by Subanu Senthilkumar | Jul 11, 2025
A Deloitte study found that predictive maintenance can reduce facility downtime by 5% to 15% and increase labour productivity amongst teams by 5% to 20%. This capability is driven by the integration of AI into CMMS platforms, where real-time analytics and machine... by Subanu Senthilkumar | Jul 9, 2025
According to PwC, predictive maintenance enabled by AI can reduce operational costs by up to 30% and cut unplanned downtime by as much as 45%. These outcomes are not future projections. They are being realized by organizations that have embraced AI-powered... 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According to McKinsey, up to 30% of data in industrial operations is inaccurate, incomplete, or outdated, which can cause substantial inefficiencies and safety risks in return.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...