Billy Tabrizi IV
This is a really interesting initiative being led by the NFL, but I wonder how much this is a PR-seeking initiative vs. a genuine attempt at driving innovation. I believe that open innovation can be a great way to drive disruptive thinking, but I wonder whether this application makes sense, given that a efficacious solution requires such scientific backing. By funding this challenge, is the NFL incentivizing the right people? And for the ideas that are generated, how will the NFL take those and translate them into products or equipment that can be used in play? Again, I think it’s important that the NFL pay attention to this important issue, but wonder whether this is the best approach and what the program results will be in years to come.
This is a really interesting way to spur creative thinking around around difficult social challenges, but as you’ve mentioned, I wonder how this can become a more sustainable and impactful practice. I feel like anytime there is a short-term challenge or push for innovation like, this is such great energy and wonderful ideas generated. But how do you translate that into an ongoing practice and make sure those ideas are carried through execution? Does that require a different skill set or group of people? How do you get the right types of people engaged in a practice like this, and create incentives for them to grapple with these big-picture challenges? Can this be translated into a permanent line of business, or can employees rotate through on special project assignments?
Really interesting take on what the role of additive manufacturing will be for athletic footwear. I think these brands still have some work to do in terms of understanding what the demand is from consumers from customized products, though. Having personalized shoes produced via 3D printing is certainty a novelty, but what will people be willing to pay for it? And to what extent can they truly be personalized to be the best possible shoe for the individual? It is interesting to think about what kind of shift this technology might drive, since the market is largely driven by trends. For example, people like to get the same popular shoe that they see everyone else wearing, or that they see a famous athlete wearing. If there is a move toward mass customization, how do brands like Nike own the shift from managing trends to managing personalization?
Thanks for this interesting take. I agree that “the future” would seem to be that Brooks can 3D print customized shoes in real-time for a customer within a retail store, such that they can walk out with the shoe that is right for them. I guess my question on that is – is there actually a one perfect design for each foot? Sure, certain runners might need more arch support or more cushion than the next, and maybe that can be identified via technology, but I also think that a lot of user preference goes into a purchase like this. When I buy shoes, I try on a few options, run with them on the treadmill, and decide what feels the best for me. The retail specialist might inform those options by looking at my feet, but they can’t necessarily pick one specific shoe for me. While additive manufacturing itself is quite sophisticated now, I wonder where Brooks is with the ability to interpret and categorize data about runners’ feet and needs in order to drive that custom manufacturing. Assuming there are able to get there, I wonder – at some point, do their manufacturing facilities that produce standardized shoe types via a traditional process become obsolete? Or will there always be demand for “off the shelf” shoes that can solve for the needs of the majority of runners?
This is so interesting; I had heard about applications that help users maximize their success with the rhythm method but did not know that new innovations were incorporating machine learning to drive higher accuracy. You make a really interesting point about the risk associated with this technology’s dependence on user-input data. This reminds me of the machine learning case we covered in class, in which we highlighted the criticality of feeding the right data into an algorithm to get the right outcomes or learnings in return. Given that the functionality of this product really depends so heavily on how the user feeds it data, how can the efficacy of the technology be evaluated? And given that the algorithms continue to learn and change over time, does that require constant re-evaluation on the part of some regulatory body? It is difficult to picture how efficacy can accurately be measured over time, which begs the question for me – is the company liable in any way for those individuals who experienced accidental pregnancies? In those cases, are we able to understand whether there was a user failure vs. a technology failure?