We have arrived at the tenth and final post of this series. When I start these series, I always think that I will be able to cover the topic off in a few posts. However, as I dive in I always seem to find more content to add.  For those that have read the entire series, thank you and I hope that I have provided some insights that will help you no matter where you are in your Asset Management (AM) journey.

Once you make your initial decision regarding what condition dataset is right for you today, you then want to turn your attention to the future as today’s decision is not the final decision that will lock you in forever.  If you are early in your AM journey, you may decide to go with a modeled dataset as it is the quickest and cheapest dataset to collect.  However, as you learn, gain wisdom and evolve your program, you will likely come to realize that you need a more granular dataset to answer the new questions that arise on your journey.

For some, a modeled dataset may be sufficient based on the overall objectives of the program.  If your main objective is to provide a high-level financial forecast of renewal needs, the modeled dataset may meet all your needs.

One of the things that we are seeing a lot more with our customers that are just starting their journey of gathering a condition dataset for their portfolios is the combination of a modeling approach, followed by an Element-Level Inventory (ELI). For example, if you have a large portfolio and cannot afford to do detailed Facility Condition Assessments (FCAs) on your entire portfolio, you may decide to phase the program in over multiple years (often 3 to 5).

However, many organizations don’t want to wait 3 to 5 years to have a complete dataset for their building based on an FCA.  In this case, we have developed building-type and/or client-informed models for the entire portfolio during the initial phase of the program and then validate the model with a detailed ELI over the course of the subsequent phase (e.g. 20% per year for 5 Years).  In the long run, the overall cost of this approach is slightly higher as you are both modeling and assessing the entire portfolio.  However, it provides a starting point in fairly short order that is built upon and enhanced over the subsequent phases (years).  With the future assessments, the dataset gets more consistent and defensible each year as the FCAs are conducted.

Not all organizations go deeper with their dataset overtime.  I have seen instances where organizations have “dialed back” the granularity of their dataset.  In most cases, this is the result of not factoring in the level of commitment and effort required to maintain and update the dataset.  Initial decision was made to gather more granular data than an organization was able to maintain given all the other responsibilities of their team.  As such, a simpler, higher-level dataset in built that is more easily managed.  More data is only valuable if you have the capability and capacity to keep it up-to-date.  Although this is a very important question for you and your team to answer, it is vital that you remember that there is truly no right or wrong answer to the question.  There is only the right answer for your organization right now.  Additionally, the answer you give today can be changed as you take your AM program into the future.  That is what continuous improvement is all about.

I hope that the last 10 weeks we have spent together has helped you in making this important decision as you continue to tell your facility and infrastructure asset management story for your portfolio.   See you next week with a new topic!!!