Data quality is one of the cornerstones of a well-functioning Human Resources Information System (HRIS). Accurate, consistent data enables the seamless management of processes such as payroll, talent management and working time management.
However, several obstacles compromise the quality of this information. Among them, insufficient harmonisation of tools, employee reluctance to enter data, and a lack of training on processes are recurring factors that affect the reliability of information in the HRIS.
Let’s explore these three major obstacles.
On the programme:
1. Insufficient harmonisation of tools
The harmonisation of tools in an HRIS is often neglected, particularly in large organisations where several HR systems coexist. Each international branch, for example, may use different tools to manage specific aspects such as payroll, performance evaluations, or absences. If these tools are not interconnected or if their synchronisation is not optimised, data discrepancies and inconsistencies emerge. This creates a significant issue: information entered in one module may not transfer correctly to another, resulting in divergences that affect data reliability.
In such a situation, it’s common for each department to have its own ‘version’ of the data, which complicates updating information. For instance, HR and finance departments may record similar information but in different formats, preventing a unified and coherent view of data across the organisation. This lack of harmonisation increases the workload for HR teams, who must spend time manually checking and consolidating data from disparate systems.
This fragmentation of tools not only leads to errors but also wastes productivity, as teams must allocate valuable time to manual verification and updates.
2. Reticence to enter data
Another major obstacle to data quality in HRIS is employee reluctance to enter or update their personal and professional information. This hesitation often stems from several factors.
First, some employees may feel intimidated by the task or fear making mistakes when entering information. This fear, combined with a limited understanding of the implications of incorrect data entry, discourages users from completing their entries accurately.
Additionally, the complexity of HR processes or the lack of clear instructions can lead employees to neglect these tasks or execute them in an approximate manner. They might, for instance, forget to update key details, such as changes in family circumstances or career developments, resulting in outdated and inaccurate system data.
Furthermore, in some organisations, users are not fully aware of the importance of entering accurate data. The impact of poor data quality is not always immediately apparent to employees. Yet this information directly influences payroll, performance evaluations, and even bonus calculations.
3. Lack of training on processes
According to Le Cercle SIRH et Digital RH’s 2024 Benchmark, 63% of companies consider that data quality depends primarily on employees’ ability to update their personal information effectively. However, in the absence of support or regular reminders, this data often becomes incomplete or outdated.
Training is a critical factor in ensuring data quality within an HRIS. Yet many employees are not sufficiently trained in data entry processes, leading to inevitable errors. Lack of knowledge about specific processes, such as paid leave management, overtime input, or updating personal details, results in inaccurate or incomplete entries.
In many organisations, initial training provided during onboarding is insufficient for ensuring optimal use of the HRIS over time. Employees can quickly forget procedures if they are not revisited or updated. Moreover, frequent changes to HR tools and processes require ongoing training to maintain a good level of understanding and engagement.
Without continuous training, employees often find themselves struggling with tools they haven’t fully mastered. This not only leads to data entry errors but also to inconsistent practices, as users adopt their own methods to compensate for knowledge gaps.
This lack of training also exacerbates reluctance to use HRIS tools, compounding the other obstacles mentioned earlier.
Conclusion
Data quality in an HRIS is essential to the successful functioning of organisations. However, there are 3 major obstacles to achieving it:
- the lack of harmonisation between various tools,
- employee reluctance to enter or update their data,
- and the lack of ongoing training on processes.
These factors are interconnected and require dedicated attention to ensure consistent and reliable management of HR information within the organisation.
👉 To learn more on this topic, read this article: 8 secrets to ensure employees enter accurate data.
