Organizations invest millions of dollars each year in information management software solutions to manage their information requirements and documents pertaining to their asset management strategy. The newly released ISO 55002, Asset management — Management systems — Guidelines for the application of ISO 55001, defines this information technology as support to the asset management system. The information requirements contained within this standard outline the gaps that routinely prevent the realization of the return defined in the business case that was used in selecting the software package. Here are six common mistakes organizations make that prevent their investment from yielding the predicted benefits.
1. Value stream: Despite the traction that lean principles have gained in manufacturing, there’s still a significant weakness in organizations inside and outside of manufacturing because they fail to define the value stream and how the human assets and physical assets come together to create value for the organization. Without this, the complexity of information management becomes overwhelming. Take the example in Figure 1, an interpretation from IEC 62264-1, of the information flow for a refinery.
Figure 1. This information flow for a refinery, an interpretation from IEC 62264-1, makes it easy to define which data and requirements are necessary for the management of information relating to the assets and how they create value for the business.
Once this information flow is clearly understood, it’s easier to define which data and requirements are necessary for the management of information relating to the assets and how they create value for the business. Without this transparent linkage to the business, it’s nearly impossible for an organization to configure a system to leverage information to make real-time asset management decisions.
2. Business processes: A lack of clearly defined business processes at the transaction level creates a significant amount of non-value-added work for an organization by allowing significant variation in the management systems. Another weakness is poorly defined roles and responsibilities for the execution of each step within the processes. Investing in technology without the process and systems alignment can actually reduce profitability due to an increase in non-value-added work such as time spent data mining, duplication of databases, duplication of information systems, and ad hoc workarounds. Without clearly defined business processes, it’s difficult to outline the functional requirements that need to be met for an effective asset management strategy.
3. User requirements: The individuals who design, acquire, construct, commission, operate, maintain, and dispose of the company’s physical asset portfolio have specific functional requirements and the resultant data, shown in Figure 2, that are needed to manage these assets throughout the lifecycle. A significant number of these requirements reside in the information technology domain. Unfortunately, the selection, configuration, and implementation of solutions to meet the functional requirements are often conducted by a group of individuals with limited understanding of those requirements, and communication across the white space is all but nonexistent. An absence of management commitment and a lack of internal partnership agreements often combine to prevent this necessary collaboration. These user requirements should be linked to business objectives and reinforced by metrics that drive the right behavior.
Figure 2. The individuals who design, acquire, construct, commission, operate, maintain, and dispose of the company’s physical asset portfolio have specific functional requirements and the resultant data that are needed to manage these assets throughout the lifecycle.
4. Master data: Another area of opportunity is the master data contained within the EAM system. Most IT-centric implementations fail to realize that installing the software on the servers or hosting the software in the cloud is a fraction of the level of effort and cost in configuring and implementing to support asset management best practices. Data integrity is important due to business, legal, and regulatory requirements. The controls put in place should be adequate for the type of information in supporting the asset management activity, according to ISO 55002:2014, Section 7.6, Documented Information. In more than 300 assessments that we’ve conducted over the past several decades, less than 30% of the data was accurate in the electronic-to-field audits. Such poor data integrity is usually due to a weak initial implementation plan, lack of management of change, obsolescence, and loose procurement controls.
The classifications of asset types, with clear definitions and a standard naming convention, should be adopted by the organization as a whole. These asset types and other criteria which distinguish these assets, such as lifecycle cost, end of life, asset replacement value, engineering specifications, and reliability data, provide the foundation for analytics. Typically, this classification doesn’t exist, due to a poor initial implementation plan, lack of management of change, obsolescence, and slack procurement controls.
5. Hierarchical structure: Taxonomy is defined by ISO 14224:2006 as a systematic classification of items into generic groups based on factors possibly common to several of the items — for example, location, use, or equipment subdivision. A classification of relevant data to be collected by this international standard is represented by a hierarchy shown in Figure 3.