You can automate everything, have wickedly cool workflow1, and perfection in the user interface. It’s all meaningless if your data is crap.
1) If data in your core HRMS is crap, then everything else is too. Let’s think about this and what the effects are downstream. A simple mis-entry of an employee as full time rather than part time means that (at least for the short term) the employee was able to enroll in the wrong set of benefits and perhaps got overpaid for the first pay period. While this is all easily fixable, you are now talking about manual fixes and intervention.
A simple data entry error takes on significantly more time to fix than to simply do right the first time around.
2) Perhaps more seriously, if data in your core HRMS is crap, then your metrics are too. Consider that you need to pull metrics about XYZ data, but that data field is not table driven. The 10 data entry clerks you have over time keyed “California” as “CA” Calif” “Cal” and so on. They have also keyed “Canada” as “CA” and “CAN.” You can begin to see the problem.
Unfortunately these are not really errors, but a lack of focus on standards. Avoiding these types of data errors is actually much easier, but the consequences of not cleaning them up are more serious as it impacts what you can use for reporting.
At systematicHR we talk about technology and what we can do with it all too often without addressing some of the core problems that plague us in our daily work. While it’s nice to be a visionary and pretend everything is beautiful, every now and then I’ll come down to earth and remind myself that there are still fundamental problems to be fixed.
- I think I just let everyone know what generation I’m from [back]