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Thanks for an interesting read on, as you say, a less-covered angle of additive manufacturing. I certainly agree that 3d printing of tools in addition to end-product parts will only grow in importance.

While it’s hard to agree outright with you that the company should continue to use additive manufacturing without seeing a cost comparison with tradition methods, you make the case effectively that this is a viable option. I think the company might be able to take a few lessons from Ford (I wrote about them here:, which has partnered with or invested in several startups specifically targeting high quality, durable 3D printing. One is Carbon3D, which uses pools of resins to form solid objects that actually are not layered like typical printed objects. The other is Desktop Metal, which specializes in metal 3D printing. A partnership with these or similar startups could allow Lumiena to overcome the durability issues they’ve been facing as they scale, and provide a happy medium between traditional and additive manufacturing methods.

I think you nicely show the importance of user input for Starbucks, as well as the amount of idea generation they have encouraged so far. Beyond your initiative ideas, I would also add bringing modern “comment cards” (e.g., iPads with a simple user interface) where customers can share ideas in-store. I think the in-store element is important because I would assume the majority of customer ideas, or at least ideas related to experience, happen in the store, and giving customers an easy way to share those ideas there should get more contribution than making them leave the store and remember to enter the idea at home (or even needing to pull up a website on their phone).

This was a good read in that it both spoke to an inherently interesting topic and injected some important business perspective (e.g., projected market size). I agree that Hershey could be doing more. You mention health awareness – one interesting avenue would be to use 3D printing to make the company’s products healthier. For instance, instead of solid chocolate, a printed bar could have air pockets that lead to a reduction in calories. While there’s been a lot of talk around using 3D printing for health foods (e.g.,, less unhealthy sweets strikes me as a more realistic starting point.

On November 13, 2018, TOM199 commented on ETSY – “Keeping Commerce Human” through Machine Learning :

I enjoyed the picture you painted of this company that is both “keeping commerce human” and forging ahead in its use of machine learning. I agree that Amazon Handmade will present a serious challenge to Etsy. The machine learning development steps that you mentioned Etsy is taking to fend off the competition make sense, though I wonder if they can seriously compete with Amazon in those capabilities (I would guess it’s a stretch). However, if they can continue to improve their algorithms and maintain brand strength (allowing consumers to channel their dismay at “sameness”), then I believe they will be well-positioned for the future.

As Etsy looks to combat mass produced goods on the site like you mentioned, I think there are some lessons the company could take from Alibaba. While Alibaba embraced mass production, its anti-fraud efforts were similar in that they needed to sift through a mass of companies and products, and ensure that any outside of the desired type were removed.

On November 13, 2018, TOM199 commented on The NFL and Machine Learning: A Touchdown for Technology? :

This is a great topic – I was excited to read as soon as I saw it. I appreciate your thorough and informative portrayal of what the NFL is doing with respect to data collection and machine learning.

I think an additional area to explore here is what the collection of such granular data will mean for sports betting, particularly given this is now legal in several states. The availability of data like speed at which the quarterback throws opens numerous in-game betting options – which can be seen as a great way to further engage fans, or a risk that players will be tempted to alter the game in ways that are extremely subtle.

I enjoyed and agreed with your thoughts on teams’ and coaches’ use of data as well. To add to those, I wonder if the increased data availability and sophistication of analysis will make teams more likely to take actions that are unusual now, but widely acknowledged from an analytics perspective as having value (e.g., going for it on fourth down, which coaches “should” be doing more). I’m curious to see how having access to other teams’ data affects interest levels in machine learning and analysis – all the sudden if one team is using the data effectively, everyone will need to also to catch up. Lastly, I’m fascinated by the thought of machine learning picking up on plays and coverage schemes real-time.

On November 13, 2018, TOM199 commented on Crowdsourcing snack food trends at PepsiCo :

Thanks for sharing this – this is a great demonstration of how open innovation can touch products central to everyday life, and how even established companies can use the principle successfully. I agree with your assessment that internal development is extremely important given the current state of the snack industry, and that crowdsourcing can be an effective way to facilitate that.

I’m intrigued by your idea that PepsiCo crowdsource recipes in addition to flavor ideas. While I certainly see the benefits, I wonder if the complexity of ingredient lists (as of 2015, Doritos had 34 processed ingredients according to The Washington Post – I recommend checking out their picture of all of them) makes this idea too challenging for a real “crowd.” I think an interesting intermediate option could be for consumers to submit both a flavor and the sub-flavor profiles that believe make it up. So for instance southern biscuits and gravy might come along with the submitter’s thoughts on the flour type they have in mind, the texture, the smell, etc. to give Pepsi’s team a head start.