The future ex Mrs. Kevin Branch-Elliman-Obara's Profile

Alon, thank you for bringing up these additional models. When SpotHero first started, they were making it possible for individuals to rent out their personal parking places (more like an AirBnB model) during local sporting events. SpotHero eventually moved away from this model in favor of working with more established private garages that could provide scale quickly, as well as a higher base from which to draw fees. There are a few apps that work as you have described to enable individuals to rent out their parking spots (SPOT and Veer: http://bostinno.streetwise.co/2015/04/14/boston-parking-mobile-parking-apps-in-boston-cambridge-area/), as well as apps that make it easier to find public parking (Haystack and Parker, which uses sensors underneath the payment to determine whether a given spot is available, tested here: https://www.bostonglobe.com/business/2014/07/26/new-parking-apps-pass-test/0SwGoccK3rSPdtLIzakNqJ/story.html and with pics here: http://www.betaboston.com/news/2014/07/25/can-mobile-apps-help-make-parking-in-boston-less-miserable/). Haystack, which let you offer to sell a street parking space before you leave it, or buy a space from someone else, was banned due to legal complications. Of these, Veer sounds the most potentially interesting to me because combines the functionality of SpotHero and SPOT, as well as adding turn-by-turn directions, though by listing only the top 3 spots in an area may reduce SpotHero’s highest value to users, which is the ability to scan many garages and discriminate based on price.

Emilie, thank you for the exciting post! KMY and Angela, your comments on how the data will be used/advertised are important points to consider. While I believe that the tone of Flatiron’s messaging is as Emilie has described, I wonder if the goal isn’t perhaps more sinister. This platform seems like an excellent way, for example, for Guardant Health to lock up customers, which is a good thing for society only so long as their diagnostics remain best in class (likely a brief window, given the pace of development in this area and ironic, given the position of Sloan Kettering and Mt. Sinai Ichan). I see Flatiron as a valuable platform in this area, but I worry that their connections to customers could be co-opted by partners in ways that are not going to be beneficial to patients in the long term.

Back in the mid-2000’s an ex-boyfriend of mine sold his WoW account for tens of thousands of dollars to someone who wanted to skip to the level he had achieved. I was frankly flabbergasted to learn that this was a fairly common occurrence, but if the game is not fun to play in the early stages, then I suppose there is really no benefit to customers by offering it initially for free. While I do not have specific information on the recent expansion packs, I wonder if WoW’s issues aren’t more mundane than dwindling network effects. Is it possible that people have just moved on from this gaming trend? We sometimes talk about planned obsolescence as a strategy for hardware, but we never seem to discuss how software products should anticipate their own irrelevance over time, even though it seems a near certainty.

Very interesting post about the potential for integrated software to disrupt even the most highly regulated regulated sectors of the economy, and especially education within the not-for-profit sector. With regard to the comments above, I wonder who holds the power in this network. Is Clever likely to be subject to the whims of the fragmented school budgeting process? Or will a move into data analytics (hinted in Jenny’s comment) make it possible for them to withstand political change?

Damla, thanks for writing about this interesting company! M2M is a fascinating sector, and I believe that many venture capitalists who are generally well-versed in asset-light tech companies will have a hard time navigating this world of interconnected hardware.

Ola, your points are well taken. From the post, it is not clear that their proprietary hardware would be difficult to reverse engineer, but it seems likely that their early mover status and resulting access to data may give them an advantage compared to later adopters. I am reminded of the energy management systems my former company developed to control the batteries we produced. While the hardware we bought was necessary to ensure accurate communication between the individual battery cells and the control systems on a number of parameters such as charge/discharge rates, voltage, and temperature, the real value added was to aggregate this information over time to refine charging protocols, improve operations, and extend battery life.

Excellent post. Terrifying concept.

Advancements such as these that reduce entire people to a list of statistics seem designed to further the interests of people who are lucky enough to have been born with means and who have never had to take any risks to succeed in life. For these people, the future seems to require a level of baseline conservatism and risk aversion that prevent real progress. For the rest of the world, this technology will likely make it easier (and more justifiable) to discriminate against already disenfranchised groups, such as people with criminal records and low credit scores.

In an increasingly connected world, I find it disturbing that so many developments in big data seem designed to diminish our humanity, rather than to help us see what we share as people.

Betterment’s system to reduce subjectivity and human bias in portfolio planning by focusing only on the numbers sounds terrific in theory. In practice, however, automated algorithms such as these make investment decisions based on such limited analyses as accretion/dilution models. Many mergers that appear to be accretive on paper (and result in fast automatic trades) turn out to be ineffectual, if not downright disastrous for the companies involved. Data aggregation and the law of large numbers would have us assume that all companies are created equal, but that is only the case if an investor is diversified broadly. Computer algorithms that pick individual stocks over others without comprehensive equity analysis remain high risk.