Computerized Maintenance Management Systems (CMMS) or Enterprise Asset Management (EAM) Systems are just software that help you organize your data. Analysis of this data can provide information allowing you to redirect scarce resources to where they are most needed and justify these actions. So, we agree that we need to get good data in to get helpful information out. With that in mind, let’s tackle repair data first.
Basic repair data fields come in four categories that cover the life cycle:
In this blog, we will only tackle Origination and Results as they will appear in all work orders, including emergency work orders that are neither planned nor scheduled.
Origination data includes the priority or at least a declaration of whether it is an emergency, identification of the originator, the asset with the problem, and the problem description. Yes, there can be more, but consider this the absolute minimum that should appear on every request. In general, this assists in getting the best resources assigned to the job. Although it is most important to get all data consistently and correctly into each field, most problems occur at work order origination and multiply as the work order is processed.
The importance of the problem description cannot be understated. Anyone who requests work should be trained on how to call in (type in, write in, message in, etc.) the problem description. This should include what was observed that prompted the call. Sample bad problem descriptions:
Bad problem descriptions do not provide enough descriptive data and they lead to bad descriptive results such as:
If the historical records within the system contain descriptions similar to these (or descriptions are null), plan to retrain everyone immediately and include a sample of these records to show how useful (or not) they are for historical analysis.
Requestors should be trained to focus first on describing the problem based on what they observed, such as:
These are genuinely oversimplified examples, but your maintenance department can use this to identify a starting point and promote a more descriptive response to the cause. For historical purposes, this can be invaluable in looking at repetitive problems and working toward engineering them out of existence, as well as creating better data for usage by Maximo Work Order Intelligence.
Improving work request / order origination data is probably the biggest and most inexpensive way to make a major leap in repair data capture. Even if you use Quick Reporting, you still begin typically with 100 characters in the main field, before you need to go to long description. You will also have access to enter a problem code if you have that developed. The use of coding in the failure hierarchy will further enhance your capabilities to quantitatively analyze your data.
Results data should at a minimum include the skill/trade that completed the work, work time, a description of what was done, materials used and their costs, the cause, any downtime and an assessment of the repair (does it need follow-up work?).
The skill should have an associated bill rate so that the hours charged can be identified as dollars charged for the repair, back to the asset. This will help build out that asset year-to-date cost field on the asset, among other cost fields.
Even better to include the identification of the actual technician, especially when follow-up is needed and you want to reach out to the correct person. Those technicians will also have a record of what they worked on when it is useful to keep track of for training and certification purposes.
The work description should explain the action taken to complete the job. There is plenty of room to describe in detail, and again, you will have access to the problem, cause and remedy of that data has been developed.
Downtime can be complicated, so it is important that everyone have the same understanding of how it is charged and used, before reporting it.
Materials used and their costs are helpful for keeping the inventory up to date and charging the materials cost to each asset. Thus providing better history on usage, as well as cost to maintain the asset.
Having the material identified by its tracking number or ITEMNUM in Maximo is essential for documenting parts usage and can serve to assist in building the bill of materials (Asset Spare Parts) if this feature is turned on for the item.
This cost is especially important in light of the fact that many materials costs can exceed labor costs significantly, and both are necessary to properly assess the maintenance requirements and provide a more complete history of a given asset.
The better and more consistent recording of all work orders, the greater potential for yielding more specific information about the maintenance of all assets in both qualitative and quantitative terms. The more quickly this can be done, the sooner actual activities will be reported and useful histories can be built and analyzed through statistical methods.
Want to learn more? Check out the resources on the Projetech website or contact our team today!
