You’ve probably heard about the Internet of Things. It’s this concept that devices connected to the Internet can stream data back and forth, essentially communicating with each other to make decisions or send notifications without human intervention.
I’ve seen a lot of articles lately about how this works, including details on IP addresses and protocols for creating applications and services that allow all of our things to interact with each other via the Internet.
You might have read similar articles and thought “So what? Now my toaster talks to my car and my iron talks to my smart phone? How does that help me?”
What’s driving this trend? And why should we pay attention? As usual, the value for businesses is not just in understanding how this works, but in paying attention to why it’s happening.
The standard examples for why you should care about the Internet of Things have focused on automation, connection and service:
- Your iron knows to turn off automatically if you’ve left home in a hurry.
- Your car knows when it needs an oil change and reminds you to schedule regular maintenance.
- Your air conditioner knows to cut back when energy use reaches a certain threshold for the day.
All three of these examples are basic alerts and simple reactions. They’re useful, and they’ll provide a lot of functionality, but they’re not the most exciting part of the Internet of Things. To get to the interesting stuff, let’s recall this chart I’ve used for years that shows two main categories of analytics capabilities.
Remember this? It compares reactive analytics capabilities with the more advanced, proactive applications on the right. So, let’s ask ourselves, how do we add predictive capabilities to the Internet of Things?
And this is where things start to get interesting.
Our connected devices are all sending streams of data through the network. Whether it’s a car or a pacemaker, the data is flowing in a constant stream from the device to the network, and sometimes back to the device.
It’s a lot of data. But when you can apply predictive models to that steady stream of data, the models know to look for patterns or anomalies in the data. This means they can predict things like potential auto accidents, impending heart attacks or imminent oil spills, so you can take action to prevent them from happening.
See, that’s interesting. Now, extend these examples into your world, and you can see how understanding the activities and interactions between devices might help you better understand your business processes and your customers.
Once you understand the true potential, you know not to roll your eyes the next time you hear someone talking about the Internet of things. Although, you do have my permission to squirm when you see the acronym IoT ... or maybe that's just me.