Why does a siloed HRIS can result in poor data quality?

A Human Resources Information System (HRIS) is an essential tool for managing HR processes. However, when it operates in silos, meaning it is separate from the company’s other systems and not interconnected with other departments, data quality is compromised.

Siloed processes lead to numerous issues, including duplication, data entry errors, missing or lost data, frequent manipulation to extract information, and lengthy verification times. This article examines these negative impacts in detail.

Highlights:

Duplicate entries
Data entry errors
Missing or lost data
Increased manipulation to extract data

1. Duplicate entries

An HRIS that operates in silos tends to isolate information in separate databases for each department or service. This lack of centralisation often leads to data duplication. Each team may input the same information but in varying formats or with inconsistent details. For example, the payroll department and the HR department might both manage employment contract details, but if this data is not synchronised, discrepancies arise.

Duplicate entries significantly increase the likelihood of errors, making it difficult to manage data effectively. Determining which version of the information is accurate becomes a daunting task. Over time, this degrades data quality and undermines the integrity of HR processes.

2. Data entry errors

When systems operate independently, users are often required to input data into multiple platforms, often without standardised processes or coordination. This frequently leads to data entry errors, particularly as validation rules may vary across departments. Additionally, users who lack proper training or are under time pressure are more prone to making mistakes. Such errors can remain undetected if not checked in a shared environment.

Data entry errors are particularly common when processes are poorly harmonised. A single data field may be interpreted differently by users, leading to inconsistencies across databases.

3. Missing or lost data

Another significant drawback of siloed systems is the frequent absence or loss of critical data. When information is siloed, it may fail to reach the departments or teams that require it. For instance, an update to an employee’s status might be recorded in an administrative system but fail to propagate to the payroll system, resulting in salary miscalculations.

Furthermore, siloed systems increase the likelihood of data being lost during manual transfers or delayed integration into centralised workflows. This poses risks not only to data quality but also to compliance with regulatory requirements.

4. Increased manipulation to extract data

In a siloed HRIS, accessing information often requires multiple manual steps to extract or reconcile data across departments. These repetitive manipulations increase the likelihood of errors during data transformation, especially when files are manually exported and modified before being shared.

The risk of data being lost or altered during these processes is high, adding complexity to HR information management and reducing the reliability of the data.

Conclusion

A siloed HRIS system weakens data quality by causing duplicate entries, increasing the risk of errors, losing essential data, and complicating verification processes.

To improve data quality and streamline HR processes, organisations must eliminate these silos by adopting a centralised and integrated HRIS. This approach allows all stakeholders to access consistent, real-time information.

👉 Data quality if often hindered by numerous challenges. Learn more in this article: 3 obstacles to good data quality in HRIS.

👉 To find out more about solutions, discover our 8 secrets to ensure your employees enter accurate data.