Big Data, Infinite M2M possibilities
Thursday, 14 February 2013
M2M is often associated to a better management. Certainly, it is the most visible feature of Machine-To-Machine technology. It is easy to see how someone can monitor the power consumption sent by a Smart Meter thanks to a smartphone app or how the HQ of a transport company organizes its fleet thanks to the M2M technology, just to mention two of many other examples.
However, business is not only about management, but also about planning and what and where to focus on. To do this right, it is necessary to use information. All the data provided in real time, coming from every M2M device form a huge collection of information that a company can take advantage of.
For companies, this advantage translates into a significant return of investment. If the devices can report how a certain machine or process works at any moment, companies can save time and money, as workers don’t have to check everything manually and periodically but only where and when it is really needed. This represents a significant improvement for industrial processes, especially if the machines are located far away from each other.
Thanks to the information collected, companies can also make better decisions when it comes to investing in machines, vehicles or any other process in which devices are involved. CIOs are beginning to trust on all these possibilities and companies such as Ford recognize them.
Another recent example on how the intelligent use of big data improve a company’s profitability is the model of insurance based on data collection through M2M technology, which allows companies to adjust premiums individually depending on the driver’s performance. It is innovative for the clients as it adapts to their needs, and it is innovative for the insurance company because with the big amount of data provided they can plan better their offer.
Big data and M2M are predestined to work together, generating a very successful relationship. If the data is big, the M2M possibilities are infinite.