Thank you for sharing KRiver! Like many of the commenters, I found this article extremely thoughtful with careful considerations on the pros and cons of open-innovation. Reading this article, I was curious about the selection process UNICEF undertakes to pursue these projects. Presumably they are working with a limited budget and face financial constraints as to how many projects they can select. How do they weigh short-term (quick win) projects versus long-term projects (e.g. blockchain)? I would imagine that some of the most impactful projects are also some of the costliest projects, with a lot of associated risk. Another question that came mind (that I also read in one of the comments) is how does UNICEF go about driving awareness to this open-innovation fund and soliciting project submissions on their platform. I could easily envision an “International Day of Civic Hacking” or “Hack for Good” campaigns that could raise the number of ideas submitted to the open-innovation platform. This is a great read for those of us who are looking for examples on how technology can create impact for government and non-profit organizations!
This is an awesome article — also a childhood lego fan here. This is a fascinating case-study on how a company is using open innovation to grow their companies. Two things came to mind here: 1. How does Lego maintain engagement with Lego Ideas users? 2. Is Lego worried at all about competitors potentially stealing some of the ideas from the Lego Ideas platform? I’d be curious to know the distribution of people who source good ideas on the Lego Ideas platform and what kind of relationship/engagement Lego (the company) has with active users. With these open ideas platforms, how do people find these platforms and what is their average level of engagement. Presumably, you’d like to keep the active users for longer period of time but I wonder how companies incentivize users to stay engaged. On the competitor front, Lego has some unique brand qualities that other competitors cannot replicate but I do wonder to what degree competitors leverage the Lego Ideas platform for “inspiration” and what legal bounds there are about copyright/trademark -ing these open-platform ideas.
All in all, this was a fantastic move on Lego’s part that has clearly yielded positive results for the company and increased brand loyalty amongst its users.
Thanks for sharing ldepoorter! I would actually disagree with some of the comments above about consumers producing these razor handles at home. I would say that niche subscription-based companies such as Dollar Shave Club (owned by P&G’s competitor Unilever) and Harry’s own the long-term competitive advantage. Since consumers are already on a subscription with these razor companies, it would be much easier for these companies to “add” these razor handles to the consumers next shipment. Consumers might be able to use their 3D printer at home but I would venture to say that there would additional steps in the process needed to print the razor handle at home, which the consumer may or may not want to take.
What concerns me at the moment, similar to Jaclyn, is the pricepoint. While I can see 3D printing producing these razor blade handles at scale, I wonder if the pricepoint will detract consumers from purchasing the product and not allow companies to reach economies of scale. In any event, this is a great article that showcases how we are seeing 3D printing in our day-to-day life.
I had a similar thought as Raleigh about the quality of these 3D printed items. My risk-adverse self would be afraid of using 3D parts in consumer sold cars and I wonder if consumers would react negatively to cars with 3D products as they would deem them “unsafe” and of “lesser build quality”. Thinking out loud: Is end goal of additive manufacturing (AM) to do produce at mass-scale? If so, will AM be able to reach economies of scale where it is cheaper to produce a part through AM rather than human-led assembly lines? These are all fascinating questions to me about the industry. I also wonder how governments will react to AM. Will there be regulation on the product usages of AM in cars and trucks? It’ll be interesting to follow how automotive companies shift to AM in the coming years and the public’s reaction to this change in the manufacturing of these vehicles.
This is a thought-provoking essay, Ricardo. It’s exciting to read about a real-life application of machine-learning (ML) to solve real-world problems. Similar to the comments above, I do too worry about what will happen to the patient-physician relationship. The question of privacy laws aside, I wonder what will happen to trust in the relationship between patients and physicians. Will patients trust the ML recommendations and will they see a need for a physician (in the extreme case)? I do believe that ML learning can help decrease throughput time and improve the overall quality of a physician visit. My concern is more about whether patients will trust this new system, and the potential unintended consequence of new machine-learning programs (created by non-hospital supervised companies replicating the technology) giving diagnostic recommendations to former patients. It’ll be interesting to see how the application of ML evolves in the health-care space and how physicians and hospitals relationships with their patients evolves over time.
This is an interesting article. I know I have been a target customer of their ads on YouTube, so I was curious to learn more about the product. I agree with mthai, the quality of the Grammarly product should improve with the increased number of users. While I have never used Grammarly, I do wonder how Grammarly goes about marketing to different consumers to scale their company. There seems to be an inherent tension between Grammarly’s growth goals (which might focus on specific population groups) and not over-sampling on the reviews from these specific population groups. Closely tied to this problem, it would be helpful to know the specific use cases of the product since it does not seem like Grammarly can be used in all cases. If Grammarly is keenly focused on a college-aged to young working professional demographic, content submissions could be more prone to biases and grammatical incorrections. Overall, I think this is a great application of machine-learning to help improve communication across countries and cultures that can continue to improve its product over time.