A mining truck in South America rolls down a dusty road on a hot day. High-tech sensors pick up an overheated bearing, and the data is instantly transmitted to the mining company’s data center. Now what?
This scenario can go one of two ways, only one of which will save the mining company from spending a lot of money on stranded trucks. If the company’s CEO instructed the engineering and business departments to have a data-driven plan for predictive maintenance, then the truck gets taken out of service and gets a new bearing, saving time and repair costs. If the overheated bearing goes unnoticed because the dataset is stuck in a dark, inaccessible corner of the data infrastructure, then you have a buildup of stranded trucks. Enough stranded trucks eventually leads to the company’s demise.
In most industries, today’s business plans can’t just focus on heavy machinery and its maintenance. Most strategic plans must encompass a third element: finding efficient ways to use performance information that emanates from the day-to-day business.
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