It’s fascinating to see that Qantas has made acquisitions in the field of data science. Beyond detecting spending patterns of individuals, and using those to later target the same individual, how is Qantas using machine learning to make predictions about their entire customer base? What features will they identify as most critical to their models? A regular business traveler expensing all costs will exhibit very different behavior from a sporadic-leisure traveler who signed up during a loyalty promotion. In order to build useful predictive models, Qantas will need sufficient data from all customer segments. For this reason, I wonder if they are pursuing look-alike modeling, where they generalize characteristics of a customer’s behavior to increase the relevant targeted audience; for example, Jane traveling from LA to DC may be surfaced a rental car ad because of Jason’s prior purchasing behavior, if Jane is deemed to “look like” Jason. I expect that key features to predictive models at Qantas will be length-of-travel, weekday of travel (as a proxy for business or leisure), average airfare, fare class, and frequented cities. Will Qantas be able to use patterns from their loyalty program to target new visitors to their site?
Fascinating! I can see that Cedar is addressing an unmet need–there is a clearly a lot of inefficiencies in medical collections. It will be interesting to see whether this technology becomes embedded in the medical ecosystem as service models begin to shift with companies like Karuna Health and ONE Medical, and with the growth in roles like Physician Assistant. Could Cedar’s technology be applied to other collections industries?
Interesting article! I had never considered applying open innovation in this way, but I wonder what learnings from UNHCR Ideas could be applied to other distress situations. It’s impossible to consider user input here without acknowledging the incredible emotional burden the users are experiencing: how do you design a digital product that is both effective and empathetic to a crisis situation? How do you prioritize input and information when much of it is dire, critical, and time-sensitive? And practically, how do you ensure your product is meeting users where they are, when they are likely without many basic supplies and possessions?
Interesting! I wonder, is AB facing an immutable change in tastes, or are beer preferences cyclical?
AB’s approach to developing Black Crown seemed strong, especially considering the huge number of talented home brewers today. Perhaps it failed because the brand is not associated with innovation/bold flavor profiles. Maybe a “DeWalt” approach of selling under a new brand would have been met with more success. Outsourcing product development and innovation to “the crowd” is only as good as the marketing that follows.
Nice article! I’m impressed with Nike’s return on investment in additive manufacturing for rapid prototyping; 3D printing clearly accelerates the learning accomplished via iterative prototyping, especially when compared to traditional techniques like casting or milling. Since 3D printing is nearing four decades of maturity, it’s exciting to see the technology accommodate the scale HP machines achieve: the technology is becoming a viable mechanism for mass production. However, I am not clear on the value proposition to consumers: do customers value the customizability (in which case, why have mass additive manufacturing at all?), or has Nike designed shoes that are not manufacturable by standard technologies? I’d be interested to understand more about customers’ true needs.
Beyond this, how does Nike view adjacent products that leverage additive manufacturing, such as custom insoles by Resa and Wiiv? These companies access customers via disparate channels–Resa with kiosks in Costco stores, Wiiv with an app–but both could be substitutionally competitive with Nike if consumers use these to satisfy their need for custom fit. Alternatively, perhaps these companies raise the overall excitement for 3D printed footwear, and ultimately aid Nike’s sales.
Great insights, thank you! I’m really interested to see whether (or how) this technology will overlap with prefabricated home construction. Additive construction offers efficiencies not seen in traditional construction, but how do the economics compare to modular/prefab design like that offered by Blokable (https://blokable.com/solution/)? Both minimize time onsite, but I imagine the process for integrating infrastructure like wiring and plumbing is quite different.