To your question about the target customer for 3D printed automobiles, I believe this product would be demanded by any consumer that is cost conscious if AM producers are able to scale appropriately. Further, cars produced using AM would save at multiple points in the supply chain. By reducing the middlemen between OEM’s and dealers, VW could offer a standard model to a large geographical area by systematically placing these machines in high density areas.
The question you pose about our emotional attachment to cars that are produced by hand is very interesting. Cars and the physical goods that exist below the hood have for a long time been something tied to emotion, even youthful romance (think Grease Lightning!). A lot of people still enjoy assembling and disassembling automobiles. It is not simply a pastime, it is a source of pride, that somehow, someway we developed this incredible steel ‘box’ originally with our bare hands. Thinking about a single machine popping out cars as a popcorn machine pops kernels is disconcerting.
Crowd sourcing content has quickly emerged as one of today’s hot button issues, and I think your questions hit the nail on the head.
In response to you question — “As Buzzfeed strives to become a more dependable news source, how can it further leverage the open innovation tactics that havemade it one of the most popular websites among young adults?” — I see one solution as tiering content based on the type of contributor. Buzzfeed could go about doing this by using a system like Instagram does where it gives users a check next to their name if they are a verified user, a user that in this case has a track record of producing value-add content that falls within the limits of the company’s broad boundaries. Although you risk alienating some of the platform’s early adopters, some sort of system that gives the best users credibility would be a step towards prioritizing strong content and implicitly fighting content that is factually incorrect.
Your questions are spot on! Machine learning and transparency around this new technology are certainly both front of mind for DHL and other logistics companies. Regarding machine learning, an opportunity that stands out to me is DHL’s role in just-in-time-distribution. Could DHL, through machine learning and other artificial intelligence, possibly be the just-in-time-shipping coordinator? All data points to a global supply chain that must adapt to demand for increased customization in physical products. As such, without restructuring the current system, increased variability surely risks toppling the entire network. If DHL were to figure out how to offer just-in-time-distribution for high demand products, reducing the negative side effects of order variability and customization (bull whip effect), this could turn out to be their next major business.
You pose a very poignant question that more smart people need to debate. I believe the tension between data and relationships is something that transcends any one business, something that is truly permeating throughout our society. This tension is something I think about a lot, something that is certainly front of mind as I progress through my job search.
To answer your question explicitly, I believe reserving certain white space for your creative visionaries is beyond essential for the livelihood of Netflix and the media industry. Consumer preferences change, and the relationship between consumers demanding content vs consumer responding to content is still not entirely clear. I believe that the greatest films, shows, and other entertainment manifest in formats and plots that are truly different. I do not see data behind these examples. I agree that data can play a role in producing content that is good enough to generate financial returns, but in a world where data is informing all content, the only way to truly differentiate may be to rely on good old creative minds.
Your question regarding Nike being able to scale to sufficiently meet customer demand is fascinating to me for two reasons.
First, most industry experts still believe that additive manufacturing’s sweet spot is producing a small number of highly complex products more cost effectively than the traditional manufacturer. As such, I question whether the investment community will stand behind companies trying to develop technology that prints already low cost items, especially as AM as an industry continues to gain steam and more VC money pours into ‘critical service parts’. On this, I am more pessimistic. I do not believe Nike will be able to properly scale to supplant traditional manufacturing for their lower cost items.
I do see an opportunity for Nike to use 3D printing to solve supply chain problems, however. In a world where UPS, Amazon, and other logistics players are using 3D printers as an alternative for traditional distribution in more remote parts of the country / world, I see Nike being able to sell their IP to these companies to operate, while they earn their usual margin.
Well done! This is a really unique peek inside a public entity that a lot of us know intimately as consumers, but know very little about as managers.
With regards to whether open innovation has a place in the organization moving forward, my first recommendation would be to clearly define parameters (financial constraints, scope of solution, deadlines) in order to receive more actionable ideas. If the MBTA is able to implement this, I do believe there is a role for open innovation in the organization in the future in solving a specific type of problem. I do not see open innovation as the best solution for larger, more systematic issues the organization is facing. I do, however, see open innovation as a means to outsourcing creative solutions for smaller, targeted, yet costly problems (late night bus volume).