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Great article. It is not surprising to see that IDEO has embraced open innovation given its culture of creativity, which is so open to new ideas. It makes me wonder whether companies that lack the IDEO culture will be able to implement open innovation as successfully. I just read @Joffrey Baratheon’s article on open innovation in the NFL and I am frankly skeptical that an organization like the NFL, which is perhaps at the far opposite end of the spectrum from IDEO when it comes to openness to new ideas, will be able to embrace crowdsourcing in the way that IDEO has.

On November 15, 2018, Trevor commented on Open Innovation in the NFL: Player Safety :

Player safety is such a huge problem in football, especially with the increasing number of former players being diagnosed with CTE, so I truly hope that the NFL adopts an open innovation approach to addressing the issue. I see the issue similarly to how the professional sports leagues addressed (or didn’t) the issue of steroids. Provided they want to address the issue, the professional sports leagues stand to gain from seeking input from distributed sources — not simply trying to find the best solution from within their own organizations. Given how long and hard the NFL has tried to deny the mounting evidence of traumatic brain injuries among its players, I am skeptical that the league will truly pursue an open innovation approach to player safety, but I hope it will.

On November 15, 2018, Trevor commented on The Rise of 3D Manufacturing in Footwear: What it Means for Nike :

Great article and discussion. I wanted to highlighted another benefit of Nike’s additive manufacturing process that hasn’t been mentioned thus far, which is sustainability. Nike’s Flyknit shoes are made with Flyleather, which is made from 50% recycled leather fiber. According to Nike: “Flyleather is both sustainable and high-performing, with the potential to be as game-changing as Nike Flyknit. During the typical leather manufacturing process, up to 15% of leather hide falls to the tannery floor and often ends up in a landfill. We gather the discarded leather scraps from the tannery floor and turn them into fibers that are combined and fused into one material.” (

As we learned in Marketing class, Nike may be wary of advertising sustainability given it wants consumers to buy their products because they are the highest quality (and not to think that some sacrifice was made on quality in order to make them sustainable), but sustainability is another great benefit of Nike’s Flyknit additive manufacturing process.

On November 15, 2018, Trevor commented on Turning Big Data into Clean Electrons at NextEra :

Great article. As someone who spent the pasts 5+ years in the renewable energy industry, I can attest that we are not always the most technologically advanced sector, so it is awesome to see that industry leaders like NextEra are finding ways to push the industry forward with machine learning. That said, as you point out, I think the biggest challenge facing renewable energy is its inherent intermittency and I am skeptical about machine learning’s ability to address that issue. Fundamentally, solving the intermittency challenge will require dramatic cost reductions in the upfront cost of energy storage and/or the construction of new transmission lines and I don’t see machine learning playing a role in either. (I would love to discuss if someone sees that differently!) But I do think machine learning can play an important role in optimizing a battery’s lifetime value by learning how to select the right charging/discharging opportunities each day. This is an extremely complicated optimization given that, among other things, electricity prices fluctuate in real time and are often unpredictable (and choosing to charge/discharge at one time of day means you forego the opportunity to charge/discharge at later time), so you can only truly know the best time to charge/discharge a battery in hindsight.

On November 15, 2018, Trevor commented on Does Additive Manufacturing Pose a Threat to Gun Control? :

The development of 3-D printed guns is indeed extremely alarming and I share Ratnika’s concerns about the US government’s ability to address the issue. The political climate makes it almost impossible to pass any sort of gun control, but even the late Supreme Court Justice Antonin Scalia noted that “Like most rights, the right secured by the Second Amendment is not unlimited.” ( It often seems that even the most limited and sensible gun control measures fail to gain traction in the US, but I’m intrigued by Trey’s suggestion that the NRA and gun makers could make for an unlikely ally in the fight given their business interests.

Another parallel approach would be to ensure ammunition remain extremely tightly controlled, limiting the ability of 3-D gun owners to buy bullets. Chris Rock has a great take on the issue of “bullet control” that is worth watching (

Thanks for the thought-provoking post. As a lifelong baseball player and fan, two of the things I love about the game is the human element and tradition, so I worry about baseball introducing elements like robo umpires or data informing which teams play each other. That said, I see the slowing pace of the game as a threat to its popularity and I am intrigued by the idea of using machine learning to improve the game. For instance, could baseball use data and machine learning to solve for the optimal fan experience — i.e. determine what balance of length of game, runs per game, pitching changes per game, etc. on average leads to the highest fan enjoyment. This could help MLB determine what initiatives to prioritize as it seeks to make the sport as popular as it can be, without surrendering the human element or tradition.

Your suggestion to allow data to inform scheduling is an interesting one, and I like the idea, but I definitely worry about this being taken to the extreme. If we seek to always pit the most popular teams against each other, the Yankees and Red Sox could play a majority of their games against each other and neither would ever play the Padres.

Lastly, as a baseball player and fan, I have to say that @Scuba Steve’s suggestion to move the mound further from the plate is a ludicrous one. Baseball will never and should never change the fundamental dimensions of the infield. That’s one element of the game machine learning should never be allowed to alter.