Advanced Analytics in Ojoor combines data from various HR sources, such as employee records, performance evaluations, training data, recruitment data, and more.
EHEADCOUNT DATA WITHIN AN ORGANIZATION
Analytics in Head Count Ojoor HRMS
Advanced Analytics in Head Count Ojoor HRMS allows for the analysis of headcount trends and patterns over time. It enables organizations to understand the fluctuations in headcount, identify peak hiring seasons or periods of attrition, and make informed workforce planning decisions.
JOINER AND LEAVER DATA
Meaningful information from joiner and leaver data
Organizations to Analyze joiner data to understand patterns and trends related to employee onboarding. Ojoor identify factors influencing employee turnover, such as job dissatisfaction, career growth opportunities, or workplace culture.
YEARS OF SERVICE DATA
Enabling data-driven decision-making and optimizing HR strategies
Advanced Analytics enables organizations to analyze the duration of employees’ service. Organizations can use Advanced Analytics to analyze years of service data to assess employee retention patterns. Advanced Analytics allows organizations to assess workforce stability based on years of service data. It helps identify departments, teams, or job roles with higher employee tenure, indicating higher stability and lower turnover rates.
LEVERAGING ANALYTICAL TECHNIQUES
overview of Advanced Analytics for Department
Advanced Analytics allows organizations to analyze the composition of their workforce across different departments. Helps identify department-specific fluctuations in headcount, such as growth or downsizing patterns. Organizations to assess the distribution and alignment of talent across departments.
MALE/FEMALE DISTRIBUTION
Analyze the composition of male and female
Distribution of genders within each band, providing insights into the representation and balance of male and female employees at various levels of the organization. Track gender diversity trends over time within each employee band.
GEOGRAPHICAL AREA
Involves analyzing and interpreting HR data related to employees
The specific results obtained from Advanced Analytics City HRMS can vary depending on the objectives and analytical models used Analyzing city-level HR data can provide insights into the demographic composition of the workforce, such as age distribution, gender balance, educational qualifications, and other relevant factors specific to that city.
DIFFERENT AGE GROUPS
Analyzing and understanding the distribution of employees across different age groups
By leveraging advanced analytics, HR professionals can extract valuable insights from age-related data within the HRMS. Some potential results and insights that can be derived from Advanced Analytics Age Group Distribution in an HRMS