Just want to lead by saying I planned on commenting on this post even before Yael’s shout out in class. And I entirely knew “Banana Bread” was your alias 🙂
Any who, fantastic job on the post! Really enjoyed the analysis and felt appreciated the use of imagery. In your intro, you mentioned that the “Brewing a Better World” strategy has generated $1.1B in incremental revenue in just three years. That number is eye-popping! I’m really curious to know what percentage of those new sales were related to the Innovators Brewhouse platform, versus institutional innovations that Heineken developed internally through traditional R&D processes. It seems like the “Brewing a Better World” strategy is an overall company initiative, which makes me wonder, how much value are the crowd sourced ideas really generating?
Additionally, is the value from the Innovators Brewhouse coming from true innovation through the product/ packaging design, or is it this platform primarily a marketing asset used to engaged the most valuable Heineken customers?
Regardless, I love the platform and think they are executing very well — and could do even better if they incorporate your recommendations! Thanks for the thoughtful breakdown.
Thanks for such an interesting dive into Netflix’s use of machine learning. I appreciate the multitude of ways Netflix is applying machine learning. They have definitely been ahead of the industry in evaluating consumer content preferences and using those insights to evaluate content acquisition or production decisions.
I wonder if there are more ways Netflix should be applying machine learning to other areas of their business. For example, in addition to the quantitative insights that it gains from consumers’ like/ dislike feedback, I wonder if they could also gather qualitative feedback from viewers about their shows. That qualitative feedback could still be mined using machine learning, and would compliment the quantitative data. I believe the combination of quantitative and qualitative could potentially further refine the algorithm and begin answering the causality question you raised.
Thanks for such an awesome, thoughtful article! It’s impressive to see that Chanel has already found ways to use 3D printing for complimenting their existing production processes rather than considering it a full substitute for traditional production.
The scalability of 3D printing is often called into question. I wonder if Chanel strategically chose smaller products to apply 3D printing to in order to increase the volume of products produced. I imagine the cycle time [ 🙂 ]to produce hings like the mascara with micro cavities is much faster than some potentially equally innovative applications that may not scale enough to serve the mass market.
Thanks for the interesting article. All of a sudden, I have a sweet tooth 🙂
I thought the future applications of 3D printing for chocolate were interesting, but I couldn’t help but wondering about the quality of the end product. Did Hershey mention anything about the quality of the products being the same standard as their traditionally produced chocolate? Or would the ingredients need to be altered to accomplish the unique melting and cooling process for 3D printing chocolate? Just another consideration I was curious about that I thought would affect their investment in the space.
Thanks for the thoughtful submission! I was a huge, huge Lego fan growing up — I literally visited the LegoLand at the Mall of America as a kid — so this article made my eyes light up.
I really agreed with your recommendations. Additionally, has Lego ever considered how they can transfer the Lego Ideas platform to social media? I imagine expecting younger generations to visit a Lego Ideas website would be a difficult proposition. However, there could be innovative ways for Lego to reach their young fans where they are — social media. There may be creative ways to launch #LegoIdeas campaigns celebrating the top submissions and soliciting new entrees. AI could even be used to crawl social media and engage with fans that have new ideas for Lego creations.
This is a really cool initiative, and a great example of successful crowd sourcing. I wish it was around when I was a kid!
Thanks for the in-depth analysis. You raised a lot of great points, especially how “fake news” culprits could conversely use AI and machine learning to actually create their content. That’s a very interesting point, and it makes me think this battle against fake news is just getting. This could be a major issue for the rest of our lifetimes.
One thing that really caught me off-guard was that Facebook chooses not to *remove* fake stories that have been identified by machine learning and fact-checkers as inaccurate. I understand that “penalizing” false posts by displaying them lower on newsfeeds will significantly limit it’s reach, but this makes me question Facebook’s true sincerity. How can they credibly launch the Journalism Project and News Integrity Initiative if they aren’t willing to remove fake content from their platform?