Billy Beane and Bill James are two of baseball's biggest revolutionaries. And they also happen to have a very unique perspective on innovation and the future of analytics.

A Sept. 17 event at the New York Stock Exchange brought the two together to discuss the subject. Beane is the general manager of the Oakland A's and a board member at software company NetSuite, which hosted the talk. James is a special consultant to the Boston Red Sox.

Before the event, Beane and James sat for an interview with the Wall Street Journal's Brian Costa. They discussed open-source innovation and what the next frontier might be for analytics. Though Beane and James are baseball executives through and through, their insights offer plenty of takeaways for leaders in other industries. Here are three of them: 

1. Performance improvement is blind to the lineage of good ideas.

Chris Bogan, founder of Chapel Hills-based Best Practices and the coauthor of Benchmarking for Best Practices, has argued that smart companies borrow great ideas from outside sources. "Performance improvement is blind to the lineage of good ideas," he writes.

In other words: In business, the only thing that matters with an idea is whether it improves your performance. Where the idea originally came from is academic. It doesn't matter if you yourself invented it. 

In their first exchange, James and Beane confirm their understanding of this concept. James is regarded as the father of the sabermetrics, or baseball stat analysis, movement; whereas Beane is regarded as the leader who made sabermetrics mainstream. If James is Xerox PARC, Beane is Apple. Beane is quick to point out that he invented nothing; whereas James is quick to thank Beane for popularizing his ideas. 

"I appreciate all the things you've done for my career, even though you didn't do them in my interests," says James at the start of the interview. Beane replies: "As I always said, we invented nothing. We just stole everything."

2. Proprietary innovations have their place, but you'll get better results from open-source innovations. 

There was a time--before Beane and the "Moneyball" era of the early 2000s--when baseball executives did not rely on sabermetrics. At that time, the kings of sabermetrics were baseball writers, hobbyists, and moonlighting statisticians. James was one of them. 

The upside of this was that sabermetrics began as an "open-source" movement, in which creators and problem-solvers shared approaches and solutions. There were no proprietary analytics because it was all for fun. Baseball teams had not yet hired these statistical minds to develop team-specific analytical models.

All of that changed once teams began following the A's lead and implementing "Moneyball" techniques for themselves. Which is why Costa asks James and Beane about the potential downsides of sabermetrics migrating from the public sphere to private offices.  

"I suspect that the best work will always be done in the public arena," says James. "What's done in the public arena has a million eyes on it. Somebody sees what you've done wrong and they figure another way to do it, and somebody else figures another way to do it." 

Beane agrees. "As soon as you come up with something, you write it and you post it, you've got a million people in there correcting it or telling you where you're wrong or taking it in another direction," he adds. "Anytime you have an open-source situation, you're probably going to have something better than three or four guys in a private situation."

Aware of the perks of open-source research, Beane is quick to point out the advantage of bringing analytics teams in-house: You can hire the brightest big data minds to focus on projects far beyond the common knowledge of the open source-community. "The people that we're hiring and other baseball teams are hiring, we're competing with the Apples and the Googles of the world," he says. 

3. The next frontier for analytics in baseball is healthcare. 

Now that sabermetrics have been part of the baseball mainstream for more than a decade, it's clear that most teams have a handle on how to use them to evaluate player talent and performance. Costa asks what area of the sport--now that using analytics in player evaluation is a norm--could still benefit the most from a rigorous big data approach. 

Beane without hesitation says it's injuries and medical information. "Even the healthcare industry is doing the same thing--trying to use big data to help solve healthcare," he says. "It's the same in a simpler form for baseball or any sport and injuries. That's the black swan for anyone involved in a baseball team--our injuries. Trying to predict them, minimize them, limit the downtime."

The challenge, Beane adds, is that there are restrictions on how much data you can collect on anyone's medical history--especially before they become an employee of your team. "But ultimately," he says, "I think we will make progress at some point, and the foundation of that will be analytics."