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MACHINE LEARNING IN RETAIL: AN EDITED APPROACH
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Last modified on November 15, 2018 at 6:40 pm
Over the last several decades, apparel retailers have struggled with the complexities of increasingly varied product assortments and changes in long established seasonal shopping patterns. As retailers implement new strategies to stay ahead of the demand for an omnichannel shopping [...]

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On November 15, 2018, mdisipio commented on Healthcare Social Networks: Can Crowdsourcing Patient-Reported Data Improve Outcomes? :

Your question as to whether or not PLM is doing enough to help patients get better is an interesting one. Most often, we consider treatment – especially for serious disease or illness – to be completely bound up in the medical treatment plan laid out by physicians. I would argue that a significant piece of the value proposition for PLM is that it is a community that provides information and recommendations without prescriptions. It offers information that can be individualized and empowerment that comes from being part of a group. I consider much of its value to be bound up in that it offers a network otherwise potentially inaccessible for a number of patients. That being said, I do believe PLM can leverage its database to identify highly skilled doctors and match them with patients through an OPT IN feature. That way, if a patient determines to change physicians, they can return to PLM to reduce the amount of time spent searching – especially in high stakes cases.

On November 15, 2018, mdisipio commented on OpenIdeo – Using Open Innovation to Tackle the Biggest Societal Issues :

This is a great application of open innovation in a much broader context than I had previously considered. I think your question about OpenIDEO’s responsibility to ensure that sponsor’s implement winning solutions is a great one. If OpenIDEO recognizes the value of its platform is driven by the participants, it needs to ensure that there is a closing of the loop and publishing / shareout of the ultimate implementation of an idea. This will drive engagement and could offset some of the perceived need for a cash reward as another form of “compensation.”

On November 15, 2018, mdisipio commented on Made In Space. Literally. :

This is really interesting and something I did not previously know much about. Your question as to how Made In Space might transition to a more commercially viable company is especially interesting. I’d like to know more about the current limitations on producing in space and what innovations might be possible in the future. What changes would be necessary to the current product and process to make this more attractive to a commercial partner looking to produce satellites? What impact would different regulatory restrictions (if any) have on the process and current product if this does go down a more commercial path? Really interesting topic to contemplate?

On November 15, 2018, mdisipio commented on For GE to Convince the World of the Benefits of Additive Manufacturing, It Must First Convince Itself :

I agree with Brett that GE needs to develop applications of AM beyond the aviation practice to take advantage of cost-reducing manufacturing efficiencies across other business units that would similarly benefit. The question you raise around how GE might leverage in-house adoption of AM technology to convince external partners of its merits is critical. This should be GE’s primary focus at this stage – to create targeted testing grounds across their portfolio. GE cannot go broad at the outset with this technology or they risk overspending and under-delivering results (and potentially unnecessarily upending production cycles). They need to focus on the two or three related areas in which cost-reductions will have the greatest impact and implementation will require the least amount of tweaking from what has already been gleaned from the aviation space. If they can successfully expand t a these additional spaces, they could have a convincing case to make to external partners – one that does not hinge on a single industry alone.

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On November 15, 2018, mdisipio commented on Block by Block: Harnessing Open Innovation at The LEGO Group :

I think your question about whether or not LEGO is too reliant on external knowledge is an interesting one that warrants more examination. On the surface, I do not think so as LEGO continues to produce a significant portion of its product line that does rely directly on its external idea pipeline. I would be interested to know, however, how much of their revenue mix comes from products developed in house (or via licensing agreements with movie studios, etc) and how much comes from concepts generated from the LEGO Ideas engine. The spotlight on innovation has, as you cited, undoubtedly driven significant revenue, but it would be interesting to know how much comes from those products and how much is a result of the buzz they create. The beauty of LEGO’s innovation approach is that it did not solely rely on concept / product innovation, but it was paired with process innovation at the same time. On their own, efficiencies such as reducing the number of parts in the catalog might have made a less significant impact; but, because this initiative was augmented with a focus on finding out what the consumer wanted to see from the brand more directly, the overall strategy was amplified that much more. I’m interested to see how LEGO continues to engage with consumers to garner new ideas that will appeal to the next generation of enthusiasts – as well as see if they bring back any retired sets that nostalgic adults might suggest an interest in seeing again.

On November 15, 2018, mdisipio commented on Building a Brave New World in Toronto’s Quayside :

Great analysis on a really interesting topic! I think your question about how this application of technology potentially changes the culture of a city is paramount – especially as we consider its application in restructuring an existing city versus applying it to a newly planned community. As redevelopers and city governments grapple with making once vibrant cities work again, this technology could present a significant opportunity to optimize infrastructure and community safety projects. Beyond that, there are major implications to physical and spacial design – literally how cities will look and function in the future. This application could help to combat some of the impact of gentrification and redevelopment that has pushed entire groups of citizens to the margins of some urban areas and disrupted long-established networks in some cities. Historically, these groups are left to carve out new areas most commonly cut off from public transportation, etc. If smart cites can start to predict movement patterns and account for changes in socioeconomics within different city neighborhoods, local community governments might actually be able to plan ahead for migration shifts that have historically left entire citizen populations forced to uproot their lives in search of more affordable housing, access to work, etc.

On November 15, 2018, mdisipio commented on Beauty in the Age of Individualism: Sephora’s Data-Driven Approach :

This is a really interesting analysis of the application of new technology in a long-established industry. As you noted, Sephora is definitely prioritizing personalization and leveraging data to do it. I am most interested in exploring the point you briefly raised around beauty being a fast replenishment category and the challenge for brands to “predict what consumers want before they buy it from a competitor.” How is Sephora using their data analytics capabilities to anticipate the consumer replenishment need and interrupt the potential convenience purchase that meets an unexpected need? Namely,
how might they extend personalization beyond predicting products or services that might be of interest to a customer, and start to use the same data to construct a unique purchasing journey / timeline to ensure an uninterrupted interaction loop that doesn’t leave room for the competition? Amazon and some specialty athletic retailers have started to leverage this data to send prompts to consumers to replenish household goods or replace a worn out pair of running shoes based on number of miles logged on a fitness ap. Can Sephora take a similar approach? While 80% of surveyed Beauty Insiders profess complete loyalty to the brand, does that number directly correlate to sales? Or might there be room to better align purchasing intent with purchasing opportunity? They seem to be zeroing in on this application and I think it will have significant benefits if they can create a complete ecosystem for the customer.