Prediction Markets Blog » Andrew McAfee

Enterprise 2.0: The Wisdom of the Crowd

Rebecca Munn — Tue, 22 Jun 2010 19:27:18 +0000

This year’s Enterprise 2.0 conference was full of new product announcements and represented continued evolution in the value of Enterprise 2.0 solutions to businesses. The most striking realization for us was the increasing focus on Enterprise 2.0 solutions from players of all sizes, including companies as large as Cisco and CSC.

For instance, Cisco used the conference to announce an Enterprise 2.0 solution called Quad and shared that the net benefits of Cisco’s own internal use of Web 2.0 collaboration solutions were more than $1B in FY09. Cisco Quad leverages existing technologies such as Unified Communications and Telepresence and expands with business focused flip video and social software. To us, this seems like it is collaboration from the application down through the architecture.

Other items of interest:

Andrew McAfee discussed some concepts from his book, Enterprise 2.0, and revealed that Gartner predicts that as of 2010 social software is an enterprise reality. This, of course, is backed up by McKinsey survey results on Enterprise 2.0.
nGenera announced a human-centered enterprise collaboration solution, called Spaces, designed in collaboration with IDEO. Spaces includes a user configurable interface and plug-in architecture, allowing data access via interactive mini applications. This strikes us as collaboration from the middleware/web services layer out.

We’re already wondering what features Enteprise 3.0 will have. If you’d like to set up a market to test your ideas on that front, let us know.

The Enterprise Strikes Back: Prediction Markets as Collaborative Tools for Success

Rebecca Munn — Fri, 05 Feb 2010 17:36:34 +0000

We’ve been reading Harvard Business Review blogger and MIT Center for Digital Business researcher Andrew McAfee’s excellent book, Enterprise 2.0, which is full of valuable lessons for the enterprise, including that prediction markets are a very useful collaborative tool.

For instance, here’s an interesting discovery from the Google Prediction Markets, originally proposed internally in December 2004:

Analyses … revealed that at every point in time, even as much as ten weeks away from the closing date of the market, the most expensive outcome was the one most likely to actually occur. It seemed that GPM’s markets, in other words, could quickly and accurately distinguish among possible outcomes, identify the one most likely to occur, and attach a high price to that outcome.

This is exactly what our Foresight platform does on a regular basis for our customers.

Regular readers might remember a few months back when we cross-posted one of his posts from the Harvard Business Review blog. You might also recall when we posted a presentation that Linda Rebrovick (our CEO) gave in Chicago at the Prediction Markets Cluster conference in Chicago last November.

Linda noted the following best practice examples in her presentation:

integrate into enterprise processes
nurture executive sponsorship
go big or go home
make accessible to all
customize to your business
make it part of your value proposition

We were struck how similar these examples were to the Six Organizational Strategies identified by McAfee:

Determine Desired Results
Prepare for the Long Haul
Communicate, Educate, and Evangelize
Move into the Flow
Measure Progress, not ROI
Show That Enterprise 2.0 Is Valued

Coming back to the commentary on GPM, McAfee continues:

Google’s prediction markets shared with all markets a fundamental property: the ability to generate highly valuable information by bringing people together who have little or nothing in common.

Okay, we don’t actually know how different Linda and Andrew are, but we’re pleased that our executive leadership understood key lessons before an interested commentator went to press with his book. It’s almost… predictive.

McAfee’s “Teaching Moment” demonstrates prediction market accuracy and versatility

Rebecca Munn — Thu, 10 Dec 2009 19:34:04 +0000

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

A couple weeks back I taught sessions on Enterprise 2.0 to executives from a very large corporation. I emphasized that one of the benefits of E2.0 is the ability to harness collective intelligence, or the wisdom of crowds . To make this phenomenon concrete I showed a couple examples of prediction markets.

They may seem like strange beasts but prediction markets are simply stock markets; they contain securities that are bought and sold by traders. As with the NYSE, traders build up portfolios of securities and try to maximize the value of their portfolios by buying and selling at the right time. The value of any particular security in the market varies according to the laws of supply and demand, and also as new information becomes available. And the price of a security reveals information. On the NYSE, for example, the price of a stock reflects the consensus estimate across all traders of the value of the company.

In a political prediction market like the Iowa Electronic Markets, securities are designed so that their price reveals other information about the future: the percentage of the popular vote that Obama and McCain were going to win in the 2008 US presidential election, the simple probability that each candidate was going to win the presidency, or the number of electoral votes that each was going to get. Other prediction markets have been set up on the Internet to predict the outcome of sporting events or the box office revenues of a movie that has yet to open.

As I wrote here , plenty of evidence exists to suggest that these markets work: in many cases they yield more accurate predictions than other forecasting methods. And as I wrote here, companies have started to use this technology and they’ve generated some impressive results.

On the second-to-last day of their program, the executives in this particular class decided to test the idea of collective intelligence. I got the following email shortly afterward:

I am one of the members of the… team that you lectured to last week about Enterprise 2.0. One message that really stuck with the team was your discussion of predictive markets. We found a creative, although somewhat rudimentary, way to use this concept in practice. Let me set the stage.

It is about 10PM on Thursday night, and there are 10 of us out enjoying a few cocktails. One of our colleagues was enjoying a few more cocktails than the rest of us. That is when we decided to create a predictive market on when he would arrive to class on Friday morning. We split the morning up into 15 minute increments, and allowed people to buy stock in each time slot for $1. All-in-all, 27 shares were purchased, with 8:15-8:30 being the most highly purchased time slot as you can see from the attached pitch [a slide showing $6 in shares purchased for the 8:15 - 8:30 slot. The next most popular were 7:45 - 8:00 and 8:00 - 8:15, each with $5. No other slot had more than $3].

As luck would have it, we were in our learning circles from 8-8:30 and we were going over what we had learned during the previous day. The person who organized the market was explaining to the class how we applied our learnings from you, and as if they were on cue, the individual arrived in the class just as the market had predicted. Once the cheers of the six people who had invested in the right time quieted down, all you heard in the classroom was one person say….”I am never making a decision on my own again.” It was priceless.

My correspondent graciously gave me permission to share the anecdote, which illustrates a few things. First, it’s another example of crowd wisdom in action. Even though they only set up a simple poll (albeit one that included both financial risk and gain) rather than a full-fledged market, the consensus answer was the correct one. Second, it shines a light on the power of incentives; both money and bragging rights accrued to the winners. Third, it shows how easy it is to set up convincing demonstrations of collective intelligence. Prediction markets and similar technologies are getting easier and easier to deploy, so why not give them a try?