Identify data attributes, sources, and purpose
Typically, asset registries contain relevant data associated with each asset including: physical “nameplate” properties, service delivery functions, technical data such as initial power curves, key operational data, maintenance data, and performance reports. The Data Standard (document) provides a common definition for types of assets and identifies the data attributes to be collected (including what, how, when, who and how recorded). The development of a Data Standard is important in order to ensure the the integrity and consistency of data across the organization. Each type of asset usually has its own section in the Data Standard. Standardizing the semantics, format, and units of measurements enables the organization to reduce or eliminate the inefficiency in collecting, validating, and managing the data.
Data attributes can include, but are not limited, to:
- Physical attributes: size/dimension, material, capacity, etc.
- Geo-reference: x and y coordinate, street address, map number, etc.
- Supporting data: Operation and Maintenance (O&M) manuals, drawings, photos, etc.
- Life cycle costs: installation cost, maintenance cost, replacement cost, etc.
- Asset criticality: failure modes/codes, probability of failure, consequence of failure, etc.
Note: depending on the sophistication of the information support system architecture, various attributes may already be stored by asset id in existing and often separate data files (for example, in the GIS system, various maintenance management systems, or as stand-alone files); where this occurs, relevant data can be relationally linked by asset id to the physical attributes stored in the asset register as required.
The most important data source is as-built drawings. Unfortunately very few organizations have high quality as-built drawings. When they are not available, design drawings can be used as a good starting point. Keep in mind that at least some modification has usually been made since the design drawings were created. Any variation to the final design (the built asset) should be identified and updated accordingly. Manufacturers’ manuals can also assist in breaking down complex assets into their component parts; bid documents and special schedules of quantity can be useful in the absence of design drawings and manufacturers’ manuals as can be process diagrams or lock-out tag-out drawings. Another very important source is the experience based knowledge of current and previous staff.
As noted, hand in hand with the asset hierarchy/asset registry is the “Data Standard”. A Data Standard is a written document that articulates in a comprehensive manner the asset naming convention, the MMI/hierarchy concept and rules, data attributes to be recorded and how, when, and where they are to be recorded, sources of the data, and responsibilities/business processes for both the initial recording of the asset registry data and how it is to be maintained (including what employee position(s) is assigned to maintain it).
To avoid adding unnecessary attributes to the Data Standard, it is recommended that the organization identify not only the attributes and their associated data sources, but also the purpose of the data. It should be clear in the asset management processes where each data attribute is going to be utilized. Adding unnecessary data attributes will complicate the Data Standard and create preventable wasted effort related to data collection. An example of a list of data attributes, sources and purposes is shown in Table 8.1.