Thanks for a really interesting take on additive manufacturing in the context of healthcare and emerging markets. While being able to print a prosthetic limb when importing one is so expensive could bring tremendous value to patients in Rwanda, I’m curious about the cost of this going wrong. How far along is 3D printing in the medical space? Have they tested its effects on a wide sample of patients? While the upside could be very positive, the costs could be equally as dramatic; and of course, mistakes in printing someone’s limb is substantially more drastic than mistakes in printing a new Nike shoe. I’m hopeful that this technology could take off in the medical space, but would love to know more about its progress to date.
Thanks for an interesting perspective. The “bias” issue is striking to me, and reminds me of the discussion we had around the Aspiring Minds case. In that class, someone brought up Amazon’s automated hiring tool (driven by machine learning and AI) that was scrapped last month because it had begun filtering out female candidates (article here: https://www.reuters.com/article/us-amazon-com-jobs-automation-insight/amazon-scraps-secret-ai-recruiting-tool-that-showed-bias-against-women-idUSKCN1MK08G). We’re at an interesting crossroads, where humans and machines are both fueled by long histories of biases, both conscious or unconscious. Until machines can master EQ like (some!) humans can, there will always be gaps in how an ML-based tool helps to hire — or in Airbnb’s case, connect hosts and guests in a fair and un-biased way.
Really interesting article — you point out great benefits 3D printing has begun to offer Adidas, and I agree with all your recommendations. It’s interesting to compare Adidas’s product strategy with that of competitor Nike. Given that Nike has historically created products by partnering with powerhouse athletes to iterate and improve upon them, I wonder how customers might respond to Adidas’ “democratization” of product design and iteration through 3D printing. Putting 3D printers in Adidas stores would put customers in the drivers seat; but will this impact Adidas’ brand as a whole? In a world where consumers can walk into a store and design/print their own shoe, does the Adidas brand slowly lose its “stamp of approval” of a shoe crafted by experts? or rather, will consumers embrace this newfound agency in the shoe purchase journey?
Great article, and agree with many of the points previously made on security and responsibility. There’s a reason that financial services firms have historically moved at a slower pace; they carry the great burden and responsibility of protecting consumers’ financial information, and moving too quickly could put this information at risk and be detrimental to their reputation. I think Capital One has done a great job of constantly redefining who they are, often playing outside the realm of a traditional bank. One example is their Capital One Cafes, which strengthen their relationships with consumers beyond simply being their place to bank [see article: https://www.bizjournals.com/washington/news/2018/10/19/first-look-d-c-s-new-capital-one-cafe-is-a-bank.html%5D. It’s no surprise that they’ve embraced an approach of open innovation to continue stretching their own limits.
This sounds like really interesting technology — but certainly comes with the pitfalls mentioned in the article and in the comments. I wonder if Pymetrics would think about switching (or expanding) their customer from HR professionals to those starting out their job search; it seems to me that it could be more successful as an individual diagnostic tool for how you think and what type of role you would thrive in. Hiring for a role from the HR perspective–especially a senior role–still requires multiple perspectives and in-person conversations to truly understand if a given candidate is the right “fit.” Until machines can master EQ like (some!) humans can, there will always be gaps in how an ML-based tool assesses potential candidates.
Really interesting article — you point out great benefits 3D printing could offer Nike, and I agree with all your recommendations. It’s clear that 3D printing could offer many synergies to Nike’s process of creating products and partnering with athletes to iterate and improve upon them. I wonder, however, if this trend might democratize product design and iteration, therefore decreasing the company’s reliance on athletes as product visionaries, and ultimately incurring a downstream impact on the brand as a whole? For instance, in a world where consumers can walk into a Nike store and design/print their own shoe, does the Nike brand slowly lose its “stamp of approval” by major athletes? Maintaining this balance in a world where additive manufacturing starts to become the norm might be challenging.
What’s fascinating about Glossier’s crowdsourcing approach is that they are simultaneously informing R&D/product development and shaping their brand as one that connects with their consumers (like one big marketing campaign!) I think they have a critical first-mover advantage over Sephora and other players in the beauty space that have been slow to catch on to open innovation. A second advantage Glossier has over Sephora / other traditional competitors is their online-only (or online-mostly) strategy; by avoiding challenges of stocking inventory in physical stores, Glossier can continue to be flexible in its product development process, iterating based on customer demand and input.
This is a fascinating application for 3D printing – thank you for your thoughts! I couldn’t help but think of our Marketing case on Gap while reading this. You imply that although 3D printing can bring many benefits for a couture designer like Chanel — customization, increased product performance/innovation — its long-term implications for designing and producing clothes on-demand could render the high-end designer’s role to be nearly irrelevant (similar to Gap’s replacement of its designers through big data). It begs an interesting question of how deeply Chanel should embrace this trend, and where they should draw the line. I also wonder how Chanel’s customers would respond to on-demand customization — if that perhaps defeats the purpose of buying high-end clothing where trust and aspiration for the brand is paramount.
Amazon has truly mastered the “invisible payment” with this technology, something we’ve seen succeed with Uber/Lyft. There will certainly be kinks to smooth out as Amazon Go scales up, such as incorrectly charging a customer or dealing with multiple guests with the same account shopping together. I’m less concerned about these glitches, which I think Amazon could quickly solve…rather, I think the value of this technology hinges on consumers’ preferences for physical grocery/retail stores. I wonder if we’ll see increased physical stores with technology like Amazon’s, leveraging ML, cameras, sensors and advanced data analytics; or instead, if we’ll see fewer retail stores as consumers move to on-demand grocery delivery services (already offered through Amazon Fresh or PrimeNow).
This is a great synthesis of the innovative work Sidewalk Labs is doing in Toronto. I also appreciate your recommendations, and agree that with the broad list of challenges any city needs to tackle–transportation, energy, housing mix, etc–it can be confusing and overwhelming for citizens to get involved, even though their involvement is paramount to the project’s success. This begs the point that “open innovation” needs to be coupled with some sort of top-down direction to help aggregate input in a helpful and specific way; for instance, Sidewalk Labs should perhaps crowdsource the top issues for a given city, put together different options to solve each challenge, and then go to citizens for more detailed input. I also wonder how Sidewalk’s current model of crowdsourcing can scale across cities. It seems to be quite personal (e.g. through town halls), but can this be shifted to a digital mode to help them gather more information more quickly? Will this degrade the inputs that they receive?