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Lego is a well-known brand around the world. It lends credibility on children related projects and has a large group of loyal followers. I would imagine this is why Tencent agreed to partner with Lego in China: Tencent is good at digital products in China while Lego is a major player in the kids’ market. The combination produces a powerful product for children in China. In a similar vein, Lego can seek partners in areas that both Lego and its partner wish to grow into.
As seen in the case of Toys R Us, rival manufacturing and digital distribution competition are bigger threats to brick and mortar stores than virtual reality in the near term. While VR may one day take over, it is difficult to see how parents will replace Lego products, physical toy that is proven to stimulate children’s brain activities, with virtual reality/computer, products that are traditionally known to slow down children’s brain development.
It would be exciting to design and then print my own customized car, all while I stay at home. However, the ease of access to lay your hands on customized cars appears to go against Honda’s role as a status symbol (at least in China). A brand becomes valuable and highly sought after if its products are scarce. If it becomes widely available to the mass, the brand may become devalued and will no longer be special.
Another potential challenge is that not all car buyers are avid car fans. While it is tempting to improve buyers’ experience by removing the dealer (i.e. removing the “middleman”), the job of educating buyers about the brand and each model will now fall on Honda. The costs saved by additive manufacturing will be somewhat offset by the new costs of educating customers.
Finally, is there any risk of patent infringement if buyers can access the detailed schematics of the cars? Honda will need to develop a robust cybersecurity system to make sure buyers cannot simply download and lay claim to the design of the cars. Furthermore, with customization, at what point does the car become yours and not Honda’s? And how will Honda protect its brand image if buyers can do anything they want to the design of the car?
Thanks for the insight into Adidas’ 3D manufacturing process, Kubs. I don’t think Adidas should have much to worry about from 3D printer producers. People buy Adidas shoes for their performance, not for their price. So long as Adidas can produce 3D-printed shoes that (1) perform just as well as, if not better than, the subtractive-ly produced shoes and (2) are similarly priced to (or at least are not substantially more expensive than) the subtractive-ly produced shoes, Adidas should be able to retain customers. The point you made regarding customers’ mixed reviews on additive manufactured shoes is a real concern. Having said that, Adidas has made a head start in this 3D printing journey. It should give Adidas some buffer (at least against 3D printer producers) to work out ways to scale up the additive manufacturing line and improve the quality of the end products. Furthermore, IP infringers are more focused on price than on performance. As such, I don’t think they will pose a huge threat to Adidas (again, based on my assumptions regarding Adidas 3D-printed shoes stated earlier).
Christie – You raised some interesting issues here, especially given the China context. With the impending implementation of the social credit system, Alibaba’s AI system could in theory be used by the Chinese government to monitor and assess the behavior of its citizens. For example, the chatbot Dian Xiaomi could be used to monitor enormous internet traffic (both the content and emotions displayed by internet users). A variant of the technology could be used to monitor the behavior and movement of citizens on the road. While this may not be seen as an issue in China (while the government aims to produce a harmonious society), there could be more resistance in other countries with priorities that are different than China.
Also, it is inherently risky to provide so much personal data to a private company. We have seen in the case of Facebook and Cambridge Analytics the damages that can be caused by privatization of personal data, to both the public and the companies keeping hold of the data. Private companies that hold vast quantity of personal data should therefore have robust privacy protection policies and systems. Ideally, this should be governed and enforced by a public regulator. It is difficult to leave this job to another private company (which may have different incentives to the public) or individuals (who don’t have the necessary time, resources, expertise or public influence). In setting up the regulatory framework, the government and legislature should solicit public involvement as much as possible. This is a public interest issue after all; it should be up to the public where the line of balance falls. As such, each society may come out with a different set of rules and regulations, even if this means businesses will have to incur additional costs of implementing a different regulatory standard to what is otherwise common pool of data across the world.
Jake, you hit the nail on its head in respect of possible causes and remedies for recent sales trends of Apple Watch and Fitbit devices. Fitbit is traditionally known as more a healthcare device than an urban lifestyle “smart” watch (a space primarily occupied by Apple Watch). As such, I agree that healthcare is where Fitbit has a competitive advantage over Apple Watch (despite the sales data). However, as you suggested, Apple Watch has various third-party app developers all too willing to enhance Apple’s healthcare capabilities through Apple Watch.
I believe that Fitbit has the ability to build a whole suite of health-related features into its devices using all the data collected from existing Fitbit users and insurance companies. One way to expand is by working with third-party component producers on diagnostic methodologies. For example, Fitbit is pairing up with Dexcom to sync certain Fitbit devices with a separate Dexcom sensor to monitor the user’s blood glucose level for diabetic risks. This way, Fitbit can rely on other parties who have already reached a sophisticated level of data analytics in specific healthcare areas.
What Fitbit needs to improve on, however, is the speed of rolling out these new machine learning features. For example, when Fitbit started selling the Ionic range around one year ago, the company claimed that the device had built-in hardware to detect sleep apnea and would eventually be a feature of the Ionic watch. However, there is still no sign as of today that this feature will be rolled out anytime soon. It may be because the application of machine learning in detecting sleep apnea is more complex than originally anticipated, but if Fitbit cannot back the enormous hype, consumers will sooner or later leave the brand. Perhaps Fitbit can adopt the same approach in the future as it did with diabetes detection to overcome the high initial cost and learning curve in a machine learning process.