Thanks for reading and for the insight. I agree with you and that is why they have a review feature where you can cross out the TV shows and movies that you watched that you definitely didn’t enjoy. They can improve this by asking you periodically which types of movies you are interested in watching or which genres are most appealing to you.
Thanks for reading and for the great insight. Independence in media is one of the main problems that we must fight for today to maintain our democracy. I would say that some balanced political commentary in my series is OK but when they introduce these sophisticated ML algorithms they can actually start very subtly influencing our ways of thinking. I think this is more a corporate governance matter of making sure Netflix is not significantly controlled by an interested party (just like they do for newspapers and other publicly-traded media outlets) and that creative departments have strong ethical sense.
Thanks for reading. I agree with your concern of killing the suspense of an ending by having you pick it but I think Netflix’s strategy is more towards giving you the ability to get in the mindset of the characters, transport yourself to that world, make decisions and see what the consequences would be (without the actual recourse).
Thanks for reading! I agree with your concern in that these ML algorithms will only take our necessity of getting leisure increasingly to an extreme. Hopefully they are able to invest in creating/acquiring relevant educational content for kids which could lead to a better societal impact than just merely entertainment.
Completely agree with you! Price points of Netflix and Hulu are not that different yet the experience in Netflix is significantly better (that might explain to some extent the difference in churn). Hulu has more relevant TV content from other networks that Netflix is strategically shifting away from but it seems like it is not enough to retain customers at a meaningful level.
Thanks for reading. I completely agree with you in that a toggle for social vs. individual could be very helpful to make more accurate suggestions given that they are able to create a control for several people ghosting other accounts (multiple users in one account can create a lot of noise in the data leading to Type 1 errors that can erode customer experience).
Tom Riddle thanks for reading and completely agree with you on the social media platforms piece (many of the shows that I watch were recommended by someone that I deem has good taste on TV shows/movies). There are many applications to these algorithms and sets of data that are worth exploring.
As I was reading your post as I was hoping you would recommend that Spotify becomes a record label and cuts the traditional record labels from their value chain (I am happy you did at the end). I think Spotify has all the tools they need to make it happen: they have access to musicians, they have big data on customer behavior and they have developed machine learning algorithms to facilitate the process. I like the possibility of Spotify partnering with musicians and leverage on its subscriber data to give the artist more insights as to how to improve their music, how to make their tours more successful and how to make their content creation efforts faster and cheaper. Companies like Google are already experimenting with complimenting artists’ creative process using machine learning algorithm to fight off “writer’s block” and speed up the rate at which they produce music.
On the music recommendation bit, I agree with Greatest of All TOM in that Spotify hasn’t really capitalized on its content suggestion capabilities that are powered by machine learning. I suspect it is because Spotify wants to provide subscribers with space for them to make decisions on which music to listen and not feel the company is pushing for an agenda. In my personal experience, I almost never explore the “Discover Weekly” category because I know my taste and I doubt that Spotify will be able to deliver me the components that I am looking for in my music.
I would encourage you to read my posting on Netflix which talks about machine learning and how they are using it to improve their content acquisition and suggestion processes as well as how they are allowing subscribers to pick the ending for one of its shows to outsource innovation and learn from their behavior while they are most actively using the product.
 Dar, Pranav. 2018. “Google Is Making Music With Machine Learning – And Has Released The Code On Github”. Analytics Vidhya. https://www.analyticsvidhya.com/blog/2018/03/google-making-music-help-machine-learning/.
Very interesting read and very socially impactful application of machine learning algorithms. I agree that for this precision agriculture technology to make any meaningful impact in the world it needs to reach developing nations at affordable prices for farmers. Having said that, I will have to disagree with the author in that Microsoft shouldn’t focus their resources on applying these machine learning capabilities into other areas to make an impact in the world’s food problem. The main issues with food around are not only the resources it takes to produce it (which the author very aptly addresses in his publication) but how to make it physically accesible to more people . If food distribution around the world doesn’t improve and yields increase then either people who had access to food before are going to consume more of it or supply will outpace demand leading to spoilage and investments in precision technology will render useless. In short, I see the value in increasing yields with less resources for geographies with great access to food but for this precision technology to make a great impact it need to be paired with improved infrastructure and better supply chain management in developing nations. Therefore, my open question is: can Microsoft apply this machine learning capabilities to help companies predict future supply and demand in areas of the world that have inadequate access to food?
 Rijpkema, Marieke. 2018. “How To Solve The Food Problem In The World? – EBF Groningen”. EBF Groningen. https://www.ebfgroningen.nl/journal/how-to-solve-the-food-problem-in-the-world/.
Even though the airline industry is getting closer to developing 3-D printing of metal pieces for plane manufacturing, I still think the regulatory environment will be a main detractor of this trend from becoming widespread in the world. The FAA says the industry is getting closer to manufacturing and approving the use of 3-D printed parts for critical components in the plane  but I remain skeptic on how long it will the rest of the world to understand this technology, the specifications of the parts and its maintenance, repair and overhaul. I also believe that (much like self-driving cars) this technology will be held to a more strict quality standard than what is currently in place proving very risky for plane manufacturers and their relationships with clients.
 McBride, Stephen. 2018. “If You’ve Missed The Iphone Revolution, This Device Is Your Second Chance”. Forbes. https://www.forbes.com/sites/stephenmcbride1/2018/10/31/if-youve-missed-the-iphone-revolution-this-device-is-your-second-chance/#4f692346584f.
 Werner, Debra. 2018. “FAA Prepares Guidance For Wave Of 3D-Printed Aerospace Parts – Spacenews.Com”. Spacenews.Com. https://spacenews.com/faa-prepares-guidance-for-wave-of-3d-printed-aerospace-parts/.
Very interesting take on additive manufacturing. My only concern is its actual expected net social contribution which I believe will be negative in the long-run. With 3D-printing mass production, it is not clear to me whether more people will have access to affordable shoes or if the same people will just be able to buy more shoes? For Nike, either answer translates into the same financial figures but the company is depleting natural resources and materials while creating externalities for other industries/geographies.
In many emerging markets, athletic shoes are imported goods which are often subject to tariffs and significant nationalization costs which render them materially more expensive than local alternatives. Unless Nike is able to deliver on a material cost reductions and to pass it on to consumers, I don’t believe the cost savings from 3D printing mass production will permeate to people that can’t currently afford Nike running shoes and create a positive social impact. Moreover, should this mass production technology become mainstream in the future, many employees would be redundant and layoffs would be massive across the shoe manufacturing industry. Overall I believe 3D printing mass production by itself will not deliver positive societal benefits unless it is combined with other initiatives such as sustainability (materials) and renewable energy (manufacturing plants).
Even though it is hard to conceptualize how 301 is a source of open innovation at first, I agree with the author that this model is providing General Mills with a competitive advantage over competitors by accelerating their innovation process and by giving the company a new avenue to experiment.
I think 301 is a very innovative, yet expensive (average ticket of USD6mm per investment as per graph in original post), way of approaching their innovation process. They are basically fast-tracking their innovation process by acquiring companies that have already gone through it and have a product that has been tested and is currently in the market. This fast-tracking comes at a step price vs. regular contest-based open innovation and it also comes with some complications to their portfolio companies which are trying to grow using General Mills’s best practices and expertise but as subsidiaries are subjected to slower processes and internal bureaucracies. What I think is really powerful from this model is that General Mills can try out new approaches on these start-ups with no effect on their master brands and implement later on if results are favorable. In other words, General Mills is buying these companies, helping them grow, and seeing how some innovative practices from these companies can be applied to their main brands after they are market tested.
Very interesting post. I agree with the limitations of driving innovation in the public sector which is faced with more challenges everyday with an increasingly tighter budget. I also recognize the limitations of incentivizing long-term initiatives when administrations change every four years leaving little room (if at all) to approve the idea, execute it and realize its value. I would try to delegate the decision-making and partner-selection process of each open innovation initiative to the country’s legislative branch or local government business subcommittees which tend to have a more long-term focus, more business sense and generally input from a more diverse set of parties.
So, how to incentivize long-term thinking on these ideas amid short political cycles? My suggestion would be to defer implementation of projects (where applicable) to the private sector while providing them with an economic incentive to succeed. Open innovation in the private sector is generally known for driving financial performance while in the public sector for driving citizen engagement. If the Argentine government is able to strike a balance between the benefits of citizen engagement with the value of getting a company’s best practices and technical knowledge towards the same goal, I believe the government can institute a system for long-term value creation for Argentine citizens.
 Baba, Jonathan. 2018. “Deloitte”. The Value Of Crowdsourcing: A Public Sector Guide To Harnessing The Crowd. https://www2.deloitte.com/content/dam/Deloitte/us/Documents/public-sector/us-fed-a-public-sector-guide-to-harnessing-the-crowd.pdf.