{"id":4499,"date":"2019-12-24T15:18:20","date_gmt":"2019-12-24T14:18:20","guid":{"rendered":"https:\/\/retaintechnologies.com\/?p=4499"},"modified":"2020-11-05T09:10:42","modified_gmt":"2020-11-05T08:10:42","slug":"strategic-asset-management-from-process-to-data","status":"publish","type":"post","link":"https:\/\/retaintechnologies.com\/en\/strategic-asset-management-from-process-to-data\/","title":{"rendered":"Strategic asset management: from process to data"},"content":{"rendered":"

Enterprise asset management<\/a> (EAM) systems are the evolution of computer-aided maintenance systems (CMMS\/CAM). CMMS focus on asset maintenance and therefore on the management and improvement of maintenance processes. In this sense, we can say that a CMMS is a system based on processes<\/strong>, from which it is also possible to obtain useful information for asset management.<\/p>\n

However, as the digital transformation of companies<\/a> advances, process-based systems are giving way to data-based systems.<\/strong> When the whole company has been digitised, what remains, in the end, is data. This data, analysed at a supra-departmental level, will condition strategic decision-making at the management level<\/strong> and the functioning and processes of each of the company’s departments.<\/p>\n

Eliminate data silos<\/h2>\n

Companies, increasingly and through their digital transformation processes,<\/a> are investing in software solutions of all kinds that store and manage specific information<\/strong> from different departments. Thus, we can find CMMS or EAM tools for maintenance or asset management, but also ERP software for human resources management, payroll or accounting, CRM for customer management, etc.<\/p>\n

Each software solution stores relevant information that can be exploited by the company’s management<\/strong> bodies to improve decision-making. However, when each system is maintained by different departments and people, useful information for management is obtained from data that is combined from each of these systems.<\/p>\n

When the systems are isolated forming silos, the consolidated information may encounter problems<\/strong> of inconsistencies in the data generated by the different applications. The metrics and analyses generated from this information can therefore contain errors that can be fatal in decision making.<\/p>\n

To avoid these problems it is necessary to always keep in mind when implementing an EAM within the company not only the operational benefits in daily maintenance, but above all, the impact it has on the strategic management of the company. Therefore, it is extremely important to have mechanisms that allow the system to interoperate<\/strong> with other business systems, so that information is always shared, accurate and unique throughout the company.<\/p>\n

Data-based EAM<\/h2>\n

The application of a data-driven EAM allows value<\/strong> to be derived from both structured and unstructured data obtained over the life cycle of the asset. This information allows the performance of the different assets, the personnel involved in maintenance, suppliers, etc. to be known.<\/p>\n

In a data-based EAM project, it is vital to start with a comprehensive inventory<\/a> of the data, including the sources from which it is obtained, the repositories in which it is stored, the format, quality and the relationships between the different repositories.<\/p>\n

The data is then modelled<\/strong> to suit the needs of the business so that it can provide useful information for decision making by the various actors and departments involved, from the operations and maintenance area to the financial departments. In this process, therefore, it is necessary to have the participation of all the departments involved, to know their objectives and information needs, aligned with the general strategy of the company and specific to the department.<\/p>\n

In summary, the following aspects should be taken into account for the implementation of a data-based EAM:<\/strong><\/p>\n