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3 Internet of Things examples from 3 industries
Real-world IoT implementations achieving results today
By Alison Bolen, SAS Insights Editor
Is the Internet of Things merely a far-fetched consumer fantasy that promises the convenience of connected appliances and smart running shoes? Or is it a business opportunity for companies that want to collect real-time information about almost every aspect of their business?
We tend to hear a lot about the consumer applications of IoT, but many early adopters in the IoT revolution have been businesses and government organizations with an interest in collecting and analyzing data about their operations. From the temperature of equipment to the performance of a fleet of wind turbines, IoT sensors are already delivering valuable information in many industries. Blue Hill Research recently conducted an in-depth qualitative research report about three Internet of Things examples, which we've summarized in this article.
Internet of Things examples from government, utilities and manufacturing
Consider these three Internet of Things examples:
- A US municipality has implemented smart meter monitoring for all the town’s residential and commercial water meters. The project involved placing water meter sensors on 66,000 devices that used to be manually read and recorded.
- A US oil and gas company is optimizing oilfield production with the Internet of Things. In this IoT example, the company is using sensors to measure oil extraction rates, temperatures, well pressure and more for 21,000 wells.
- An international truck manufacturer created a new revenue stream by outfitting trucks with sensors for predictive maintenance. The system automatically schedules repairs when needed, and orders the required parts for the repair. More than 100,000 trucks have been outfitted with devices that transmit more than 10,000 data points a day for each truck.
As you can see in the table below, the data streams for each of these applications create more than a million data points per day.
Table 1: Case Summaries. Source: Blue Hill Research, September 2015
The ROI of IoT
How are these three companies converting raw IoT data into business insights and tangible benefits? They’re using analytics to realize both direct and opportunity costs associated with analyzing IoT data.
The US municipality that switched to smart meters for its water usage monitoring saw immediate and sustained savings. Its data collection process evolved from a manually intensive process (in which field technicians traveled to every meter) to one where meter readings were automatically recorded and transmitted to a central database. This saves a lot of money, both in work-hours and in field equipment, such as trucks. The town is projecting a total savings of $28 million and a net savings of approximately $10 million over the lifetime of the initiative.
The indirect savings came when the organization was able to make a fundamental shift to a proactive service-oriented organization. Now the town can identify issues within hours, rather than weeks or months. With better and more accurate data, the town proactively reaches out to households to mitigate overuse or unexpected fees. The billing and management teams have shifted from an internal reporting organization to a customer-facing hub that provides residents a markedly better experience.
Likewise, the oil and gas company is able to monitor the performance of oil wells at the end of every day or week. This allows it to identify opportunities for improvement (such as increasing production levels) and areas of potential concern. Ultimately, the company can take this information and disseminate it to field crews to make adjustments or repairs. The result is reduced downtime and increased production levels. The company estimates that it loses $500 for every hour that a single oil well is not in operation. After analyzing the initial impacts of sensor deployment, the organization estimates that quicker oil well repairs saves approximately $145,000 in cost avoidance per month per field.
The international truck manufacturer provides a mature example of using sensor data. Sensors in the trucks, combined with predictive models, detect when a mechanical failure is likely to occur. When this happens, the system schedules a maintenance appointment for the truck based on the truck’s route and optimized for scheduled delivery times. Further, the system orders and ships the appropriate parts to the identified service center, and then notifies technicians about what needs to be fixed. The result is an interconnected web of sensors and operational systems that communicate to save time and money across the operation.
In each of these cases, bringing the Internet of Things and industrial-grade analytics together yielded significant and persistent business enhancements. The key to extracting sustained business value from IoT initiatives is, ultimately, sound business analytics practices.