Despite the buzz of condition-based maintenance and smart-scheduling, we still see a massive missed opportunity for collecting condition information in every-day work. Many operations we see will perform large-scale and intermittent condition assessment initiatives, yet will miss daily opportunities to understand current conditions of assets and use this information to prioritize work.
This comes down to a very simple concept of designing all work to accommodate some level of asset data collection. Let’s take for example a hydrant painting work order: we often see that organizations want to capture a) did the work get done or not? And b) what “went into” the task? But – why not utilize this as an opportunity to collect critical information on the hydrant – after-all, you’ve already spent the money to send an FTE or contractor out to the location tooled up to perform the task. With the right data collection strategy, it might take the person in the field 20 incremental seconds to collect key information on the hydrant and its related assets.
This condition data, in combination with the asset’s criticality can and should be utilized to derive which assets get worked on when. We already know that operations cannot perform every task that it wants to – so prioritization of the right work is paramount to functional operations with high-levels of uptime and happy customers.
With up to date condition and criticality, you can think about which assets should get replaced (and when), how frequently your assets should be preventatively maintained across each category of risk.
If your existing work order platform cannot accommodate this level of data collection, that’s a problem.
This is just one simple way to meet the expectations of doing more with less.