Organizations can use a variety of data sources to support their people analytics initiatives, and the choice of data sources will depend on the specific goals and objectives of the initiative. It is important to ensure that the data used is accurate, relevant, and up-to-date to ensure that the insights generated from the data can be trusted.
There are several types of data that can be used for people analytics, including:
- Structured Data: This type of data is organized into fixed fields, and can be easily analyzed using tools such as spreadsheets and databases. Examples of structured data include demographic information, compensation data, and performance data.
- Unstructured Data: This type of data is unorganized and cannot be easily analyzed using traditional tools. Examples of unstructured data include email, chat logs, and social media posts.
- Semi-Structured Data: This type of data contains elements of both structured and unstructured data, and can be challenging to analyze. Examples of semi-structured data include resumes and performance reviews.
There are several sources of data that can be used for people analytics, including:
- Employee Data: Employee data includes information such as demographic information, compensation data, and performance data.
- Recruitment Data: Recruitment data includes information such as resumes, interview notes, and candidate assessments.
- Workforce Data: Workforce data includes information such as employee turnover, absenteeism, and overtime.
- Survey Data: Survey data includes information collected through employee surveys, exit interviews, and engagement surveys.
- External Data: External data includes information such as market trends, competitor data, and demographic information.
- Social Media Data: Social media data includes information collected from platforms such as Twitter, LinkedIn, and Facebook.
- Operational Data: Operational data includes information such as time and attendance data, project data, and customer service data.
Uses
Data can provide valuable insights into HR initiatives, and can be used to inform decision making, measure the impact of initiatives, and evaluate their success. By using data effectively, organizations can make more informed decisions, increase the effectiveness of their initiatives, and ultimately drive business value.
Data is a critical component of people analytics and has several uses in the field, including:
- Talent Management: Data can be used to support talent management initiatives such as performance management, succession planning, and employee development.
- Recruitment: Data can be used to support recruitment initiatives such as candidate selection, onboarding, and retention.
- Workforce Planning: Data can be used to support workforce planning initiatives such as forecasting future workforce needs, analyzing workforce demographics, and identifying workforce gaps.
- Employee Engagement: Data can be used to support employee engagement initiatives by identifying drivers of employee engagement and areas for improvement.
- Diversity and Inclusion: Data can be used to support diversity and inclusion initiatives by providing insights into the representation of different demographic groups within the organization.
- Compensation: Data can be used to support compensation initiatives by providing insights into compensation trends, pay equity, and market competitiveness.
- Culture: Data can be used to support culture initiatives by providing insights into cultural norms, values, and beliefs.
- Organizational Effectiveness: Data can be used to support organizational effectiveness initiatives by identifying areas for improvement, measuring progress, and determining the impact of changes.