What is common among BMW, JohnDeere, & GE? These are the companies, who are investing heavily in gathering sensor data, which provides valuable information when processed with the help of predictive analytics; it could be leveraged to operate and manage the machines in an optimal way.
While BMW is embedding test cars with sensors, which send valuable real-time information to plant floor so that the company can act upon the data and make changes accordingly, JohnDeere is doing the same with its tractors and other machinery to optimize the running conditions of its machines. GE, which has acquired in-depth knowledge in data gathering and analytical business, is planning to offer value-added services to its customers.
Bill Jacobs, director of product marketing at Revolution Analytics, says “I think the Internet of Things in manufacturing will be ubiquitous in just a few years. The realities of the supply chain will demand it.”
Extending support to the above statement, Forrester analyst Michele Goetz says, “The holy grail of predictive analytics in manufacturing is the “just in time” supply chain.”
However, to accomplish all the above, we need free movement of data across geographies. At the time of writing this blog, both US and Europe are focusing on regulating the movement of data; particularly Germany, which has decided and enforced a regulation that inhibits the full potential of the speed of the data.
In summary, we are seeing a clash between two different domains here; security and engineering. While engineering needs free movement of data across geographies, security of a nation demands restrictions to be enforced when it comes to data movement.
This blog recommends a middle path; why not we categorize the data into sensitive [as per all countries satisfaction] and insensitive and use the insensitive data for engineering purpose.
Any better thoughts?