August 9, 2016 | Written by: Oystein Haaland
Categorized: Blog | Environment | Manufacturing
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Savvy leaders already understand that the Internet of Things will radically reshape the way we do business in the years to come. But the extent of this transformation can’t be overstated. According to a McKinsey report, IoT brings with it a total potential economic impact of $3.9T to $11.1T by 2025. Nowhere will this impact be felt as significantly as the energy sector, where the economic impact of connected devices and analytics may reach $930B from mining, oil and gas companies in the next ten years*. Companies who figure out ways to extract insights from more of their IoT data, and to separate valuable data from noise, are poised to reap the greatest economic benefits of IoT, while stragglers risk losing out to competitors.
But unlocking the value of IoT is easier said than done in a complex industry like energy. Though sensors have become inexpensive and are widely used, the sheer volume of data being produced has become unwieldy. Massive amounts of data are being created at the edge of the network:
- Utility companies may process 1.1 billion data points per day
- A large refinery generates 1TB of raw data per day
- A single large offshore oil rig can produce terabytes of data daily*
The challenge for businesses is how to get the insights they need from data despite the fact that their equipment may be operating remotely – with an intermittent network connection or in a location where bandwidth costs may be prohibit transmitting sensor data to the cloud.
IoT data challenges on a single oil rig
A recent McKinsey report looked at IoT data on a single oil rig, and the findings were startling. As little as 1% of the data generated was ever used for decision making. The rest seems to disappear into a sort of “data black hole.” So where is the other 99% of data going?
Where is 99% of the data going?
Most of the missing data is lost right at the point of collection. Because of this, data can’t traditionally be managed or analyzed in real time.
Unfortunately, existing solutions fall short of meeting these data challenges. On-premise IoT solutions are often expensive to implement and, for businesses running remote operations, may require IT skills in remote locations. They also create data silos; in the age of IoT, a business needs to be able to analyze data across all of their hundreds of rigs. Alternately, implementing cloud-only IoT solutions can be an equally tough sell for businesses with remote operations. The cloud can give you visibility across all of your assets and sites, but the cost of transmitting data centrally for analysis can quickly become prohibitively expensive.
What’s needed is a breakthrough new approach – one that brings the analytics to the data, rather than the other way around.
Analytics at the edge: A new hybrid approach to IoT
IBM and Cisco have teamed up to provide real-time IoT insight at the edge of the network, providing businesses in remote locations with the ability to tap the combined power of IBM’s Watson IoT and business analytics technologies and Cisco’s edge analytics capabilities. Now businesses to more deeply understand and act on critical data on the network edge. This first-of-its-kind solution offers a new way to produce immediate, actionable insight at the point of data collection. It’s a breakthrough approach, designed to help companies operating on the edge of computer networks such as oil rigs, factories, shipping companies and mines, where time is of the essence but bandwidth is often lacking.
This new capability — enabling businesses to perform analytics where they make the biggest impact — will allow businesses running remote and autonomous operations, and those managing fleets of assets, to truly tap the value of their connected devices.
The economic impact
Benefits for the energy industry
Critical business operations in the oil and gas industry, can’t afford to shut down when a network connection is lost, They often can’t afford the extra time it takes to send data to the cloud and back. Analytics at the edge will enable these businesses to run business analytics instantly at the edge, while data flagged as high-value can be transmitted to the cloud to be analyzed by the cognitive Watson IoT Platform in the cloud, strengthening overall analytical performance and insight.
Remote operations — such as an oil platform in the middle of the North Sea or in the Gulf of Mexico or a mine deep underground — can now evaluate their remote sites for hazards, triggering action based on safe operating directives at the edge. External conditions such as weather can be monitored, triggering mitigation plans. And asset performance can be evaluated at the point of monitoring, driving corrective action and reducing wasted work.
Companies managing fleets of assets, whether trucks, tankers or oil rigs, will now be able to monitor geographically dispersed assets by choosing precisely what data is best analyzed at the edge and what should be transmitted centrally.
With this first-of-its-kind hybrid offering, IBM and Cisco have taken a very important first step on the path toward helping businesses across the energy industry harness the value of IoT, at the edge, in the cloud or wherever their needs demand.
Want to learn more?
Visit our edge website to watch a replay of the groundbreaking announcement, view our infographic, hear client voices and more.
- McKinsey https://www.mckinsey.de/sites/mck_files/file/unlocking_the_potential_of_the_internet_of_things_full_report.pdf
- Source: Cisco Consulting Services Global IoT Study, 2014