Unplanned downtime is the enemy of efficient service. When technicians are forced to react (rather than predict), the resulting service is expensive, inefficient, unsustainable over time, and harmful to customer relationships. Predictive maintenance provides actionable insights to predict and resolve equipment issues before they result in costly downtime—but the perceived mystery behind data science and AI can be daunting enough to deter service organizations from pursuing a predictive maintenance solution. How can you move past AI’s difficult reputation and harness it to gain real, tangible results?
By following the right steps with an experienced Internet of Things (IoT) partner, you can implement predictive maintenance to decrease unplanned downtime by up to 30%, realize up to 83% faster service resolutions, and spend up to 75% less time on site1.
Before you and your team begin implementing an IoT-driven predictive maintenance strategy, you’ll likely need to build consensus, alignment, and even virtual teams to ensure success. To secure enterprise-wide buy-in, your colleagues will likely need a clear picture to understand how predictive maintenance directly improves equipment uptime, service efficiencies, and customer relationships.1 Predictive Maintenance