First, know what you have
A minimal inventory of the assets that matter. Without this, everything else floats.
Guide
Digitizing a process that doesn't work makes it fail faster
That's worth saying first, because half the disappointment with these projects comes from here. The tool amplifies the process you already have; it doesn't replace it.
What digitizing maintenance actually means
It doesn't mean giving up paper: it means information gets recorded where it happens and stays available without anyone having to carry it around. That's the real difference. A work order a technician fills in on their phone and one they fill in on paper for someone else to type up later contain the same information, but the second one arrives late, incomplete, and with the cost of a transcription. What changes with digitization isn't the data itself, it's the moment it comes into existence and who can use it.
The order that works
Almost every successful rollout follows this sequence.
Then, log the work
Orders with their hours and materials, charged to the asset. This is what starts generating history.
Bring it into the field
Getting the record to happen at the installation, not after getting back. If this fails, none of the rest matters.
Then, automate the recurring work
Once the team is already working inside the system, preventive plans get adopted on their own.
And finally, measure
Indicators arrive once there are months of reliable records behind them, not before.
What it doesn't fix
Four problems that survive any tool intact.
- A workflow where nobody is responsible for making things move: digitized, it still won't move.
- An inventory nobody maintains: the system will just reflect it out of date, more precisely.
- Not enough staff: software doesn't carry out work orders.
- Decisions nobody wants to make: having the data doesn't force anyone to act on it.
Adoption is the project
People usually plan the setup and the data migration, and leave adoption for a two-hour training session at the end. It should be the other way around: setup gets fixed in an afternoon, and adoption, if it fails, doesn't get fixed. A manager will use the system because it's their job; a technician will use it if it makes their job easier, and if not, they'll find a way to keep working the old way. What actually works is sticking with them the first few days, on their own orders, and fixing the specific friction points that come up: a missing status they use daily, materials not where they expect them, a checklist asking for something that makes no sense on that machine.
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What to expect, and when
In the first few weeks, one thing and only one thing shows up: work stops getting lost. Requests don't sit in an inbox and reports don't get misplaced. A few months in, the second effect appears, which is being able to answer questions without reconstructing anything: what was done on that unit, how much has been spent at that site. And from around the one-year mark, once there's history, comes the third and most valuable effect: deciding with data instead of intuition. Promising the third one in the first month is what makes these projects disappointing.
Why paper hangs on for so long
It's worth understanding why the paper work order survives so many attempts to replace it, because whoever doesn't understand it will fail again. Paper wins on the things that matter in the field: it never runs out of battery, it works in a basement with no signal, you can write on it with gloves on, you can rest it on anything, and it doesn't make you navigate menus. A digital tool that loses on every one of those fronts won't get adopted no matter how much management decides it should be; what will happen is the usual thing — the technician will keep writing on paper and transcribing it later, which means work has been added instead of removed. What does beat paper is an app that works offline, that shows the day's work without having to search for it, and that fills in on its own everything that's already known. The honest comparison isn't digital versus paper: it's this specific tool versus the notebook, in the basement, with gloves on.
What to measure in the first year
The temptation when starting out is to build a full dashboard, and that's a bad idea: in the first months the data is still thin and sophisticated indicators come out wrong, which discredits the system right when it's most fragile. In the first year it's worth watching three simple, hard-to-argue-with things. How many interventions get logged versus how many are estimated to actually happen, which measures whether the system reflects reality. What proportion of preventive jobs get done within their due date, which measures whether the plan is sustainable. And how many orders stay open for more than a month, which measures whether the workflow actually closes. Those three catch nearly any adoption problem. Cost and reliability indicators arrive on their own later, once there's enough history for them to mean something.
Frequently asked questions
How long before something is noticeable?
It depends on what you expect to notice. Visibility arrives quickly, within a matter of weeks: knowing what's open, who's handling it and what was done where. The improvements that depend on history — adjusting frequencies, deciding whether a unit gets repaired or replaced, comparing sites — need a good year of data, because before that there's nothing to compare against, and any conclusion would just be an impression dressed up as a report.
Do you have to digitize everything at once?
Almost never a good idea. Projects that succeed start with a defined slice — one site, one line, one type of work — and grow once that first piece already works on its own. A full rollout forces a hundred configuration decisions without any hands-on experience, and half of them get made wrong precisely because there isn't yet enough knowledge to make them well.
Where do you start digitizing maintenance?
With a minimal inventory of the assets that matter and by logging work against them. Automating recurring work and measuring come later, once the team is already working inside the system.
How long until you see results?
Within weeks, work stops getting lost. Within months, you can answer questions without reconstructing anything. And from a year on, you can decide with data. Promising the third one in month one is what makes these projects disappointing.
What problems doesn't digitizing solve?
Ownership problems, staffing problems and decision-making problems. If nobody is responsible for making something move forward, the system will reflect that more precisely, but it won't fix it.
What fails most often?
Adoption by the field team, usually because it's planned at the end with a generic training session. What works is sticking with them the first few days, on their own orders.
Where are you at?
If you've tried this before, tell us: knowing what went wrong then saves half the work now.