In order to effectively implement people analytics, it is essential to establish robust processes for
data collection, storage, and management. This chapter will discuss best practices for collecting and
maintaining HR data, as well as strategies for ensuring data security and compliance.
Effective data collection is the foundation of any people analytics initiative. Organizations must
ensure that they are gathering accurate, complete, and timely HR data from various sources,
HR Information Systems (HRIS): Centralized databases that store employee data, such as demographic information, job history, and performance records.
Applicant Tracking Systems (ATS): Platforms used to manage the recruitment process, capturing data on applicants, interview outcomes, and hiring decisions.
Employee Surveys and Assessments: Tools for gathering feedback on employee engagement,satisfaction, and performance.
Learning Management Systems (LMS): Platforms used to deliver and track employee training and development activities.
Once data is collected, it must be securely stored and easily accessible for analysis. Key
considerations for data storage include:
Centralization: Consolidate HR data into a centralized repository, such as a data warehouse or cloud-based storage system, to simplify data management and ensure consistency across the organization.
Scalability: Choose storage solutions that can accommodate growth in data volume and complexity as your people analytics initiatives evolve.
Integration: Ensure seamless integration between your data storage system and other HR platforms, such as HRIS, ATS, and LMS, to facilitate data sharing and analysis.
Example of storing and intergrating HR data into Power BI.
Tip: Ensure data quality and consistency by establishing clear data governance protocols and
investing in tools that facilitate seamless data integration and analysis. Clean, accurate data is
critical for generating reliable insights.
Effective data management ensures that HR data remains accurate, up-to-date, and consistent. Implement processes and guidelines for data entry, validation, and maintenance, including:
Data Entry: Standardize data entry procedures, including the use of templates, naming conventions, and validation rules, to minimize errors and inconsistencies
Data Validation: Implement regular data audits and quality checks to identify and correct errors, duplicates, and missing information.
Data Maintenance: Establish protocols for updating and archiving employee data, ensuring that records remain current and relevant.
DATA SECURITY AND COMPLIANCE
Protecting sensitive HR data is critical for maintaining employee trust and complying with data
protection regulations. Develop a comprehensive data security strategy that includes:
Acess Controls: Implement role-based access controls to restrict access to sensitive HR data, ensuring that only authorized personnel can view, edit, or delete records.
Encryption: Use encryption technologies to protect data during storage and transmission, preventing unauthorized access or disclosure.
Data Privacy: Develop and enforce data privacy policies that outline how employee data can be collected, used, and shared, in compliance with relevant regulations such as GDPR or CCPA.
Tip: While building a data warehouse or data mart has traditionally been the go-to approach in many IT departments, modern cloud architectures can simplify the process and ensure that security and compliance standards are met. By leveraging cloud-based solutions and DPA (Digital Process Automation), you can streamline data management, reduce infrastructure costs, and maintain high levels of data protection in line with your organization’s requirements.
By establishing robust processes for data collection, storage, and management, organizations can lay
the groundwork for successful people analytics initiatives. In the next chapter, we will explore
strategies for analyzing and interpreting HR data, including the use of advanced analytics techniques
and data visualization tools.