Internet of Things (IoT)
Previously, the Internet had been dependent on people for its supply of information. But now impersonal “things” can themselves generate and receive data.
Now things are connected and can communicate with each other. Billions of devices, including laptops, PCs, and especially smartphones, generate trillions of data points.
Connecting devices to automated analytical systems makes it possible to gather information, analyze it, and create a response without human intervention.
Now every “thing” can have a chip inserted to communicate data to other devices. A “thing” could be a hairbrush, a home thermostat, a shirt or dress, a toaster, a refrigerator, a fitness collar for your dog, or a baby thermometer.
In business, countless tiny sensors can be woven into things as large as a jet engine or a railroad locomotive or a factory machine, all of which are transmitting data via the Internet.
Each of these dumb items can become smart, with capability for two-way communication. For example, in a “smart” home, keyless door locks send a text message when activated and containers holding medications “note” whether a patient has taken prescribed pills and send an email or text message reminder.
The IoT also enabled the latest innovation in digital organizing, which is a new platform-based form of organization. Siemens wind energyOpens in new window business provides an illustration.
|IN PRACTICE | Siemens Gamesa|
|Siemens Gamesa, a leader in renewable energy industry, maintains the industry’s largest amount of historical data in a database growing daily with data collected from over 10,000 wind turbines worldwide. Inside each smart turbine are hundreds of sensors that continuously transmit more than 200 GB of data per day to a state-of-the-art diagnostic center in Denmark. At this center, advanced analytics and 24/7 human monitoring convert raw data into valuable insights.|
Siemens Gamesa uses data analytics techniques and experienced personnel to “see” what is happening inside the wind turbines and to understand why it is happening. These data enable Siemens personnel to prevent unscheduled breakdowns. Around 130 analytics experts check data on factors such as vibration diagnostics indicative of potential damage, wind direction, weather, service reports, and the performance of similar models, to determine when and how a turbine should be serviced days, weeks, or months in advance. The predictive capability reduces unplanned maintenance and downtime, adding weeks of profitable production and months to the life of the turbine.
Also in this series include:
- Richard L. Daft and Norman B. Macintosh, “The Nature and Use of Formal Control Systems for Management Control and Strategy Implementation,” Journal of Management 10 (1984), 43 – 66