A lack of expertise and technical knowledge prevents many companies from using predictive analytics for maintenance.
A report from Technavio identifies opportunities and challenges in the global predictive maintenance market. The report indicates the market will register an incremental growth of $16,576.78 million at a CAGR of 29.44% through 2027. The report includes multiple factors, including special coverage on the Russia-Ukraine war, global inflation, Covid-19 recovery analysis, and other factors.
North America expected to dominate the global market
According to the report, North America will account for 39% of the market growth thanks to the early adoption of sophisticated technology. This tech generates substantial amounts of data, driving the demand for advanced analytics to derive intelligent insights. Additionally, the mature tech ecosystem and developed industrial sector in the region make it an ideal environment for easy adoption of these advanced software solutions.
PdM solutions are proving to be highly beneficial in achieving sustainability goals and enabling remote machine monitoring. Other factors driving growth include the increased adoption of advanced analytics by small and medium-sized enterprises thanks to cloud computing. Cloud-based PdM tools offer these SMEs new opportunities to leverage cutting-edge tech like artificial intelligence and the Internet of Things.
See also: How Connected Products Enable Predictive Maintenance
Challenges remain to unhindered adoption
Unfortunately, a lack of expertise and technical knowledge prevents many companies from managing and operating predictive analytics. This shortage of skilled personnel negatively impacts the accurate and efficient development of predictive maintenance models. These models are crucial for micro-segmentation and health monitoring of equipment to prevent failure.
Overall, the market will still witness substantial growth despite these challenges. Once companies address these obstacles, we could see even more interest in the capabilities of predictive maintenance as companies seek out ways to streamline operations and prevent unnecessary downtime across large enterprises. Small to medium enterprises that manage to work out expertise issues will also find themselves in a highly competitive position, even among larger peers.
