All objects of our daily life become connected: our car, house, oven, stove, washing machine, bike, tv, we can also be through a connected bracelet! All these sensors generate a titanic volume of data that doubles each year. These are similar to the new oil of the 21st Century.
How, then, do companies succeed in acquiring such a deposit? How to transform this data into “Smart Data”? What is the impact on his business model? And what are the risks?
I begin this year with a series of reflections and sharing of experiences on this theme, starting naturally with the first issue: How to acquire a huge amount of data called “Big Data”?
Companies with these Big Data will be given a considerable competitive advantage, provided that they are then able to value them. This phenomenon affects all areas, from targeted advertising to Industry 4.0 through personalized medicine and precision agriculture.
So what strategies can be put in place to create such a pool of data? Let’s take three examples of areas, health, online advertising and mobility.
1. Build a global biobank of genomes
The medicine will be transformed by the actors who will arrive at obtaining this Big Data. In fact, to offer a predictive medicine and subsequently a preventive medicine, the industry needs to train these algorithms with a considerable amount of data. Many players are tackling this market with different strategies, here are two examples:
- To aggregate the data collected by the hospitals – University hospitals are voluntary biobanks for patients. By developing partnerships with hospitals, it is possible to concentrate a large amount of data. To obtain this data, storage solutions, secure data sharing and analysis of genome sequencing results are offered to hospitals.
- To offer a service for which the customer must provide his/her data – For US$99, the startup 23andme offers you to know your origins over the past 200 years. We can thus discover that our origins are for example, mostly Swedish and Danish, but that we have Italian descendants. As early as this year, we can also get information such as the risk of having a genetic disease such as Parkinson’s or his predisposition to be leaner or larger than average. The process is very simple, just order a kit in which is a specimen. We put some saliva in it and we send it back. At most two months later, we have the results online. By offering this service, 23andme has already collected more than a million genomes.
2. Know all our actions on the internet
As a second perspective, let’s look at a more mature area, that of advertising with the case of Google. Its business model is data-centric, with more than 80% of its revenue being generated by monetizing its Big Data through the sale of targeted online advertising. How did they go to access this Big Data?
Access to the data flow on our computers: Google introduced the free Chrome browser in 2008. The following graph shows the evolution of the market shares of different browsers: in 10 years, Google Chrome has captured almost 80% of the market.
Access to the data flow on our mobiles: Google bought the Android start-up in 2007 and its operating system is currently used on more than 80% of smartphones.
3. Capturing the data of the mobility of the future
Cars are all connected to their environment and they send back data continuously. Multiple applications will emerge: for example, if we get information on the triggering wipers of a large number of cars, we would be able to map in real time the position and movement of thunderstorms.
Three examples of strategies to access this Big Data:
- Google (again!) Wants to get into our cars and offers Androidauto , which, in the same way as with Chrome or Android, will allow it to capture our data.
- Tesla offers a connected and increasingly autonomous vehicle that integrates its own operating system. Tesla understands that it must keep control of the data produced by these vehicles.
- Offer an innovative mobility service based on a platform that collects all mobility information. This is the strategy adopted by companies like Uber or Lyft. Uber already offers this anonymized data, Uber Movement, to improve urban planning.
In conclusion, these three sectors are just as examples, but the challenge of successfully accumulating Big Data is present in all areas. There are many data acquisition strategies, but as the online advertising industry shows, companies that anticipate this trend will find themselves in a favorable position. There may also be a second question: Is a highly polarized distribution of Big Data likely to create economic and societal imbalances?