“For the past year, every Monday morning around 7.30, the courier service has rung my doorbell, delivering my groceries for the week. It’s so easy because we no longer have to draw up a grocery list and yet we can enjoy varied and delicious meals every day of the week.
Because of the sensors on the fridge and on most of the packaging, the grocer knows, even before we do, when we have almost run out of milk or water.
What’s more, the supplier is familiar with our taste and behavior. For example he knows that Tuesday evenings are always busy because our daughters attend music school which is why he has scheduled something that is easy and quick to prepare.
As our agendas are linked to his system he also knows that we are dining out on Thursday and that we don’t need food for that particular evening.
In spite of the fact that the average temperature rarely drops below five degrees, even in wintertime, now and then we have the odd frosty morning in the middle of winter. Today happens to be one of those days. Thankfully I no longer need to scrape the ice off my windscreen. My car can access my agenda and knows that I have a client meeting. My smartwatch has already informed my car that I effectively got up this morning and am not ill in bed. Sufficient reason to start defrosting my windscreen a few minutes before my scheduled departure. Of course I have an e-car now, but it’s not one of the latest generation “active intelligent” cars, like my neighbor has. Now that the first section of motorway has been equipped with the required sensors he could read his newspaper while driving in to work or even take a nap. Anyway, it’s no longer his car because his wife got it after the divorce. Hackers have published the driving history of thousands of drivers online. When our neighbor realized that her husband spent a lot of time at the home address of his secretary she threw him out.
No, I’m not ready for one of those self-driving cars yet but I do value the “passive intelligence” in my car. My car constantly sends information about traffic and road conditions to a central system which, in turn, informs other nearby cars of fog, delays or icy roads. And because I also opted to send data about my driving style, i.e. sudden acceleration or frenetic braking, to my insurance company I receive an interesting discount on my insurance premium. Well… “opted” and “discount” are not exactly the right words. If I hadn’t done it my premium would have simply become much more expensive. The data of our scale and fitness apps are also similarly sent to our health insurance fund’s systems. Which reminds me… I need to train another hour this week to avoid an increase of my health insurance premium…”
Obviously we are not quite at this point yet and as is the case with most predictions I’m sure that it is very wrong. That said, we cannot deny the existence of two of the technologies discussed in this post: companies must take into account the rise of “Big Data” and the “Internet of Things (IoT)”.
“The Internet of Things”
The “Internet of Things” is literally that: all kinds of “things” are connected to a network so they can efficiently exchange information. This could be to improve the product experience – like smart sensors in a car – or to pre-emptively warn you – just think of the low milk supplies or for example sensors in your car that warn you that it is due for maintenance.
On the one hand this creates opportunities but it also leads to a whole host of new threats. The opportunities lie in providing these smart things as well as creating a service model based on this information. Threats include the breach of privacy, which may give rise to a negative image and securing the data against unlawful use and hacking.
All these “things” create an enormous volume of data. On the one hand about the behavior of one specific person, on the other about the behavior of the population in general. The former can be used to supply highly personalized services if you have the right tools to analyse this data. Just think of promotions based on your purchasing history, which are already being used. In a world of smart, connected things your car will not only tell you that you need a rest after two hours of driving but also where you can find the nearest favorite fast food restaurant with a play area because it detected that your children are also on board.
Meanwhile, general data is interesting because it can be used for the forecasting and pricing of products. It can, for example, calculate the correlation between the registered G-force in a car and the accidents the driver has caused to adapt the insurance premium or driving behavior.
Here too companies will have to make sure that big data doesn’t turn into Big Brother!