Thanks for the comments! We’re definitely starting to see it happen. SAP recently introduced a tennis analytics solution and some tennis coaches (incl. Linday Davenport) swear by the potential of data to improve performance especially in combination with on-court coaching.
I am optimistic that as long as sophisticated analytics is widely available, a player’s ability to easily uncover the weaknesses of his opponent will be balanced by increased ability of other players to identify and overcome their own weaknesses. This will hopefully lead to even more exciting games with fewer unforced errors and a wider group of players able to challenge the very top.
I agree that TrueCar’s service alone doesn’t address the lemons issue but it goes a long way in providing a baseline price for a negotiation between a buyer and a seller which alone is a valuable service.
A lot of people (myself included) would have no idea about a reasonable price for a second hand car with a certain set of attributes which brings a lot of potential for getting taken advantage of by a seller or a dealer. While I may still end up overpaying for a lemon after research a car on TrueCar I would have more confidence people won’t laugh at what I paid for a car.
There’s not doubt this is an impressive company with an incredible valuation ($10m per employee) but I have a couple of concerns about their model.
First, it’s clear that introducing new systems in a business does not alone drive business value. Once the systems are introduced it is in the hands of the clients to prove the new tools are working. If companies systematically lack capability to generate value from the systems introduced by Palantir this will put the value of Palantir’s services questions and may stand in the way of repeat customers.
Second, Palantir’s valuation is a clear indication investors expect the company to grow rapidly. This puts into question both Palantir’s requirement for CEO backing of projects as well as its ability to attract top engineering talent, especially if some of the excitement of new solutions gives way to the more mundane work of porting previous solutions to new clients.
With dunnhumby holding customer data for more than a billion customers it seemed a bit surprising at first that limiting access to data from two of its accounts would make such a huge dent to the perceived value of the company especially if we consider that part of the $700m bids may be paying for dunnhumby’s data analytics capabilities (at the time of Tesco’s rise these were considered cutting edge – maybe dunnhumby missed the train since then?). On second thought the value of customer accounts must vary widely depending on how rich the individual data is (someone’s email vs. someone’s grocery shopping history since 1989) and it’s plausible that the Tesco and Kroger datasets that dunnhumby is losing account for a major chunk of the truly valuable customer accounts leaving a large number of accounts behind that have little potential to make money for anyone.
I would love to understand more about how sophisticated investors think about the value of companies with large customer data assets!
Thanks for the post! Medium is clearly doing a great job at attracting people to publish and for some original writing to bubble up. I wonder whether there is also scope for Medium to also transform the way content is curated and fed to users. I personally find the amount of relevant content that is getting published online rather overwhelming and would really appreciate a service that would ensure my reading time is spent on the most relevant content while allowing for some experimentation and discovery.
I think the selection of places by location, price range, a few pictures, rating and a very quick swipe through the review for something one would really hate goes a long way to have a pretty good experience with little investment in research. However, I agree that Yelp could provide a much better experience if there was a way of seeing ratings/reviews from people whose ratings are similar to mine. If I were in the shoes of Yelp’s management I would think long and hard about ways of getting people to give places stars to build a better understanding of the likes of its users.
Thanks for the post Yannis! Do you have a view on why pharma companies have been unable to sufficiently diversify their research project portfolios in-house? If the new model is feasible it would appear that a company could internalize the benefits of diversification by raising sufficient capital to use multiple research funnels.
Do you think it will be feasible to raise such a large amount of money for what is essentially a new venture? I wonder whether investors if they are not able to assess the likelihood of success of different projects within the portfolio.
For individual investors, do you think there is any way crowdfunding could be used to make investors feel good about their investment in drug development and thereby reduce the returns they require? It would be awesome if this could get us closer to socially optimal level of investment (incl. the positive externalities)!
I would argue that the key risk of throwing the doors open that is on the minds of elite school administrators, alumni and students is not just changing the perception of selectivity – there is also a risk of reducing the average ‘quality’ of a member of the network which may impact the quality of the education experience and the quality of future alumni interactions.
I think that much of the value created by some platforms comes from controlling access to the platform to parties that create rather than destroy value for others. In many ways elite schools end up playing a similar role to that of sites like BeautifulPeople.com. Even platforms that are trying to build large numbers of collaborators (eg Amazon Marketplace or Uber) have to vet these to prece t compromising the experience of everyone else.
I’m very curious about the impact this will have on how garages set their prices. With differentiated (and possibly real-time) pricing, the ability to price capacity effectively may become an important source of competitive advantage in the business. This might result in major consolidation of the industry as garages aim to split the fixed cost of cutting-edge pricing systems which might in turn diminish the bargaining power of platforms like SpotHero.
I would argue that both the direct and indirect network effects for taxi platforms are local and that the scale benefits of Uber are fairly limited once a certain level of scale is reached (both locally and globally). This suggests that multiple platforms may compete within a city and make reasonable margins.
If we believe this, the strategy of getting a few cities right before moving on to new markets may be better than an aggressive expansion into new cities that will not necessarily strengthen the existing network. After all, how do people in Boston benefit from Fasten getting a new driver in Toronto?
The Guardian also deserves credit for its role in promoting data journalism (Guardian gives readers access to the datasets underlying its articles) and for educating its readers on data analysis and visualization (http://www.theguardian.com/news/series/facts-are-sacred). As we move into a world with more and more data becoming public, Guardian’s investment in its ability to tell stories from data will likely become a great asset.
John Lewis, a leading UK department store and omnichannel retailer, started charging its customers last year for its click-and-collect (order online, pick up in store) service on minor orders claiming that getting small inexpensive items into stores for free is unsustainable despite its major investments in supply chain and IT (http://www.theguardian.com/business/2015/jul/01/john-lewis-to-charge-for-click-and-collect). Walmart may have sufficient scale to make this work as part of a portfolio of channels but it will need to face the fact that the economics of different channels may vary widely and, if pricing is not differentiated, customers may start cherry-picking delivery deals.
I’m curious to see the impact of in store operations as the share of online ordering and payment increases. With shorter average time to order and pay, the balance of the process will change and drink preparation will become the clear bottleneck. Unless the current model changes customers may end up waiting awkwardly at the end of the line instead. What will Starbucks do then? Buy more espresso machines and shift staff there? Automate some of the drink preparation process? Build an inventory of skinny caramel lattes to go? Very interesting indeed!