Anyone who’s been involved in migrating an HRIS knows how monumental a task it is.
The selection and purchase process can be challenging enough on its own, but how can you actually get your information into the new system once it’s set up? What’s the best way to manage the transition?
It will depend a lot on the quality and quantity of data you’re bring across. If your system and the new system will display the same fields (standards like First Name, Last Name, Address plus more in-depth stats like performance rating or job experience, for example), and your data is 100% accurate and up to date, then fantastic – you don’t need to clean up your data.
Pipe-dreams aside, the rest of us will need to cull, update and merge a whole selection of data before migration is possible.
Someone needs to be responsible for getting the data ready for migration. It can be a difficult task, and you’ll need dedicated resources to make it happen.
There’s no point delaying the migration – by this stage, you’ve already invested the time and money into the new system, so you want to reaping the benefits sooner rather than later.
This team will likely consist of HR personnel, HRIS specialists and IT resources, depending on your organisation. It’s important to include the actual users of the HRIS (payroll and HR) in this team, even if it’s only in an advisory capacity.
Information needs change over time, and with many HRIS systems nearly a decade old, you’re going to have some unnecessary data.
Whilst it’s tempting to try and bring everything with you into the new system, remember that this is not only going to create extra work during the migration, but it’s also going to make the system more complex for HR and Payroll.
For every data field, ask yourself:
If you answer no to any of these questions, consider leaving the data behind. If you’re not sure, survey other users and directors of HR strategy to see if their answers corroborate yours.
Similarly, this is the time to ask yourself what data is missing that you’d like to include in the new HRIS. Again, remember to ask the above questions to make sure it’s needed.
We’d all probably love to know complete psychographic profiles of all our staff, but if we can’t (or won’t) measure this, there’s no point preparing your HRIS to include it.
Bear in mind that while there may be some data that you want to transfer over, due to system differences it may not necessarily be an option. For example, historical data is notoriously difficult to migrate between systems. This could include org structure history (where the employee has moved between positions) or even something as simple as change logs to their personal details.
If this is something that you really do need to keep a hold of, consider using your existing HRIS as an archive system, purely for reference, so that you can refer back to this information as required.
There’s really 4 ways you can go about actually cleaning up the data.
The (potentially) easiest option is to pay a data cleansing specialist to clean up your data.
This is great for freeing up internal resources for other tasks, but it does have some serious drawbacks.
Firstly, it’s generally an expensive process, as most data cleansing specialists focus on records with only a few fields.
Secondly, the data you’re cleaning is confidential. It’s your team’s personal data, after all. Not only is it a security risk, you also have legal obligations to manage this data safely, so you’ll need to choose your agency very carefully.
Using a specialised data cleansing tool can make the process far quicker and simpler than a manual approach, and can actually end up being cheaper because of the time savings.
Remember to factor in the time it takes to learn how to use this tool. It can sometimes be more effective to purchase the tool and a consultant who knows how to use it purely for the HRIS migration process.
If your team is already pretty comfortable cleaning up data in your existing HRIS, this can be a good way to clean the data.
Of course, if cleaning the data in the HRIS was easy, why haven’t HR and Payroll done so before the migration? It may be a time constraint (setting aside time each month to fix data is often a lower priority than other activities), but it could also be because it’s not really that easy to fix data in the system.
It will depend on your HRIS, as some are better than others at actually identifying data issues (and allowing users to fix them en masse), but the advantage here is that your team will already understand the system.
The last option is to move the data as is into the new system and try to fix it once it’s in.
This can be problematic, as the team will need to learn to use the new HRIS effectively before they can clean the data, but if the new HRIS is good at identifying issues, it could ultimately be a more effective solution.
Once you’ve got the data into the new HRIS, you can’t assume everything’s worked and the old HRIS is ready to be switched off.
It will be a headache maintaining two systems at once for Payroll, but moving prematurely can create even more headaches, so it’s a necessary pain to endure.
By using the data in actual business applications, you’ll quickly identify and errors or shortcomings with the migration process – much faster than if you just pulled a few data extracts and compared them.
Don’t be too quick to decommission your old HRIS. You may find that you’ll need the old system for longer than anticipated due to problems during migration or use, or you might want to keep the system running as an archive for future use.
HRIS migrations are rarely a seamless process, but taking these steps to clean up your data before and during migration will prevent a lot of the usual hiccoughs we see.