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I think open innovation is a very relevant alternative for mature and declining industries. The toys industry is a good example of that. The important consideration that LEGO should have in mind is that other industry players are also betting on it. For instance Mattel created My Mattel Ideas, which is a portal for people to contribute with ideas of products (see link below). This doesn’t represent a threaten per se but it is important that LEGO executes the right strategy so this can become a competitive advantage (as you mentioned above).
I think this is a great application of additive manufacturing and it is great to see that big automotive companies like BMW are open to incorporate this technology to their processes. In my opinion, this has the potential to become a competitive advantage depending on the strategy that they follow going forward. On that note, I read a press release of the company (please see link below) in which they explain some of the recent and potential next steps on additive manufacturing. They are planning to open a campus in Germany to consolidate their technological expertise in the field and eventually they want to decentralize the use of printers by integrating them in different existing production facilities.
3D printing for houses could definitely contribute to start addressing the housing deficit in several geographies and especially in developing countries with vulnerable communities. Perhaps an important set of questions related to the impact that this can have is the following: How to make this technology available to communities?, how to find people with the necessary skills to operate the technology in far places? and how to avoid that by trying to contribute with houses to vulnerable communities, people in the communities end up being negatively affected by an important loss of construction jobs?. In my opinion, figuring these aspects out will help with the impact and scalability of the technology.
I think that machine learning can be very helpful for the discovery process of a drug, especially considering the length of the process and the amount of data involved. Pharma companies have realized that and they are increasingly trying to enter into partnerships to get access to these tools. Pfizer in particular announced another partnership in March of this year with XtalPi to work on drug discovery through quantum mechanics and machine learning. Please see the press release below for reference:
I think this is a great application of machine learning but it is definitely important to get to build a database that is large enough to be reliable. Perhaps the way of solving the concern about sharing data is by avoiding disclosure of the name and other specific details that could potentially give an indication to competitors of the specific name of the airline. The one thing that in my opinion is relevant to consider is the fact that because safety is a very sensitive topic in the aviation industry, as the use of Skywise gets more popular and while the database becomes large enough, airlines need to find the right mix of resource allocation for predictive maintenance guided by data and traditional maintenance. It is key that airlines make sure that the traditional maintenance made by experts is still taking place. Since an error in maintenance can have fatal results, it is important that airlines do not over rely on data and neglect traditional maintenance.