I looooooove legos. Thanks for inspiring the nostalgia trip 🙂
Re the issues on admin overhead for the idea vetting process, it seems like Lego has an opportunity to outsource the idea vetting process too: why not let users vote up stuff? I imagine a lot of people (myself in cluded) might find it fun to flip through a randomized set of submissions and give it a thumbs up or down (or swipe left/right, if they created a simple Tinderized web app). Ideas above some threshold could then be forwarded to the Lego team.
WOW – we truly live in the future.
Re: your first question about using this business and tech for social good, it seems to me that this is a natural application of the TOMS business model: buy one, give one. If you contract with CC to build your home, you are saving a significant amount on labor and other costs associated with delays; why not offer a “philanthropy option” where consumers can allocate, say, 50% of their savings back to CC to sponsor the building of homes for those in need? This would allow a broader reach for CC than you might think; I imagine that the homes to be given to the homeless or underprivileged communities could be smaller and made with less deluxe materials, enabling a lower “give one” than “build one” cost for CC.
Very cool! I find this tech fascinating, especially since they seem to be a rare bird in the fitness tech space by seeking to leverage other hardware’s data rather than build their own. It simultaneously lowers their R&D costs while also reducing concerns that users will feel that their fitness tech experience is too fragmented across platforms.
It also seems like an issue to me though; if they’re dependent on data from other platforms, a) they’re vulnerable to being shut out, b) especially in the case where Fitbit or another hardware company start to compete in the analytics space as well, or start to pursue horizontal integrations (such as the one you suggested, with MFP). An interesting line to toe 🙂
Thanks ET – love the topic (and the handle).
I find the premise of this article interesting – using crowdsourcing to crunch through massive data sets. Rather than answer to the topics you raised (which have already been thoroughly discussed above), I’d like to note an irony. The project highlighted above seems more like a use case for ML or image processing. While free human labor is great, I think it’s likely that a) not all image sets will get attention by the most careful or trained participants, and b) even those that do are subject to human fallibility. Seems like a job best suited to a computer, no?
I completely agree with your assertion that ML and other innovative tech is especially critical for incumbents. I think this hints to the answer to your question re: whether Comcast can expand into a non-cable space; failure to cope with disruptive competitors and compete on their terms usually spells doom for large companies (examples abound, most recently Sears). It’s my belief that these companies go out of business not just because they fail to respond to competitors, but because they don’t understand the significance of the forces that drives these competitors’ success: changes in customer preferences.
Comcast can’t wish that the world would return to the “good old days” of cable – nostalgia gets them nowhere. They have no choice but to innovate.
I find these initiatives you described compelling because they demonstrate that Comcast recognizes the need to address consumers’ new behaviours and expectations, and leverage the company’s strength (great content and ubiquity across the US) to meet consumers’ new needs. Time will tell whether they’re successful in staying ahead of the curve…