“The central principle behind the success of the giants born in the Web 1.0 era who have survived to lead the Web 2.0 era appears to be this, that they have embraced the power of the web to harness collective intelligence.”

O’Reilly, 2005

Predictive markets, often also referred to as information markets, aggregate the knowledge of the crowd to make predictions regarding unknown future events. By aggregating distributed knowledge the predictions of the crowd are often more accurate than when companies rely on only a handful of experts.

How do they work?

In prediction markets, individuals buy and sell “futures” or “shares” based on their beliefs regarding the probability of the event taking place. If they are correct, they are rewarded for their efforts. Because of U.S. laws related to online gambling, rewards often take the form of play money, gift certificates, or recognition within the market.

What is interesting about prediction markets is their structure creates incentives for individuals to act on their closely held information. Because rewards are tied to correct predictions, individuals in the crowd who have access to more information, which may aid in their understanding of the market, tend to buy more shares than those who are just guessing.

For example, Google uses over 300 internal prediction markets to assess events such as customer demand for new products (“How many Gmail users will there be on January 1, 2009?”), company and product performance (“When will the first Android phone hit the market?”), and competitor performance (“How many iPhones will Apple sell in the first year?”). In addition to new sources of predictions, Google has used these prediction markets to better understand and improve the flow of information within their company.

Do predictive markets work?

As with many new uses of the crowd, we have only scant evidence regarding the effectiveness of prediction markets. Best Buy reports internal prediction markets designed to predict holiday sales of gift cards were 99.5% accurate compared to a 95% accuracy rate from external consultants. Intel also reports success with their internal “forecasting markets.”

Faced with the difficult task of predicting demand of products requiring lead times of months or even quarters, Intel found their internal markets were at least as accurate as official figures and in some cases more accurate by 20% (i.e., 20% less error).

There is, however, evidence that outside factors can impact results of these markets. Some data suggests employees may be overly optimistic regarding company performance tending to artificially inflate positive results. For publically traded companies, stock performance can influence predictions upward or downward in line with the latest market swings. And finally, there are also numerous issues related to providing the right incentives for participation as well as obtaining executive buy-in for such initiatives.

One area where the crowd is being leveraged is to supplement or even replace call centers. Because companies often struggle with issues related to ensuring operators have the right level of expertise to efficiently and effectively answer incoming questions, some researchers are suggesting that turning to active user communities as a source of expertise may be a more efficient and cost effective way of providing continuous and expert-level support. Active community members often represent the most knowledgeable customers and are likely already providing advice as part of their online activities. Even if only a small percent of calls can be re-directed to these über-users, it could result in substantial cost reductions and potentially more satisfied customers.

Companies such as HP, Microsoft, and AT&T are currently leveraging their user communities to supplements call center staff. In fact, Intuit reports a reduction in total support calls for TurboTax during tax season by 40%. Other companies such as giffgaff, a UK mobile phone operator, leverage their user community forums to handle 100% of their customer support issues, most within 5 minutes. In addition to leveraging their own communities, companies are working with intermediaries who connect them with other knowledge communities. For example, FixYa.com is an online service that “leases” access to knowledgeable crowds to help companies supplement their current customer support services. And Arise leverages 120,000 highly trained, home based independent contractors to provide high quality support resulting in a 25-30% cost savings relative to traditional brick-and-mortar call centers.

Of course, there are many potential issues with leveraging the crowd for customer service. How do you motivate über-users to act as on-call experts? How can you ensure that someone in the community can answer the question in a timely fashion, after all they don’t work for you? And what are the risks of having non-employees act in a capacity that suggests a company sanctioned response? Certainly these are difficult questions.

So the next time you call a customer service line, you might strike up a conversation and see who’s actually answering the phone.

We’ve only begun to examine the economic impacts of crowdsourcing initiatives on the corporate bottom line. Some studies are finding that turning to the crowd has reduced cost and time for product innovation and problem solving, improved quality, and increased market acceptance of new products. In fact, TopCoder a site that runs contests for developing complex software applciations reports that projects typically requiring over a year of development have been completed in slightly over five months. Additionally, TopCoder programs average .98 bugs per thousand lines of code, significantly better than the industry standard of six per thousand. These initial findings are promising, but more research is needed to determine the true benefits to corporations.

While potentially more economical than traditional innovation methods, crowdsourcing does not come without costs. It is not a “build it and they will come” solution. Success requires defined business goals, an understanding of crowd dynamics as well as collaborative technologies. Additionally, those who are getting the crowd to participate are often finding it difficult to sort through and evaluate all the information and ideas that are generated.

One of the biggest hurdles is organizational culture. I saw a similar issue when working with companies to leverage social media for marketing initiatives. Success at leveraging the crowd requires an organizational culture that embraces open methods from the top down and is willing to give up some control. Exposing yourself and your company to the crowd can be scary and isn’t without risk. Lawyers raise concerns about leakage of trade secrets and issues related to intellectual property. Employees may feel they are becoming obsolete and fear for their jobs. And, executives may pull the plug when they encounter negative feedback or comments from customers.

Every day there are new and different uses of the crowd for innovation. While companies like P&G and intermediaries like InnoCentive seem to have it down, most are only beginning to experiment with leveraging the crowd for innovation. I do agree that crowdsourcing may be an excellent opportunity for companies to supplement or even replace their current innovation initiatives – saving money and time in the process. But currently we have only scant evidence of the how best companies can extra value from the crowd.

(Cartoon (c) Geek and Poke, 2009)

They recently competed in a competition held by DARPA to create a combat support vehicle for delivery and evacuation missions. Leveraging a chassis created in a different Local Motors crowdsourced vehicle, DARPA invited the general public to design the size, shape, and features of the car. Local Motors hosted the contest providing requirements, engineering guidelines, deliverables, “ignition kits” with necessary design tools, and a discussion forum on their website. Local Motors experts work with the crowd to ensure specifications are met and all cars meet safety requirements. Prize money of $1500 for 1st place, $1500 for 2nd, and $1000 for 3rd were given to the best design. The car was designed in 4 months, and built in 14 weeks. Significantly faster and at less expense than typical military vehicles. It is combat ready and meets all specs. Even President Obama got in the mix.

A similar contest was held by Local Motors to crowdsource a desert race vehicle called the Rally Fighter. What’s interesting about the Rally Fighter is it consists of mostly off the shelf parts. GM engine, Honda Civic taillights, Miata door handle, etc. By leveraging existing parts Local Motors avoids costs associated with manufacturing. The car is built in a limited run (2000) at Local Motors microfactories. Purchasers go to the microfactory for 2 3-day weekends to build the car from the chassis up. Makers can also create a custom car wrap with whatever design they choose. After the 2nd weekend the new owner drives the car off the lot or ships it home.

What’s up next? Local Motors announced at the conference they will be crowdsourcing an electric vehicle. I believe this will be a wake-up call for auto manufacturers. Stay tuned.

Here are the top 10 ways you know it’s spring in State College.

1. Red chairs pop up outside at Cafe 210.

2. Gaggles of college kids in matching t-shirts wondering around town (the annual bar tour).

3. The fragrant scent of cheap beer everywhere.

4. Blue Natty Light cans scattered across the lawn.

5. Red solo cups impaled on unsuspecting bushes.

6. Skin everywhere (guys in shorts, girls in sundresses) even when it’s 50 degrees and raining.

7. The slap-slap sound of flip-flops.

8. A sudden increase in desperate emails from students trying to figure out how to make up for missed assignments.

9. Mattresses, broken bookcases, and the odd papasan chair without a cushion left on the curb.

10. And finally, an eerie quite hush blankets the valley as the students leave for the summer.

Coming from business and writing for the web, academic writing was the antithesis of what I was used to (yes I just dangled my participle). But over time, I’ve come to feel comfortable with academic writing and have even somewhat adjusted my writing style. Who’d of thought? It’s a cultural thing. It’s not that one style is better than the other, they’re just different.

I have come across authors who are great at weaving an argument, moving the reader from one point to the other, and supporting their arguments with well-written prose. I have also come across those who like to throw in ridiculous words such as “finalizability” or “multiperspectival.”  I typically roll my eyes and say, “seriously who are you trying to impress?” But I’ve gotten used to academic writing (made up words and all) and I find that within academic literature there is a wide variety of styles just like within business writing.

I will likely always have a conversational tone to my writing, but some academic reviewers have said that it’s “refreshing.” When I first started reading academic literature I wasn’t sure that there was room for different styles. But as I’ve become more familiar with academic literature I am beginning to find my style. This will no doubt keep evolving, but I’m glad now that even with the thick descriptions and multi-syllabic words there is also room for individuality.

P.S. Speaking of academic language, if you’re a PhD student and aren’t aware of PHD comics (Piled Higher and Deeper) you need to check it out. Case in point…deciphering academese…

I agree that this is a cool idea. Actually back 1989 when this concept first emerged it was cool too. I guess my surprise at the story was how this concept was being portrayed as novel. These eBooks are really “something entirely different” the story continues.

Sure the touch component and portability that comes with iPads is new. That certainly makes these books more accessible, but the concept of interactive books for children that are designed to help them learn to read and interact with characters and objects on the page isn’t. Back in the day they were called “living books.”

One of my kid’s favorite was “Just Grandma and Me” but there were many to choose from.  These living books (CD-ROMs) were totally engaging and even had little hidden fun thing the kids could look for. Of course she used a mouse and by today’s standards an ancient bulky desktop computer (complete with upgraded graphics card I might add). I have to admit that sometimes I just wanted to play with them myself.

I find it interesting that the iPad is being viewed as an entirely new medium. It is revolutionary in terms of mobility and the gestural interface, but we need to give credit to the really smart instructional designers, graphic artists, and programmers who came before and truly conceived of “something entirely different.” Not to mention the fact these people were working with many more constraints in terms of computing, graphic output, and programming tools.

I think I’ll call my daughter and ask her if she remembers these books. My guess is she will.

Author: Steven Johnson

Pub Date: 2010

Excellent look at ideation and the development of ideas over time. Both theoretical and practical.

Key to Johnson’s discussion is the concept of the “adjacent possible.” Simply put, like ideas tend to cluster together. When you bring different clusters together you benefit from ideas in adjacent groups. Ideas bleed into adjacent  groups, or spillover, and generate new ideas.

Johnson also debunks the notion of the “eureka moment.” Instead, Johnson shows that new innovative ideas are often born of long held hunches. Those hunches that ruminate in the back of your mind for weeks, months, and even years.

According to Johnson, “the secret to organizational inspiration is to build information networks that allow hunches to persist and disperse and recombine.” By creating high density liquid networks, organizations make is easier for innovation to happen.

But don’t take my word for it, hear Johnson describe where good ideas come from in his own words.

There are tons of different types of crowdsourcing sites and researchers are only beginning to examine the different uses of the crowd.  I wrote a post about the crowdsourcing site eBird a while back. Here’s another example of a crowdsourced site. This one for crowdsourced software development.

TopCoder.com connects companies with programmers in the crowd to collectively build complex programs.

Here’s how it works:

• Clients specify requirements, timelines, and budgets and the crowd competes to see who can produce the best code in the allotted timeframe.
• Qualified reviewers evaluate weekly submissions, scores are posted for everyone to see, and a winner is selected.
• After all modules are complete, a new contest is held to assemble the modules into the final program.
• Winners are paid a pre-defined fee and coders in second place receive half the amount of the winner.
• Winners turn over code (and all rights to it) to the paying company.

You’d think that throwing out a programming challenge to an undefined group of people without set standards or guidelines would result in pretty “iffy” code. But, what’s interesting is that TopCoder code actually exceeds the industry standard for quality. TopCoder reports an average of .98 errors per 1000 lines of code, compared to the industry average of 6 per 1000.

TopCoder manages to create complex programs in less time, at less cost, and at a higher quality than typical of internal development teams. Is this the end of internal software development teams?