When HRIS installations fail, and they sometimes do, it is often the result of the failure to install quality data. You put bad stuff into any system, and bad stuff comes out. When an installation is complete and the HRIS vendor has walked away, the vendor assumes you supplied current, verified, and functional data.
Global Data Synchronization Network (GDSN) defines good quality data as “complete, consistent, accurate, time-stamped and industry standards-based.” If quality data checks in to the system, quality information should be the outcome. Now, a considerable problem arises when most Human Resources personnel do not fully understand these criteria. With time, it has simply become rather inconsequential data entry to a staff not fully immersed in Information Technology. So, there is real risk that the data they present to the HRIS vendor is not complete, consistent, or accurate, let alone current, verified, and functional. With all due respect, most HR personnel think of information systems as little more than virtual files.
However, poor data quality performs poorly. In “The Butterfly Effect On Data Quality,” a white paper by talend,* they compare the situation to the “butterfly effect” in which “even a small error – the transposed letters in a street address or part number – can lead to revenue loss, process inefficiency and failure to comply with industry and government regulations. Organizations depend on the movement and sharing of data throughout the organization, so the impact of data quality errors is costly and far reaching.”
When HR brings HRIS in the door, the department owes all stakeholders the confidence that the data offered is quality. HR cannot expect IT to know the input; it cannot expect Operations or Finance to know what it knows. Quality starts with collaborative data.
- Work with the HRIS vendor to identify measures of quality specific to your operation.
- Establish procedures and policies that define quality entry for the HR personnel and for other functional participants – from front door to back, from marketing through shipping and handling.
- Identify areas and avenues of potential data corruption.
- Aged data may be beyond review, but you can outsource validation to recent, current, and ongoing patterns.
Systems are most successful when there is mutual respect among all members of the Installation Team. Functional jealousies and silo parochialism will assure disinterest at best and sabotage at worst. When the players recognize each other’s intelligence, competence, and contributions to core issues, the vendor will chase to keep up with the momentum.
