avisa

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On November 15, 2018, avisa commented on Volkswagen: Additive Manufacturing as a Tool for Success :

3-D printing is such an interesting topic. This article makes me want to ask so many different questions. The first one is 1) would there be a need for car companies if they are just using 3-D printing to manufacture cars? Subsequently, if there is a possibility to do so cheaply, then 2) why hasn’t this been done already? This second question actually makes me a bit angry. If there are ways to offer vital resources (cars, homes, etc) at really discounted prices by leveraging the benefits of 3-D printing, we should enact these new technologies as soon as possible.

What an interesting article! I think the major tradeoff here is safety versus cost. Although the costs of replacing different naval equipment would be much cheaper, I worry that using AM technology might not be as safe as using traditional material. If there is a way to ensure the safety of parts created using AM technology is just as safe, and the only difference between the two options is cost, I can see this technology becoming prevalent in the Navy. I’m curious to know if other branches of the military, it was mentioned that other industries, have adopted this technology and if so, if there have been any downsides.

On November 15, 2018, avisa commented on Sherwin-Williams: A Case Study of Open Innovation :

My opinion might be biased because I am a HUGE HGTV fan; but, I can totally see crowdsourcing opinions on paint colors working out well for Sherwin-Williams. However, I don’t think simply posting different colors on instagram and asking customers to opine on them would work. I think the company would have to partner with HGTV or other home improvement media companies to push for open innovation. One thing I could see really working would be partnering with HGTV on their annual “Dream Home Sweepstakes.” They could paint the rooms of the house in different colors and those people who enter the sweepstakes could also get extra prizes by submitting their opinions on the different paint color options.

On November 15, 2018, avisa commented on Building industrial-scale LEGOs using open innovation :

Where is my engineering degree when I need it? What an amazing way to drive innovation in an industry that has been grappling with flat growth for five years. This is an innovative way to become a clear market leader. One of the things I really like is the fact that Vention is allowing those who iterate on their designs to share in their profits. Because contributors have the potential to be compensated for their contributions, I imagine the quality of contributions would be high. I can see other industries copying this model and getting high-quality ideas from a variety of customers/contributors.

On November 15, 2018, avisa commented on Stitch Fix: Using Machine Learning to Help The Grinch :

“I wonder if monetizing their inventory management machine learning algorithm would be beneficial or whether that point of differentiation will keep competitors from succeeding.”

I am such a fan of this company. 1) The CEO is a Harvard alumna and 2) she is super young! What an amazing example of leadership for all current HBS students and women entrepreneurs. With that being said, I the threat of competition in the apparel industry, especially concerning the use of machine learning to predict one’s wardrobe, is a real and urgent one. I thought the Stitch Fix model was unique, until I noticed that Amazon came out with a similar product. I don’t believe that Amazon uses machine learning to pick your wardrobe, but it does allow customers to pick items, try them, and then return them out. I would not be surprised if Amazon develops its own algorithm that will recommend different styles to customers. If that happens, Stitch Fix will have to determine a new competitive advantage.

On November 15, 2018, avisa commented on Machine Learning at the heart of JP Morgan’s growth strategy :

Your point regarding the safety and fairness of the technology is well taken. One issue that the bank will have to grapple with is using machine learning to approve loans for customers. Safety, because JPMorgan will have to ensure that the information customers provide is safeguarded and not used in fraudulent transactions. Fairness, because a process that once included human judgement, the loan application process, would be fully taken over by machines. Balancing safety, fairness, and “keeping up with the times” by leveraging machine learning will be one interesting task for JPMorgan especially as the organization tries to retain its competitive advantage amongst global financial institutions.