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Very interesting read, Yaping! Your point about Nestle using Open Innovation to lower its R&D spend is interesting. How should the company think about an appropriate balance of continuing to invest in Open Innovation vs. its own internal R&D, and what are the tradeoffs of investing in each? I suspect that Open Innovation has more potential in terms of long-term disruption, but the variability is also likely significantly higher. A minimum level of internal R&D is likely necessary to supplement Open Innovation and to diversify the innovation and development process. Lastly, as other comments have mentioned, I would recommend Nestle lean toward a proactive approach to Open Innovation, particularly in light of its key competitors now starting to focus more on Open Innovation as well.

Interesting article, with some parallels to the Aspiring Minds strategic decision of whether to go B2B or B2C. Given the importance of network effects in this type of business, how does The Bounties attract an initial network of users/consumers and tasks (i.e., how does the company incentivize potential users to get “boarded”)? Additionally, how does The Bounties develop a monetization strategy?

On November 13, 2018, warriorcat123 commented on Machine learning ruined baseball. Machine learning will save baseball. :

Interesting post – which highlights the necessity of tying machine learning to a company’s business model. Baseball is unique in that the MLB has 30 clubs all focused on their own P&L – which is often most easily influenced by winning. Machine learning / sabermetrics may help any individual team increase its odds of winning, and thus improve its P&L, but at the expense of the overall enjoyment of games and the league as a whole. As you addressed at the end of your post, how can the MLB (and individual teams) leverage machine learning to better appeal to the casual and serious baseball fan? And how can machine learning and advanced statistics be used to increase the watch-ability and market-ability of baseball? Both the NBA and the NFL have grown massively in popularity over the last decade, a portion of which can be attributed to the leagues’ marketing of its stars. Can the MLB do something similar to increase its popularity?

I really enjoyed this post, as I agree that the beauty industry will see meaningful disruption in years to come. In terms of business model efficacy, one concern I have is around the amount of data and length of time that it will take to create a truly personalized recommendation that a consumer is happy with. For an individual customer, can Proven collect enough months of data and personalize the product well enough to ensure customer satisfaction before she/he churns? What happens if I’m dissatisfied with the product after one month and I stop using the product/service, and I don’t give the algorithm enough time and data to adjust to my individual needs and preferences?

On November 13, 2018, warriorcat123 commented on Nike’s 3D Printing: Just Do It :

Interesting post – particularly in light of today’s case on Nike!

Has Nike provided any information on the cost of 3D-printed products and whether the technology will be higher-margin over the long term? A huge benefit of 3D printing in the aerospace and medical device industries is the cost savings that result by reducing the amount of wasted material – which can be substantial when small parts and components are welded and cast from large pieces of metal using subtractive processes. Intuitively, I wouldn’t expect the same benefit to exist for Nike. Additionally, how does the quality compare to that of traditional processes? Is the quality high enough for 3D-printed products to be used by world-class athletes, in addition to the casual consumer?

Wow – really fascinating article, with a number of thought-provoking implications for the future! In particular, as mentioned in your post, my immediate reaction was around the impact this home-building process will have on the local construction industries, which often are very important employers in countries with less technological innovation. Are the majority of these homes providing shelter for individuals and families that otherwise would be homeless, in which case the impact on those employed by the construction industry would be limited? Or will this result in a reduction in home prices across the country and a displacement of those currently employed by the construction industry? Additionally, depending on the answers to the prior questions, what are the political implications of this innovation, and has there been any political push back thus far? Regardless, a very well-done and thought-provoking post!