Answered June 12 2019
When a CMMS is implemented properly, an organization can start to gather some really amazing data. Unless, of course, the data put into the system is garbage, in which case the data we get out of the system will also be garbage. For many employees, this may be their first time using a system like this, so it’s important to pre-empt bad data by encouraging a culture of solid data input. How do we do this?
More often than not, there’s a communication disconnect between the people implementing CMMS software and the people using it.
For instance, a maintenance manager might tell their employees, “Input quality data.” While this seems like a simple request, it may not be clear to some employees what “quality data” means. They might think that good data means lots of data, or that they should input anything and everything they can find. This results in a massive influx of work orders that aren’t useful and don’t point towards real problems.
In these cases, to help employees understand the implementation of quality data (or align on what you both believe to be quality data), it is helpful to use examples and meticulously walk through the input process.
This goes hand-in-hand with leading by example: training is incredibly important for encouraging quality data input.
Some employees may feel that they’re not sure what kind of data to input and so they are either too vague or excessively wordy. In other cases, they may not report any data at all because they don’t know how to use the system.
Training solves these problems by providing employees with the tools and skills they need to use a CMMS effectively. Knowing how to use the system (and then training on what qualifies as useful data input) is vital to creating a culture of good data.
With a CMMS, it’s also useful to understand how you can influence the quality of the data being put in.
If failure codes are employee-generated, for example, there is sure to be a massive lack of consistency. Or if the failure codes are too short or too general, there’s very little you can do to extract good data because there’s not adequate data there to pull from.
Finding the right balance in failure codes and work orders is critical. Sometimes, it’s better to have lengthy, specific failure codes if that means that the data input is useful. In other instances, it’s valuable to have qualitative feedback from employees. Ultimately, it’s a good idea to consider both perspectives to find that balance that works for your team.
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