By: Jason Chomic
In today’s fast-paced digital asset intensive environment, where the need for timely and informed business decisions is crucial, organizations must ensure that reliable, high-quality data is readily accessible to the right individuals at the right moment. Having the necessary information drives many key business processes ranging from capital investment projects to routine preventative maintenance scheduling. Every organization is at a different stage in their Asset Master Data maturity journey, while some may already be progressing toward more advanced steps. Regardless of where your organization is today there are opportunities to improve and progress through the next stage of development to advance asset management practices with Asset Master Data being the foundation to build from.
While specific Asset Master Data will be unique from one organization to the next, the concept the Institute of Asset Management (IAM) outlines is this collection of structured data covering the core information and attributes that describe and identify an organizations assets. Some examples of the typical structured information covered under Asset Master Data are:
- Asset Identification – Unique identifiers and basic descriptive information for each asset
- Asset General Details – General information about the Asset including Manufacturer, Model, Size, etc.
- Asset Location Data – Describes the asset’s physical location and relationship to its environment, including geospatial data
- Asset Classification – Grouping of assets based on common characteristics, such as asset types
- Asset Lifecycle Information – Information on the potential or actual value of the asset to the organization
- Asset Value and Acquisition Information – Information on the potential or actual value of the asset to the organization.
- Technical Specifications – Information about the asset’s performance, capabilities and or operational details
…and more.
After the Asset Master Data content has been determined and established for the organization the journey to maturing in Asset Master Data Management can be on its way. While there may be a variety of activities that need to be carried out, at 21Tech we see three major steps in progressing as an organization:
- Catalog Data – After the organization’s asset master data standards have been set, the first and vital step is to understand the current state of the data. What does your organization have readily available today? Where is it? Once the current state is clarified then the focus should shift to the future. What does your organization need for tomorrow to meet the Asset Master Data standards? Finally, the output should be a clear identification of these gaps and strategies should be detailed to address them accordingly.
- Data Governance – Policies and standards should be created or updated to ensure quality, clarity and consistency for this data. Without these standards in place organizations will struggle to create the common expectation of how this data will be handled. Establishing ownership by defining roles and responsibilities will be pivotal in detailing out a well-defined governance model as people within the organization will need to understand who is responsible for what data elements in the working environment. This clarity will help individuals work together and maintain clear expectations. The final and most important element for continued success is monitoring. Without monitoring, how would an organization know how well the data governance model is working? Ideally, monitoring can and most likely will take many shapes and forms. This could range from short term reporting or daily system dashboards to routine meetings focused on data monitoring and/or audits. As an example, deep and detailed audits, while time consuming, could be a potential better fit at longer time sequences (1 year or more) versus short term reporting or weekly meetings could keep eyes on this data topic more routinely without being time consuming.
- Actively Manage Data – Asset Data will need to be managed frequently and on an ongoing basis during its lifecycle for organizations to maintain reliable and quality data.
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- Storage – The proper location where this data will reside will need to be determined. When exploring enterprise software, factors like cloud or on-premises deployments will need to considered, along with security and compliance.
- Onboarding – With the proper data governance model in place, this should dovetail with the asset onboarding process to ensure the Asset Data is being entered either manually or integrated automatically at the right time.
- Updates/Improvements – Throughout the lifecycle of the asset, especially if the asset has a higher frequency of being repaired, it will undergo many important updates and changes to key asset datapoints.
- Disposal – When an Asset is offboarded or disposed of by an organization the data equivalent should also reflect this change.
- Archive – As time passes, aged Asset Data will reach a point where archiving makes practical sense to keep the actively used data concise and more easily useable. Regulatory and Compliance requirements should be considered when determining the archive process.
- Data Deletion – Deletion policies should be set and determined with a high level of care and thought. If it is determined Deletion is the right action, it should be done comprehensively, across all systems. Deletion Logs should also be used to track what Asset Data was deleted, by whom and when.
Well structured Asset Master Data combined with proper Asset Master Data Management offers serval key benefits which pave the way for improved organizational efficiency and decision making. Your organization may be well on its Asset Master Data Management journey or just starting off with the basics, but either way, if you have questions or are looking for guidance do not hesitate to reach out to us here at 21Tech as we would be glad to discuss!