This is an attempt for Unilever to keep up with nimble consumer goods startups especially in the direct to consumer space. Unless these initiatives become significantly commercially viable, the open innovation effort remains similar to a marketing or PR stunt. Another question I would ask would be how Unilever can absorb an entrepreneurial culture via the Foundry. The current efforts all seem like Unilever providing one way assistance to budding entrepreneurs, but not necessarily absorbing learnings on how to make its own end to end business processes more agile. I would question whether learning how to innovate further in a company like Unilever is better done by the Foundry or by the Ben & Jerrys or Dollar Shave Club acquisitions.
Interesting topic! I am doubtful on whether master chefs like the Adria brothers would like to gain artistic or gastronomic inputs from machines. I believe that the artisan movement will continue to grow as aggressively as machine learning and AI as a form of counterculture. (There is evidence that machines can produce art though: a computer has composed a classical music piece which critics deem the same quality as master composers.) However, I liked the application on whether machine learning and AI can develop to a point where they can become a full restaurant management team (versus hiring staff). Part of the failure of El Bulli is despite its gastronomical achievements, it was not managed well. Instead of forcing artists to gain business sense, outsourcing key business decisions could allow chefs to focus completely on their craft and potentially draw up forecasts on how profitable each dish is.
I’m a fan of Adidas shoes and was very excited when the Futurecraft 4D dropped! Although revolutionary today, the cost of technology usually drops with quick industry adoption and I wouldn’t be surprised if the shoes are much more affordable in the near future. In order to successfully sell massive volumes, 3D printed shoes can utilize the following strategies to sell even at high price points:
1) There is a market for custom shoes particularly for those people who’s feet are in between sizes or require additional support features. Lots of medical applications on this front.
2) There is a large market in the sneakerhead community for customizable design shoes.
Shortening the product innovation cycle inevitably also shortens the product fashion cycle, so I suspect this adds pressure on Adidas to release more and more sneaker innovations (on top of their already dizzying number of colorways).
I’ve always LOVED flying Singapore Airlines, and wish I could do that more while being an unemployed grad student. Regarding the question on how open is too open – idea generation may be the easier part of the funnel to crowdsource, but business results are behind excellent execution that Singapore Airlines is known for and difficult to replicate. Open innovation might also be more useful as SIA continues to play much more in the luxury segment. Sourcing inputs from extreme consumers (Solitaire PPS club members, business travellers that optimize for points collection) allows the power consumer base to co-create the product and thus increases customer loyalty for a very lucrative segment. The high investments required to upkeep and innovate on first class and above also create a natural barrier to entry as many airline players are choosing to drop first class from their offerings.
I had a fun time reading this post! On your two questions:
1) I believe machine learning could be a huge contributor to Spotify’s revenue. I would explore Spotify’s content mix against licensing costs. A lot of the big data analysis around Spotify mentions that most of the top played songs are not actually Billboard Hot 100 hits but more dated songs (e.g. Mr Brightside, released 2004). There’s an opportunity to do revivals for popular songs that may not have as exorbitant licensing fees, as they’re more dated. Another revenue stream could potentially be providing consulting services to media and entertainment companies based on their data findings.
2) One edge that Spotify currently has and could exploit further is its integration into more technology ecosystems. A simple but strong example is that whenever people identify a song on Spotify or Shazam, there is an option to add the song on Spotify. I would tie Spotify to more points of consumer contact around music discovery to keep relevance and active usage. Unlike big tech companies, Spotify does not have adjacent hardware and software, and thus relies on partnerships which could be the quickest way to remaining indispensable.