Consistent and structured. Quality assured. Complete Master Data.
The efficiency of any improvement work is greatly compromised with poor master data, restricting visibility into identifying improvement areas and comparison of like assets and plans manual and complicated. Quite simply, maintenance plan execution quality can be compromised through incomplete or inconsistent master data. Through our comprehensive approach to maintenance strategy development, we have developed deep expertise in structured master data generation for all maintenance strategies and plans and the related data elements, such as assets and materials. Our process involves the deployment of consistent, generic structures and master data elements, where agreed master data rules and quality standards are used to automatically generate consistent, quality assured, master data.
Are you experiencing any of these challenges?
Inefficient work execution due to incomplete master data
Gaps in master data lead to delays and inaccuracies in maintenance activities, reducing overall operational efficiency.
Inconsistent maintenance plans across similar assets
Differences in maintenance plan structures for identical assets create confusion and hinder standardization, increasing the risk of unplanned downtime.
Disparate asset structures across sites and systems
Inconsistent asset hierarchies and plans across plants or areas make it difficult to implement and scale improvements without extensive manual effort.
Why your master data needs this rules-based approach
Master data underpins the effectiveness of the work execution management process. It is virtually impossible to effectively plan and schedule work when the master data is incomplete or inconsistent.
Unfortunately, while most organizations may have some guidelines or a framework for master data, they simply aren’t prescriptive enough. What’s more, the guidelines allow for personal preference to creep in. Yet Enterprise Asset Management (EAM) system experts can have differing opinions about the best way to structure the master data within any given system – it’s not uncommon for site and corporate EAM specialists to fundamentally disagree on how best to structure the master data for a given list of maintenance tasks.
How we help
A consistent approach to asset hierarchies enables the development and deployment of effective maintenance strategies to the right asset, consistently. This approach also enables consistent master data collection, in the form of work order history, which supports ongoing improvement of asset performance.
A holistic approach to master data helps ensure that the execution of maintenance strategies is accurate and efficient, from planning and scheduling phases, through to the physical execution of maintenance activities. It is this approach that delivers value to your maintenance execution team, by providing them with the most up to date master data required to execute the maintenance plan.
Rule-based master data generation ensures a consistent and standardized approach to generating master data associated with functional location hierarchies, materials, maintenance strategy task packaging, and creating new or updating/removing maintenance strategy datasets.