Jeff Boyar's Profile

Great post and I share your concerns about the balance between additive manufacturing and maintaining a feeling of luxury. While I think mass production of luxury eyeglasses using 3D printing may not be here yet, there could be an element of luxury within customizability, which could fit within the brand’s image. For example, 3D printing could be used to customize eyeglasses, which could be marketed as more unique and exclusive, which fits within its luxury image.

Love this article – especially since I loved playing with LEGOs as a kid! I slightly disagree with your concerns about open innovation in other markets. I actually think open innovation may be the key to success in growth markets – allowing LEGO to tap into the cultural differences and needs of each group. This goes for digitization as well. I believe digitization is probably not a one-size-fits-all solution either and requires open innovation to determine how to best deploy it to growth markets as well.

Great article! To me, the competitive advantage of 3D printing in the short term is less about mass production and more about rapid prototyping, and therefore faster innovation timelines, which is something Nike has been known for. However, a big question I have is what will happen if consumer preferences shift? For example, there is a large trend now towards athleisure, something that Adidas has capitalized on quite well, while Nike has not. I wonder if 3D printing provides any type of advantage in this scenario. In my opinion, it does, but requires Nike to shift overall strategy first, rather than just hoping 3D printing will be the competitive advantage rather than a means to deliver against a strategy.

Great article and something I’ve always been very interested. As other comments mention – these types of machine learning initiatives have a huge impact on city governments, especially from a budgetary perspective. In that sense – I think they can really help make city governments more efficient.

To your questions though – I am very concerned about how these get implements. First, data in produces that data that comes out and I worry that the data going into these models is biased in some fashion. Second, there has been a huge push recently for community policing where officers are more connected to their communities. I worry that machine learning and “policing through data” removes the human element of crime prevention and can give police departments an excuse to further remove themselves from the communities they serve.

Great post – I love learning about space! In general, I think the spirit of innovation relies on an openness to new perspectives and ways of approaching and solving problems. With this in mind, standard and open innovation models should and could work in the same organization. That sounds more difficult to manage from an organizational perspective, but tackling big problems through many approaches seems to be in line with the overarching spirit of NASA. I would encourage the organization to avoid formalization of innovation and let ideas come about however different teams feel they can reach them.

This is really interesting and reminds me of the Big Data case we read about Gap or even how Netflix leverages machine learning to develop new movies and television shows. I think it makes sense for these more “artistic” fields to leverage machine learning to better predict consumer tastes and develop products accordingly. However, I wonder what the consumer reaction will be in the future as more brands begin to leverage machine learning for product development. Will there be a reversion back to authenticity vs. perfection? Perhaps in the future, consumers may appreciate products that may not get it “right” but produced their product in a way that was not reliant on big data.

In the meantime though, a very cool and interesting topic!