Thanks for a fantastic look into a creative application of machine learning in the public sphere. I grew up in Wake County and am very interested to see how this unfolds in the Research Triangle Park area. The program makes a lot of sense—having the system continuously update with verified home sale prices and refining the model accordingly. A few concerns I would have with its implementation are:
1) Will auditors put in enough data to build a precise model by 2020? Considering that this initiative may displace them in the long run, it seems the incentives are not aligned to build the machine learning capabilities in an efficient way
2) How will the market adjust to the new pricing tool? Considering this new valuation mechanism may reduce or eliminate inefficiencies in the market, that transition may be challenging for property owners
3) Data security will be a large concern as the data points collected to price homes may be intrusive or require sensitive information which could easily lead to abuses or privacy violations
I would also be interested in seeing if Wake County may be able to scale this product to other districts or license the program to real estate agencies as a new source of revenue for the local government. This is definitely an exciting development, but one that must be handled extremely carefully to ensure it does not harm Wake County’s residents.
Thanks for an interesting glimpse into the world of high fashion and how technology is helping designers stay at the forefront of innovation! It is interesting to think about the fundamental tension between traditional standards for Haute Couture and the commodification of clothing. Having worked in the apparel industry, it seems that retailers are incredibly sensitive to their supply chain, its responsiveness to trends, and their ability to build brand identity among consumers. From your essay, it seems that additive manufacturing will enable designers to address all three of these topics—printing items on-demand and adapting to real-time fashion trends, while appealing to consumers’ individual preferences and customizing to their fits. While this seems advantageous to designers, it also presents a challenge to not only stay true to the roots of fashion, but also adapt as barriers to entry fall.
New clothing companies like Everlane and Allbirds are able to reach consumers directly through DTC business models. Amazon Alexa enables individuals to scan their bodies to have custom-fitted items sent directly to them. Even shoe companies like Nike can print personalized products meeting individual needs (e.g., orthotics, performance). While Chanel has a strong brand identity on which it has built its success, these innovations all pose threats to its sustained competitive advantage. It will be hard to control brand image when customers can “print at home” or the market is flooded with fake goods. Managing the spread of leaked designs which can be printed by anyone at any time is a daunting prospect. These brands will need to become more closely integrated with their supply chain moving forward, and likely need to find new ways to differentiate which competitors and scammers cannot replicate.
Thanks for an interesting glimpse into innovation in the world of Heineken! I have toured Heineken’s main brewery in Amsterdam, and it seems that they really are implementing the cutting-edge of technology from machine learning to IoT solutions. With the introduction of open innovation, Heineken has done an excellent job of giving power to its customers and helping them become more involved and invested in the brand and its products. As you said, this has reduced costs and the amount of time invested in research and development.
One major drawback of this approach, however, is that consumers do not always know what they want. Henry Ford famously stated that “if I had asked people what they wanted, they would have said faster horses.” Similarly, Steve Jobs built much of Apple with the idea that people don’t know what they want until you show it to them. While having local competitions can improve regional brand identity, or distributing open innovation among its 300 portfolio brands may reduce overall costs, this may not actually help Heineken lead the market. Overindexing on crowdsourcing ideas and selection processes may have the unintended consequence of hampering innovation in the long run.
Thanks for sharing—this is a very interesting look at how open innovation is shaping the operations of one of the world’s most recognizable scientific organizations! Over the past few years, we have seen a surge in open platforms increasing transparency in an effort to advance idea generation. One example that comes to mind is OpenAI which has democratized the development of AI/ML technologies to accelerate progress but also ensure distribution of power associated with this technology. In a similar sense, NASA benefits from others’ input without necessarily making the same sacrifices private companies would have to exchange by releasing patents and intellectual property.
That said, there may be concerns regarding NASA’s control, mission, and sense of purpose. Without a centralized view or direction, it is difficult for small projects to come together to support long-term success. I also imagine there may be some security tradeoffs as aerospace and defense agencies worldwide will have access to NASA’s cutting-edge patents and technologies. Furthermore, the legacy organization may reject this new role as contributors become question-askers rather than problem-solvers. It may be beneficial to use the IBM Watson approach and have teams working in parallel to the “garage band of engineers” instead of relying so heavily on outsourced contributions.
Interesting piece—thanks for sharing! The two main challenges I see with leveraging additive manufacturing for growth at Nike are 1) competition, and 2) scalability. It seems that Nike’s main competitors are aggressively leaning on 3-D printed shoes as a core component of their innovation strategies, making this technology application less of an opportunity for Nike, and more of a necessary investment to keep up with the competition. That said, it seems that one solution may address both of these obstacles to growth. Nike needs to get more personal with its approach if it hopes to continue its market dominance in the space and reach customers directly—rounding out its triple double strategy.
To do this, Nike should leverage its large store footprint to push for personally customized shoes fit to the needs of each individual. This follows closely with how Dr. Scholl’s used its fit-finder kiosks to differentiate from other orthotic options and capture market attention. Furthermore, Nike making individual shoes for each customer would enable the company to build more of an emotional connection between customers and products. Beyond having a better product fitting each individual’s needs, consumers customizing colors, patterns, and textures will both yield a premium price and leave customers with positive feelings towards Nike for future purchases. More users for its machines would also reduce unit costs, making the prices more affordable and accessible for buyers. This also fits with Nike’s promotional push to “Just Do It” and be yourself.
I absolutely agree that the rise of artificial intelligence and machine learning are transforming the automotive industry in multiple ways—ranging from manufacturing to business model innovation. What strikes me about this new landscape is the pressures this has put on traditional manufacturers like Ford. Tesla positions itself as a technology / battery company rather than a car manufacturer. Will Ford need to adopt a similar mindset? If so, can it make the transition given its history? Will Ford be willing and able to radically shift its business model and become more integrated with alternative energy and transportation companies has Tesla has with Hyperloop / Boring Company / SpaceX / SolarCity?
Additionally, you mentioned Ford installing Jim Hackett as CEO, but I’m curious if the organization itself needs to make a greater shifts in how it is structured. Given that companies like Tesla have comparable market value while taking on significant losses and attracting top talent, how can Ford compete? Much like networking infrastructure businesses in the modern era, it seems that Ford may need to make bold, significant moves—larger acquisitions, dedicated teams, lateral moves, leadership disruption—or face a slow decline over time. I would assert that Ford is not making fast or large enough moves to stay competitive as Google and Apple begin encroaching on its traditional OEM market.