Earlier this year, Ralph Rio, VP of Enterprise Software, at ARC Advisory Group wrote in his blog “to serve as an effective planning and management tool for high uptime and safety, the information in an EAM system requires high data integrity” (Improving Uptime and Productivity at Alliander with Asset Information Data Integrity.) There is no better way to achieve high data integrity than through strong data governance practices. Governance of the entire complex, inter-related structures within the EAM system can be accomplished with SAP’s Asset Information Workbench (AIW). Since it’s built on the SAP Master Data Governance (MDG) for Enterprise Asset Management (EAM) platform, users achieve a centralized and streamlined approach for reliably managing asset data across an enterprise. Rules for new data or maintained data are defined by the business, allowing every field to have the rigors of complete and consistent validation. Furthermore, those in the organization who need to review or approve the data are directed to do so by automatically generated workflows.
When using SAP AIW, the entire structure, typically comprised of multiple levels of functional locations, equipment, and sub-equipment hierarchies, Bill of Materials (BoMs), maintenance plans, unstructured documents, and more, can be created, copied, or maintained within one SAP AIW Multi-Object Change Request (MOCR). Here, the integrity and completeness of the entire structure’s composition are automatically reviewed while the data is still in a WIP status. No updates to the backend systems occur until stringent business rules are satisfied, and SME reviews and approvals are completed. There is a solution available that allows these virtual, WIP inner-connected master data elements to be simulated, viewed, linked to one another, and verified while still in a staging area.
Another significant benefit that SAP AIW provides is the ability to have predefined master data templates that are aligned to industry standards such as ISO 14224, as well as an organization’s own best practices. These templates can be quickly copied and applied to plant-specific hierarchical structures when the need exists to stand up new structures or perhaps append existing operational structures with new or updated equipment hierarchies. Through built-in data inheritance routines, key master data shared between parent/child structural relationships are enforced. Examples of this shared data may be cost centers, work centers, planner groups, and more.
By using SAP’s AIW, the asset data professional now has a tool where he/she can focus on the master data within the structures themselves to ensure that all related data is complete, correct, and properly linked and constructed before the data is consumed by the backend systems. With SAP AIW, a data-driven intelligent enterprise can be assured that the asset data is ready to be used and relied upon.
For more information visit SAP Asset Information Workbench (AIW) by Utopia.
