When machines talk...
One of the major themes at the recent Mobile World Congress in Barcelona and CeBIT conference in Hannover, Germany was machine to machine communication. This is sometimes known as the Internet of Things and involves sensors communicating to databases.
Producing and collecting all this data seems to be the easy part. The real issue is what do you do with it? If you own 100,000 soda machines and the machine is smart enough to tell you at the current rate of consumption, it's going to need refilling in 10 hours, or that it had been vandalized and needs to be repaired, this is valuable information. And if it could tell you that it appears that in the next 24 hours it's going to need a new part, all of this information could be incredibly useful.
If you could anticipate the service needs of the machines before an incident happens that brings it off line, that could be very powerful -- if you could find the data.
The trouble is that when you have 100,000 machines yacking at your database, figuring out the key information you need to know from the noise might not always be easy to do.
Jurgen Hase, vice president at M2MCC at Deutsche Telecom told me at the CeBIT Conference in Hannover, Germany last week that he he sees machine to machine communication as a growing trend in the coming years.
He says these types of scenarios in the enterprise could be complicated by the fact that IT might not let machines from another company tie into the IT infrastructure to communicate the information back to the mothership. That means you have to build in ways for the sensors to communicate independently and Hase expected we will see this more and more.
The copy machine will transmit billing codes, usage numbers, maintenance needs and so forth. He sees the service implications of this kind of data going back and forth to be huge. You can start out small with a couple of metrics and add new ones over time building a bigger and bigger database of information.
He says the idea is to use this data to learn about other services you can offer, ones you might not have thought of prior to collecting all this data.
Hase says the analytics layer is the next step and building up a global view to generate neutral information.
He believes this ability to monitor, collect an understand data could lead to whole new industries and whole new ways of doing business, because when machines talk, big data happens, and if you can process that data and understand your customers needs before something breaks, it could be a powerful differentiator in the future.
Photo Credit: CanStockPhoto
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