The Importance of Data Quality for HR and Organizational Development

Data is one of the most valuable resources for a company. It influences decisions, processes, and strategies at all levels. In particular, in the fields of Human Resources (HR) and Organizational Development, the quality of data plays a crucial role. This blog post explores why this is the case and how companies can improve their data quality through data harmonization.

The report “Creating People Advantage 2023” by the Boston Consulting Group (BCG) in collaboration with the World Federation of People Management Associations (WFPMA) has highlighted that digitalization continues to be a critical success factor for HR departments. However, many companies lack the necessary skills to implement this. Therefore, it is necessary to drive digital transformation in HR not only more comprehensively and quickly but also to intensify employee training. Despite the fundamental principles being known, strategic workforce planning remains a significant challenge for most companies. The urgency to act has further increased as the growing availability of data-driven insights has made the competitive environment more dynamic. Data quality is a crucial factor in this context for several reasons:

Informed Decisions
HR departments make numerous decisions that affect the entire company. These decisions are often based on data. From hiring new employees to developing training programs to evaluating performance, high-quality data is essential to making informed and effective decisions. Poor data quality can lead to poor decisions that are both costly and time-consuming.

Efficiency and Productivity
Good data quality has a positive impact on efficiency and productivity. When data is correct and up-to-date, HR professionals can complete their tasks faster and with fewer errors. This not only saves time, but also resources that can be put to better use elsewhere. It also reduces the need for data cleansing and corrections, which also helps to increase efficiency.

Employee Satisfaction
Employees rely on their data being stored correctly and securely. Incorrect or outdated data can lead to frustration and mistrust. For example, incorrect payroll accounting can cause considerable dissatisfaction among those affected. Ultimately, high data quality also has an impact on employees’ trust in the company.

Compliance and Risk Management
In many industries, companies are obliged to comply with certain data standards. Poor data quality can lead to compliance violations, which can have legal and financial consequences. Inaccurate data can also make risk management more difficult, as decisions are made on an uncertain basis.

HR departments are responsible for collecting and managing data and must ultimately ensure the quality of this data. The best way to achieve this is by establishing clear processes for data collection and storage. This allows those responsible to trace the data history and make connections if information needs to be updated later. Additionally, implementing automatic data checks can provide significant value: inconsistencies that could affect the accuracy of the analysis can be identified and resolved at a glance. Ultimately, by improving the quality of their HR data, HR departments can also ensure that their analyses are reliable and accurate, leading to better decision-making outcomes for all involved in the long run.

One of the most important tasks for an HR department is to establish the necessary processes to improve data quality. A proven approach is the implementation of a data model for a structured and standardized procedure. To ensure the accuracy and completeness of the data, automated software solutions can be used to continuously check the data for inconsistencies and errors. This eliminates the need to manually scrutinize each piece of information. Automated data quality solutions also identify and rectify duplicates, ensuring a consistent definition of all raw data used in the analysis. Additionally, it is advisable to review the data sources to ensure that the datasets are up to date. Lastly, it is crucial to evaluate whether there are enough data points available to draw well-founded conclusions and achieve accurate analysis results.

Data harmonization is the process of merging and standardizing data from different sources to create a consistent and uniform data foundation. This is particularly important for companies that need to integrate data from various systems and departments. By harmonizing the data, it ensures that all data is consistent, accurate, and up-to-date.

Inventory of Data Sources
The first step in data harmonization is identifying all relevant data sources. This includes internal systems such as HR software, payroll systems, and employee management systems, as well as external sources like applicant portals and training databases.

Data Mapping and Standardization
After inventorying the data sources, the data needs to be mapped and standardized. This means that all data fields and formats are made uniform to create a consistent data foundation. All relevant data attributes should be considered and aligned during this process.

Data Integration
The next step is to integrate the standardized data into a central system. This can be a data warehouse or a central HR management system. The integration should ensure that the data is regularly updated and synchronized to maintain its accuracy and timeliness.

Quality Assurance
After the data integration, continuous quality assurance is necessary. This includes regular reviews and audits of data quality, as well as implementing mechanisms for error detection and correction. Additionally, employees should be trained to understand the importance of data quality and to incorporate best practices into their daily workflows.

Although data harmonization offers many benefits, its implementation can be complex. Here are some of the most common challenges:

The importance of data quality for HR and organizational development cannot be overstated. High-quality data is essential for making meaningful decisions, ensuring efficient processes, maintaining employee satisfaction, and achieving compliance. On the other hand, poor data quality can lead to high costs, loss of trust, inefficiencies, and compliance risks.

Data harmonization offers an effective way to improve data quality. By merging and standardizing data from various sources, organizations can create a consistent and reliable data foundation that supports efficient HR processes, informed decision-making, and ultimately, a well-founded business strategy.

Companies should be aware of the challenges associated with data harmonization and take appropriate measures to address them. With the right strategy and suitable tools, they can sustainably improve data quality in their HR departments and organizational development, thereby enhancing their efficiency and competitiveness.