Last week I introduced the Element-Level Inventory (ELI) scope of work for facility condition data, and talked about what information is gathered including some of the opportunities that exist and decisions that need to be made as you develop longer-term forecasts of capital renewal needs.  Today, we will wrap up the discussion on ELI and look at some of the upsides and downsides of this approach.

The level of effort to collect an ELI is higher than a Time-Limited Forecast (TLF) in most cases.  For example, if a building is in good or near-new condition overall, the level of effort to gather an ELI would be the greatest as very few elements would require attention within the near term and therefore be captured in a TLF. This increased level of effort requires more internal resources at a higher cost if you are using an outside consultant to gather the data.  However, the older a building is and the worse the condition it is in, the less the incremental increase in effort is.  In theory, if all the elements in the building are old and require attention within the next 10 years they would be captured as part of a TLF and it would essentially be the same dataset as you would capture if you did an ELI.   Additionally, the ELI will provide you with the most robust dataset in terms of granularity. The upside is the defensibility of the dataset and the available planning capabilities.  The downside is that maintaining the dataset will require additional time/resources given the level of detail. 

One other key benefit of an ELI dataset is that it can most easily and effectively be integrated with your Operations and Maintenance program.  An Equipment Inventory (dataset used to populate a Computerized Maintenance Management System (CMMS) and as the foundation of a Preventative Maintenance (PM) Program) is more granular as it is based on individual pieces of equipment, whereas Elements will bundle similar pieces of equipment together based on like age/condition, etc.   

Since an ELI dataset is the most granular condition dataset available (but is still not as detailed as an Equipment Inventory), it is the easiest to align with your Equipment Inventory data.  However, it is important to note that equipment inventory data is generally not collected on all elements.  It is typically reserved for (major) mechanical and electrical elements and roofs (sections). 

For organizations that have a sophisticated facility AMt program and the resources to gather and maintain an ELI, it is our opinion that it is the best-in-class solution for your organization.  An ELI dataset provides unlimited forecasting ability and a granular dataset that can integrated with other critical elements of your AM program allowing you to take a more whole-asset view of your portfolio and spend your limited capital dollars more wisely.

Thank you for being on this blog journey with me for the last couple of months.  Over the next couple of posts, we will bring all the elements of this series together so that you and your team can decide what facility condition dataset is right for you today, and also where you want to take it in the future as you evolve your program.