One of the pet-peeves I have with asset management software is that they are basically Access on steroids. There’s not much to the inner workings of the software other than showing you information about an asset – its location, street name, type and maybe some historical information. Once you get past the attributes, the applications get very complicated because they need to handle some business logic and one-to-many relationships, etc. The list of attributes can be exhaustive, but how much of it is useful when making a decision about what to do to an asset with limited funding.
I’m working with a vendor who understands this relationship and the role it plays in prioritizing asset rehabilitation and we are getting some promising results. Imagine trying to prioritize which roads you will be resurfacing next year based on their condition alone. The worse condition they are in, the higher priority they will receive when you are ranking them based on condition alone.
What if you added risk analysis into the mix?
Then, you can ask these questions of your data – If this road fails, what kind of impact will it have on the travelling public? Does the road carry large volumes of traffic, or is it in the boonies?
If you can answer these questions, you add another level of intelligence to your data. Start incorporating traffic volumes, functional classification, detour and access constraints into your model and you’re on your way to prioritizing with intelligence.