by Subanu Senthilkumar | Jul 4, 2025
Reports have found that data issues impact 60% of AI implementation efforts in asset-heavy industries, and this shows how data quality remains one of the biggest barriers to success. The value of industrial AI lies not just in algorithms but in the data those...
by Subanu Senthilkumar | Jul 2, 2025
Nearly 70% of industrial companies say data quality and structure are the biggest obstacles to successful AI initiatives. In industrial operations, data drives insight. Yet, without the right structure, even vast amounts of asset data lead to inefficiency. An...
by Subanu Senthilkumar | Jun 27, 2025
According to Deloitte, 40% of an industrial asset’s total cost of ownership is influenced by data quality and lifecycle information. Reliable data extraction during plant walkdowns improves asset verification and helps teams maintain accurate and current asset...
by Subanu Senthilkumar | Jun 25, 2025
According to McKinsey, up to 30% of data in industrial operations is inaccurate, incomplete, or outdated, which can cause substantial inefficiencies and safety risks in return. Plant walkdowns are critical in addressing these data gaps. These structured field...
by Subanu Senthilkumar | Jun 20, 2025
According to McKinsey, predictive maintenance powered by APM can reduce maintenance costs by 15 to 30% and unplanned downtime by up to 50%. These results demonstrate why APM (Asset Performance Management) is no longer optional in modern EAM strategies, especially...
