Abstract
Asset-intensive businesses across industries rely on physical assets to deliver services to their customers, and effective asset management is critical to the businesses. Today, businesses may make use of enterprise asset-management (EAM) solutions for many asset-related processes, ranging from the core asset-management functions to maintenance, inventory, contracts, warranties, procurement, and customer-service management. While EAM solutions have transformed the operational aspects of asset management through data capture and process automation, the decision-making process with respect to assets still heavily relies on institutional knowledge and anecdotal insights. Analytics-driven asset management is an approach that makes use of advanced analytics and optimization technologies to transform the vast amounts of data from asset management, metering, and sensor systems into actionable insight, foresight, and prescriptions that can guide decisions involving strategic and tactical assets, as well as customer and business models. © 2011 by International Business Machines Corporation.