationality — although it seems to be correlated with the absence of depression in planners.

Documented examples include:

* Second-year MBA students overestimated the number of job offers they would receive and their starting salary.
* Students overestimated the scores they would achieve on exams.
* Almost all newlyweds in a US study expected their marriage to last a lifetime, even while aware of the divorce statistics.
* Professional financial analysts consistently overestimated corporate earnings.

Optimism has the advantage of encouraging risk taking. How many start-ups would be formed if the entrepreneurs were true to them selves about their chance of success for example?

However, optimism bias can also have significant costs. For example, a project which is expected to take 6 months and $1MM to complete, will run out of money in month 7. In addition, if sales are below forecast, investors may be disappointed and the credibility of the entrepreneur is reduced. Managing resources across a portfolio of optimistic projects is a planners nightmare. When is project A really going to complete…?

How can managers and investors gain better forecasts by avoiding optimism bias?

1. Reference Class Forecasting (RCF) – takes into account the “inside view” and also the “outside view”. It considers past experiences and typically requires the planner to make their estimates more reasonable by comparison with past forecasting errors. For example, the UK Government requires project planners to apply an uplift to forecasted costs for major infrastructure projects (bridges, roads etc). This increases the projected costs by up to 60% (depending on what type of project). However, if the planner anticipates this uplift, they will likely sandbag the original forecast, and defeat the object.
2. Prediction Markets (duh!). By aggregating information from many sources, the forecast will likely contain more knowledge of the likely outcome. Most projects have been done before, and by including experience and also views from those less attached to the outcome, a more accurate and reliable forecast can be obtained. Unlike RCF, prediction markets are much harder to be gamed by the planner. A well-crafted prediction market draws from a diverse group of people, ensuring a balanced point-of-view.

Enterprise technologies are always a hot topic – especially when it comes down to predicting their adoption rate and how they will change the future of the business operations. This week we had the opportunity to sit down with Susan Scrupski, founder of the 2.0 Adoption Council, which is a peer-based, information-sharing group of global business leaders interested in facilitating adoption of 2.0 practices and methodologies within the large enterprise.

Susan is teaming up with Crowdcast to launch a new prediction market at this year’s Enterprise 2.0 Conference. The market will predict the outcome of the 2.0 Adoption Council’s annual survey, which forecasts enterprise adoption of 2.0 practices and technologies. E 2.0 attendees will have the opportunity to lock in their bets during the conference, and there will be prizes for the most accurate bets. We’ve already started to give out exclusive invites to participate – you can request an invitation here. The market isn’t just for E 2.0 attendees – it’s for everyone with interest in 2.0 technologies.

In our chat with her, Susan shared her perspective on 2.0 technologies, hurdles to their adoption and a glimpse into the future.

CC: How did you become interested in Enterprise 2.0?
SS: I was a stay at home mom for five years after the dot com crash. When I came back to work in 2006, I started looking around the technology industry for something I was interested in. At that point, E 2.0 was appearing on the scene. I was passionate about the dot com visionaries and then, almost six years later, we had the technology to implement and deliver their original vision. I was excited by the opportunities before me, could see what the real impact for business could be and wanted to take part.

CC: What is your vision for the 2.0 Adoption Council?
SS: Having seen so few successful case studies and technology that did not fulfill expectations, I was at a point of frustration. But, the last E 2.0 conference in Boston had a different feeling from years before – customers were showing up in droves. Some of the most productive sessions were the “un-conferences,” where customers could find other end users to talk to and share their experiences. My vision for the Council was to give these folks a home in a private setting to discuss the joys and sorrows of E 2.0. The Council would give them an opportunity to share and could simultaneously accelerate the pace of adoption.

CC: How do you envision 2.0 concepts changing the way enterprise does business?
SS: When we began to talk about 2.0, we were referring to the technology itself. Now, 2.0 is moving towards something I like to call socio-collaborative transformation. There are four tenets of Enterprise 2.0: transparency, authenticity, trust and collaboration. How will these concepts change business? Well, they change working relationships. This technology is changing the dynamics of how customers relate to others and themselves – changing worldwide business by increasing efficiency and the amount of quality information we have to work with.

CC: What are the adoption challenges you’re seeing right now?
SS: In my opinion, from the beginning, the challenge in this space was awareness. People are not aware of what is possible. There is a need for awareness around what these tools can do and how they can be implemented. Another challenge is the culture of business. It seems radical for so many companies to transform from a hierarchical environment to an open, porous, collaborative one.

CC: What are your hopes for participation in the 2.0 Adoption Index Prediction Market during the E 2.0 conference?
SS: I would love to see 100 percent engagement! If nothing else, this is a learning experience to try out a few new tools. The larger the percentage of audience participation, the more meaningful the results are, leading to more accurate forecasts. I have a suspicion about the zeal of this community – with so many of them excited about Enterprise 2.0, I can’t wait to see the results.

CC: What do you hope to learn from the collective insight gathered by the prediction market?
SS: This data is valuable in terms of tracking the growth in the sector. We are looking to create a continuing measure so that year after year we can plot the evolution of the market and how it takes shape over time. Because of the social web, we tend to subscribe to voices we agree with. There is a danger in not seeing what the whole world is doing – hopefully these markets will reveal this, allowing us to leave the echo chamber and broaden our horizon.

CC: How do you plan to utilize the prediction market model as you move forward with the project?
SS: We want to try to set a benchmark by creating an index to track progress. In 24 months the market may be different, but at that point we will customize it to reflect the current environment.

With the recent Adoption Council survey we conducted, we are hoping to establish a credible benchmark for measuring progress. Following up with the prediction market, we hope to have an accurate, forward-looking forecast about the adoption of 2.0 technologies in the enterprise. We need to look beyond what is happening now – there is value in having a view into future trends in our industry.

CC: Susan, it was great speaking with you, any closing thoughts?
SS: We are passionate believers in enterprise technology and have our own skin in the game. Our goal with the Council and Crowdcast is to elevate the conversation around these tools, using them to drive our own business growth. Prediction markets haven’t yet gotten a lot of buzz and discussion, but they certainly play a role in Enterprise 2.0. It is exciting in terms of awareness to have people voice what they believe are reasonable forecasts in the industry. Prediction markets are a very handy tool and I would love to see more people in the space taking advantage of them. This is an interesting case study, and we are very eager to see the results!

For more thoughts on the 2.0 Adoption Index Council and Prediction Market, visit Susan’s blog, ITSinsider here.