Interesting article – you mentioned getting customer feedback but I wonder what other open innovation approaches might work for Juul. For example, would a contest for idea generation or a poll for idea selection be beneficial? Would setting up a VC fund to invest in innovative periphery ideas help Juul’s own product development? The biggest issue for Juul right now is proving to the Food and Drug Administration and the public that the company will be able to curb underage usage of its products (ideally without too much disruption to their legal customers). This is an extremely difficult strategy/marketing/design issue that I don’t think they have solved and maybe a really creative idea could come from the crowd.
With regards to the pivot to health, in this regulated industry, individuals won’t be able to legally test or produce vapor medicine or other products until controlled studies are conducted so perhaps the best way to leverage the crowd right now is just to solicit high-level ideas regarding medical, vitamin, and energy applications.
Crowdsourcing of content and news is a really interesting concept. It is also a very delicate issue in the era of “fake news.” Facebook has attracted so much scrutiny and criticism for allowing fake news to filter through in user generated posts and sponsored political advertisements. Buzzfeed needs to carefully balance giving its content-generators creative freedom to drive traffic with upholding editorial responsibility to maintain baseline standards of truthfulness and quality.
Relative to social media or user-generated content, a news platform like Buzzfeed News should also be held to a much higher standard – journalism ethics, which involve accuracy, verification of sources, and impartiality among other norms. Open innovation definitely helps widen the top of the funnel sourcing of ideas (the aforementioned tip submission page and Sourcedrop) but probably so much so that many non-credible tips are let in. Buzzfeed News needs to manage the pressure of delivering fast product turnaround (hot news takes) with maintenance of Pulitzer-worthy reporting and editing integrity.
This is a really interesting article and issue for Disney. As you mentioned, the Consumer Products and Interactive Media division contributes approximately 12% of operating profit for Disney. I think the intellectual property issue at hand though is more than just that though – there are massive synergies across the Disney empire and the company is obsessed with managing its brand and experience for its consumers. Some poorly produced 3D printed Disney toys not only detracts from direct consumer products sales but also dilutes the overall brand. For this reason, I really like the idea of Disney branded printers but don’t agree with the open innovation contest and dropping attempts to thwart at-home 3D printing. I think Disney should continue to aggressively pursuit IP infringement, to the fully extent allowable by law.
There’s definitely an interesting legal question with IP infringement in 3D printing. If a consumer has bought a printer, uses software, and downloaded an illegal Disney print online, which of the 3 parties to the act (printer, software, online print) are also liable? I think the online print publisher should definitively be targeted for copyright infringement and distribution of that material should be curbed through cease-and-desist letters (and potential lawsuits). The printer hardware is probably not directly liable but what’s most legally ambiguous might be the software (which might be produced by the same hardware manufacturer but can also be separate). The US courts have clearly held torrent websites liable to the aiding and abetting of illegal digital content distribution (and shut down the ones without proper controls), and I think there might be an argument to hold 3D printing software providers to the same standard on IP infringement.
Finally, if you’re a big Disney fan like I am, I would highly recommend the book Disney Wars (https://www.amazon.com/dp/B000FCK0IU/ref=dp-kindle-redirect?_encoding=UTF8&btkr=1). It’s a fascinating account of Disney’s board-level strategy and infighting.
Interesting article! I think there are some real questions about this model though. What strikes me as most innovative relative to the traditionally construction model for WinSun is actually less additive manufacturing and more the systems based approach where components of the house are pre-built in a factory and then assembled on site. This reminds me of what the startup Katerra is working on right now in the US (see some interesting links below). The systems based approach creates tremendous costs improvement due to procurement, standardization, and avoiding layers of contractors and subcontractors relative to the traditional model of building on site. With WinSun, I wonder how much of the efficiencies realized is due to the systems based approach and how much is the 3D printing. Additionally, I question how innovative WinSun’s “3D printing” technology actually is because layering the “ink” of this concrete-like material to create shapes doesn’t seem intuitively different from using wet concrete to create shapes. Finally, concrete (and presumably concrete like structures) are more susceptible to damage in major earthquakes and floods.
A machine learning sourcing model can potentially be helpful in outbound sourcing but I don’t think it changes the venture capital skillset or is a source of sustainable competitive advantage in the industry. The machine learning sourcing can be incrementally beneficial to reducing large lists of companies to slightly smaller lists but ultimately, capital is a commodity in the VC industry (as you mentioned with how much money has been raised in so many different formats). In most good deals, investment firms need to compete. For the best companies, founders can chose their source of capital and care about the signaling effect provided by the investment firm, the value-add that the investor can bring, and the potential relationship with (and trust in) the investor that might have been built over a long period of time. For example, Sequoia and Benchmark commonly win the best deals (and the home runs are the only deals that really matter in the VC portfolio model). It’s also exceptionally rare for there to be home-run caliber top-of-the-funnel opportunities that no one else has seen. Thus, ultimately, even for Hone Capital, I think the source of competitive advantage is not algorithmic sourcing but maybe relying on potential strategic synergies with their anchor LP CSC, which is a large and influential private equity firm in China, to “win” competitive deals.
This is a really interesting article.
SoFi’s lending model was a big component of our thesis to invest in the company in 2016. Traditionally lending firms underwrite based on very similar outdated models (essentially only weighing FICO, salary, net worth) which as you mentioned leaves a demographic underbanked but additionally also misprices loans for individuals with high-level similarities but very different backgrounds and credit risk profiles (for example, a recent graduate from HBS MBA whose income and worth will scale vs. someone who’s been working a stable job). However, it will take time to develop a more sophisticated, more accurate credit model since closing the feedback loop (% defaults, prepayment, etc based on the independent variables tested) takes longer with loans that are for several years to even decades for mortgages. Experiments are also potentially quite costly. When SoFi tried to eliminate FICO all together from its personal loans credit models last year, the cohort data showed disproportionate losses. It is inevitable that the future of lending is going towards an automated, multi-factor model – it’s just a question of how long (and costly) will it be for us to get there.
Your suggestions about direct lending and public service data are really interesting and also timely given that rising interest rates are making the core business of student loan refinance less profitable – will pass along.