Your Employee Onboarding Data Template

This attribute describes a single step or event within the larger onboarding process. Examples include 'Offer Accepted', 'Background Check Completed', or 'IT Provisioning Requested'. A clear and consistent naming convention for activities is crucial for building an accurate and understandable process map.

In analysis, the Activity Name is used to visualize the process flow, identify bottlenecks between specific steps, and measure the frequency of each activity. It forms the backbone of the process map and allows analysts to understand what is happening at each stage of the onboarding journey. Analyzing the sequence and frequency of activities helps uncover process deviations and inefficiencies.

It defines the individual steps of the process, enabling the creation of a process map and the analysis of workflow, bottlenecks, and deviations.

Sourced from event logs, task management modules, or audit trails within HR, IT, and onboarding systems.

Event Time is the timestamp that records the exact moment an activity happened. This timestamp is critical for ordering events chronologically and for calculating durations between different steps in the process. It should represent the completion time of an activity or the occurrence time of an instantaneous event.

This attribute is the foundation for all time-based analysis in process mining. It is used to calculate key performance indicators such as cycle times, wait times, and processing times. By analyzing the timestamps, one can identify bottlenecks, measure process performance against service level agreements, and understand the temporal distribution of activities.

This timestamp is essential for ordering events, calculating all time-related metrics like cycle time and wait time, and discovering process bottlenecks.

Found in system logs or transaction records associated with each onboarding task or milestone, often labeled as a completion date or creation date.

The Onboarding Case ID serves as the primary key for tracking the entire onboarding journey of one new hire from start to finish. Each distinct onboarding process, from the initial offer acceptance to the completion of all required tasks, is assigned a unique identifier. This ID links together all related events, tasks, and milestones.

In process mining, this attribute is fundamental for case correlation. It allows the software to reconstruct the end-to-end process flow for each new hire, connecting disparate events like 'Background Check Initiated' and 'Equipment Delivered' into a single, coherent timeline. Analyzing processes at the case level is impossible without a reliable case identifier.

This is the essential key for connecting all related events for a single new hire's onboarding journey, making end-to-end process analysis possible.

Typically generated by the primary HR or onboarding management system when a new hiring process is initiated for an employee.

This attribute provides a timestamp that marks the last time the data was synchronized from the source system. It is a metadata field that is essential for understanding the freshness and recency of the data being analyzed. This is different from the Event Time, which records when the business activity actually occurred.

The Last Data Update timestamp is important for data governance and for ensuring that analyses are based on current information. It helps dashboard users understand if they are looking at real-time data or a snapshot from a specific point in time. It is also critical for debugging data pipelines and verifying that data extraction processes are running as scheduled.

It indicates the freshness of the data, which is essential for data governance and ensuring that process analysis reflects the most current state of operations.

This timestamp is typically generated and recorded by the data extraction, transformation, and loading (ETL) tool or data pipeline during the data ingestion process.

This attribute identifies the originating information system for each event in the dataset, such as an HRIS, an Applicant Tracking System (ATS), or an IT Service Management (ITSM) tool. Since onboarding processes often span multiple systems, tracking the source is vital for data validation and for understanding cross-system interactions.

In a process mining analysis, knowing the source system helps in diagnosing data quality issues and understanding handoffs between different platforms. For instance, analyzing the time delay between an activity in the HR system and a corresponding activity in the IT system can reveal integration problems or manual data transfer delays. It provides context for why certain process steps behave the way they do.

It identifies the origin of each event, which is crucial for troubleshooting data quality and analyzing process handoffs between different corporate systems.

This information is typically added during the data extraction, transformation, and loading (ETL) process, or it may exist as a standard field in a centralized data warehouse.

This attribute specifies the organizational unit, such as 'Sales', 'Engineering', or 'Finance', to which the new hire belongs. It provides crucial business context for each onboarding case.

In process mining analysis, the department is a key dimension for filtering and comparison. Analysts can use it to segment onboarding processes to understand how performance varies across the organization. For example, you can compare the average onboarding cycle time for the Engineering department versus the Marketing department to identify best practices or areas needing support. It also helps in understanding resource allocation and identifying department-specific bottlenecks in the onboarding journey.

It allows for the comparison of onboarding efficiency, process variations, and new hire experiences across different business units, highlighting opportunities for standardization.

Typically sourced from the new hire's employee profile or job requisition data in the HR system.

The Employee ID is the unique code assigned to a new hire upon their official entry into the company's human resources information system (HRIS). This identifier is distinct from the Onboarding Case ID and serves as the primary key for the employee's permanent record.

While the Onboarding Case ID tracks the process, the Employee ID links the onboarding activities to a specific individual. This allows for long-term analysis, such as correlating onboarding experiences with future employee performance, engagement, or retention. It is also used to enrich the onboarding data with other employee attributes like tenure or role changes from the main HR system.

It connects the onboarding process to the permanent employee record, enabling long-term analysis of how onboarding impacts employee retention and performance.

Sourced from the core Human Resources Information System (HRIS) or employee master data file once the new hire's profile is created.

This attribute is the official date on which the new hire begins their employment. It is a critical milestone in the onboarding process and serves as a key reference point for many performance metrics.

The Employee Start Date is used to separate the pre-start and post-start phases of onboarding. It is essential for calculating KPIs like 'First Day Readiness Rate' and 'Pre-Employment Cycle Time'. By comparing the timestamps of activities like 'Equipment Delivered' to the start date, companies can measure how effectively they prepare for a new hire's arrival. This date acts as a crucial deadline for all pre-boarding activities.

It is a critical date that separates pre-boarding from post-boarding activities and is essential for measuring 'First Day Readiness' and other key KPIs.

This is a fundamental date field stored in the employee's contract or profile within the Human Resources Information System (HRIS).

The Event End Time marks the moment a durational activity is completed. While many onboarding events are instantaneous, some tasks like 'Background Check' or 'Mandatory Training' have a distinct start and end. This attribute captures the end point of such tasks.

In process mining, having both a start and end time allows for precise calculation of activity processing time. This is different from wait time, which is the duration between activities. Analyzing processing time helps identify which specific tasks are taking the longest to complete, rather than just identifying long delays between steps. It is crucial for creating accurate resource utilization models and for detailed bottleneck analysis within specific tasks.

It enables the precise calculation of how long specific activities take to complete (processing time), which is key for resource analysis and identifying inefficient tasks.

Typically found in task management or workflow systems where an activity has distinct states, such as 'In Progress' and 'Completed'.

This attribute identifies who or what performed a given activity. The performer could be a specific user like the hiring manager, a role like 'IT Support', or an automated system or bot. This information is key to understanding resource involvement and handoffs in the process.

Analyzing the Event Performer helps to create a social network or organizational map showing interactions and workloads. It can pinpoint which departments or individuals are bottlenecks and highlight opportunities for automation by identifying repetitive, manual tasks. Understanding who does what is fundamental to resource optimization and improving cross-functional collaboration.

It reveals who performs each task, enabling analysis of workload distribution, handoff efficiency, and opportunities for automation.

Found in the audit trail or event log data of the source system, often recorded as 'User ID', 'Changed By', or 'System Agent'.

The Hiring Manager attribute identifies the direct supervisor of the new hire. This is the person primarily responsible for the new employee's integration, training, and initial performance.

In process mining, analyzing activities by Hiring Manager can highlight variations in managerial engagement and effectiveness during onboarding. It can help identify managers who are highly efficient at completing their onboarding tasks versus those who may need additional support or training. This information is key to improving manager accountability and the overall consistency of the new hire experience, which is heavily influenced by the direct manager.

It helps assess the performance and consistency of managers in executing their onboarding responsibilities, directly impacting new hire experience and time to productivity.

Sourced from the job requisition data or the employee's reporting structure defined in the HR system.

The Job Title attribute defines the official title of the position the new hire is filling, such as 'Software Engineer', 'Account Manager', or 'HR Generalist'. This information adds a layer of granularity to the analysis of the onboarding process.

Analyzing the process by Job Title or job level can reveal important patterns. For instance, the onboarding process for executive roles might be significantly different and longer than for entry-level positions. This attribute allows for the creation of tailored process views for different employee cohorts, ensuring that comparisons are made between similar roles and helping to design role-specific onboarding paths.

Enables analysis of how the onboarding process differs for various roles, helping to identify needs for role-specific process optimization and customization.

Sourced from the job requisition or the employee's position details in the Human Resources Information System (HRIS).

This attribute specifies the geographical or physical location where the new hire will be based. This could be a city, country, specific office building, or a designation like 'Remote'.

Location is a critical dimension for analysis, as onboarding processes can vary significantly based on geography due to different legal requirements, office logistics, or regional management practices. By filtering or comparing processes by location, organizations can identify regional inconsistencies, ensure compliance with local regulations, and standardize the onboarding experience where appropriate. It is particularly important for global companies aiming to balance local needs with corporate standards.

It allows for analysis of geographical variations in the onboarding process, which is crucial for ensuring compliance and standardizing the experience in a global organization.

This information is usually stored in the employee's profile within the HR system and is often determined by the job requisition.

This attribute categorizes the new hire's employment arrangement with the company. Common values include 'Full-Time', 'Part-Time', 'Contractor', or 'Intern'. The type of employment often dictates the complexity and requirements of the onboarding process.

Analyzing the process by Employment Type is essential for understanding process variations. For example, the onboarding for a contractor may be significantly shorter and involve different legal and IT steps compared to a full-time employee. Segmenting the analysis by this attribute ensures that performance metrics are evaluated fairly and helps organizations optimize distinct onboarding paths for different types of workers.

It enables segmentation of the onboarding process for different worker types, ensuring fair performance comparisons and helping to optimize distinct process paths.

This is a core attribute found in the employee's job or position data within the main HR system.

This attribute contains the full name of the new hire. It provides a human-readable identifier for each onboarding case, making it easier for users to investigate specific instances without needing to cross-reference ID numbers.

While not typically used for aggregated process analysis, the New Hire Name is invaluable for operational monitoring and drilling down into individual cases. For example, a live dashboard tracking onboarding progress might display the names of new hires who are stuck at a particular stage, allowing HR personnel or managers to intervene directly. It adds a crucial layer of usability to process mining dashboards.

Provides a human-readable identifier for individual cases, making it easier for managers and HR staff to track and investigate specific onboarding journeys.

Sourced from the new hire's profile in the Applicant Tracking System (ATS) or Human Resources Information System (HRIS).

This attribute provides a high-level summary of where the onboarding case stands in its lifecycle. Typical statuses include 'In Progress', 'Completed', 'Canceled', or 'On Hold'. This is often a case-level attribute that changes as the process progresses.

Onboarding Status is particularly useful for operational monitoring and creating high-level dashboards. It allows stakeholders to quickly see the number of onboardings that are active, completed, or facing issues. In process mining, it can be used to filter for incomplete or canceled cases to perform root cause analysis and understand why some onboarding processes fail to complete successfully.

It provides a high-level view of case progress, enabling operational monitoring and root cause analysis of incomplete or canceled onboarding processes.

This status is typically managed and updated in the primary onboarding or HR workflow management system.