Miguel Dysenhaus

  • Student

Activity Feed

On November 14, 2018, Miguel Dysenhaus commented on Open Innovation at General Assembly :

Great read Ennis. Their development process using open innovation seems to be very fast and dynamic. One question that comes to mind is if this were to scale how would they organize and leverage the synergies that might come from many contributors working on similar topics at the same time? This is something that software companies have struggled with and that can lead to incompatible version of the same software.

Titi, I really enjoyed this piece. Unlike other sports, in football data and analysis have not become mainstream and are only use by a handful of teams and managers. I think there is a big opportunity for advancements like these to make a very big positive impact on the game. I think being able to measure a player’s performance and physical condition during a match in order to make data driven decisions, just like it is done in basketball, is where the sport needs to go and the fact that a team like Benfica is supporting it could be the major breakthrough.

On November 13, 2018, Miguel Dysenhaus commented on WinSun – Print into the Future :

Zoey, very interesting read. I wonder, not knowing much about the 3D printing process. Is the technology evolving at a rate that makes such a large upfront investment still worth while? Or are people just “waiting” for newer and better technology to appear? Second, are there any regulatory constraints regarding 3D printing for construction? Given the potential dangers involved, are countries freely allowing these types of construction?

On November 13, 2018, Miguel Dysenhaus commented on Open Innovation at Nestle – Establishing an extended innovation ecosystem :

Great read Yaping! Very interested to learn about how a CPG industry does product development and how they can improve. My doubt regarding this is, with the nature of the industry, product development cycles are usually a lot longer than in technology / software companies, where open innovation started. I assume this makes taking advantage of the dynamism of open innovation a little harder, since it is more difficult to iterate on the go. How do you see this conflict between sticking with an idea and changing while you are developing the project due to new input in a company like Nestle? Again, thanks!

On November 13, 2018, Miguel Dysenhaus commented on Promise and Peril for Machine Learning at Netflix :

Great read! I think Netflix’s algorithm on how to recommend content is probably one of the most advanced out there, since there is so much subjectivity involved in how someone will appreciate something that is basically an art form such as movies and tv shows. This, combined with the enormous catalog that they have on Netflix makes it a very big challenge. You mentioned how it saves them a lot of money by reducing the churn rate. Do you think there are any other benefits that Netflix can extract from this? Maybe like shorter term licensing contracts for content that is not theirs, dropping content that they predict won’t be appreciated by their current an potential subscriber base. Or, using the data to develop original content themselves based on the type of audience they try to target.

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

Very interesting Alex! It makes me wonder how can Nike increase the speed with which they take this technology to the customer. As you mention, we are still some time away from being able to print our boots at home. But how far away are we from being able to do it in the store? The fit of your football boot is key when it comes to performance on the pitch, so this would probably be very appreciated by consumers, who could have something made specially for them, instead of using standardized sizes.