Well, it only took me six posts to finally get to a point where you put boots on the ground in your buildings to start to build your condition dataset. This is a big step in terms of creating a consistent and defensible dataset on which to build a capital plan.

However, there is a cost associated with gathering these enhanced datasets. A team of professionals are required to mobilize to each building and spend between a few hours to a few days on-site to interview your staff, walk the buildings, take photos of the elements, and observed deficiencies and go back to the office and prepare a report and dataset. These costs will be considerably higher than the modeling exercises outlined in the previous posts.

The first type of on-site assessment that we are going to tackle is the time-limited forecast. For these projects, you provide a forecast of capital needs over a specific and limited time horizon, what we call the evaluation period.

In the commercial real estate sector, this is where the Property Condition Assessment (PCA) typically falls. If you are doing a finance-level PCA, the evaluation period is usually based on the term of the loan plus two or three years. For example, if the loan term is 5 years, your PCA Opinion of Probable Cost (OPC) table would likely cover 7 to 8 years.

To support the acquisition of a property, the evaluation period is most commonly 10 years. The purpose of the acquisition PCA is to provide a purchaser with an understanding of future near-term capital needs that can be used in negotiating a haircut on the purchase price, and also to provide some guidance to their asset and facility management teams of what to expect upon taking the building into their portfolio.

There are some public sector and institutional clients that include an evaluation in their Facility Condition Assessments (FCAs) to support on-going asset management. Evaluation periods can range from 10 years to 30 years.

In a time limited PCA or FCA, the future capital recommendations and corresponding data are limited to the evaluation period. The rest of the building is generally only mentioned within the narrative section of the report. The condition of the elements that do not have recommendations are assumed to be good as they do not require any “attention” until outside of the evaluation period.

The benefit of having an evaluation period for the commercial sector PCAs, is that the work is limited to the timeline of interest for the various stakeholders, including lenders, investors etc. The cost to collect a time-limited dataset is lower that an element-level inventory (more details to come next week). For those that don’t need a longer-term view of their portfolio renewal needs, whatever the reason, why would you pay the additional price.

The biggest issue with time-limited dataset is that your planning horizon gets shorter every year. If you do a 5-year evaluation period, next year you only have a 4-year forecast, the next year, 3-Years and so on. Given that the standard cycle for FCAs is 5-years, you can literally run out of future forecast data if you do a 5-Year evaluation period.

The other issues as well is that you will not have data (dates of construction, quantity, condition, remaining useful life, photos, narratives, replacement value etc.) on all of the elements within your buildings. If you don’t want or need this data, then it isn’t an issue. However, if you are trying to take a longer view in terms of Asset Management, there will be holes in your data.

Also, if you are going to use the “Sum of the Parts” methodology to calculate your facility Current Replacement Values (CRV), the denominator of a Facility Condition Index, you won’t be able to do so with a time-limited dataset. Sum of the Parts involves adding up the Element Replacement Values for all the elements within the building. You won’t have ERVs for all elements in a typical time-limited FCA or PCA.

Next week we will explore the highest-level, and most resource intensive approach to gathering an condition dataset for your portfolio, the Element-Level Inventory.