Really interesting! As you suggest, it seems like Vention is using open innovation more to drive its sales than to create a true open marketplace for designs. I’m not sure that monetizing the platform is really necessary, as long as costs for the effort are covered as marketing/sales costs for their product sales. I agree that universities would be a great way to expand the library; Vention could also add some “expert” designs that they sponsor. (Are there influencers/thought leaders in this space?) However, I’m not convinced that competitors/incumbent players would participate, unless Vention manages to change the industry so much that these players are fighting for survival.
Super interesting! In thinking about your first question, I would want to know what the cost and time benefits are. I assume that these products represent cost and time savings for researchers against full-scale trials, given the regulatory environment. It may be a way to fail faster, and cheaper? Another consideration you mention is ability to predict adverse effects. I would be curious to know if it’s easier/harder to identify these effects with this kind of tissue as opposed to animal studies? For example, is it easier to control for other diseases, etc.?
Enjoyed the post, Lori! I think the question about consumer behavior depends on price sensitivity and a bit on psychology. A major driver of electricity consumption in Florida must be air conditioning, so it may not be enough to say, “Prices are going up. Turn down your air conditioning” because people are pretty set in their ways. The app may need to integrate with other smart home devices to say, “If you turn down your AC by 2 degrees, you’ll save $x on today’s bill.” Some people still may not be compelled, so they may need to consider a steeper rate difference to see a major effect. I know Opower (now part of Oracle) tried to tackle consumer demand reduction using similar tactics, with mixed success.
On the weather side, I think that global warming will necessitate machine learning advancements in weather prediction for a number of industries, including renewable energy. If they succeed in building accurate models, they would have a broad market outside of their own core business.
Really enjoyed reading this! I think that if Glossier plans to aggressively pursue an omnichannel strategy, they don’t really have a choice other than to analyze trends across channels. As you pointed out, the customer purchase journey often crosses channels, including some non-purchase engagement channels, so KPIs will also need to cross channels. Certainly, they can track some single channel trends, as well, but a holistic approach may have the additional benefit of driving a more unified omnichannel experience. With regards to customer interactions, I think it’s possible to do both. If the algorithms are correctly making predictions, customers should still feel heard. However, marketing teams will need to give this process a “human” face, which may require some old-school interactions, as well.
Really enjoyed reading this! To respond to your questions: Since Mayor Liccardo’s initiatives have demonstrated that open innovation can help drive innovation in San Jose, the mandate for open innovation should now be picked up by civil servants who are not elected, such as the office of the city manager. (This team could of course work collaboratively with the mayor’s office.) This will help ensure that the initiatives are a long-term priority. Another possibility is to involve local high schools and universities by having students pilot technology projects in their local communities. Students are often able to develop imaginative and relevant solutions for their communities. Such a program would have the added benefits of scaling the number of ideas being tested, involving youth in open innovation and community development from a younger age, and tapping into new engineering talent at universities.
Your first question raises another interesting question about how innovation can scale in manufacturing and even in other large organizations. In this case, I do think it would be possible to implement this additive manufacturing process at a larger plant like Wolfsburg if the teams are specialized and autonomous. The crews and production engineers working on the tools should have enough expertise on their parts of the manufacturing process to drive innovation. If teams are rotating across the line, it will be difficult for them to learn and make improvements quickly. The teams also need to be autonomous so they can feel empowered to test, fail, and iterate. If they must submit each design change through a centralized management system, they will be less inclined to take risk and the process will slow down.