How long have you been working with Information Markets?

I’m dealing with Information Markets since 2005. Back then we did an International Benchmark Research at the Witten/Herdecke University in cooperation with a global mobile phone manufacturer, which ordered the study to be done. Because of the great potential I saw in the „Wisdom of the Crowds“, I kept on working in this area, focusing on the insights Information Markets provide into complex and almost unpredictable situations.

You have used Information Markets in HR and change management. What exactly have you done there?

A global insurance company had big organizational changes coming up. The challenge in this task was that changes, even positive ones, always create a feeling of insecurity and are often being rejected in the beginning.

We used an Information Market tool as a Live-Ticker to monitor the employees‘ reactions while implementing the changes. This served as an real-time indicator of dissatisfaction or insecurity, thus we managed to keep the process transparent.

The Information Market was used as an indicator for the top management in order to intervene early and effectively. For example, to see which departments where already committed to the changes and which departments needed further explanations and support. In big companies not all departments need readjustments, so this allowed us to see on which we should concentrate. The market then also showed us, whether the adjustments were successful.

Finally, establishing an Information Market was also a clear signal form the company’s board towards its employees that they would have a word in this big change management process.

What were the biggest challenges of this project?

Transparency was a big asset but also a kind of a liability. Transparency required managers to be serious, i.e. as a manager at the top your decisions now had to be well argued for. For many managers this appeared to be more of a limitation at first, creating more work for them. But it turned out to be a good thing, since now ones decisions are even more thought-through and hence of a higher quality. Moreover, since decisions are now more transparently discussed they meet with less opposition in the company once they are to be implemented. These are significant efficiency gains by introducing such a style of collective decision-making– while the final word always remained with management.

What are the benefits of using Information Markets?

Information Markets are an approach to make your employees aware of certain strategically relevant topics because in Information Markets employees voluntarily get involved in topics they would otherwise dismiss as ‘corporate whatever’. The feedback which employees leave in the markets is relevant information for management. As a result, it gives the possibility to make more accurate decisions, due to additional information and a positive commitment from the whole organization.

What are you working on at the moment?

I’m working on implementing the Open Strategy concept at Volkswagen. I am also working on my PhD thesis on „Information Markets in the Context of Strategic Processes“.

Dear Caroline, thanks for taking the time to share your insights and experience with us. We wish you all the best for your future work!

Source: en.wikipedia.org/wiki/Ibm

According to several media reports (Reuters, Techgig), IBM plans a huge job reduction and restructuring of their workforce. This plan incorporates the release of up 300,000 of its employees (ca. 70% of its worldwide workforce) and then rehiring them as freelancers without the social benefits of a full-time worker.

We, at CrowdWorx, think that this is not the way things should work with crowdsourcing. We believe, employees do not have to be fired in order to crowd source their potential. Our own crowdsourcing approach shows how employee-based crowdsourcing can work effectively. In our approach the crowdsourcing happens within the company. This is in contrast to traditional crowdsourcing, which is used to gather inputs from consumers or external experts.

 The major difference and advantage of employee-based crowdsourcing: The employee is both your „consumer“ and your „expert“. Each of your employees is a consumer in their private life outside the company, but still an expert for his company and its products and market.

Big companies like Henkel or Tchibo have already successfully introduced CrowdWorx amongst their employees. German Telco giant Deutsche Telekom is using this kind of crowdsourcing to gather the knowledge of 240,000 employees to get accurate predictions and decision support. Global Consumer Goods corporation Henkel used CrowdWorx to raise its forecasting accuracy by 22%, which results in an annual EBIT increase of 40 million Euros, just by using employee-based crowdsourcing.

Time will show which approach is going to last and we will be keeping you up to date on any new developments in the industry.

Nathan Bricklin

Nathan, how do you go about engaging team members at Wells Fargo? 

It starts with the recognition that Wells Fargo team members are collaborative in nature and regularly engage their existing contacts across the organization. Adding social tools to the process simply enhances the reach of these existing personal contacts and leverages the knowledge and experience of people in a broader network.

What benefits did Wells Fargo achieve using Web2.0 tools?

Team members can generate new ideas faster and can more quickly identify experts across the organization. That allows us to create a shared focus on addressing real customer needs in a timely and innovative way. Social tools also increase team member engagement, which we believe results in the retention of both key people and institutional knowledge.

In your opinion, what are the top 3 reasons why a company should use Social Business methods?

To extend collaboration beyond scheduled meetings and across geographical, organizational, and hierarchical boundaries. To reduce operating costs by creating more efficient and multichannel collaboration opportunities. To extend team member engagement, satisfaction and productivity.

Thank you Nathan for sharing your insights and thoughts with us!

Carol Gebert

Carol, you are one of the pioneers in using Prediction Markets in business. Tell us how you have applied Prediction Markets in a corporate environment?

We setup Prediction Markets at Eli Lilly to predict enrollment rates into a clinical trial that was taking too long to enroll its patients.  That put the entire drug program behind schedule, so Lilly wanted to know when the enrollment would be complete  The participants in the market were meant to be the clinical sites that were enrolling patients and performing the clinical trials.  However, ten years ago, few of these clinics provided easy access to websites.  We were warned that many of the clinics were low-tech, with little more than a fax machine.   Under the rules of the time, we could offer only token prizes such as coffee mugs.  Rather predictably, participation in the market was too low to allow liquidity, so the Prediction Market failed in its goals.

We were also involved in setting up a market aimed at the public, to predict market share in several drug markets.  That market was more successful in attracting traders, but we had to wait for one year to declare the outcome, and during that time, participation dropped off.  However, the predictions were pretty accurate.  So it was declared successful.

What were the biggest challenges in using Enterprise Prediction Markets in the pharmaceuticals industry?

One big challenge is the long timeline of development in the pharmaceuticals industry. Most traders in a Prediction Market would be reluctant to wait for more than a year for their bets to be settled. There are ways to overcome this, e.g. using the average price for giving interim payouts or splitting up a long-term project into short-term milestones and forecast the probability of meeting these goals.

Another challenge is the fact that in most companies, not just in the pharmaceuticals industry, forecasting means simply planning or goal setting. Somebody sets an optimistic goal and no one is interested in an actual forecast..  Perhaps Prediction Markets are better suited to industries where forecasts are truly actionable, rather than simple forewarnings.  When HP ran its pioneering Prediction Markets, it wanted to know how much manufacturing it should commit to, for each printer version, before the next model was released.  Thus, forecasts of sales were actionable and better forecasts resulted in cost savings.  But for some business applications, real-time forecasts do not result in more cost savings, compared to simple projections from historical numbers.  In these situations, forecasts are merely used to confirm that operations is being run according to plan.

If you could start out again today in pharmaceuticals, which areas would you try for Prediction Markets?

For a pharmaceutical corporation the most money to be saved is in the last phases of the clinical trials. Trials themselves cost many tens of millions of dollars to conduct, and each day of delay loses $1million in lost patent time. So potentially, the forecasting of outcomes is valuable.  However, these clinical trials are deliberately double-blinded to ensure purity of the data, so forecasting the outcome of such experiments undermines the process..

Therefore, I’d probably go into the earlier, discovery stage.. Here the savings are not as large but still worthwhile.  For example, a molecule showing promising activity during discovery may still run into solubility/dosing or metabolic problems and be shelved in preclinical or early clinical testing after spending perhaps $10million.  So predicting physical and pharmacologic properties of a molecular series when it is still in its medicinal chemistry cycles would be valuable, actionable and have some results known in under a year.  The traders in such a market should be the medicinal chemistry team, the metabolism, pharmacology and toxicology teams, and perhaps even the process development team.

I can see licensing professionals appreciating Prediction Markets, too.  The licensing departments of big pharmaceutical companies are constantly searching for good drug candidates partially developed by smaller companies.  They typically review dozens of these each year.  All licensors paint rosy cases for their particular molecule, so it is hard for the big pharma professional to pick which drug candidates really are worth the licensing fee and remaining development costs.  Licensors typically approach big pharma licensing offices just before a major milestone is due.  Maybe a Prediction Market designed around those promises would help the licensing team make purchasing decisions.

As for areas beyond my home turf, I think toys would be high on my list.  Toy makers get a lion’s share of their income seasonally, in December.  Their product successes are dependent on personal taste (i.e. fashion) to a degree that technology products are not.  And they need to commit to manufacturing many months in advance. That sounds like a clear need for good forecasting.

PMs could also make valuable tools for supply-chain cost forecasting where supplies tend to have irregular availability or volatile pricing.  For example, I think chocolate makers might like to better predict pricing for cocoa, sugar and cream.  Similarly, electronics manufacturers might like to have better forecasting of rare earth supplies.

You have been in the Prediction Markets industry already 10 years ago. In your opinion, what are the Top 3 developments for Prediction Markets since then?

One of the major obstacles in the past was the way Prediction Markets were accessed: Online via the Internet, which at that time meant sitting at a dedicated desk and going through several steps to even access a desired page.  And all pages needed to be visited separately, with conscious intent.  Nowadays, browsing habits have changed and people are getting used to visiting Intranet portals and consolidated social sites on a routine basis. Mobile phones and mobile apps have opened up another access channel which was not available 10 year ago.   Everywhere I look, I see people wanting to play with their mobile devices.  I think Prediction Markets would make a perfect mobile app for expert-level professionals.  For consumers, Prediction Markets embedded into Facebook would be the way I would go.

Ten years ago many of the things we wanted to forecast were not measured so we could not know the actual outcome, even if there was an objective event which could have been measured. Nowadays, much more data is collected and readily available.  So the outcomes vital to defining the stocks or bets in a Prediction Markets are available in a way that restricted us before.

Last but not least: Until not long ago Prediction Markets have been banned in the U.S. under internet gambling regulation. U. S. companies were very hesitant to apply Prediction Markets, even when there was just play money.  Around the time I was talking to Lilly, DARPA funded a PM pilot to predict terror threats, but quickly canceled the project when two politicians misconstrued the effort, and denounced it publicly.  In the US, if your words can be twisted and misconstrued, then they will be.  Pharmaceutical companies are very nervous of that public reflex.

But in 2006 Professor Robin Hanson, of George Mason University successfully championed an effort to exempt Prediction Markets from this regulation, on the rationale that it is a business tool. That was a big step forward for PMs.  Before this change, PMs were severely limited in the types of incentives offered.  The Hollywood Stock Exchange demonstrates that people will play for no material reward if there is entertainment value to participating, but I suspect this is true only for topics of special interest, like movies.  For most business topics, a significant reward is required to attract and maintain participation.  From first-hand experience, I can tell you that you cannot motivate professional participation with coffee mug prizes, alone.

Thank you Carol for sharing your insights and thoughts with us!

The success of the pilot stage will result in the roll out of CrowdWorx to Henkel’s S & OP process in its major European markets in 2012. We’re excited about this opportunity to optimize the supply chain for Europe’s leading consumer goods and FMCG manufacturer and will report on the learnings from the roll-out soon.

For more details on the pilot project please refer to our Henkel case study.

Crowdpark is a B2C spin-off of Analyx, which is also the maker B2B Prediction Market platform CrowdWorx. Crowdpark uses Prediction Market technology to make legal betting with play-money more fun. The first product Bet Tycoon is the no. 1 betting game on Facebook. Since its launch in late 2010 Bet Tycoon has received over 1.5 million bets on such diverse topics as Politics, Gossip, Music, Technology, and Sports.

Recently, Crowdpark was featured in Forbes Magazine, Tech Crunch, Dow Jones Venture Wire and others. To find out more about Crowdpark visit http://www.crowdpark.com.

Dr. Thomas Bungartz

Why is Deutsche Telekom using prediction markets in Marketing?

We have made use of prediction markets to evaluate the success probability of new product concepts. To do this, we wanted to gather the opinion of all our marketing employees. Each and every employee has his or her own special capabilities, experience and point of view – we wanted to use this collective Know How. Moreover, we wanted it to be an innovative method that would also be fun to use and would surpass market research methods which are already in use at Deutsche Telekom. This is how we arrived at the approach of prediction markets.

Where do you see the USP and the use of prediction markets in marketing?

The gamification and the stock exchange attributes of prediction markets make participation more interesting. The response we got and a participation rate of almost 40% during the pilot phase showed us, that the tool is not only easy to use but is actually a lot of fun.

Apart from a good quantitative result (participation rate and activity) we also received specific results in the form of ranking product success probability. And through the built-in comment function we have gathered about 2,000 opinions. Thanks to this we were able to comprehend why some product concepts ended up the way they did. Finally, the feedback helped us to understand how certain concepts are being perceived within the marketing community and which product concepts we should improve. The high correlation rate with results from consumers“ made us consider using prediction markets for „quickchecks“ as an alternative to external market research.

Last but not least, such a tool can be used beyond Marketing for surveying different topics. This gives employees the feeling that they have a greater impact on the decision making process.

Where would you say the challenges lie?

When you converse with market research experts, the question about the generalization and replication of results coming from prediction markets in comparison to other market research methods arises quickly. Even with the high correspondence of the results of employees and consumers, there is surely some scientific education and persuasion work to be done. Finally, prediction markets are ‘just’ a tool. They supports the decision making process within a company through providing new insights. However, in the end the decision is still with management.

MVS-Zeppelin trusts the knowledge and experience of its employees and by using the CrowdWorx prediction market, information that is coming from more than 100 rental stores from all over Germany can now be aggregated.

After one month, 16 000 bets on various predictions have been made and the first results are already promissing:

• In the region of North Rhein-Westphalia the rental revenue of construction equipment was predicted with an accuracy of 95.78% (100% being the perfect prediction).
• For all of Germany the prediction accuracy for the KPI rental revenue of construction equipment is 91.94% .

However, for management there is more than prediction accuracy to Prediction Markets. Thanks to Prediction Markets, each and every employee gets the chance to be part of important decisions, which creates a stronger bond amongst the staff and towards the company.

In this particular version of CrowdWorx the new Enterprise Survey Module is being used for the first time, too. It allows, in addition to predictions, for employees also to take part in traditional surveys. See it in action here.

Read the full article here (German only).

Beispiele für einen messbaren Nutzen von Enterprise2.0-Tools finden sich in unseren Fallstudien – insbesondere die Cases bei Henkel und Tchibo zeigen, wie bei Prognosebörsen der Nutzen glasklar messbar gemacht werden kann.

Aber nicht alle E2.0-Tools sind so klar messbar und hier kommt ein Blogbeitrag von Alexander Stocker ins Spiel, der darlegt, wie man den Nutzen von E2.0 systematisch quantifizieren und messen kann. Es wird erläutert, wie man auch den Nutzen “softer” Tools, wie Wikis und Blogs, messbar machen kann. Spannend ist das allemal!