One of the biggest and most complicated tasks of an HRIS or HCM system implementation is gathering, reviewing, and reconciling data prior to importing into the new system. We’ve all heard the phrase, “bad data in = bad data out.” No matter how small or large the project, getting the data right is key to a successful HR technology implementation. Gathering data can be daunting, especially if multiple systems are involved, if data resides with service providers, or in more challenging cases, where the data has to be compiled manually. Still, with planning and a well-defined approach, you can achieve an easier and more seamless implementation.
The following is an overview of the key steps and considerations to help you achieve success.
What Data to Migrate?
A critical step in any HR system implementation is to identify what data needs to be migrated and where that data is stored. Typically, this includes employee demographics, benefits, payroll, time and attendance, recruiting, performance, and learning. If you are a small employer, this may simply mean you need to obtain demographics from your payroll company and benefits data from your insurance carriers. If you are a mid-size or large employer, this could mean consolidating data from multiple legacy HR, payroll, time keeping and learning management systems (LMS). The scope of the project is entirely dependent on thoroughly considering and mapping out this data landscape, to ensure all the necessary information and systems are considered.
How is Data Migrated?
Most HCM/HRIS vendors provide a template or workbook (i.e., in Excel format) that companies use to provide the data. Once all the data sources are defined, the data is gathered and compiled into the vendor templates. This can be a time consuming task and many companies opt to engage the vendor or an external consultant to manage some aspects of this work. Keep in mind that you as the employer know more about your own organizational data than an external resource. Only HR can tell that a group of employee locations are off, or that titles are wrong, or that the company identifier for a business unit does not look right. For these and other reasons, we encourage you to adopt a rigorous data quality assurance (QA) process before sending your org data to your vendor (more on this below).
Data issues typically arise not due to a lack of due diligence, but rather, due to an external resource not fully understanding all the ins and outs of an organization to detect anomalies early. At HCM Tech Advisory, we recommend having someone in the organization who is familiar with the data be the data lead. At a minimum, the data lead should be the one sourcing and gathering org data prior to passing off to an external resource to assist with compiling into implementation templates.
Data Migration Quality Control
What quality control measures should you have in place during data migration? Since you will need to pull data a few times during an implementation, you want to create a repeatable process so that the act of compiling the data into templates becomes easy and traceable. Documenting where and how you gathered the data is key to avoiding headaches later.
Let’s say a division is missing from the new system. If you have a well-documented process, it would be easy to detect that a division was simply forgotten and not extracted from a particular system, and that this omission does not represent a global issue requiring a full data resync.
Each time the data is pulled, we recommend documenting the following:
- What source system was the data pulled from? Or if not a system, what vendor or carrier? For example, demographic info may have been pulled from the payroll system, employee benefits may have been pulled from a carrier system, and phone numbers may have been pulled from the recruiting system.
- On what date was the data pulled?
- What populations of data were pulled? Some organizations store data in different systems based on population types or class of employees.
- How was the data combined?
- How was the source data reviewed to ensure accuracy?
Once data gathering and QA processes are documented, the data integration process becomes easily repeatable throughout the implementation.
Remember that data drives what your system is going to look like and what its outputs will be. Getting the data process down at the onset of an implementation is key to your success.
HCM Tech Advisory has the expertise and experience to help answer your questions related to HR data or provide a deeper dive into best practices for migrating data into new HRIS systems. To learn more and for a complimentary consulting review, contact us at info@hcmtechadvisory.com.
