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Rob Stark
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Cool article, and very inspiring to see that machine learning applied in this context hews towards improving diversity of target companies, whereas in other machine learning contexts (Amazon’s recruiting software) the opposite is true at the individual level. The biggest question for me is why CircleUp is seeking to disrupt VC, and not PE? It seems that if the underlying thesis is that algorithms trained on quality data-sets could be more effective at identifying investment opportunities than humans, then it would be easier to prove out in a landscape where data is more prevalent. My thought would be that established companies (classic PE targets) would have a significantly larger amount of data that Helio could crunch on vs. early stage companies (classic VC targets).
Awesome article! Besides the idea of the data being potentially biased, I have another concern. Does opening up civil data to public use present any sort of privacy concern? In the era of data scandals such as Cambridge Analytica and Equifax, data privacy has become a hot topic. Would citizens object to having any of this data spread widely? Perhaps none of the data you are referring to here contains personal information…but for this idea to really gain traction and become beneficial to the government, I would think that this concern would need to be discussed!
Very interesting article! I am concerned that this open innovation model won’t take-off in the auto industry because it interferes with the market feedback mechanisms of price and profit. By effectively outsourcing design, there is no doubt that Local Motors is able to drastically reduce their design costs for a vehicle. But, this comes at the expense of potentially failing to meet a need that is being signaled by the market. If the collective wisdom of the participating community produces a vehicle that the market doesn’t want or need, then Local Motors has a low cost product that will go for a very low price indeed. I’d be interested to see what kind of controls they put in place to ensure that they are producing vehicles that fit a need in the market!
Awesome article! I agree that decentralized manufacturing vis-a-vis additive manufacturing (3D printing) would worsen BMW’s cost profile unless significant efficiency improvements were made to the technology. However, I am also skeptical about the usefulness of 3D printing in the repair “aftermarket” in the long-term. In my opinion, if self-driving cars come to fruition, then there will be very few accidents, meaning the market for replacement parts will dry up significantly. For these cars of the future, the components that receive the most wear and tear won’t be those that a #D printer could replace (such as tires and elements of the electronics chasis).
I agree with your analysis that additive manufacturing techniques can improve Nike’s cost profile. However, I also see a more significant opportunity for Nike outside of additive manufacturing. Looking at the shoe cost bar, 50% of the price is consumed by an intermediary, the retailer, in order be a POS for the shoe product. Why can’t Nike sell direct to consumers and reduce price? It seems that this would allow for significant market share capture from their close competitors. I don’t think the brand image would be dented by shifting to DTC. A quick google search actually indicates that Nike is making a DTC push, so maybe it won’t be long before we no longer have to pay a 50% markup to a middleman?