Purpose:
- Identify areas for improvement by tracking how long it takes to fill positions and hire candidates, helping reduce delays and inefficiencies.
- Improve candidate experience to increase offer acceptance rates.
- Determine the most effective sources for finding quality candidates, allowing organisations to allocate resources more effectively.
- It helps analyse the retention rates of new hires to evaluate the effectiveness of the recruitment and onboarding process, aiming to improve employee longevity.
Given the vast amount of useful employee data types available, you might be wondering where exactly you can begin to collect all this information.
employee data collection can be done through a variety of sources. Here are some key sources:
- HR Information Systems (HRIS): A centralised database that collects and stores data from various touch points throughout the employee lifecycle. HRIS can integrate data from payroll, benefits administration, performance management systems, and more.
- Applicant Tracking Systems (ATS): ATS are used during the recruitment process to collect and store resumes, cover letters, and applicant information. They help in tracking the progress of candidates through the hiring pipeline. Storing historical applicant data can be useful for understanding recruitment trends.
- Application forms and resumes: The initial source of data comes from the application process. Resumes, cover letters, and application forms provide a wealth of information about the candidate’s educational background, work history, skills, and competencies.
- Onboarding documents: When a new employee joins, they fill out various forms, such as tax forms (e.g., W-4 in the U.S.), benefits enrollment forms, and policy acknowledgement forms. These documents collect essential legal, financial, and personal information.
- Interviews: During the hiring process, interviews and assessments offer insights into a candidate’s capabilities, personality, and fit within the company culture. Behavioural assessments, skill tests, and situational interviews can also provide detailed data on a candidate.
- Employee surveys:Feedback on engagement, satisfaction, and workplace culture through anonymous surveys.
- Performance evaluations: Regular performance evaluations provide data on an employee’s achievements, strengths, areas for improvement, and career development plans. These can include manager assessments, peer reviews, and self-assessments.
- Time tracking and management software: Tools that monitor when employees clock in and out, their work hours, absences, and leave balances.
- Training and development records: Records of completed training sessions, certifications achieved, and skills acquired through company-provided or external professional development opportunities.
- Exit interviews: When employees leave the company, exit interviews can provide valuable information on their reasons for leaving, their experiences at the company, and suggestions for improvement.
Now that you understand how to collect employee data, it’s important to understand how to store and manage it compliantly and securely due to its sensitive nature.
Best Practices in Employee Data Management
Managing employee data effectively and ethically is a must in today’s workplace. Here are some best practices for managing employee data:
1. Data Privacy and Compliance
- Understand Legal Requirements: Familiarise yourself with local and international data protection laws (like GDPR in Europe, CCPA in California, etc.) that apply to your organisation. Ensure all employee data management practices comply with these regulations.
- Privacy Policy: Develop a clear privacy policy that outlines how employee data is collected, used, stored, and shared. Ensure employees have easy access to this policy.
2. Data Collection, Storage, and Management
- Minimise Data Collection: Collect only the data necessary for legitimate business purposes. Do not collect sensitive information unless necessary.
- Secure Storage Solutions: Use secure, encrypted databases to store employee data. Frequently update security measures to guard against breaches.
- Data Lifecycle Management: Have clear policies on the retention, archiving, and deletion of employee data. Make sure data is kept no longer than absolutely needed.
3. Access Control
- Limit Access: Ensure that only authorised personnel have access to employee data, and that access is based on the principle of least privilege (i.e., employees should only have access to the information necessary for their job functions).
- Authentication and Authorisation: Implement strong authentication methods and regularly review access permissions.
4. Data Accuracy and Integrity
- Regular Updates: Encourage employees to update their information regularly and provide easy ways for them to do so. Regularly audit the data for accuracy and completeness.
- Cross-validation with Multiple Data Sources: To further ensure the accuracy and integrity of employee data, employ cross-validation techniques by comparing information across multiple data sources. When discrepancies are found, investigate to determine the most accurate information before making any updates.
5. Transparency and Communication
- Open Communication: Communicate clearly with employees about how their data is being used and the measures in place to protect their information.
6. Data Use and Sharing
- Purpose Limitation: Use employee data solely for the purposes for which it was collected, as stated in your privacy policy.
- Third-Party Data Sharing: Be cautious when sharing data with third parties. Ensure they have strong data protection practices in place and are compliant with relevant laws.
7. Handling Data Breaches
- Incident Response Plan: Create and regularly update an incident response plan. This plan should include steps to take in the event of a data breach, including notifying affected individuals and regulatory bodies as required by law.
8. Regular Audits and Assessments
- Conduct Regular Audits: Regularly audit your data management practices and security measures to identify and address potential vulnerabilities.
- Risk Assessment: Perform risk assessments to understand the potential risks associated with employee data and to implement appropriate controls to mitigate these risks.
If you’re using an external vendor to collect and store employee information, review their compliance certifications and privacy policies.
Using People Analytics Software to Make Data-Driven Decisions
If you have read this far, well done! However, collecting, storing, and managing employee data is just scratching the surface. You need software that leverages the latest technology, AI, and data analytics capabilities to truly harness the full potential of all this data.
That’s because for meaningful analysis, different types of data must be interconnected. For instance:
- Understanding the influence of compensation and benefits on employee retention, satisfaction, and recruitment requires integrating these datasets.
- Similarly, to assess whether training programs lead to performance enhancements, performance metrics need to be analysed alongside training data.
These are just a few examples underscoring the necessity of a unified platform that consolidates varied data points, serving as a single source of truth. A people analytics tool makes it quick and easy to aggregate the data through APIs and integrations.
Not only that, it also simplifies analysis with advanced reporting, dashboards, and predictive analytics. The visual representation of trends and patterns empowers HR teams to make quick, data-driven decisions – to make sure you stay competitive and fully leverage the insights employee data can offer.
Peoplebox provides OKR, Talent Management and People Analytics platform that helps companies attract, align and retain top performers. Leveraging cutting-edge Generative AI technology, we transform raw data from various work tools (SQL, Jira, Asana, Hubspot) into actionable insights. It also offers strategy execution and people-ops platform to convert those insights into tangible actions for growth and success.