Using WO Data in a Well Rounded PdM Strategy with Frank Emery
We’re excited to have Frank Emery, the product manager of AI at Fiix Software, with us to talk about how to make the Work Order data work. Fiix Software is a CMMS that was initially called Maintenance Assistant. He’s been in the software industry for at least ten years, figuring out how to use data. Frank’s work at Fiix is to try and make maintenance technicians’ lives a little bit easier.
Key highlights from this episode are:
- What is Work Order data?
- What type of data are you looking for in a WO?
- How to develop a well-rounded PM program using WO data
.. and so much more!
What is Work Order data?
All the data you type into a maintenance system or write on paper helps you to find out:
- What a Work Order is
- How you’re going to do it
- When it’s expected to be done
These include the tasks associated with the work you’re doing, who’s assigned, when you expect to finish, or how long it may take. All that data makes up a WO. Even the name of a WO or maintenance request is data you can pull and learn from.
How important is having WO data?
It’s critical. If you’re doing things without having that data tell you what you did, how it went, and how it’s going to go next time, then you’ll get lost. You won’t know what’s working and what isn’t. You won’t find issues in your processes or figure out where teams are doing great things that you can cross-pollinate.
What type of data are you looking for in a WO?
The most important things when looking at a WO are:
- The problem with the asset
- What to do to fix it
- How long did it take?
Those are the core fields to start looking at. Everything else helps describe those three. For instance, looking at a task list is important because it says what you did to fix the problem. With those tasks, you’ll have other things like parts, durations, or signees, which help. But without those tasks, you can’t do anything else from there.
How to ensure data meets the expected needs
There are two ways to look at this. To ensure the data’s high quality, you must make it easy. If it’s hard to fill the data in, or it takes time, that barrier comes up, and that person won’t do it to do it. So, ensure it’s easy to get data in, thereby ensuring it fits into someone’s routine.
Another aspect is that you need to have the tooling to figure out when there’s bad data in there. If you know your technicians aren’t filling in data correctly because it’s too difficult, then you need to have a mechanism in place to fix that so you can still make the right business decisions.
You can make data collection easy by:
- Making all the data that’s there contextual
- Making auto-complete features and spell checks available
- Being able to fill in the details on mobile devices
These are all about muscle memory. If you make the data input a part of someone’s daily routine, that will also make it a lot easier to do.
How does the data help create a PM strategy?
A good PM strategy is about:
Data comes in to make sure that the culture and process are working and being adhered to. It’s there to help you figure out where the gaps are to improve things. With a good PM program, data is what lets you know what’s working so that you can go back and make adjustments. Data lets you know you have the right program because you’re getting the results you need
How to develop a well-rounded PM program using WO data
People are using this data to figure out where processes are failing and not failing. It also tells you which assets need maintenance and which ones don’t. It helps you understand your environment and what’s going on with your assets and teams so you can adjust.
A good rule of thumb is that you should be seeing some corrective maintenance coming in there. You don’t want to be doing PMing only since that’s overinvesting. Another pointer is how often you’re doing your PMs. If you’re never getting around to them, that’s a sign of process problems. Finally, make sure that you’re doing the full body of work. You have an issue if the PMs are coming, but you’re not finishing the whole thing.
You can also use a 1:1 ratio for traditional PM activities. So, if you spend an hour on a traditional PM inspection, you should be creating one hour of follow-up work for corrective. It’s a lot higher for PDM because those are a lot less intrusive and less time-consuming.
Trends in the WO data
One of the trends is around data quality. Keep the data consistent and have an idea of what the ideal work order looks like. That will give you a good feel for whether or not the data collection processes in place will give you the data you need so you can trust the decisions coming out of it. How often are things like rework or parts not showing up happen? That all ties into whether or not you have more downtime than you need to be having.
What is data quality?
When looking at data quality, are you filling in all the fields needed, and are you filling them correctly? Some people do a lot of pencil whipping so that the forms look completed, which means you’re collecting the wrong data.
How to improve WO data quality
Ultimately, it comes down to the culture. You could have the best tools and processes, but if your team doesn’t value the data, you’re always going to have problems. So, ensure a feedback loop around why you need the correct data, and reinforce that culture and consistency to build that muscle memory.
What makes the biggest difference with WO data?
The technology that lets you go through it makes a big difference. There’s a lot of data that can get generated. So, you have to go in knowing what the metrics you’re checking or what’s the tooling you’ll use to clean up and read through the data are.
Working through and learning from that WO data is more impactful than any other new technology coming out these days. You’re sitting on a gold mine of information that can help your team get better. So, the sooner you start working with that and learning from it, the sooner you’ll start to see benefits.
Frank Emery Links:
- Frank Emery LinkedIn
- Fiix website
- Fiix Foresight: AI tools for maintenance
- The Drunkards Walk: How Randomness Rules Our Lives
Rooted In Reliability podcast is a proud member of Reliability.fm network. We encourage you to please rate and review this podcast on iTunes and Stitcher. It ensures the podcast stays relevant and is easy to find by like-minded professionals. It is only with your ratings and reviews that the Rooted In Reliability podcast can continue to grow. Thank you for providing the small but critical support for the Rooted In Reliability podcast!
Eng Carlos De Leon says
For this specific case in which the system does not yet use some type of Handheld, How does it solve in a Paper WO that the data written by production operators, mechanics, electricians and the maintenance supervisor are readable for the system, since In the WO Corrective Action fields carried out, handwritten information of great utility is specified. How can the handwriting of different people be transformed? Do you use artificial intelligence algorithm?