So Many Cranberries

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On April 28, 2017, So Many Cranberries commented on Nvidia – The Way It’s Meant to Be Played :

Very interesting post. One asset Nvidia has as it pursues this multi-sided platform strategy is its brand strength with gamers, which may contribute to them having more developers than AMD. The Nvidia team members are treated like gods at PAX East.

On April 28, 2017, So Many Cranberries commented on VR Physio: Solving Neck Problems :

Having spent many hours doing physical therapy (runner problems), I see a ton of potential for integrating VR into the space. And as you’ve said in the comments, I also see it as a complement and not a substitute for physical therapy. Physical therapists use manual therapy techniques that could not be replaced by VR, and I imagine many would welcome a tool that got their patients to actually do their exercises between appointments.

One downside I see is that people who have a one-time injury may not want to purchase the equipment. Renting it, though, seems totally reasonable, and pharmacies already do this for other equipment. I wonder if and how they should target pharmacies or someone similar as a channel partner and what that arrangement might look like.

On April 23, 2017, So Many Cranberries commented on Vertebrae – The Advertising Platform for VR :

As always, YuvalG, great post. Given that Vertebrae went public with this business model in advance of a large VR user base, I can’t help but wonder if their ultimate goal is to be acquired by Facebook or Google. Leading the development of a large VR user base only gives competitors time to copy and improve upon Vertebrae’s product/model. This seems foolish when some potential competitors are tech giants that develop VR platforms and rely on advertising revenues.

The Taco Bell/Doritos example reminded me a lot of product placement in TV/movies (specifically, Apple products in House of Cards). Perhaps this type of advertising requires different organizational capabilities than those at Facebook/Google? If so, Vertebrae’s early move could be a signal to these companies that they could acquire these capabilities instead of developing them internally.

On April 6, 2017, So Many Cranberries commented on Palantir – Big Brother is Watching You :

I think the point you raised about operating in a closed niche is an important one. I imagine that Palantir’s future success rests on its ability to share learnings (e.g., algorithms, organizational knowledge) across government and non-government clients. On the one hand, serving government clients has its advantages. In my experience in the defense sector, big brother tends to have a lot of data and has a more receptive attitude towards machine learning approaches; the use cases for big data/cybersecurity emerged pretty early in the defense sector, so it’s more of a proven concept than in other sectors. On the other hand, Palantir may not be able to reuse technologies or knowledge they developed while working with a government client due to the sensitive nature of the data/information. I often wanted to collaborate with people outside of the defense bubble in my last job, and this required very creative structuring of programs/development processes to separate the sensitive from the non-sensitive information/data. So it can be done, but it’s tricky.

On April 6, 2017, So Many Cranberries commented on The Business of Hillary vs. Trump :

Great topic to choose for this assignment–it’s illustrative of the practical challenges and limitations of data science. Some of the errors you mentioned are systematic errors; for instance, “Shy Trumpers” could cause all polls–not just random ones–to have errors that are biased in the same direction (towards Hillary). One way to handle this is to build a model that accounts for these biases. FiveThirtyEight had one of the few models that did this (they assumed polling errors were correlated) and indeed gave Trump a higher chance of winning than others. Even with this assumption, however, they still got the final prediction wrong. Perhaps, as you suggest with “sentiment analysis”, forecasters need to look to new data sources to eliminate this potential bias.

On April 6, 2017, So Many Cranberries commented on The City of Chicago and its Array of Things Project :

Thank you for taking the time to write such a well-organized and well-researched post. I have a soft spot for both public sector and big data, so I loved the concept of this project. I think it’s success will be determined by how well the city can leverage this data to its advantage, particularly cost savings (if the city chooses to fund its expansion). It’s too early to tell, but other cities have had a few stumbles in this area because digital product design & data analytics aren’t in their current set of capabilities. I wonder if some of the crowdsourcing ideas mentioned in other comments could be extended to the creation of products/solutions that help the city capture value from this data.

On March 19, 2017, So Many Cranberries commented on MShop: what if we crowdsourced mystery shopping? :

What an interesting concept! I agree with dk_22 on the potential challenges, though I think your business model sets up the company to exert control over those challenges through thoughtful design.

This concept seems like it would be complementary to a small company in Boston called Locately. They run analytics on survey and GPS data to generate insights about shopping patterns, purchase behavior, etc. for retail clients. If you thought about developing your idea further, it might be worthwhile to see what they do. There’s an HBS PLD alum at the company.

On March 19, 2017, So Many Cranberries commented on PatientsLikeMe: Finding Cures for Chronic Diseases :

Great explanation of how PatientsLikeMe works, Alice. I agree that broadening their partner set is a critical next step on their growth path. It seems like PatientsLikeMe could have a very active/responsive crowd with a pay-it-forward mentality; I imagine that many people living with a chronic disease are motivated to help others going through the same thing. I wonder if they will leverage this as an asset if they broaden their partner set. If a potential partner needed information not already in the database, PatientsLikeMe could try to activate its crowd to provide that information. This of course could pose ethical concerns, but those may be mitigated by a strong commitment to the company’s current mission.

On March 18, 2017, So Many Cranberries commented on [Option 2] Glassdoor: Rant about your boss AND help the community :

This post made me curious to keep an eye on the competition between Glassdoor and LinkedIn. It seems like the two companies are crowdsourcing information to replace/support headhunters, but they’re coming at it from different angles. Though both companies list jobs, Glassdoor is crowdsourcing information to answer the “Would you want to work here?” question for jobseekers. LinkedIn seems to be crowdsourcing information to answer the “Who exists in the talent pool?” question for employers and the “How can I get my foot in the door?” question for jobseekers. I feel like they will eventually converge on a complete solution, and it will be interesting to see who is more successful in deploying their crowd to get there.

On February 27, 2017, So Many Cranberries commented on UPS Prepares to Take on Amazon :

A very interesting approach to taking on the behemoth that is Amazon. I think suppliers that have developed somewhat tense relationships with Amazon’s fulfillment services would see the value in this proposition. One thing I might add is thinking about a partnership with a robotics company on fulfillment center automation. When Amazon acquired Kiva, it left a hole in the space. That was 4-5 years ago, and several startups have entered to fill that hole. I bet one of them would be eager for the opportunity to partner with a large player like UPS.

On February 27, 2017, So Many Cranberries commented on – The Original Tinder :

Thanks for the post, Charu. I enjoyed reading about how Shaadi leverages local culture/customs to create value for users. It sounds like Shaadi is a prime example of what a company should do when being the first mover into a market that has significant network effects: invest early in growing the user base. A truly disruptive product would need to enter the scene to rock Shaadi’s traction in the market; incremental innovations are not strong enough to bring down Shaadi’s competitive advantage. This is a story I will keep in mind when thinking about what a company should do to ensure its first-entrant advantage doesn’t wear down over time!

On February 27, 2017, So Many Cranberries commented on This Chinese Man is Battling for Women’s Fertile Ground :

Loved the title–very witty. Your post touched on something that I think can be very powerful about digital platforms: using anonymity as a value creator. Anonymity allowed Dayima to tap into a market that had few competitors (at the time of entry) and offer a way for consumers to feel comfortable engaging. Per YuvalG’s point, though, virality is limited because people want to maintain their anonymity. I’m curious if there are any ways for Dayima to achieve a high viral coefficient while protecting anonymity. Maybe package it with other features that the consumer would feel comfortable recommending to others?

On February 2, 2017, So Many Cranberries commented on Minerva Schools: Disrupting the university model? :

As pvuong alluded to, the reputation of a university is a huge part of how it creates value (and maybe even more so than the actual learning experience). Since Minerva was founded as a partnership with KGI, it is linked to the esteemed Claremont Consortium. Piggybacking off of another institution’s reputation is a creative way to get traction with an initial cohort of students and slowly build a reputation for themselves through a low-cost, high-quality experience.

I’m not well-versed in the education sector and really appreciated the context you gave in this post. Thank you–I learned a lot by reading it!

Thank you for posting–I’ve never heard of this company before and am very glad I clicked on your post! It’s true that nonprofits often struggle to raise funds for technological investments (IT, digital, etc.). Based on my limited experience consulting for nonprofit foundations, my understanding is that donors typically want to see their funds mapped directly to the organization’s social outputs; conveying the need to invest in other areas is a complex message. IGG circumvents this challenge by having the technology be the vehicle through which social output (and thus impact) is delivered. It’s a truly brilliant alignment that will save the organization fundraising headaches going forward, and I imagine many new nonprofits with similar alignments could emerge. It will be interesting to see if the digital era will shift the types of value capture challenges nonprofits face going forward.

On February 2, 2017, So Many Cranberries commented on Netflix: Winning in 21st Century Media :

Thank you for the post on a company that’s survived a digital transformation itself. The point around curating original content is going to become even more important going forward. Much like Netflix, Amazon Prime can offer on-demand content for the OTT crowd and has expertise in building recommender algorithms; the only way for Netflix to differentiate is to have content Prime doesn’t have.

On a related note, I’m curious to see how the competition between Prime and Netflix plays out. I’d lean in the direction of saying that Prime has a stronger value proposition since it is packaged with free 2-day shipping on Amazon purchases. When I think about my purchasing decisions, however, I purchased both and never really thought of it as a choice; Prime is my package delivery service that happens to come with streaming content while Netflix is my streaming content service.