Archive for April, 2006
The following is a copy of a posting by Jim Novo (jimnovo.com) in the Web Analytics Group at Yahoo. His post highlights how Ford is combining the wisdom of crowds via web analytics to actually schedule production, order parts, etc…
"For me anyway…
Ford Motor Company has run a pilot where they are using the info from a
"Build Your Car" configurator on the web to predict demand for certain cars
and features. When they matched the "predicted" data from the config to
"actual" sales data, the fit was simply amazing. So amazing you would
immediately question if the data was "tortured" somehow.
But that's the nature of near frictionless environments like the web. You
tend to get behavioral data that is simply more "true" then asking people
their opinions, which is the more common way to get affirmation for auto
design from the customer.
What is probably more important, from an analytical culture perspective, is
that this gigantic metal-bender with very long lead times is actually using
this web data to modify production plans because it has been such a
reliable predictor of demand.
This concept was so far outside the expected norm that in the Q & A, I made
a fool of myself by asking Stacey Coopes (from Ford) if I had heard her
correctly. The conversation went roughly like this:
Jim: Are you saying that Ford is actually using web demand data to drive
"Yes", she said.
Jim: "You mean, to actually schedule production, order parts, configure
"Yes", she said
Bottom Line – I simply do not want to hear anyone ever again whining about
problems with getting management to pay attention to web data. If Stacey
can make this kind of thing happen at Ford, you can do it where you are.
This is a monumental achievement.
It should be an interesting 2006 for Travel Search Engines based on the recent press the sector has received.
Here are some highlights from a recent Bob Tedeschi's article in NY Times on travel meta-search:
… Kayak's chief executive, Steven Hafner, said his company would embark next month on a multimillion-dollar television advertising campaign — the first for a travel meta-search site.
Other analysts say they believe that Google and MSN may simply follow Yahoo's lead (purchased FareChase) and buy the niche search players. "I've always thought pretty much all of them are ripe for acquisition," said Ms. Dougherty, of Nielsen/NetRatings. "If someone wants to play catch-up fast, that's the way to go."
Paul R. La Monica from CNN Money filled a report on how Google might spend their $10 billion dollar war chest, a couple of highlights:
…Bill Tancer, general manager of global research with Hitwise, an Internet research firm, thinks Google needs to make more deals in social networking. He said Google's biggest threat will not come from search engines like Yahoo!, Microsoft's, MSN or IAC/Interactive's Ask.com but from MySpace, the social networking site owned by News Corp.
…He added that online travel search is another area Google should target, with sites such as privately held SideStep, Kayak and Mobissimo being possible buyout candidates.
“…Large groups of people are smarter than an elite few, no matter how brilliant—better at solving problems; fostering innovations, coming to wise decisions, even predicting the future” -The Wisdom of Crowds by James Surowiecki.
Applying the Wisdom of Crowds to Email
- When sending an email to a large group of people asking for feedback on a specific problem try the following:
Ask for original solutions from everyone, but do not include everyone on the TO: or CC: line, but rather set all email recipients to the BCC: line.
- After receiving all responses, aggregate the solutions
- Once the solutions have been aggregated, again send them out to the original group, using the BCC: line instead of the TO: or CC: line asking for feedback.
- Based on the next round of responses you will be able to get unbiased feedback and then aggregate again and present to the group.
- Applying the wisdom of crowds, you should find that the most popular answers is the best possible solution.
Wisdom of Crowds Email Scenario (Setup)
I’ve found it is common for a manger to send out emails with a problem, and ask for solutions from a large group of people. What typically seems to happen is the first handful of responses sent to the group have original responses. By original, I mean they do not references anyone else point of view, but rather their own opinion. After the first handful of responses, the answers become less original, and reference early responses more and more (assuming everyone chose to REPLY ALL). Based on my interpretation of Surowiecki’s book this is the wrong way to take advantage of the wisdom of crowds (email recipients).
The reason why this is the wrong way to take advantage of WofC in terms of soliciting feedback via email is because of what is described as the cascading effect:
“Effectively speaking, a few influential people—either because they happen to go first, or because they have particular skills and fill particular holes in people’s networks—determine the course of the cascade. In a cascade people’s decisions are not made independently, but are profoundly influenced—in some cases, even determined—by those around them… The fundamental problem with cascades is that people’s choices are made sequentially, instead of all at once.”
Wisdom of Crowds Email Scenario (The Problem)
Let’s go back to the example of a manager sending out an email to the entire team to get ideas on how to solve a problem. The first response is from the Director of Marketing (DM) who suggestions some ideas, the second response is from the CFO of the company who suggests a couple of other ideas, and even references some points from the DM. The remaining three people who haven’t responded to the email are lower level employees, but are more suited to provide options to solve this problem.
By reading the responses from the DM and CFO, the remaining three employees have been tainted. They will use the responses from the DM and CFO to come-up with their own responses. While this isn’t necessarily bad, there will be instances where an employee might not want to “rock the boat” so they work within the options provided by upper management. Another possible scenario is that the DM and CFO came-up with some great ideas, so the three employees decide to run with them, instead of coming up with their own solutions which may have resulted a more favorable outcome. This is an example of the cascading effect. The cascading effect has an impact on the ability for the manager to take advantage of the combined wisdom of the team.