The Industrial Internet is revolutionizing the way companies collect, analyze, and benefit from big data. By installing sensors on industrial machinery and tapping machine learning analytics software to pore through observable data, companies are better able to act on insights and optimize their products. But the new digital industrial era may also be revolutionizing the shape of the workforce within the manufacturing industry. Increased optimizations brought about by advanced data analytics means a decrease in the need for on-the-ground technical support. Manufacturing technicians, whose expertise in machinery repair made them essential, will likely need to supplement their technical skills in a world optimized for efficiency.
Among the many manufacturing companies making the leap toward digitization is Schindler group: one of the world’s biggest elevator, escalator and moving walkway companies. Its products carry billions of people every day, and soon it will also move gigabytes of data.
Schindler recently teamed up with GE Digital to connect above a million elevators, escalators and moving walkways to the Industrial Internet. Using Predix, GE’s cloud-based software and analytics platform, Schindler can securely monitor and analyze the data. “Schindler’s partnership with GE is a game changer,” says Schindler Group Chairman Alfred N. Schindler. “It will boost Schindler’s digitization strategy and reaffirm our innovation leadership.”
Schindler is already gathering data from service calls and sensors that keep track of how well its products are performing, but the new partnership will take data analysis to another level. The data flowing from Schindler’s connected elevators and escalators will help the company identify and respond to possible service issues before they happen. Schindler’s ahead of the game: The majority of companies have yet to unlock the predictive power of data, which reduces the odds of product malfunction and interestingly, also reduces the number of on-site technician visits necessary.
For technicians, the Industrial Internet is empowering, as it helps to clarify and simplify objectives so as to better improve efficiency. For example, rather than arriving on-site to assess a reported broken elevator, a technician would arrive equipped with sensor data that had already identified the source of the problem and the most straightforward technical solution. As predictive capacity improves, the problem may even be fixed before a machinery malfunction occurs.
Though the reduced workload might be a relief, a drastic shift would prompt a fear commonly associated with the digital revolution—that advanced technology may replace the need for human expertise altogether. “We love to use the machines and we love to use them to do things that we don’t like doing, but at the same time we have this instinctive fear that machines might somehow replace us, replace workers and not work in our interest,” says Marco Annunziata, GE’s chief economist.
In reality, what appears to be happening is perhaps less apocalyptic, but will likely require a pivot toward new skills. Replacing the time and energy of the manufacturing technician is not new technology or robots, but a data-analytics expert who can interpret and respond to the massive influx of product data.
For now, companies are looking far and wide for skills to bridge the existing talent gap between companies’ needs and industry demands. Although much of the search is external, 46% of companies are using in-house resources to train employees as analytics specialists. With the right training, that former repair-worker could step into a new hybrid role: analyst meets technician.
This article was produced on behalf of GE by Quartz creative services and not by the Quartz editorial staff.