Wired Pursuits

Posts Tagged ‘innovation

Leveraging the crowd for its artistic talents.

In the category of it’s “incredible what hundreds of people around the world who don’t know each other can collectively create,” artist Aaron Koblin leverages the power of the crowd to create an amazing crowdsourced video one frame at a time.

The Johnny Cash Project allows anyone to recreate, alter, or embellish a frame from the late Johnny Cash’s last video. Using Flash-based tools, individuals across the world add their unique mark to create a stunning and visually arresting video. From simple line art to more complex multi-textured renderings to words and symbols that flash across the screen, the video is transformed into a truly amazing piece of work.

How it works.

  • On the site, visitors can create their own renditions of a frame, explore others’ work, and even search by highest rated or most recent.
  • Using drawing tools built into the interface, visitors can render frames using a number of different styles such as pointillism, realistic, and abstract.
  • Visitors can also “vote up” individual frames to move them to the top of the stack for inclusion in the video.
  • Clicking on an individual frame shows you information on the artist and allows you to watch how the frame was created in either real time, 2x, or 3x speed. That is, you watch a replay of what the individual artist drew.

Illustrating our humanity through massive amounts of data.

Aaron Koblin believes that modern technology makes us more human and has a number of projects where he transforms massive amounts of data into visualizations that tell us something about ourselves. For more on Arron, check out his 2011 Ted Talk.

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So much about innovation is changing. Globalization, increased need for speed to market, increased costs, mobile workforce, and maybe most importantly the proliferation of the Internet and online collaborative tools. I think O’Reilly’s quote sums it up nicely.

“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

Instead of turning to paid analysts, or internal experts some companies are using the crowd to help improve the accuracy of demand forecasts as well as better manage inventory and manufacturing capacity.

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.

Often the term crowdsourcing is associated with large groups of people contributing information or data (e.g., Wikipedia), with product innovation (e.g., Dell’s IdeaStorm), or with advertising (e.g., Doritos and Pepsi superbowl ad). But a number of companies are also leveraging the crowd to better serve customers and reduce those long wait times.

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.

As a researcher studying crowdsourcing I was excited to see that Haydn Shaughnessy of Forbes magazine predicts that crowdsourcing will be top of mind for companies in 2012.  While I agree that crowdsourcing examples are on the rise, I’m not sure I agree that crowdsourcing is a “fail safe” option that is a “mature” as Haydn suggests.

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)

Title: Where Good Ideas Come From: The Natural History of Innovation

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.


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