By Jeff Howe
3. The Tinkerer
The future of corporate R&D can be found above Kelly’s Auto Body on Shanty Bay Road in Barrie, Ontario. This is where Ed Melcarek, 57, keeps his “weekend crash pad,” a one-bedroom apartment littered with amplifiers, a guitar, electrical transducers, two desktop computers, a trumpet, half of a pontoon boat, and enough electric gizmos to stock a RadioShack. On most Saturdays, Melcarek comes in, pours himself a St. Remy, lights a Player cigarette, and attacks problems that have stumped some of the best corporate scientists at Fortune 100 companies.
Not everyone in the crowd wants to make silly videos. Some have the kind of scientific talent and expertise that corporate America is now finding a way to tap. In the process, forward-thinking companies are changing the face of R&D. Exit the white lab coats; enter Melcarek – one of over 90,000 “solvers” who make up the network of scientists on InnoCentive, the research world’s version of iStockphoto.
Pharmaceutical maker Eli Lilly funded InnoCentive’s launch in 2001 as a way to connect with brainpower outside the company – people who could help develop drugs and speed them to market. From the outset, InnoCentive threw open the doors to other firms eager to access the network’s trove of ad hoc experts. Companies like Boeing, DuPont, and Procter & Gamble now post their most ornery scientific problems on InnoCentive’s Web site; anyone on InnoCentive’s network can take a shot at cracking them.
The companies – or seekers, in InnoCentive parlance – pay solvers anywhere from $10,000 to $100,000 per solution. (They also pay InnoCentive a fee to participate.) Jill Panetta, InnoCentive’s chief scientific officer, says more than 30 percent of the problems posted on the site have been cracked, “which is 30 percent more than would have been solved using a traditional, in-house approach.”
The solvers are not who you might expect. Many are hobbyists working from their proverbial garage, like the University of Dallas undergrad who came up with a chemical to use inart restoration, or the Cary, North Carolina, patent lawyer who devised a novel way to mix large batches of chemical compounds.
This shouldn’t be surprising, notes Karim Lakhani, a lecturer in technology and innovation at MIT, who has studied InnoCentive. “The strength of a network like InnoCentive’s is exactly the diversity of intellectual background,” he says. Lakhani and his three coauthors surveyed 166 problems posted to InnoCentive from 26 different firms. “We actually found the odds of a solver’s success increased in fields in which they had no formal expertise,” Lakhani says. He has put his finger on a central tenet of network theory, what pioneering sociologist Mark Granovetter describes as “the strength of weak ties.” The most efficient networks are those that link to the broadest range of information, knowledge, and experience.
Which helps explain how Melcarek solved a problem that stumped the in-house researchers at Colgate-Palmolive. The giant packaged goods company needed a way to inject fluoride powder into a toothpaste tube without it dispersing into the surrounding air. Melcarek knew he had a solution by the time he’d finished reading the challenge: Impart an electric charge to the powder while grounding the tube. The positively charged fluoride particles would be attracted to the tube without any significant dispersion.
“It was really a very simple solution,” says Melcarek. Why hadn’t Colgate thought of it? “They’re probably test tube guys without any training in physics.” Melcarek earned $25,000 for his efforts. Paying Colgate-Palmolive’s R&D staff to produce the same solution could have cost several times that amount – if they even solved it at all. Melcarek says he was elated to win. “These are rocket-science challenges,” he says. “It really reinforced my confidence in what I can do.”
Melcarek, who favors thick sweaters and a floppy fishing hat, has charted an unconventional course through the sciences. He spent four years earning his master’s degree at the world-class particle accelerator in Vancouver, British Columbia, but decided against pursuing a PhD. “I had an offer from the private sector,” he says, then pauses. “I really needed the money.” A succession of “unsatisfying” engineering jobs followed, none of which fully exploited Melcarek’s scientific training or his need to tinker. “I’m not at my best in a 9-to-5 environment,” he says. Working sporadically, he has designed products like heating vents and industrial spray-painting robots. Not every quick and curious intellect can land a plum research post at a university or privately funded lab. Some must make HVAC systems.
For Melcarek, InnoCentive has been a ticket out of this scientific backwater. For the past three years, he has logged onto the network’s Web site a few times a week to look at new problems, called challenges. They are categorized as either chemistry or biology problems. Melcarek has formal training in neither discipline, but he quickly realized this didn’t hinder him when it came to chemistry. “I saw that a lot of the chemistry challenges could be solved using electromechanical processes I was familiar with from particle physics,” he says. “If I don’t know what to do after 30 minutes of brainstorming, I give up.” Besides the fluoride injection challenge, Melcarek also successfully came up with a method for purifying silicone-based solvents. That challenge paid $10,000. Other Melcarek solutions have been close runners-up, and he currently has two more up for consideration. “Not bad for a few weeks’ work,” he says with a chuckle.
It’s also not a bad deal for the companies that can turn to the crowd to help curb the rising cost of corporate research. “Everyone I talk to is facing a similar issue in regards to R&D,” says Larry Huston, Procter & Gamble’s vice president of innovation and knowledge. “Every year research budgets increase at a faster rate than sales. The current R&D model is broken.”
Huston has presided over a remarkable about-face at P&G, a company whose corporate culture was once so insular it became known as “the Kremlin on the Ohio.” By 2000, the company’s research costs were climbing, while sales remained flat. The stock price fell by more than half, and Huston led an effort to reinvent the way the company came up with new products. Rather than cut P&G’s sizable in-house R&D department (which currently employs 9,000 people), he decided to change the way they worked.
Seeing that the company’s most successful products were a result of collaboration between different divisions, Huston figured that even more cross-pollination would be a good thing. Meanwhile, P&G had set a goal of increasing the number of innovations acquired from outside its walls from 15 percent to 50 percent. Six years later, critical components of more than 35 percent of the company’s initiatives were generated outside P&G. As a result, Huston says, R&D productivity is up 60 percent, and the stock has returned to five-year highs. “It has changed how we define the organ-ization,” he says. “We have 9,000 people on our R&D staff and up to 1.5 million researchers working through our external networks. The line between the two is hard to draw.”
P&G is one of InnoCentive’s earliest and best customers, but the company works with other crowdsourcing networks as well. YourEncore, for example, allows companies to find and hire retired scientists for one-off assignments. NineSigma is an online marketplace for innovations, matching seeker companies with solvers in a marketplace similar to InnoCentive. “People mistake this for outsourcing, which it most definitely is not,” Huston says. “Outsourcing is when I hire someone to perform a service and they do it and that’s the end of the relationship. That’s not much different from the way employment has worked throughout the ages. We’re talking about bringing people in from outside and involving them in this broadly creative, collaborative process. That’s a whole new paradigm.”
4. The MassesIn the late 1760s, a Hungarian nobleman named Wolfgang von Kempelen built the first machine capable of beating a human at chess. Called the Turk, von Kempelen’s automaton consisted of a small wooden cabinet, a chessboard, and the torso of a turbaned mannequin. The Turk toured Europe to great acclaim, even besting such luminaries as Benjamin Franklin and Napoleon. It was, of course, a hoax. The cabinet hid a flesh-and-blood chess master. The Turk was a fancy-looking piece of technology that was really powered by human intelligence. Which explains why Amazon.com has named its new crowdsourcing engine after von Kempelen’s contraption. Amazon Mechanical Turk is a Web-based marketplace that helps companies find people to perform tasks computers are generally lousy at – identifying items in a photograph, skimming real estate documents to find identifying information, writing short product descriptions, transcribing podcasts. Amazon calls the tasks HITs (human intelligence tasks); they’re designed to require very little time, and consequently they offer very little compensation – most from a few cents to a few dollars.
InnoCentive and iStockphoto are labor markets for specialized talents, but just about anyone possessing basic literacy can find something to do on Mechanical Turk. It’s crowdsourcing for the masses. So far, the program has a mixed track record: After an initial burst of activity, the amount of work available from requesters – companies offering work on the site – has dropped significantly. “It’s gotten a little gimpy,” says Alan Hatcher, founder of Turker Nation, a community forum. “No one’s come up with the killer app yet.” And not all of the Turkers are human: Some would-be workers use software as a shortcut to complete the tasks, but the quality suffers. “I think half of the people signed up are trying to pull a scam,” says one requester who asked not to be identified. “There really needs to be a way to kick people off the island.”
Peter Cohen, the program’s director, acknowledges that Mechanical Turk, launched in beta in November, is a work in progress. (Amazon refuses to give a date for its official launch.) “This is a very new idea, and it’s going to take some time for people to wrap their heads around it,” Cohen says. “We’re at the tippy-top of the iceberg.”
A few companies, however, are already taking full advantage of the Turkers. Sunny Gupta runs a software company called iConclude just outside Seattle. The firm creates programs that streamline tech support tasks for large companies, like Alaska Airlines. The basic unit of iConclude’s product is the repair flow, a set of steps a tech support worker should take to resolve a problem.
Most problems that iConclude’s software addresses aren’t complicated or time-consuming, Gupta explains. But only people with experience in Java and Microsoft systems have the knowledge required to write these repair flows. Finding and hiring them is a big and expensive challenge. “We had been outsourcing the writing of our repair flows to a firm in Boise, Idaho,” he says from a small office overlooking a Tully’s Coffee. “We were paying $2,000 for each one.”
As soon as Gupta heard about Mechanical Turk, he suspected he could use it to find people with the sort of tech support background he needed. After a couple of test runs, iConclude was able to identify about 80 qualified Turkers, all of whom were eager to work on iConclude’s HITs. “Two of them had quit their jobs to raise their kids,” Gupta says. “They might have been making six figures in their previous lives, but now they were happy just to put their skills to some use.”
Gupta turns his laptop around to show me a flowchart on his screen. “This is what we were paying $2,000 for. But this one,” he says, “was authored by one of our Turkers.” I ask how much he paid. His answer: “Five dollars.”
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