How do you combine HR data?

1 Identify your data sources and goals

Before you start combining HR data, you need to identify what data sources you have and what goals you want to achieve. For example, you may have data from your HRIS, payroll, performance management, employee surveys, and external benchmarks. You may want to use the combined data to analyze trends, patterns, and correlations, or to create dashboards, reports, and visualizations. By clarifying your data sources and goals, you can plan your data integration strategy and prioritize your data needs.

2 Choose your data integration method

When combining HR data, the method you choose will depend on your data format, volume, and frequency. Manual data integration involves manually transferring, copying, or entering data from one source to another and is simple and low-cost, but also prone to errors, inconsistencies, and delays. Data consolidation involves creating a central repository or database that collects and stores data from multiple sources, making it more efficient and consistent than manual integration but requiring more technical skills and resources. Data federation creates a virtual layer that connects and queries data from multiple sources without storing or copying it; this method is more flexible and dynamic than data consolidation but requires more complex and secure data infrastructure. Lastly, data transformation converts or transforms data from one format or structure to another; this method is useful for ensuring data compatibility and standardization but requires more data processing and validation.

3 Clean and validate your data

Before you combine your data, you need to clean and validate it to ensure its accuracy, completeness, and relevance. Therefore, you should check for any missing, duplicate, or incorrect data and fill in or correct them accordingly. Additionally, you should look for any outliers or anomalies and investigate or remove them as appropriate. Furthermore, it’s important to check for data inconsistencies or conflicts and resolve them with a common rule or logic. Moreover, you should verify the relevance and timeliness of the data by excluding or updating any outdated or irrelevant information. Finally, it’s essential to check the quality and reliability of the data and verify or cross-check any questionable or suspicious records.

4 Protect and secure your data

When you combine your data, you need to protect and secure it to ensure its confidentiality, integrity, and availability. To do this, you should follow the applicable data privacy and security laws and regulations. Additionally, encryption, authentication, authorization, and auditing techniques can safeguard your data from unauthorized access or modification. Furthermore, backup, recovery, and contingency plans can prevent or minimize data loss or damage. Finally, data governance and management policies and procedures can define and monitor your data roles, responsibilities, and standards.

5 Analyze and visualize your data

After you combine your HR data, you need to analyze and visualize it to extract meaningful insights and actionable recommendations. To do this, use descriptive, inferential, and predictive analytics techniques to explore, explain, and forecast your data patterns and relationships. Additionally, apply appropriate statistical methods and tools to test your data hypotheses and assumptions. You should also use clear, concise, and consistent data definitions and metrics to communicate your data results and findings. Furthermore, use relevant, engaging, and interactive data visualizations to display your data trends, comparisons, and distributions. Finally, storytelling and narration techniques can help convey your data insights and implications. Following these tips can help you combine your HR data more effectively and efficiently.

6 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?