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Edge computing: Putting the confidence back into decision-making

(Image credit: Image Credit: Freepik)

Connectivity has evolved rapidly, and connected devices are now a key part of both our personal and professional lives. It only takes a Google search to see the obstacles that businesses are having to overcome in a more connected world. However, there are also plenty of benefits that need to be recognised if businesses are to accelerate outcomes.

The number of connected devices has skyrocketed and with that, their capabilities are ever-increasing. Decision making is one area which has seen significant benefits, with the ability to make informed decisions in real-time seen as vital to improve operations.

Having a computer architecture which can handle rapid data transactions can greatly facilitate real-time decisioning. However, businesses fail to reap the benefits as a result of systems which are too centralised – edge computing changes all of this.

What is edge computing?

Edge computing is undeniably one of the biggest developments in the blossoming Internet of Things (IoT) sector to date. In fact, McKinsey’s top trends list reports that in many industrial sectors, particularly those with mobile and remote assets like in the oil and gas industry, analysing data at the edge may be more cost-effective than moving data from the edge. This allows analytical decisions to be made in real time.

Edge computing therefore presents the opportunity for businesses to make large-scale decisions, by analysing data procured at the edge – at the edge. Real-time insights like these improve both speed and accuracy by removing the need to stream all data from the edge back into the enterprise or cloud. As such, organisations need to push their analytical computer power further out to the edge, if they are to be more cost effective.

What’s more, edge computing is only set to grow. Predictions from McKinsey suggest that it will represent a potential value of $175B - $215B in hardware. Before we know it, edge technology will be all around us. Tech companies are disrupting the sector and those opting to move to the edge will be able to make smarter decisions, while feeling more confident in the decisions that they are making at the time they make them.

From theory to practice

You may be wondering how edge computing can help a business to make more informed decisions when it comes to IoT projects.

Enterprise companies are now having to deal with large volumes of complex data. More often than not, most of this is never analysed and no value is gained from it as a result. This is because it can be costly and complicated when there are so many transactions happening in multiple systems all the time. This is why businesses are working to join the data across systems, normalise them, analyse the data and make decisions from it. The competitive advantage this offers is the reason that data management and analytics is now such a massive industry.

Edge analytics meets the Industrial Internet of Things (IIoT)

Companies adopting IIoT initiatives have millions of devices producing data in real time. Even prior to IIoT, these organisations were struggling to cope with the large volume of data that they had – today that struggle is epic. This is where edge computing comes into play – enabling enterprises to analyse the data that adds value.

Let’s take the manufacturing industry as an example. The manufacturing sector is leading the way in embracing smarter technologies such as sensors, to become more connected – and smarter. Currently, it is the “lighthouse” factories which are paving the way for manufacturers looking to become smarter. By this, we mean those early-adopting factories which are implementing advanced manufacturing and AI-driven technologies and seeing meaningful and significant benefits as a result.

Edge computing is essential for smart manufacturing. This is because, in an IoT world, it is the sensors and the connected devices that live at the edge. With this in mind, the analytics on the data is best placed to happen on location, rather than being moved to a centralised storage location.

Edge analytics delivers the right data to those who are best suited to act on it. By leveraging AI to automate the manually intensive work, businesses can enable their employees to concentrate on the tasks which add more business value. The edge therefore helps to streamline all manner of processes, rather than flooding workers with large volumes of complex, analytical data.

By using edge analytics combined with the IIoT, there are myriad opportunities for manufactures – equipment performance and production are optimised, quality is improved, and new and innovative business models are implemented.

There are few industries where the impact of edge computing will not be felt. In fact, businesses of all sizes and sectors have the opportunity to derive value and improve decisioning. The alternative, however, will see businesses inundated with data and increased costs. So – what are we waiting for?

Joanne Taylor, Director of Digital Strategy, Software AG (opens in new tab)