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Pareto Ninja
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While this was an interesting read, I fail to understand the “case for change” behind adopting additive manufacturing at Hershey. It’s unclear what the benefits are, and to what extent, they justify the investment in 3D printing. That being said, Hershey makes significant revenues from selling the “Hershey experience” at the Hershey World in PA. So I can envision installing a 3D printer that prints customized chocolates being a great tool to drive customer engagement, and hence greater ticket sales, at the Hershey World. Beyond that, I don’t see the need to scale additive manufacturing just yet.
Interesting read! My general sense from reading this article is that H&M is leveraging ML to drive operational efficiencies. While operational improvements can positively impact bottom-line, they will only bring “incremental” changes to the company. In my opinion, what H&M needs at this point is a “radical” change, similar to the case where IDEO helped the Latin American theater-company reshape its customer experience. So, in that way, I agree with your point that H&M should focus on its culture, talent, brand vision etc. versus over-investing in implementation of ML and other such technologies.
Great article! In my mind, questions 1 and 3 have a similar response – we cannot rely on machine learning alone. There is need for human intervention; and an appropriate mix of human and artificial intelligence is probably what’s most effective. What that means for question 1 is: at the risk of oversimplifying, we can input a list of distinct key words that each organization uses for the same concept in order to customize it for different organizations. As for question 3 around accuracy concerns, it is critical to compare and contrast what the data reveals with human intuition/perception and avoid over-indexing on specific data points. While this is in direct contradiction to the concept of using technology to gauge feelings, simple things like talking to people in the hallway/cafeteria can reveal interesting insights that may/may not have been captured in the data. Of course, this approach isn’t scalable, but may be a good way to sense-check or confirm what the data is saying, particularly before making radical changes based on that data.
It was interesting to learn that Siemens is not only investing in technological trends to evolve their own products/services, but also to create an ecosystem that can leverage these trends. To your question, while it’d be nice if corporate behemoths looked at this as an “obligation” to provide solutions for other smaller organizations, I think serving/enabling smaller players and investing in a community can actually serve the interests of these big companies themselves. For example: we’re seeing a lot of companies like Google, Tesla share their technologies on open platforms. There are several possible benefits of this approach such as development of complementary products/services that increase adoption of the company’s technology, augmentation of their own product/service stemming from further research beyond where they left it at, and more.
Great article! The question you raise is an extremely important one given it’s typically much easier to source ideas, especially social impact ones, than to commercialize them in a sustainable way. With that in mind, I believe for-profits can drive social change in a much more sustainable manner than non-profits/NGOs, and hence should be included in the effort. Besides engaging other partners early on allows for greater resources, for example potentially more relevant local expertise, that could enhance the program’s effectiveness.