In today's HR landscape, data is having a moment. But I'd like to suggest that not all analytics are created equal.
HR data is essentially HR business intelligence. This should be the basis on which decisions are made about the people of the organization. All of the cool technology in the world cannot override bad data, which is why the accuracy of HR data is a highly strategic function.
First, let me provide some perspective.
In 1980, I was responsible for a department that included personnel records. There was a supervisor who had been in the organization for years. Her staff had been with her for almost the same amount of time. I was used to the impeccable (and regularly audited) records from my prior position with the Marine Corps, and this department maintained similarly accurate and credible personnel information.
Next I went into banking, and while "records" were not part of my responsibility, I relied on the data for my compensation analysis. When I got there in 1989, I found another amazing records overseer who kept our data clean by checking and rechecking all of the personnel forms that arrived on his desk. Our job codes, EEO codes, departmental hierarchy — everything needed for good analysis — was clean.
Then came automation.
The records-keeper job was eliminated because our HRIS was going to take over. We worked hard reviewing, auditing and cleaning data so that the "go live" would contain good data. That lasted about a week.
The good news: We could access, sort and analyze data quickly and easily. The bad news: The data got progressively worse.
Why? Because we shifted the job of keeping the HRIS up-to-date from an individual who knew the importance of the data to managers who couldn’t care less. I haven't seen an organization with good data since. The promise of technology, which could have been such help, fell prey to a system that didn’t review, audit, analyze or even really see the importance of clean data.
Today, organizations not only have an HRIS, but many also have add-on human capital management systems which provide applicant tracking, learning management, compensation planning and other specialty modules. If they are smart, however, the HRIS is the "system of record" meaning that all core data is entered in one place and is fed to other modules. This is a critical first step of having accurate data.
You must take the accuracy of your data seriously. Here are a few ways:
- Every data field should have a business owner. It is the business owner’s responsibility to audit the data in that field. As an example, the compensation department "owns" job codes. They should be the only one allowed to update the job code table, but should also audit the use of job codes regularly to ensure that managers are assigning them properly. Job codes are a critical element of HR analysis, in everything from compensation to employee relations. One wrong job code can throw a job’s comp-ratio way off.
- Organizational hierarchies should be deliberately established by a collaborative group of HR sub-disciplines. This should happen with the understanding of the implications of each structure on data reporting. For one sub-discipline to change a hierarchy without informing others can do damage to the reporting credibility.
- Reports should be produced by a single source within the HR team, regardless of the "owner" of the data. HRIS and human capital systems are too complicated, and a novice analyst can pull the wrong data too easily. One source for reporting should help to catch discrepancies before reports are distributed.
Photo: Can Stock
