Buying a film studio is an interesting move for Hasbro, but it’s a huge investment in an increasingly competitive space. It’s no secret that the only films succeeding are high-budget tentpoles, like the Marvel superhero films or Transformers, but it takes a long time and significant upfront capital to create one of these films. Even then, many of the Transformers films weren’t as successful as they had hoped. I imagine that there will be some fatigue in the near future for these types of films. It’s a risky bet for Hasbro to sell toys. I wonder if they could pursue other channels to engage audiences, such as YouTube. Younger generations are more likely to watch YouTube for short-form video content, and Hasbro could engage influencers or create their own content (e.g. web series, etc) based on their IP. There have also been huge communities built around activities that fit in well with Hasbro’s brand — unwrapping packages/toys, creating homemade slime — which seem like perfect opportunities for Hasbro to leverage for growth.
To ensure sustainable change and improvements, the NYC government must also attract top talent with expertise in digital innovation. These people tend to flock towards organizations where they can make meaningful impact and observe the results quickly. Speed and results are not necessarily two words that the tech world tends to associate with bureaucratic government agencies. In addition, working at a government agency tends to be far less lucrative than joining some early-stage start-up or even a tech giant. I hope that the NYC government is also considering how they can better attract top talent to their organizations. Without redefining the way that they work, it will be an even greater challenge to push the city’s digital progress much further ahead.
I agree that Disney is one of the few legacy media companies well-positioned to actually compete with Netflix and Hulu in offering direct-to-consumer offerings. Netflix continues to spend exorbitant amounts (reportedly up to $8 billion this year) on content, but since they first launched their streaming service, they have made only minimal improvements to the user experience. They derive most of their power now from their ability to attract and pay high-profile talent (for example, luring Shonda Rhimes from ABC and Ryan Murphy from FOX), with the process of complete artistic license. Their streaming service was novel for its UX at the time, but they’ve barely invested much into it since. In addition, there has been slight pushback recently as content creators prefer to go to traditional distribution channels because they don’t want their content lost Netflix’s endless library — they want more control over the way that people watch it (e.g. in a theater). Disney has an opportunity to compete by vastly improving the UX, since it is already embedded into their culture, as Laura noted.
In another example of how Spotify is cleverly using data, they recently announced the feature “Line-In,” which crowdsources data on the music library. It asks users to confirm and/or edit tags used to bucket songs, on everything from genre, languages, mood, to explicitness. This tool brings together our modules on crowdsourcing and data in a unique way. By leveraging the crowd, Spotify accesses more data and gains a better understanding of how their users are interacting with the platform and with music. This could offer a huge leg up against other music streaming services, such as Apple or Pandora.
I absolutely agree that organizations need to be very careful with how they are designing machine-learning algorithms, in order to remove inherent biases and to avoid a Tay situation. It’s something very top of mind with the self-driving cars movement and two recent accidents (one with Uber in Arizona and one in a Tesla in California), since the vehicles need to be programmed to make decisions. This issue is raised via MIT’s Moral Machine, which asks people to evaluate moral decisions made by machine intelligence. For example, one of the dilemmas posed is how a driverless car should react in a situation that kills either two passengers or five pedestrians. It’s a tough question to answer, but important for reminding us that people are still behind the data input into these situations to make the decisions.
I wonder if data “footprints” like the ones Laurie captures via the app will become a key source of identification in the future. Your post also highlights the importance and power of data visualization to draw insights from the data. As we’ve learned in class, the data itself isn’t enough on its own, but requires someone to contextualize it. One of the dangers of the app, however, is that people may try to self-diagnose without fully understanding how to correctly or effectively interpret the data. This reminds me a bit of companies like 23andMe that offer genetic testing to individuals that can easily be misconstrued. In addition, I wonder if Laurie has been approached by companies interested in the data she is collecting from users of the app.
Reddit conducted a fascinating “experiment” to create a microcosm of the internet to see how users would behave (link below). They set up a blank page of pixels whose color could be changed by users, but users could only change them once per every five minutes (in order to prevent one person from taking over within seconds). Users gravitated into groups to “wage war” against each other (e.g. turning the page red versus blue), but in the end most of the work of trolls was wiped out by other users. In the New Yorker article below, there was an interesting story as well of how users reacted negatively when the founder unilaterally closed toxic accounts. It does beg the question of how much regulation should happen (or even needs to happen, in the case of the pixel experiment) to create a safe but totally open environment.
This is so interesting, I’ve used Duolingo and I had no idea that they were also monetizing the translation content. Another challenge is that I wonder if Duolingo will hit a ceiling in the level or style of language that they can have translated by users. One of the things I appreciated about the app as a user is that the text and phrases seemed very applicable to content I would need as a tourist or beginner-level speaker. If they are working with companies like Buzzfeed, I wonder if it would feel forced to the user to have those types of phrases appear in lessons.
Another interesting part of the story is that GE partnered with Quirky at the peak of the start-up’s trajectory. GE opened their dormant IP library up to the crowdsourcing platform, in the hopes that Quirky’s inventors and audiences might create interesting products in the internet of things space. However, the quality issue really was key here, and GE’s bet on Quirky didn’t pay off. Continuing the story you posted above, many of the “Wink” line of IOT products had bugs and were poorly made, even with GE’s involvement. On one hand, I laud GE for taking that risk; in the long-run their reputation has not been hurt much. On the other hand, I wonder if the demands of this partnership may have pushed Quirky to the brink even earlier.
One potential criticism I have for ZocDoc is that it lowers patient switching costs across doctors, which can create a negative experience in the long run. It definitely addresses the pain point of long wait times to reach doctors, but patients who only select doctors based on availability and convenience may jump around among providers, to the detriment of sustained and consistent care. I found myself jumping around among dentists to accommodate my schedule but it led to a worse overall experience because I had no continuity of care.
The League is an interesting entrant into the dating app space. I absolutely agree with your points that it strikes a delicate balance — on one hand, branding itself as more exclusive and carefully curated than Tinder, but on the other, it can’t be so elitist that it misses out on tapping into network effects. Dating apps are tricky because their incentives are at odds with those of the user — a successful match means users no longer need the app, whereas the apps want to keep as many active users as possible. In terms of the newer entrants, Bumble actually addresses a pain point (starting and maintaining conversations) and differentiates itself the best, whereas The League is not so differentiated from The Hinge or Tinder. Perhaps The League can also offer recommendations on local date spots (and even offer a concierge service to access exclusive spots) to encourage stickiness and to better differentiate itself, while sticking to its exclusive brand.
My concern for Strava is that if they focus on engaging just their existing user base, their attrition will eventually outpace their growth to begin their decline. If they can’t bring on new users, their data won’t be as compelling of an offering to governments and urban planners. Many of the companies in this space have expanded into wearables to ensure seamless tracking. It makes sense that Strava would not have the capacity to develop into this area, but pushing into a recommendations service does not seem that inspired, especially with the number of big players in that space.
Interesting! I had never heard of Planet before or thought that companies would be moving into this space, though now it seems to be the very logical next step to Google mapping out the world on the terrestrial plane. It raises questions about the ethics of the business. For example, what responsibility should Planet have to escalate or to report things they observe to the government or regulatory bodies, outside of their contracts? As they bring on new clients, especially across different industries, there may be conflicts of interest that they must address. I wonder whether the founders have thought about this; Google must have had similar conversations when beginning to map out the world, so perhaps Planet could learn from them.
Interesting post on Mattel. I wonder if a solution for them might be to focus on developing their own brands and content. It sounds like they are relying heavily on licensing franchise IP, but one of their most successful and proprietary brands has been Barbie. Especially given the increased need for storytelling and better branding across platforms, that you pointed out, perhaps the best way for them to survive is to expand their portfolio away from other companies’ IP (e.g. Disney). This could also offer new ways of approaching digital marketing, which is extremely regulated in the children’s space.
Xiaomi’s rise is remarkable. It seems like Xiaomi has been able to carve out a space for itself through great branding and marketing, not necessarily a very differentiated product. An advantage they had was entering the market later and being able to integrate e-commerce and social media into their strategies from the outset. I wonder if incumbents can learn anything from Xiaomi, and whether it’s too late for them to leverage earned media in the same way. Similarly, I imagine it’s too difficult for the incumbents to extract themselves from the relationships that they have built up over the years. It will be very interesting to follow Xiaomi’s trajectory from here.