Digital transformation of the global workplace has impacted every aspect of the way companies do business. Much has been made of how smart, connected technologies are working behind the scenes to ingest, blend, and analyze data 24 hours a day, empowering companies like never before to form closer relationships with their customers and partners, gather market intelligence, and develop targeted products and services.
However, less emphasis has been placed on how companies can use data to introduce new capabilities for optimizing daily operations via data science and analytics. By strategically applying insights from data collected internally, companies can maximize efficiency, proactively manage physical assets, increase staff productivity, improve product and service quality, and enhance logistics.
For companies charged with maintaining and repairing equipment – such as the owners of transportation fleets, infrastructure, or production machinery – these new data streams are invaluable.
How significant are the financial benefits of data-driven maintenance and repair? A large company operating a fleet of industrial assets implemented advanced technology from Hitachi to provide optimal repair recommendations – supported by data collection, analysis, and artificial intelligence – which enabled technicians to follow a prescribed repair path based on operational knowledge and previous experiences. Using this approach, the company saved 15 minutes on each visit to the repair shop, based on a faster, more accurate diagnosis of equipment failure. While a 15-minute improvement might seem insignificant, this operator conducts millions of repairs per year across its collection of assets. Based on labor costs alone, this company forecast saving over $15 million annually from this one solution.