In our new executive profile series, we take a closer look at our leaders' roles in shaping the future of Yahoo!, and share a few insights to help you get to know them better. Today we're getting to know Duncan Watts, who heads up Yahoo!'s Human Social Dynamics Group and has just published his third book - Everything is Obvious (When You Know the Answer). Duncan will discuss the book in a special 'Have a Seat' event today. We caught up with him to find out why we shouldn't trust our common sense when it comes to business.

You direct the Human Social Dynamics Group. Can you explain your role and what the group is working on?

We work on a range of questions to with the structure of online social networks and other associated processes, such as how information spreads , or how people influence each other.  We even conduct lab-style experiments in which networks of people play games or solve problems in order to understand how network structure impacts collective performance.

How does that work tie in with Yahoo!’s strategic business priorities?

At a high level, a better understanding of social networks and behavior can have all sorts of implications for future products, both consumer and advertising facing.  For example, one project we're working on now is designed to extract small, context-specific groups from a user's outgoing email.  These groups can then be stored and used for other purposes, like sharing content or photos, a la 1:Few. In another example, we're trying to estimate the value of social targeting strategies that exploit the fact that friends are more likely than strangers to buy the same products, sign up for the same services, or click on the same ads, even controlling for attributes like gender, age, and socioeconomic status.  Clearly this kind of information would be of interest to our advertising partners, who might be prepared to pay extra to reach friends of existing consumers.  And in a third example, we've used counts of search terms to predict various real-world outcomes, such as box office movie revenues and song rankings; results that suggest that search and audience data might be directly monetizeable.

How helpful is Yahoo!’s scale when you are a research scientist? Does access to so much data give you different opportunities than you would have in, say, your previous academic roles?

Both the scale of the data and also the scale of the computing resources are extremely helpful. I certainly did plenty of interesting work before I came to Yahoo! over three years ago, but for both those reasons, it would have been very difficult for me to do some of the projects that I've worked on here.

From a scientist’s perspective, what makes Yahoo! an interesting and challenging place to work?

As trite as it sounds, the most interesting thing about Yahoo! is the people.  The scientists in Y! Labs are among the best I've ever worked with, and they're also refreshingly interested in scientific problems and puzzles, rather than which academic silo a particular problem falls into.  One thing we'd like to do better is partnering with business units. On the one hand, a great potential upside of working at Y! is that we run these hugely popular properties that generate massive amounts of data and are naturally occurring laboratories in which we could experiment.  On the other hand, it can be difficult to align our scientific agendas with product roadmaps and other kinds of resource constraints. So that's a challenge for us.

Critics and reviewers are saying that your third and most recent book, “Everything is Obvious (Once You Know the Answer)” invites people to challenge conventional wisdom as a way to really understand politics, business, and marketing. Is that a fair summary of what you were aiming at with the book?

Actually, I wouldn't say I'm challenging conventional wisdom. I would say that I challenge common sense, which I think is much deeper seated. Conventional wisdom is just what we happen to believe about something at any point in time, and it changes constantly. Common sense is something we always trust. People are always telling us that conventional wisdom is wrong, but when was the last time someone told you not to use your common sense? Yet common sense too can be misleading.

You’ve said that common sense often misleads us, stopping us from truly understanding cause and effect in strategic planning. Can you give us an example?

Sure. In the late 1990's Cisco Systems was the most valuable company in the world, and the darling of the business press.  Everyone praised them for their awesome strategy, strong leadership, and laser-focused execution.  Two years later, Cisco had lost 80% of their market valuation and its reputation was in a shambles, with the same business press accusing them of being strategically shortsighted, of having arrogant, out of touch leadership, and lousy execution.  But what nobody emphasized was that all this time, Cisco was pursuing the same strategy, with the same leadership, and executing the same way.  So which of these accounts was right? Probably neither.  The problem is that common sense is so good at coming up with cause and effect stories, that given any set of facts we can always explain them.  What we can't explain is how our explanations are equally adept at accounting for radically different outcomes.  Yet instead of facing this inadequacy in our explanations and trying to understand reality more deeply, we simply discard whatever story we previously had as wrong and embrace whatever seems right now -- ignoring that that's also what we were doing the last time.  The result is that most of the time when we "explain" outcomes in the business world -- or in politics, economics, marketing and so on -- we're really just telling stories that paper over what we don't understand. They seem to describe why something happened, but really all they're telling us is what happened.

What advice would you give to Yahoos about overconfidence in our ability to predict human behavior, and learning how to manage our systems more effectively?

Measure everything, design experiments where possible, and keep track of your predictions.  Most of all, don't assume your intuition is reliable.  Sometimes you may have no choice but to trust it, but you should still check back later to see how accurate it was.  Actually I think Y! is probably more scientific and data driven than most companies.  But there is always room for improvement, and for challenging ourselves to prove that what we think we know is right, and not merely something we happen to believe.

In your research on Twitter, Facebook, and other social platforms, what do you think would surprise most people to learn?

So far the result that most people seem to find interesting is that although the most followed users are also likely to be the most influential on average, they are not necessarily the most efficient wielders of influence. Instead, it may be what we call "ordinary influencers": relatively anonymous users who have unremarkable numbers of followers, but who can still generate a positive impact.  It may be a small impact, but if you can harness lots of them you can still diffuse information more efficiently than by using the Kim Kardashians of the world.  I should say, however, that this result is somewhat speculative, as are most results about influence on Twitter.  To really answer questions like these, we need to run large scale field experiments, and hopefully we'll get to do that soon.

Mobile and connected devices are very much the future in terms of products planning for Yahoo! Do you see any differences in the way people respond to mobile user experiences as opposed to more traditional PC- or laptop-based ones? How do we have to think differently about those experiences?

I'm not an expert in mobile communication, but the most interesting aspect about mobile devices to me is the geo part.  Obviously I'm not the first person to make that observation, but I do think there is huge untapped potential in products and services that exploit the precise location of user.  Just to take one example, I live in SoHo in New York, which is sort of like living in an outdoor luxury shopping mall.  Every day the streets are teeming with people desperate to throw their money at retailers; and the retailers are desperate for their business.  Every day I walk down the street and think "lf we knew that one of these people wanted a particular product that is in a particular store that is two blocks away, we could broker that transaction, and everyone would be happy: the consumer, the store, and us".  There are at least hundred of millions of opportunities like that every year, and billions of dollars of revenue at stake, that's just one simple-minded application.

What’s the next project you’ll be working on?

I'm currently working on several projects, but I'll mention two: one is about tracking the diffusion of influence online, and trying to identify generic properties of diffusion networks; and the second is a new tool that we hope to launch soon that uses social referrals to help Yahoo!'s find answers to very specific technical questions by helping them find the person within the company who knows the answer.

It’s always fun to learn more about our experts - what do you like to do in your free time when you’re not delving into the mysteries of human behavior?

Well, I live in New York, so there are endless after-hours distractions in the form of theater, restaurants, music and so on. But my two favorite activities are probably devouring a fine steak and skiing steep bumps, where the latter followed by the former is arguably the best day of all.