While using our voice to activate electronics sounds very desirable and convenient, it comes with many risks as well. This means that all of our devices will basically be recording our conversations 24/7 in the living room, in the car, or in the bedroom. This is probably happening already today without us even knowing it is happening as we send a text to a friend or say something to a friend on the phone, and suddenly get relevant commercial to that comment the next day on our browser. All these major internet companies have an enormous amount of data on each and every one of us, and with Alexa becoming more prevalent the situation is becoming worse. I believe to stand out from competition Amazon will have to do an amazing job at showing that it is protecting our precious information and basically not freak the user out with how much information it has on us. While it might have the superpowers to give us an extremely accurate and helpful recommendation it should not in that case that it would freak out the user, and make the user to avoid using the system in the future. Understanding how to make the user feel safe with us storing his or her data is extremely important as a competitive advantage.
This is an extremely well written article as you explained complex ideas in a simple manner to comprehend. This article has pointed out a very interesting point as we set very challenging and ambitious goals it tends to accelerate the development of technology tremoundsly. As mentioned in the case with SpaceX or even if we go back to Kennedy’s mission of choosing to go to the moon. Relativity’s goal is clearly ambitious and as society we will learn a lot about 3D printing as they push the edges of the field. I believe another industry that could be transformed in a similar matter is the real estate construction industry. If we think of the ways buildings are being constructed it is a very tedious and inefficient process. In theory could we 3D print a building? This is a major question. Today some real estate firms are trying to move towards modular buildings where you produce some of the units in factories and just do the assembly on site instead of constructing everything on site. But 3D printing a building would required creating printers on a completely new size and scale and is definitely a challenge worth exploring!
I am personally a big 3D printing fan, and I found this article fascinating as it exemplifies how 3D printing is transforming yet another industry. While it is true that 3D printing has the ability to easily create more complex products which otherwise could not be created, what I find especially interesting about the transformation happening in the clothing industry is that it is a double transformation. 1. 3D printing allows to create more complex products 2. (IoT) Internet of Things and wearable electronics are integrating slowly into the fashion world. Given these two transformations which are happening now at the same time with regards to the question: “If so, are these sports apparel brands inevitably destined to be disrupted if they cannot commercialize the use of this groundbreaking technology?” I believe the answer is a strong YES. And the reason is whoever will be innovative early adaptor with these early technologies will basically reap the benefits of two transformations at once. I am personally going to work this winter-break on a startup idea that uses these 2 technologies to create wearable tech in the HBS Startup-bootcamp as I believe this field is very hot and still has enormous potential.
Tina! This is a very well written article. I found this article very insightful as I am not a fashion expert and did not know about this type of fast-copy-fashion, where companies try to pick up on “micro-trends” in the market and then respond fast enough while the trend/signal is alive. You mentioned in the article that: “H&M has built a team of 200 data scientists, analysts, and engineers to analyze data ranging from external blog posts to internal purchasing data.” I would recommend that H&M goes even further with their Machine Learning activities – beyond analyzing internal data and external blog posts, they should analyze their competition websites and try to see what comes up on their websites, how long does it stay, and what comments people have on those items. Perhaps, some companies are using advanced dynamic pricing models, so by using Machine Learning we could reverse engineer their models to identify the trends they are saying. Given H&M’s terrible situation at the moment I think they need to be very aggressive with their ML strategy and use any data available at their disposal.
I found this article extremely interesting! As it is focused on one of the largest industries in the world, with the least amount of digitization so huge potential. Was also cool to see new applications of Machine Learning, which I did not think about previously or was exposed to as using security cameras to automate an automatic safety process in the company or building 4D project management schedules. While this sector is ready for a transformation my main concern is how do you implement these massive behavioural and adoption changes required to adapt new and complex software while most of the industry still works in a very old fashioned way and will probably be reluctant to change:
“A large portion of the industry still communicates through hard copy documents and spreadsheets. Multi-billion-dollar infrastructure projects teams are still more comfortable with email and spreadsheets rather than more structured project management systems.“