Learning about Nike’s entry into additive manufacturing / 3D printing leaves me wondering whether 3D printing will provide a meaningful improvement to Nike’s product development and process, or whether it is more of a marketing/PR strategy playing off the trendy nature of 3D printing. It is early days for 3D printing in the shoe space, and I am unsure if 3D printing will enable a shoe manufacturer to improve its product development innovation or process to the extent required to gain a competitive edge (i.e., for Adidas to overtake Nike). As posts above have described, Nike’s longer product development cycle may be necessary to sustain the quality and innovation that the brand is known for (e.g., through using their athletes to test/iterate on the product design), and I am skeptical that 3D printing will provide a meaningful benefit in this realm. In terms of process improvement and cost/logistics/timing efficiencies, more time and experience integrating 3D printing into the process will be required to draw any conclusions.
I was surprised, and very intrigued, to learn about how NASA is using open innovation effectively. As an extremely specialized, high profile, and at times, highly secretive organization, NASA is not an organization that would immediately come to mind as a target for implementing open innovation. However, as the post articulates, open innovation has produced tangible, positive results. From my perspective, there are limited to no downsides to expanding open innovation opportunities at NASA in all ways possible and appropriate, pending any security or confidentiality considerations. Improving NASA’s processes and outputs benefit us all; and, if non-NASA employees are able to develop better solutions at a lower cost (similar to the semiretired radio engineer who developed at 25% more accurate algorithm than the NASA scientists), then those crowd-sourced/open innovation ideas should be given a platform to be expressed, and if justified through outcomes, pursued.
It’s great to learn more about how a classic toy brand is innovating and staying competitive within the rapidly evolving digital landscape. In response to your first question, I believe that the competitive benefits of open innovation outweigh the potential brand risk. For LEGO, open innovation appears to be an important strategy for both accelerating product innovation and enhancing brand loyalty. To the product innovation topic, your research on the accelerated product development timeline (from 2-3 years to 1 year) is striking, and I expect that as the crowd-sourcing efforts grow, this timeline could continue to shorten (i.e., as more super-fans and fans provide input, more innovative ideas that will be feasible to efficiently develop will be shared). In addition, open innovation and crowd-sourcing provides a second advantage around enhancing brand loyalty through tapping into the creativity and nostalgia of the fan-base. By providing an avenue for super-fans to be directly involved in generating product ideas and enhancements for LEGO (including through competitions), LEGO will increase the loyalty and involvement of its customer base for years to come.
Regarding your second question, if I were Bumble (or any of the other apps that are focused exclusively on dating), I would be very concerned about Facebook as a competitive threat. Though I am not familiar with the details of Facebook’s dating app’s set-up, it strikes me that Facebook has some significant, immediate advantages:
1) Customer acquisition, which is critical to amass data to feed the machine learning algorithms, is not a concern for Facebook, as 185M already are active daily users and many more have a Facebook account. Basic information from a person’s Facebook account can be ported over to create the dating account.
2) When a successful match is made and a person decides to leave a dating app platform, that may be a long-term or permanent departure on Bumble. In contrast, Facebook dating app users will continue to use Facebook, and should those users decide to start using a dating app again, will be much more likely to use the Facebook dating app, as this brand/product will still be integrated into their lives.
These dynamics lead to Facebook having a) more data per user to leverage in the matchmaking process and b) more users / more active time per user on the platform, which are critical advantages in the machine learning / matching space.
Very interesting topic – thank you for posting. Healthcare indeed appears to be an industry where technology and machine learning can have outsized effects given both the lack of technology implemented across stakeholders and the various problems facing the industry (e.g., manual PA processes, lack of interoperability). This post made me think about our TOM discussions around resource allocation, in addition to the FRC Springfield Hospital case, and the importance of allocating resources (extrapolated as applying to both labor and machines) efficiently, and not having high-cost labor (e.g., physicians) completing PA work that could be more efficiently completed using other resources (e.g., Evicore). I agree the comment above – it will be important for companies to assess the cost/time savings of implementing this tool, and ensure that doing so will not create unanticipated work (e.g., due to lack of interoperability, or additional manual labor needed to “fix” a manual -> automated flow).