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On November 15, 2018, CrackingLogistics commented on Nike’s Stance on 3D Printing: Just Do It :

Melcom Ruffin… I’ve always hated you for your skill at adeptly referencing learnings from past cases in other classes. Most of all I hate how interesting this development in Nike’s production line is and how it could both create significant cost savings for them as a company while maintaining the brand’s reputation through the steps you suggested. This fits particularly well with their history of innovation and, as much as I hate to admit it, I agree that pairing it with high profile endorsements would go a long way to making this well selling product. If anything it actually seems common sensical for them to do this. Damn you and your insightful insights Melcom Ruffin… Damn you.

On November 15, 2018, CrackingLogistics commented on Betabrand: Too Much Open Innovation? :

While I agree with many of the concerns you lay out I still think this could be an interesting case for engaging customers that aren’t necessarily professional designers- at least not yet. At the very least this could be an interesting way for them to build a portfolio while still making money as they develop or seek work at larger fashion houses. I also see that while the clothes themselves might not necessarily follow fashion trends as closely as other brands might, this strikes me as something that would be sold more on the crowdsourcing notion than the actual style. I suppose that could be both a bad and a good thing though. Either way interesting way to attract talent and potentially develop it if someone becomes a regular bestseller

On November 15, 2018, CrackingLogistics commented on Smarter Eating, Smarter Fitness: AI supports your goals :

This app poses a lot of interesting questions for the future, some concerning some exciting. You get to the crux of the main issue which is the use of such data for reasons other than your public health. If this were purchased by a health insurance firm for instance it could lead to higher premiums for people with health issues. Then again, it could also be an opt in program, like already exists for others as a way to try and reduce your premiums by living a healthy lifestyle. It’s also intriguing to think of the applications for large scale consumer goods from companies such as amazon

On November 15, 2018, CrackingLogistics commented on When Chanel trades sewing machines for 3D printers :

This is a really interesting innovation in what often feels like a very traditional market. Given some of the restrictions around “Haute Couture” it definitely feels like this is most applicable in the fast fashion or “H&M” space, but it would still be interesting to see the level to which this could be used in higher fashion should restrictions be lifted.

On November 15, 2018, CrackingLogistics commented on Straight to the Source: Open Innovation at Buzzfeed :

I’m interested at whether crowdsourcing in the way discussed here actually benefits buzzfeed as it seeks to transition from memes and quizes. It strikes me that, as you mention, it doesn’t quite solve the problem of making it a more credible site. I understand how this would help push more traffic to the site however and help increase reader involvement

On November 15, 2018, CrackingLogistics commented on Machine Learning vs Poachers :

PAWS is a really interesting example of applying machine learning in an environment not normally thought primed for it, yet very much so in need of it. Particularly given the large swathes of land that Wildlife Services and anti-poaching officials cover, using this technology and process could make their jobs both easier and safer. What other types of data do you think would make this more scalable and applicable? Do they need more geomapping, or, on the darker side, more instances of poaching in order to predictively map their patterns? On a regional level how could this be scaled to allocate resources across countries?