Very interesting! I wrote my post about Siemens which uses sensors and data analytics in its wind turbine business to detect major defects before they happen to prevent severe damage. Fasciniting to see that an identical approach can be applied to “human capital” as well. I wonder if similar technology is soon picked up by non-professional athletes, too. This would definetely expand the market for Catapult!
Visualization of data is certainly very important for people to make sense of the data they have. At least in my experience, it is definetely a gap in many companies. I am wondering whether Tableau could expand its business model by offering their customers consulting services around data analytics and visualization or employee training on how to make the best use of their software. This might by one way to set the company apart from its competition and create a more loyal installed base. Thanks for the blog post!
Very interesting! I can very well imagine that certain skills can be tested by playing relatively simple games. However, I am a bit more skeptical when it comes to “emotional intelligence”. I would like to believe that assessing skills such as empathy still requires some human interaction. But maybe they could complement their games with data measured with webcams about emotions expressed. Thanks!
Henkel, a European CPG company, did not follow your advice when they received some creative suggestions for their crowdsourced design of a detergent bottle. Instead they announced that there was a “mistake” in counting the votes and that some of the more controversial but previously successful suggestions had in fact received fewer votes than indicated. The backlash in social networks was enormous. It would probably have been much better to just “pull the plug”.
Great post! I have been using Kiva for years and keep on going back although it has some flaws as you pointed out.
An intersting aspect of Kiva in the context of crowdsourcing is that they “outsource” a range of tasks to the community. For example, translations of loan applications are often done by community members as well.
One explanation that I have read might be that the microfinance institutions that Kiva is partnering with “pay back” the loans to Kiva if their lenders default in order to keep access to Kiva’s borrowers.
Great post – thanks!
Interestingly, the vast success of crowdsourcing reviews in this industry has brought new challenges (and opportunities) to hotel managers. How can you track and react to thousands of reviews on a range of websites? Some start-ups (for example: http://www.trustyou.com) have capitalized on this by using software to semantically analyze and aggregate all the reviews’ text and not just generic star ratings on a few categories.
Very interesting, thank you! It still seems a bit strange to me to shop for a house on my smartphone but the fact that they hire their own real-estate agents and change their incentive scheme should make it more trustworthy in my opinion. It is an interesting contrast to Uber and likewise platforms that simply connect both sides and don’t employ service providers themselves. The “old-fashioned” employment model is certainly a safe way to avoid multi-homing by agents. Do you think it decreases the value for independent agents as they might fear that Redfin is somehow favoring their own agents?
Thanks for the post! I did not know that Duolingo captures value by “employing” users for translation services – that is brilliant!
I have not tried Duolingo myself but have used competitor Babbel instead. They are harnessing direct network effects by encouraging users to interact and help each other progress. For example, someone who is a native speaker in English and wants to learn Spanish is paired up with a native Spanish speaker who wants to learn English. Does Duolingo try to do something similar?
Very insightful, thanks Jeff!
I love the “Mix of the Week” playlist that Spotify introduced recently curating a playlist based on the songs I listened to during the previous week. It is quite impressive to me how accurately it matches my taste. This recommendation engine is another example how direct network effects work for Spotify: the more user on the platform the better it can recommend new artists and tracks based on what other people with similar tastes listen to.
Interesting read David!
As further evidence of Otto’s digital transformation the company is trying to establish an open platform for e-commerce. It lets third-party developers create and publish apps to enhance the online shopping experience. Otto named the initiave “project collins” as a reference to management guru Jim Collins and his book “built to last”. Time will tell if they are right…
Interesting read Fridtjof!
I haven’t used Waze yet – do you know if it also includes information on available public parking space? This would be a great contribution to alleviate urban traffic as around 30% of congestion is caused by drivers looking for a parking space. Some apps allowed users to “sell” public parking spots but have had problems with regulation – and I think rightly so (http://techcrunch.com/2014/06/23/parking-apps/). It seems like Waze users contribute without monetary incentives. It would be great if it worked with parking as well.
Very interesting Angela!
A friend’s start-up, Soma Analytics (www.soma-analytics.de/), has developed an app for HR departments to monitor the wellbeing of employees. This seems like an interesting application of Cogito’s software. Similar to the application in mental health treatment you described, it could gather data during phone calls to prevent burn-out for example.
Hi Erika, thanks for your post!
Affectiva already analyzed viewers emotional reactions to the election debate between Obama and Romney in 2012. Here is the paper Affectiva published about their findings: