Now that we have introduced and dove into the details of each of the different types of facility condition datasets, I thought it would be important to circle back around and look at how you and your team can make the right decision for your team today, as well as decide if/how you want to evolve your program over time.

To help in this process, I want to once again introduce Integrated Asset Management Framework or as we like to call it “The Onion” to our readers below.

The core of the onion represents an understanding of your current business objectives and processes, where we recommend everyone start each time they are looking to develop or enhance their Asset Management (AM) program.  It is critical that you understand both of these factors when deciding what condition dataset to gather.  Are you trying to provide a high-level forecast of future renewal needs for the first time or do you need to develop a prioritized multi-year capital plan?  What resources (staff and financial) do you have to gather and manage the dataset?  How quickly do you need answers to your critical questions?

With answers to these and other key questions, you are in a better position to start to address the second layer of “the Onion” determining your desired dataset, which for capital renewal planning, is picking the methodology to get your condition dataset.  Jumping straight to the data question without understanding your current state risks building the wrong dataset for where you are today.

When making the critical decision of how deep to go with your condition dataset, there is one other key thing that you want to understand which is the ability of your team to adapt to change.  AM is Change Management in many ways.  AM is all about continuous improvement, which requires constant change as you continue to stretch and evolve your program and practices.

If your team is fairly open to change and adaptable, you can probably take a larger step from where you are to where you want to go in terms of your condition dataset.  If your team is more “steady as she goes”, then you may want to start smaller and build some momentum before you go for a more detailed and resource intensive approach.  Finding the “goldilocks” point for your dataset, based on your teams capacity for change is as much art as science.  You don’t want to bite off more than you can chew, but you also don’t want to take it too easy, or you risk a lost opportunity to advance your program.

Based on looking inwards, you will be in a much better position to decide where to start or evolve your current program and pick the condition dataset that is right for you today.  However, the decision you make today should just be the first of many decisions on how to evolve the capital renewal planning aspect of your AM program.  Next week, we will wrap up this series talking about how to evolve your condition dataset over time as part of a continuous improvement approach to AM.