Homyze provides a guide on what is planned preventative maintenance (PPM) and how to go about implementing this maintenance strategy
What does good look like?
How to judge good performance from maintenance contractors? A guide to evaluating facilities management and property maintenance suppliers and contractors
Maintenance metrics and what they mean
From the earliest ages, we have been used to evaluating performance based on scores. Sometimes, we would get a 7 out of 10 for a maths test. Hopefully, sometimes we would get a higher score.
Either way, these scores allowed us to benchmark our performance, to highlight areas that might require improvement and illustrate strengths and weaknesses. At Homyze, we use the same approach with our own performance evaluations.
When we first started engaging with clients, we were surprised that they did not keep this information themselves, in order to ensure that they were hitting their own performance expectations. Having been involved in the development of a system that is required to measure the data, we now understand - it’s complicated. But like many complicated things, it is also quite powerful.
We score performance across a number of different metrics and use them to highlight areas where we can improve and whether clients are receiving the standard of service that we try to deliver.
We use these data to define what good looks like.
What we measure
Just a caveat on the below, these data are solely related to performance within the context of supplier operations and focus more on reactive works than planned.
We have separate frameworks for maintenance metrics which detail such parameters as time between failures, downtime, percentage of planned versus reactive maintenance and more.
In being a good property maintenance partner, your client has to feel that you are responsive and that when they send requests (for information or action), they will be answered.
The below metrics detail what we use to measure our performance for clients in this regard and form a basis for highlighting if there are jobs which require further investigation
- Time to accept jobs
- Time to attendance
- On-time arrival rate
- 1st Fix rate
- Average job length
- Average job value
- Engagement rate (% of jobs offered that are accepted)
- Time to submit job report
- Time to submit quote
- Time to close down job
Most of these metrics are not looked at in isolation but rather will be tracked over time. We know that there are circumstances and situation that may distort the data, and we use baseline levels to decide on whether this requires further investigation.
Are there others that you think we need to include?