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Predictive Maintenance (PdM) is a system that uses condition-monitoring techniques and predictive analytics to detect anomalies in machine operation and flag issues before they result in failure. This is achieved through the real-time evaluation of data received from smart sensors and IoT-connected machines. This AI-based predictive model minimizes machine downtime, saving costs and maximizing equipment lifespan. Current challenges to adoption include the high initial investment required and the relative immaturity of IoT technology. Restrictions on data usage, sharing, and privacy concerns may also limit the technology. Predictive analytics has been making waves across other industries. Now we foresee it disrupting marketing. Predictive analytics isn’t new. It’s been used in underwriting and credit scoring for several years, using existing big data to predict potential future outcomes. We’ll see more marketing and social media professionals start to integrate predictive analytics into their processes. Social listening can quickly and easily provide the big data needed, and now we’ll see the AI capabilities catch up to provide accurate and valuable predictions. The capability brings so much potential, with the ability to look into the future of a trend, topic, or campaign and understand how it will adapt in the coming months. Yet, only 42% of marketers say they have predictive analytics capabilities. Expect this to change in 2023.

Predictive Maintenance


Artificial Intelligence (AI)