Automation Automotive Research

Automation’s Evolution and Promising Future

Automation's Evolution and Promising Future

In its simplest form, automation includes any improvement to a process that reduces human labor while resulting in an outcome that’s the same or better than that of the previous process. The goals of automation include improvements not only in productivity but also in quality and consistency.

SwissCognitiveMost of us are familiar with information systems that automate and streamline decision-making using tools to aggregate, extract and analyze information. All of that has been around for a while. But newer systems — based on automation — now include , machine algorithmsAn algorithm is a fixed set of instructions for a computer. It can be very simple like "as long as the incoming number is smaller than 10, print "Hello World!". It can also be very complicated such as the algorithms behind self-driving cars., real-time computing, big dataBig Data describes data collections so big that humans are not capable of sifting through all of it in a timely manner. However, with the help of algorithms it is usually possible to find patterns within the data so far hidden to human analyzers. data analyticsData analysis is simply put the study of data in order to take better informed decisions. All business decisions should be made with the best information available, data analysis tries to provide this information through different algorithms and statistical techniques. and evidence-based-. This level of automation opens up exciting possibilities.

automation — basically, the intersection of () and computing — has become one of the fastest-moving technologies because of the rise of the digital and connected workforce. According to one forecast , the global robotic process automation market will generate revenue of $50 million in 2017 and will expand at a compound annual growth rate of 60.9 percent from 2017 to 2026.

Buzz: C-Suite Interest?

The earliest successes in the field of automation involved products such as warehouse robots powered by , automated restocking systems, self-driving cars and systems that predict electricity demand. However, despite the influx of billions of gigabytes of data and vast investments, deployment of is still relatively low — though it appears that, thanks to the current wave of buzz, C-level executives are taking an interest in how investments in can result in greater success.

In a Harvard Business Review article, researchers from the McKinsey Global Institute reported that only 20 percent of respondents to their survey said they use one or more technologies at scale, while 41 percent said they were experimenting or piloting . Nonetheless, a McKinsey report sees as a new disruptor that will accelerate “shifts in market share, revenue, and profit pools.”

McKinsey identifies early adopters as digitally mature larger businesses that will use in core activities through multiple technologies, and that focus on growth over savings. […]

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