Nice little article in the Economist about the connected car. As expected, it has some interesting points especially on how a connected car would foster a different business relationship between the car manufacturer and the car buyer. One titbit that caught my eye:
Mobile-phone operators see the connected car as yet another device to be hooked up to their networks. In America, AT&T is letting drivers of GM cars add their vehicles to their data plans, alongside their smartphones and tablets, for $10 a month. In future, which mobile network you use may affect your choice of car. In a recent poll Nielsen, a market-research firm, found that half of Americans who owned cars made since 2009 would be less likely to buy a new car if it had a different data plan from their smartphone.
Worth a read.
Both HBR (“Pushing the limits of personalization“) and the New Yorker (“Make me a match“) had related articles on the creepiness of Big Data. The part that caught my eye was from the new book Dataclysm (by Christian Rudder – founder of OkCupid):
Just from your pattern of likes on Facebook (and without relying on status updates or comments), an algorithm can determine with eighty-eight-per-cent accuracy whether you are straight or gay. Sixty per cent of the time, it can tell whether your parents were divorced before you turned twenty-one.
There’s a lot of pablum about Big Data. Most of it is either too high level (i.e. Big Data is going to save the world) or too deep (i.e. developer documentation). So it was nice coming across this article on how Hadoop actually works under the covers. It’s probably the clearest explanation I’ve ever seen.
There’s a lot of talk in enterprise clients about the “right” big data tools/platforms (e.g. Cloudera vs. Hortonworks vs. MapR etc). I think this kind of discussion misses the point. The war is not going to be won by picking the right platform/tools.
The real war in Big Data is of course for the talent. Both for engineers (who can understand the rapidly evolving software space) and for the data scientists (who can do something useful with the data). So it was not really a surprise when I saw the “whiteboard” at the Hadoop conference in California (over the last few days) full of big data jobs. (There were actually 3 such whiteboards, full of jobs.)
This is what companies should be worried about.
Interesting little article in the Economist about how McKinsey is moving into the restructuring consulting space (typically dominated by Alvarez & Marsal and Alix Partners). Although the incumbents are saying (rightly) that one needs experienced hands (and not just smart young consultants), there’s no reason why the strategy firms can’t hire experienced hires.
Yet another example of digital disruption, this time from the hotel industry. Fast Company has an article about AirBNB (“the room sharing company”) that has some interesting data, including the fact that AirBNB now is available in 99% of the countries world wide. Compare this to its nearest rivals (Intercontinental and Starwood which only covers ~50%).
In addition, AirBNB expects to offer around 1M listings by the end of 2014. Wow.
According to an article the Economist, the average American spends 4.5 hours watching TV every day. Assuming ~8 hours of sleep and ~8 hours of work, this works out to about 60% of all non-work waking hours.
The key question that comes to my mind (as a consultant): How do people have ~5 hours to spend on themselves? :)