Enabling Career Explorer
You can enable Career Explorer when your Employee Central data is qualified for the People Connection system to recommend career opportunities.
You’ve configured the integration settings for People Connection.
After data sync between your system and the People Connection system is successful, we provide a data quality report with multiple parameters in Manage People Connection Integration. After data training is successful, you can check one of the parameters to see if your company can use Career Explorer.
In Admin Center, go to Manage People Connection Integration.Check the data quality report.
If Recommended Roles is Ready for Use, you can go to Upgrade Center and turn on Career Explorer
Parameter Description Number of Employees The total number of employees in your tenant data Employee Data Quality Compared to total employees, the ratio of the employees that have background education and competency rating information in your tenant data Number of Positions The total number of positions in your tenant data Position Data Quality Compared to total employees, the ratio of the employees that have corresponding job code information in your tenant data Employee-Position Ratio The ratio between the number of employees and the number of positions, calculated as the number of employees divided by the number of positions. Number of Pairs The total number of employee-position pairs in your tenant data. For example, if an employee has held a position in a company, the employee and the position is regarded as a pair in the data. If an employee has held two positions in a company, the employee and one of the positions is regarded as a pair, while the employee and the other position is regarded as another pair.
The larger the number of pairs, the better the data quality.
Data Sparsity Data Sparsity indicates unpaired employee and position data in your tenant data. It is calculated as: 1 − Number of Pairs / (Number of Employees * Number of Positions).
Tip: The lower the level of data sparsity, the higher the data quality.
Sparsity Threshold Sparsity threshold is an ideal data sparsity level of your tenant data. It is calculated as: 1 − Max (Number of Employees, Number of Positions) / (Number of Employees * Number of Positions).
Note: If your data sparsity level exceeds the sparsity threshold, machine learning doesn't proceed.
Recommended Roles When Recommended Roles is Ready for Use, employees can see one or more future roles in Career Explorer. If Recommended Roles is Not Ready, your tenant data is insufficient for the system to recommend roles, and therefore, you can't turn on Career Explorer. Recommended Career Paths When Recommended Career Paths is Ready for Use, employees can see a future career path for each future role. If Recommended Career Paths is Not Ready, your tenant data is insufficient for the system to recommend career paths.
Go to Upgrade Center, select the Career Development Plan module, and enable Career Explorer.In Admin Center, go to Manage Permission Roles User Permissions Career Development Planning and grant users the permission of Career Explorer.