1,2, (or 3?) & me

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On November 15, 2018, 1,2, (or 3?) & me commented on Block by Block: Harnessing Open Innovation at The LEGO Group :

Great topic! I’m pretty inspired by the success that Lego has had to-date with open innovation. One additional potential future idea that they could consider to innovate further without over-simplifying would be to take the open innovation offline (esp. in developing countries).

On November 15, 2018, 1,2, (or 3?) & me commented on The Artificially Intelligent Brewer: Carlsberg’s Breakthrough Project :

Such an interesting topic. I agree with each of your points, but my bigger picture takeaway is a bit of a ‘wow’ reaction that Carlsberg leadership jumped straight to ‘optimal taste’ as their initial application of ML. More “traditional” applications of ML like production quality and customer feedback seem like low hanging fruit for Carlsberg to cut their teeth on and develop the data science competency needed to take on such a complex tasting algorithm.

On November 15, 2018, 1,2, (or 3?) & me commented on 3D Printing…we should ‘Just Do It’! :

Interesting article. Strongly agree with the sentiment that Nike needs to keep their focus on the performance of their shoes that get to market. For that reason, the quality of manufacturing that comes from the 3D process is the number one qualifier for me. That said, given the ability for 3D printing to manufacture many dynamic designs in a short period of time, I’m less concerned with a given 3D prototype design’s impact on performance while they’re building out the tech. From the perspective of Nike’s long term R&D team, if they can get high quality 3D shoe manufacturing ready for market, then I think their product design team can do the rest.

On November 15, 2018, 1,2, (or 3?) & me commented on Machine Learning in Credit Assessment at Capital One :

Nice work on this article. Your comment about using ML to open up credit/banking access for the un/der banked got me thinking a bit. In particular, that segment is probably the segment of the population with the fewest datapoints to draw on to make a credit decision (unlikely to own property, hard to verify rent, credit scores not reliable, etc.).

While that is a barrier to Capital One using ML effectively today due to the narrow dataset on each individual, we are likely to see a future where more aspects of our financial lives continue to move online (e.g. rent payment, car payment) and into one place (with broader adoption of services like Intuit’s Mint). If Capital One continues to push the envelope, they have an opportunity to be the first mover in the unbanked segment in the future.

On November 15, 2018, 1,2, (or 3?) & me commented on Kevin Stein at TransDigm Group :

Interesting conversation. I think an interesting piece that could also be considered is TDG’s relationship with GE as a supplier. While not totally familiar with TDG’s full product suite, my assumption is that many of the parts that they supply are on GE engines, rather than the broader airframe (fuselage, wings, etc.). If that is the case, could TDG actually partner with GE to accelerate AM in future engine designs by integrating into TDG parts in GE engines?

Alternatively, if more of TDG’s services business is actually driven by parts on the broader airframe, is AM at GE even a risk at all?

On November 15, 2018, 1,2, (or 3?) & me commented on Resurging Queen: Singapore Airlines and Its Open Innovation Scheme :

Really enjoyed this article. Great work!

One thing that struck me in your recommendations for SIA is the idea of breaking down the innovation topics into more granular problem areas. I’m sure the tension between sharing narrow and broad problems inside and outside of the company for an open innovation question is a difficult one – it sets up a hard trade off between feasibility of solution and uniqueness/revolutionary nature of the innovation.

On quick glance, I think I agree that they should be more granular for customer-facing problems that an airline traveler can think through in-depth. For internal problems shared through open innovation (which are likely less likely to find an innovative solution to begin with), perhaps the broader approach is more useful, especially if the likely result of open inno on those problems is nothing more than creating a radically different but less sophisticated potential solution to test the status quo.