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According to McKinsey, up to 30% of data in industrial operations is inaccurate, incomplete, or outdated, which can cause substantial inefficiencies and safety risks in return.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... by Subanu Senthilkumar | Jun 18, 2025
The global EAM market is projected to reach $13.69 billion by 2032, driven by the growing demand for cloud-based CMMS tools and digital twin capabilities. In this evolving landscape, IBM’s MAS9 positions asset managers to better control lifecycle costs, improve asset... by Subanu Senthilkumar | Jun 13, 2025
A study by McKinsey shows that standardized engineering practices can reduce project costs by up to 15% and cut errors by 50%. In this context, reference designation systems such as RDS-PP and RDS-PS are transforming how industrial plants manage complexity, especially...