The use of data analysis techniques to improve hiring processes and outcomes.

Quantifiable metrics used to evaluate the success of recruitment strategies.

The graphical representation of data to help stakeholders understand complex information.

Specific data points that measure the effectiveness of recruitment efforts.

Decisions made based on data analysis rather than intuition or personal experience.

The process of identifying and attracting potential job candidates.

Software that automates the hiring process, including resume screening and candidate management.

The process of making sense of collected data to extract meaningful insights.

The practice of examining data over time to identify patterns or trends.

Information that is delivered immediately after collection, allowing for prompt decision-making.

A visual display of key metrics and data points relevant to recruitment strategies.

Techniques that use historical data to forecast future recruitment trends.

Comparing recruitment metrics against industry standards or best practices.

A strategic planning tool used to identify strengths, weaknesses, opportunities, and threats.

The overall experience a user has with a product, including ease of use and satisfaction.

The process of involving individuals or groups affected by recruitment decisions.

The accuracy and consistency of data over its lifecycle.

Non-numerical information that provides insights into candidates' experiences and perceptions.

Numerical information that can be measured and analyzed statistically.

A subset of AI that enables systems to learn from data and improve over time.

The overall perception job seekers have of the recruitment process.

An iterative approach to project management that emphasizes flexibility and collaboration.

Groups composed of members from different departments working towards a common goal.

Protecting data from unauthorized access and breaches.

Adhering to legal and regulatory requirements in recruitment practices.