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Few technologies rival the latest advances in automation in their anticipated ability to enhance organizations’ performance, regardless of industry. The potential adoption rate is stunning by any measure: the McKinsey Global Institute estimates that, using demonstrated technologies, more than 81 percent of predictable physical work, 69 percent of data processing, and 64 percent of data-collection activities could feasibly be automated.
Increased availability of low-cost connected devices has made it possible to collect vast amounts of data from the field. At the same time, advances in machine learning allow companies to apply analytics to discover, interpret, and communicate insights. The combination is already opening new opportunities for those companies that are building significant new capabilities in a part of the business that long seemed resistant to change.
Innovative industrial companies are swapping a reactive, manual, and labor-intensive repair lifecycle for one that’s proactive and automated, with machine learning and advanced analytics at its core. Increased availability of low-cost connected devices has made it possible to collect vast amounts of data from the field. At the same time, advances in machine learning allow companies to apply analytics to discover, interpret, and communicate insights.
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