Your Recruitment & Talent Acquisition Data Template

This attribute describes a specific event or stage in the recruitment lifecycle, such as 'Application Received', 'Interview Scheduled', or 'Offer Extended'. Each recorded activity represents a point in time where the application's status changed or a significant action was taken.

In process mining analysis, the sequence of activities forms the basis of the process map. It allows analysts to visualize the actual flow of the recruitment process, discover common pathways, and identify deviations from the standard procedure. Analyzing activities is crucial for understanding the recruitment funnel, identifying where candidates drop off, and measuring the time spent in each stage.

It defines the steps of the process, allowing for the visualization of the recruitment funnel and the identification of bottlenecks or deviations.

Found in event logs, status change records, or activity history tables related to job applications.

This timestamp indicates the precise moment an activity occurred or was logged in the system. For activities that have a duration, this marks the start, while for instantaneous events, it represents the time of occurrence. Accurate timestamps are critical for reconstructing the chronological order of events for each job application.

This attribute is the foundation for all time-based analysis in process mining. It is used to calculate the time between activities (cycle time), the duration of specific stages, and the total time to hire. By analyzing these timestamps, organizations can identify delays, measure performance against service level agreements, and pinpoint opportunities to accelerate the hiring process.

This is the primary timestamp used to order events chronologically and calculate all time-based metrics, such as cycle times and total time to hire.

Typically located alongside the activity name in event logs or transaction records within the recruitment system.

The Job Application ID uniquely identifies a single instance of a candidate applying for a job requisition. Each application process, from initial submission to a final decision like 'Hired' or 'Rejected', is tracked under this ID. It acts as the thread connecting all related activities, timestamps, and data points for one application journey.

In process mining, this attribute is fundamental for case analysis. It allows the tool to reconstruct the end-to-end process flow for each application, visualizing different paths candidates take. By grouping all events under a common Job Application ID, analysts can accurately measure case durations, identify bottlenecks in specific application lifecycles, and compare process variants.

This ID is essential for tracking each application's journey from start to finish, enabling the calculation of key metrics like Time to Hire and the analysis of process variations.

Typically found in the main job application or candidate activity records in the recruiting system.

This attribute marks the date and time when the data was last synchronized or pulled from the source application. It serves as a metadata field that reflects the freshness of the information being analyzed. This is distinct from the activity timestamp, which records when the business event actually happened.

In a process mining context, this timestamp is vital for maintaining data integrity and understanding the recency of the analysis. It helps users know if they are looking at up-to-date information, which is especially important for ongoing monitoring and operational dashboards. It can also be used to filter out stale data or to trigger data pipeline refreshes.

This timestamp ensures users understand the freshness of the data, which is critical for the relevance and accuracy of ongoing process monitoring and analysis.

Typically added by the data integration or ETL (Extract, Transform, Load) tool during the data loading process.

This attribute identifies the system of record, such as the Applicant Tracking System (ATS) or Human Capital Management (HCM) platform, where the recruitment activities are managed and recorded. In environments with multiple systems, this field helps distinguish the origin of different data points, ensuring clarity and traceability.

For process mining analysis, knowing the source system is crucial for data validation and governance. It helps in understanding the context of the data and can be used to filter analyses to specific systems if multiple are integrated. This is particularly important during data preparation and when troubleshooting discrepancies, as it points to the correct place to investigate data quality issues.

It provides context about the data's origin, which is crucial for data governance, validation, and troubleshooting in multi-system environments.

Often added during the data extraction process or available as a standard field in data warehouses.

This attribute captures the conclusion of activities that span a period, such as an interview or a background check. While many recruitment activities are recorded as single points in time using a start timestamp, having an end time allows for precise duration measurement of specific process steps.

For process analysis, the end time enables the calculation of activity-level durations, distinguishing between waiting time and processing time. For example, you can measure the exact duration of an interview, not just the time between scheduling it and receiving feedback. This provides a more granular view of where time is spent and helps identify inefficiencies within specific tasks, not just between them.

It enables the precise calculation of the duration of individual activities, helping to differentiate between active processing time and idle waiting time.

Found in event or activity logs, often in the same record as the start time, for systems that track activity durations.

This attribute tracks the origin of a job application, indicating how the candidate found out about the role and applied. Common sources include career websites, employee referrals, direct sourcing by recruiters, LinkedIn, or university job fairs.

This is a critical attribute for evaluating the effectiveness of different talent acquisition strategies. By analyzing the volume and quality of candidates from each source, organizations can calculate the return on investment for their sourcing channels. Process mining can show which sources yield candidates that progress furthest in the funnel or result in the most hires, helping to optimize recruitment marketing spend.

It is essential for measuring the effectiveness and ROI of different sourcing channels, helping to optimize recruitment marketing and strategy.

Usually captured at the time of application submission, either through tracking links or self-reported by the candidate.

This attribute indicates the final state of an application within the recruitment process. Common statuses include 'Hired', 'Rejected', 'Offer Rejected', or 'Withdrawn by Candidate'. It represents the conclusion of the process for that specific application case.

In process mining, the final status is crucial for outcome-based analysis. It allows for the filtering of process maps to compare the journeys of hired candidates versus rejected ones. This helps identify the 'happy path' and understand what process patterns lead to successful outcomes. It's also the basis for calculating key metrics like offer acceptance rates and candidate drop-off rates at different stages.

Defines the final outcome of each case, enabling analysis of what process variations lead to successful hires versus rejections or withdrawals.

Found in the main job application record, representing the final disposition.

This attribute identifies the organizational unit, such as 'Sales', 'Engineering', or 'Human Resources', that is hiring for the open position. It provides a way to structure the analysis of recruitment processes according to the company's organizational hierarchy.

Analyzing recruitment data by department is essential for understanding how hiring performance varies across the business. It helps identify which departments have the most efficient hiring processes and which may need support. This attribute is used to create departmental dashboards, compare KPIs like time to hire and offer acceptance rates between teams, and allocate recruiting resources effectively.

Enables analysis of recruitment efficiency and workload by business unit, helping to identify department-specific trends, challenges, and resource needs.

Sourced from the job requisition or position master data associated with the application.

The Hiring Manager is the individual who ultimately makes the hiring decision and to whom the new employee will report. They are a key stakeholder in the recruitment process, responsible for defining job requirements, interviewing candidates, and providing feedback.

Analyzing process performance by Hiring Manager can reveal important insights into process efficiency. For example, it can highlight managers who are slow to provide interview feedback, leading to delays, or those who have very high offer acceptance rates. This information can be used to provide targeted training or support to managers to help streamline the overall hiring process.

Helps identify bottlenecks and delays related to specific hiring managers, such as slow feedback times, which directly impacts the overall time to hire.

Sourced from the job requisition data associated with the application.

A job requisition is a formal request to fill a vacant position. The Job Requisition ID is the unique code assigned to this request, tracking it from approval through to fulfillment. A single requisition can have many associated job applications.

In process mining, this ID is a powerful attribute for aggregation and filtering. Analysts can use it to analyze the recruitment process for a specific role, compare the efficiency of hiring for different types of positions, or assess the total volume of applications per opening. It helps answer questions like 'Which job requisitions take the longest to fill?' and 'What is the average number of applicants per role?'.

It allows for grouping and analyzing all applications related to a single job opening, enabling performance comparisons across different roles or departments.

Located in the job application record, often linked from the job requisition or position master data.

This attribute specifies the official title of the job opening, such as 'Senior Software Engineer' or 'Marketing Manager'. It provides essential business context to the recruitment process, describing the nature of the role being filled.

Job Title is a critical dimension for analysis. It allows stakeholders to segment recruitment performance by role seniority, function, or specialization. For example, it can be used to compare the time to hire for technical roles versus administrative roles, or to analyze the effectiveness of different sourcing channels for executive positions. This segmentation is key to uncovering role-specific bottlenecks and tailoring recruitment strategies.

Provides crucial business context, enabling performance analysis and benchmarking across different job roles, levels, and functions.

Sourced from the job requisition details associated with the job application.

This field identifies the primary individual from the talent acquisition team who is handling the recruitment process for a given application or requisition. This person is typically responsible for screening candidates, scheduling interviews, and communicating with stakeholders.

In process mining, the Recruiter attribute is key for analyzing team and individual performance. It allows for the creation of workload balancing dashboards, showing how many applications each recruiter is managing. It also enables the comparison of performance metrics, like time to fill or candidate quality, across different recruiters to identify best practices and areas for coaching or process improvement.

Allows for workload analysis and performance measurement of individual recruiters and the talent acquisition team as a whole.

Typically found in the job application or job requisition records.

This attribute distinguishes between applicants who are current employees of the organization (internal) and those who are not (external). This is a fundamental segmentation, as the recruitment process, timelines, and policies often differ significantly for these two groups.

Analyzing processes based on candidate type is crucial for understanding internal mobility and external hiring effectiveness. Process mining can be used to compare the time to hire, cost per hire, and success rates for internal versus external candidates. This helps evaluate the performance of internal mobility programs and ensure that both hiring paths are efficient and effective.

Differentiates internal and external candidates, whose hiring processes often differ, enabling comparative analysis of internal mobility versus external hiring efficiency.

Often derived by checking if the candidate's ID or email exists in the employee master data. Some systems may have a dedicated flag.

This attribute specifies the physical work location for the job requisition. For remote positions, it might indicate a region or be marked as 'Remote'. This provides a geographical dimension to the recruitment data.

In process mining, location is a key attribute for regional analysis. It allows companies to compare hiring cycle times, sourcing channel effectiveness, and offer acceptance rates across different offices or countries. This can highlight regional differences in labor markets, recruitment team performance, or process compliance, enabling more tailored management and strategy.

Enables geographical analysis of recruitment performance, helping to compare hiring efficiency and challenges across different regions or offices.

Found in the job requisition details associated with the application.

This attribute records the monetary value of the compensation package offered to a candidate. It is a key piece of data in the final stages of the recruitment process. The value is typically recorded in a local currency.

In a process mining view, analyzing the offer amount can provide valuable context. It can be correlated with offer acceptance and rejection rates to understand if compensation is competitive. It also allows for analysis of compensation trends across different roles, departments, and locations. When combined with other data, it helps in evaluating salary benchmarks and ensuring equitable pay practices.

Helps analyze the competitiveness of compensation packages by correlating offer amounts with acceptance and rejection rates across different roles and locations.

Sourced from the job offer records within the recruitment or HR system.

When a decision is made not to move forward with a candidate, a reason is often recorded. This can range from 'Not a culture fit' or 'Lacks required skills' to 'Position filled by another candidate'. This attribute captures that qualitative information.

Analyzing rejection reasons provides valuable feedback on the recruitment process and job requirements. By correlating rejection reasons with application sources or interview stages, organizations can identify issues such as poorly defined job descriptions attracting unqualified candidates, or inconsistencies in interviewer assessments. This helps in refining recruitment strategies and improving the quality of the candidate pool.

Provides insight into why candidates are disqualified, helping to refine job descriptions, improve sourcing quality, and identify potential biases in the screening process.

Typically recorded by a recruiter or hiring manager when they update an application's status to 'Rejected'.