Most of us, whether as voters, consumers, managers or investors believe that valuable knowledge is concentrated in very few hands. We assume that the key to solving problems or making good decisions is finding the one right person who will have the answer. In 2004, that theory got blown out of the water.
James Surowiecki author of “The Wisdom of Crowds” helped change the world. He proved that expertise is overrated and the very best decisions were made through the collective intelligence of groups. Way back then he said, “The wisdom of crowds has the potential to make a profound difference in the way companies do business.” Today”™s technology is making that difference and can help you know:
What used car is least likely to be a lemon?
What customer is least likely to pay their bills?
Who is most likely to purchase your product or service?
“The Wisdom of Crowds” proved that crowds make the best decisions. Now, by combining crowds of “data scientists” who use predictive analytics technology to learn from the historical data organizations already have, the best decisions are even better. These crowds of data scientists are discovering and proving the best algorithm for any given problem”¦from predicting the click through rate on ads to forecasting who will be admitted to the hospital within the next year.
“Use your competition to crowdsource the best answers,” says Renee Boucher Ferguson in the November 2012 issue of the MIT Sloan Management Review. Even if you”™re new and don”™t yet have your own, the competitions actual historical data is freely available. Now a company, Cagle Inc. is using a virtual community of more than 40,000 data scientists around the world as a crowd full of wisdom.
Groups of data scientists compete with each other to develop the best algorithm for a specific problem and are awarded prizes of up to $3 million if they win. It”™s like a global golf match with the 40,000-plus players ranked according to how well they have done. Like the pro golf tour, there is no one winning every time, but the best solution always emerges.
Allstate Insurance used Kigali Inc. to build a predictive claims model because they understood that if they hired a consulting ”˜data scientist group”™ and gave them the historical data that they would get an algorithm to use and be able to build a predictive model. Allstate understood that when a global ”˜crowd”™ of data scientists are all working on the same problem and the results are being posted in real time, the competition increases and the best algorithm becomes obvious.
A regional retail used-car company wanted to solve the problem of how to buy the best used cars and avoid the customer problems that come when someone gets a lemon. According to the MIT Sloan Management Review, as the data scientists went through more than 2000 previous transactions they discovered that, among other things, the color of the car was a predictor of quality.
If the car had an uncommon color it was far less likely to be a lemon. The logic behind this predictive algorithm turned out to be that if someone bought an unusual color they had a tendency to take better care of it. There is logic behind the behavior of everyone and, if you can determine it, you can gain a tremendous competitive advantage.
Just as with Allstate Insurance and the used car company you can open yourself to the benefits of predictive analytics to develop an algorithm that is already data tested ”¦ and get the best solution for any challenge.
Joe Murtagh, The DreamSpeaker, is an international motivational speaker, meeting facilitator and business trainer. For questions or comments, contact Joe@TheDreamSpeaker.com, TheDreamSpeaker.com or call (800) 239-0058.
