Enterprise Asset Management (EAM) is the systematic practice of tracking and monitoring the physical assets of complex organizations across large industries from acquisition through to disposal. Assets across all departments, locations, facilities are included, and can vary from buildings, plants, machinery, heavy and light equipment, vehicles, ships, planes, handheld devices, computers, and more.
Asset-intensive industries, like construction, energy, manufacturing, utilities, and government, struggle with tracking and measuring asset performance, reducing maintenance costs, and maximizing asset uptime. To account for and monitor such large numbers of assets, the adoption of Enterprise Asset Management software has become the standard industry practice for these large organizations.
Enterprise Asset Management software can be conceptually imagined as the organization's central inventory, with features for planning, funding, construction, maintenance, optimization, replacement, and asset disposal. These functions overlap computerized maintenance management systems (CMMS), however, modern EAM software further adds greater sophistication by employing Industrial IOT, automation and machine learning to efficiently monitor and analyze the state of assets well beyond the capabilities of CMMS software.
EAM features are vast, and perform many functions found in other packages, notably, the features of CMMS, and Application Performance Management (APM) software. Furthermore, EAM software integrates with ERP systems, and if necessary, with facilities management apps, fleet management software, and aviation maintenance, repair, and operations software.
Enterprise asset management can be divided into seven functional areas each under constant planning, execution, and control. Those areas include:
In asset-intensive industries, companies with thousands of trackable assets must rely on EAM software and data collecting devices to realistically carry out efficient operations. Data collecting devices include IoT enabled devices, sensors, and smart equipment. Data is collected and analyzed using AI techniques to produce insights that improve teams' abilities to make better decisions, stave off critical events, and maximize their time and the asset. The best software will integrate other systems and data sources, such as Enterprise Resource Planning systems, and streamline processes.
Enterprise Asset Management software provides many features that are found in other software packages, however, EAMs are exceptionally robust, and designed to serve the complexity of multi-location, asset-intensive industries. To be considered an EAM, the package must include the following features.
Enterprise Asset Management software benefits asset-intensive organizations, enabling them to achieve operational efficiency and ultimately improved profitability. To achieve this, EAMs provide three key benefits:
Large organizations with extensive assets, sometimes in the millions, are challenged with tracking, monitoring, managing, and optimizing the resources necessary to keep those assets operational, achieve business goals and maximize ROI. The solution is a purpose-built enterprise asset management system that is designed to support the largest most complex operational environments. Without such robust software, organizations would be at a loss, resorting to manual processes, or a hodge-podge of disparate software or technologies, disconnected and siloed, ultimately limiting overall effectiveness. With EAM software, compliance and best practices are built-in, maintenance teams can collaborate with managers more effectively, and organizations are empowered by:
Enterprise Asset Management software will continue to evolve with the times and the needs of organizations. Recently, much attention has been paid to digital transformation and the benefits that cloud environments are bestowing on companies. For EAM systems, the cloud will be the next evolutionary step, reducing many current technical burdens for organizations because SaaS requires less IT support than on-premise deployments. Cloud environments are also flexible, agile, and scalable, allowing companies to select and only pay for the resources they use, and access integrations to new technologies as they are introduced. And since upgrades are made by service providers in cloud environments, it reduces technical risk and future-proofs company capabilities.
Enterprise asset management integrates three key components, people, processes, and technology, to achieve effective performance that delivers value to customers. Consistent and reliable value delivery is ultimately the goal of EAM practices. The following EAM best practices highlights areas where focused organizational effort can bring positive impact.
Computerized maintenance management systems (CMMSs) are used by small and medium companies that need to manage assets and equipment. CMMSs help to track and optimize the use of assets and their maintenance. Tracking can cover multiple stages of the product's useful life from acquisition to disposal. CMMS features are also found in enterprise asset management (EAM) systems, but EAMs deliver advanced features, including automation and AI techniques, for complex organizations in asset-intensive industries and organizations (managing thousands, even millions of assets) like government, manufacturing, energy, mining, or construction.
The best EAM software systems keep pace with technological trends. Two trends impacting EAM designs are predictive and prognostic techniques enabled by AI, and Industry 4.0 automation technology.
Artificial Intelligence and predictive maintenance attempts to go beyond preventative maintenance or reactive maintenance models. using data analysis with asset characteristics, and other circumstantial data points, the system can optimally schedule maintenance events for workers. More advanced systems can collect greater sums of data and accurately prognose at what future time an asset is most likely to fail, and schedule repairs, order components, and allot appropriate workers.
Industry 4.0 technology includes IoT, automation, robots, smart factories, sensors, and cloud computing. The introduction of these systems has transformed asset intensive industries like manufacturing into globally expansive systems acting as one. EAM systems are challenged with these circumstances, as well as the advanced expertise required to administer them.