Thanks for the great sharing! Really like how you use Apple store as a comparison to Capital One’s platform, and totally agree with your saying on Capital One need to invest more to foster the environment to encourage development on their platform, and on they need to make it easier for customers to compare different developments. I think open platform can play a really effective and important role when the industry knows the direction, but doesn’t know the destination and the path toward it. Especially in the more conservative industry, banking, open platform can be critical to bring out innovation and to figure out the potentials.
As for the incentive question you raised, I think it really depends on the stage of the platform. If it’s still at the stage trying to encourage ideas and developments, it might make more sense to keep it free to the developers. However, if Capital One realizes that the end users are annoyed by the noise on the platform and found it difficult to find the useful apps, then it might be a better idea to charge developers to have a better control over the overall quality.
Thanks for the interesting sharing!
I think to IKEA, the value of 3D printing is allowing them to have additional product lines — more complicated interior decoration and high-end customized furniture. I think these two directions of using 3D printing are actually quite different from their current brand image — affordable, designed but mass-produced furniture. I believe this will open up new business opportunities for IKEA, though I’m also more conservative on how much profit it can bring as the market should be relatively small. I think the overall question for me is that does IKEA want to use 3D printing to just add more colors and products to their main brand, or they believe in the potential and would like to push forward on creating specific product line using 3D printing? No matter which way they choose, it’s for sure that IKEA will be more diversified and have more customized touch on products.
Very interesting article — and I do beleive that machine learning/ big data analysis’s role in logistic industries has become more and more important.
Overall, I completely agree that data collection is the key challenge for leveraging machine learning in optimizing operation efficiency. Therefore, I’m a little bit confused about your suggestion on setting up and AI office. While I agree that it is critical for them to develop their own algorithm if they want to use machine learning to build up their core competence, I’m a little bit lost about how this initiative can help them solve the issue of getting clean data? I feel like focusing on operation and helping the partners in the network to upgrade their data collecting system might be a more straight-forward way to solve the challenge.
And back to your first question, I do believe that machine learning expertise should be built in house because in the future the competition is based on who has better forecast capability. And you wouldn’t want to miss this critical skill.
Thanks for the sharing — very cool topic.
I think Lego is very smart to take the move of collecting innovative ideas from their customers. First of all, the platform can be used as consumer research, giving the company the confidence that the product is worth investing in. Second, this is also a good way to strengthen customer relationship and build up higher customer loyalty as they feel like they are a part of the product development, and will be more related to the company. They have brought the meaning of open platform to a new level.
As for the concern over product design team, I believe that this is a good opportunity for them to stay close to the market and to get inspirations. Also, I believe that this is a good method to keep them alert, as now they need to compete with all kinds of people in the market. This might leads to better performance and better quality in internal innovation.
Thanks for the sharing! However, similar to the comments above, I’m more skeptical about whether Hotel Tonight has really built up the entry barriers and competitive advantages with machine learning. Hotel booking has been a data-driven industry with floating pricing across various platforms, and demand forecast has always been a key part of most of the booking platfroms. So, for me, what makes Hotel Tonight different should be that they’re adding “location” data as an input to their model. However, this competitive advantage doesn’t play that much a role once they shift to website and to support a longer period for “pre-booking”. Therefore, I’m quite skeptical about whether they are able to be competitive on the laptop war.