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Data Template: Hire to Retire - Employee Lifecycle

Adp Workforce

Hire to Retire - Employee Lifecycle Attributes (23) Hire to Retire - Employee Lifecycle Activities (14) Extraction Guides (1)

Your Hire to Retire - Employee Lifecycle Data Template

This template provides a clear guide for extracting the necessary data to analyze your Hire to Retire, employee lifecycle process. It outlines the essential attributes to collect and key activities to track, along with practical extraction guidance. Utilize this resource to ensure you gather all relevant information for a comprehensive process mining analysis.

Recommended attributes to collect
Key activities to track
Guidance for data extraction

New to event logs? Learn how to create a process mining event log.

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Hire to Retire - Employee Lifecycle Attributes

These are the recommended data fields to include in your event log for comprehensive analysis of your employee lifecycle process.

3 Required 6 Recommended 14 Optional

	Name	Description
	Activity Name ActivityName	The name of the specific HR process step or event that occurred.
Description This attribute describes a specific milestone or task within the employee lifecycle, such as 'Employee Onboarded' or 'Performance Review Conducted'. Each recorded activity represents a single step in the overall Hire to Retire process. Analyzing the sequence and frequency of these activities is fundamental to process mining, revealing the actual process flows, variations, and bottlenecks. Why it matters It defines the steps of the process, enabling the visualization of process maps, analysis of process variants, and identification of deviations from the standard procedure. Where to get This information is derived from transaction logs or event records within different modules of ADP Workforce Now (e.g., Recruiting, HR & Benefits, Payroll). Examples New Hire Record CreatedBenefits Enrollment CompletedPromotion ApprovedTermination Initiated
	Employee ID EmployeeId	The unique identifier for an employee's lifecycle record within the organization.
Description The Employee ID serves as the unique case identifier for each individual's journey from hire to retire. All events, such as application, onboarding, performance reviews, and termination, are linked to this ID. This allows for a complete and connected analysis of an employee's entire lifecycle, tracking their progression and interactions with various HR processes over time. Why it matters This is the essential key for tracking an employee's entire journey, connecting all related activities and milestones into a single, coherent process view. Where to get This is typically the primary key for an employee record in ADP Workforce Now, often referred to as File Number or Associate ID. Examples 100523984321E-00451
	Event Timestamp EventTimestamp	The precise date and time when the activity was recorded.
Description This timestamp marks the exact moment an activity occurred or was registered in the system. It provides the chronological order of events for each employee's lifecycle. This temporal data is crucial for calculating cycle times, analyzing durations between process steps, and evaluating performance against service level agreements (SLAs). Why it matters This is the backbone of process analysis, allowing for the calculation of all time-based metrics like cycle time, waiting time, and SLA compliance. Where to get Typically found alongside every transaction or status change record in ADP Workforce Now, often labeled as a creation date or status update time. Examples 2023-01-15T09:00:00Z2023-03-20T14:35:10Z2024-05-01T11:21:00Z
	Department Name DepartmentName	The department to which the employee is assigned.
Description This attribute specifies the organizational department of the employee, such as 'Sales', 'Engineering', or 'Finance'. It is a critical dimension for analysis, allowing process metrics to be segmented and compared across different parts of the business. For instance, it is used to build the 'Employee Turnover by Department' dashboard and investigate if certain departments have longer hiring cycles or higher turnover rates. Why it matters It allows for filtering and comparing process performance across different business units, helping to pinpoint department-specific issues or best practices. Where to get This is a standard field in an employee's profile or job data within ADP Workforce Now. Examples SalesIT EngineeringHuman ResourcesFinance
	Event Completion Timestamp EventCompletionTimestamp	The date and time when an activity or task was completed.
Description While StartTime indicates when an activity began, this attribute marks its conclusion. This is particularly useful for activities that have a distinct duration, such as a background check or a review process. Having both a start and end time allows for precise calculation of the processing time for individual activities, rather than just the time between different activities. Why it matters It enables accurate measurement of activity processing times, which is critical for identifying bottlenecks at a granular level and calculating KPIs like 'Average Background Check Duration'. Where to get Consult Adp Workforce documentation. This may be captured in fields indicating a status change to 'Completed' or a record closure date. Examples 2023-01-18T17:30:00Z2023-03-21T10:00:00Z2024-05-01T11:25:00Z
	Job Title JobTitle	The employee's specific role or position within the company.
Description This attribute defines the employee's official job title, like 'Software Engineer', 'Account Manager', or 'HR Generalist'. It provides a more granular level of detail than the department for analyzing processes. It's essential for understanding how processes like onboarding, performance reviews, and promotions vary for different roles and seniority levels. Why it matters Analyzing processes by job title can reveal role-specific bottlenecks or trends, such as high turnover for a particular position. Where to get Available in the employee's job data or position management module in ADP Workforce Now. Examples Senior Software DeveloperMarketing CoordinatorRegional Sales Director
	Recruitment Source RecruitmentSource	The channel or method through which a candidate was sourced.
Description This attribute tracks the origin of a new hire, such as 'LinkedIn', 'Employee Referral', 'Company Website', or 'Recruiting Agency'. This data is essential for the 'Recruitment Source Effectiveness' dashboard and KPI. By analyzing the entire lifecycle of employees from different sources, companies can determine which channels yield the most successful, long-tenured employees, and optimize their recruitment spending. Why it matters It is key to calculating the return on investment for different recruiting channels and helps optimize talent acquisition strategy. Where to get Consult Adp Workforce documentation. This is typically managed in the recruitment or applicant tracking module of ADP. Examples LinkedInEmployee ReferralCareer FairIndeed
	Termination Reason TerminationReason	The reason provided for an employee's departure.
Description This attribute captures the reason an employee's employment ended, which can be categorized as voluntary (e.g., 'Resignation - Better Opportunity') or involuntary (e.g., 'Involuntary - Performance'). This information is vital for turnover analysis, helping to distinguish between healthy and unhealthy attrition. It provides the core data needed to understand the drivers of employee turnover and inform retention strategies. Why it matters It provides the 'why' behind employee turnover, which is critical for developing effective retention strategies and addressing root causes of attrition. Where to get This is recorded during the offboarding or termination process within ADP Workforce Now. Examples Voluntary - ResignationInvoluntary - PerformanceRetirementEnd of Contract
	User Name UserName	The name or ID of the user who executed the activity.
Description This attribute identifies the HR professional, manager, or system user responsible for completing a given process step. For example, it could show which recruiter initiated a background check or which manager approved a compensation change. Analyzing activities by user helps to identify training needs, compare performance across team members, and understand workload distribution. Why it matters It provides visibility into who performs specific tasks, enabling analysis of team performance, workload balancing, and identification of automation opportunities. Where to get This information is often available in audit logs or transaction records within ADP, frequently associated with a 'Changed By' or 'User ID' field. Examples j.doeasmithhr_system_admin
	Business Unit BusinessUnit	A larger organizational unit, often a collection of related departments.
Description The Business Unit represents a high-level segment of the company, such as 'Consumer Products' or 'Corporate Services'. This attribute provides a broader organizational context than 'Department'. Analyzing HR processes at the Business Unit level helps senior leadership understand strategic differences in workforce management and process performance across major divisions of the company. Why it matters It enables high-level strategic analysis of process performance across major company divisions. Where to get This is part of the core organizational structure defined in ADP Workforce Now. Examples Retail BankingGlobal TechnologyCorporate Functions
	Compensation Amount CompensationAmount	The monetary value associated with a compensation-related event.
Description This attribute captures the financial amount related to events like 'Compensation Change Approved' or 'Offer Accepted', representing the employee's salary or a change in salary. When analyzing compensation processes, this field allows for segmentation by salary bands or analysis of the magnitude of pay increases. It is critical for understanding compensation practices across the organization. Why it matters It enables financial analysis of compensation-related processes, such as reviewing the distribution of salary increases or bonuses. Where to get This information is stored in the compensation and payroll modules of ADP Workforce Now. Examples 750005000125000.50
	Compensation Currency CompensationCurrency	The currency of the associated compensation amount.
Description This attribute specifies the currency, for example, USD, EUR, or GBP, for the 'CompensationAmount'. For multinational organizations, this field is essential to correctly interpret and aggregate financial data. It ensures that all currency values can be properly converted to a common currency for consistent analysis across different regions. Why it matters It is crucial for accurate financial analysis in global organizations, allowing for correct aggregation and comparison of compensation data. Where to get This is typically stored alongside any monetary value in the compensation or payroll modules of ADP. Examples USDEURCAD
	Country Country	The country where the employee is legally employed.
Description This attribute indicates the country of employment for the employee. It is a critical dimension for global companies to analyze processes under different legal and cultural contexts. KPIs such as hiring cycle time, turnover rates, and SLA compliance can vary significantly from one country to another, and this attribute makes it possible to perform such comparative analysis. Why it matters It is fundamental for comparative analysis in multinational corporations, highlighting process variations due to different labor laws and market conditions. Where to get This is a standard field in an employee's personal and location information within ADP Workforce Now. Examples USAGermanyIndiaBrazil
	Employment Type EmploymentType	The employee's work arrangement, such as full-time or part-time.
Description This attribute categorizes employees based on their employment status, for example, 'Full-time', 'Part-time', 'Contractor', or 'Intern'. This dimension is valuable for comparing HR processes across different worker categories. For instance, the onboarding process for a contractor might be significantly different and faster than that for a full-time employee. Why it matters It helps in segmenting the analysis to understand how processes differ for various types of workers, ensuring fair comparisons and tailored process improvements. Where to get This is a standard field within the employee's job or employment record in ADP Workforce Now. Examples Full-TimePart-TimeContractorTemporary
	Is On Time IsOnTime	A flag indicating if an activity was completed by its SLA target date.
Description This calculated boolean attribute compares the 'EventCompletionTimestamp' with the 'SlaTargetDate'. It is set to 'true' if the activity was completed on or before the target date, and 'false' otherwise. This simplifies SLA analysis, allowing for easy creation of dashboards and KPIs that track on-time performance for critical HR processes. Why it matters It simplifies SLA monitoring by providing a clear, binary outcome for each time-sensitive task, making it easy to track and report on compliance. Where to get This is calculated during data transformation (EventCompletionTimestamp <= SlaTargetDate). Examples truefalse
	Is Rework IsRework	A flag indicating if an activity is a repetition of a previous step.
Description This calculated boolean attribute is set to 'true' if an activity occurs for a second or subsequent time within the same case, particularly after intervening steps. For example, if 'Payroll Setup Completed' is followed by a correction and another 'Payroll Setup Completed' event, the second one would be flagged as rework. This helps quantify process inefficiencies and errors that require manual correction. Why it matters It directly quantifies process inefficiency by highlighting activities that need to be repeated, pointing to quality issues or process flaws. Where to get This is calculated in the process mining tool by analyzing the sequence of activities for each case. Examples truefalse
	Last Data Update LastDataUpdate	The timestamp of the last data refresh or update from the source system.
Description This attribute indicates when the data was last extracted or updated in the process mining tool. It is essential for understanding the freshness of the analysis and ensuring that conclusions are based on current data. This is typically a single value applied to the entire dataset during each refresh. Why it matters It confirms the timeliness of the data, ensuring that any analysis reflects the most recent process activities and performance. Where to get This value is generated and stamped onto the dataset at the time of data extraction and loading. Examples 2024-06-10T05:00:00Z2024-06-11T05:00:00Z
	Location Location	The physical work location or office of the employee.
Description This attribute specifies the geographic location, such as a city, office building, or country, where the employee is based. Analyzing processes by location can highlight regional differences in efficiency, compliance, or hiring practices. For example, background check durations might vary significantly between countries due to local regulations. Why it matters It enables geographical analysis of HR processes, helping to identify regional disparities in performance and ensure compliance with local policies. Where to get This is typically part of the employee's core HR record or organizational assignment in ADP Workforce Now. Examples New York OfficeLondon, UKRemote (California)Singapore
	Manager ID ManagerId	The unique identifier for the employee's direct manager.
Description This attribute links an employee to their direct supervisor. It enables analysis of process metrics based on the managerial hierarchy. For example, one can analyze turnover rates, promotion frequencies, or performance review cycle times by manager or team, which can help identify high-performing managers or teams that may need additional support. Why it matters It allows for analysis by team or manager, helping to understand how different leadership styles or team dynamics impact HR process outcomes. Where to get This is a standard part of an employee's organizational assignment in ADP, often called 'Reports To'. Examples 800123MGR-456743901
	Processing Time ProcessingTime	The duration taken to complete a single activity.
Description This calculated metric measures the time elapsed between the start and end of a specific activity. It is derived by subtracting the 'EventTimestamp' from the 'EventCompletionTimestamp'. This attribute provides precise measurements of how long individual tasks take, which is invaluable for identifying specific bottlenecks and inefficiencies in the process, such as a slow background check. Why it matters It measures the actual work duration of activities, helping to pinpoint which specific steps are consuming the most time and are prime candidates for optimization. Where to get This is calculated during data transformation (EndTime - StartTime). Examples 2592008640003600
	SLA Target Date SlaTargetDate	The target date by which an activity should have been completed.
Description This attribute defines the expected completion date for a time-sensitive activity, such as a performance review or an onboarding task. It serves as the benchmark against which actual completion times are measured. This data is fundamental for calculating SLA compliance rates and identifying activities that are consistently delayed, helping to monitor and improve service delivery across HR functions. Why it matters It is essential for measuring SLA compliance, enabling proactive monitoring of deadlines and identifying systemic delays in the process. Where to get Consult Adp Workforce documentation. This might be a calculated field based on policy or a manually entered date in a task management module. Examples 2023-06-30T23:59:59Z2024-01-15T17:00:00Z
	Source System SourceSystem	The system from which the event data was extracted.
Description This attribute identifies the origin of the data, which is 'Adp Workforce' in this case. In broader analyses that might combine data from multiple systems (e.g., a separate ATS), this field is critical for data lineage and troubleshooting. It ensures clarity on where each piece of process information comes from. Why it matters It provides crucial context about data origin, which is important for data validation, governance, and understanding process integrations. Where to get This is typically a static value added during the data extraction process to label the dataset's origin. Examples ADP Workforce NowADP Vantage HCM
	Tenure Duration TenureDuration	The total length of an employee's service, calculated at termination.
Description This calculated metric measures the total time between an employee's hire date ('Employee Onboarded' event) and their termination date ('Termination Initiated' event). It is primarily used for turnover analysis, such as calculating the 'Early Turnover Rate' KPI. Understanding tenure helps identify if the organization is losing new hires quickly, which might indicate issues with onboarding or job fit. Why it matters It is essential for analyzing employee retention and calculating turnover KPIs, providing insight into when and why employees leave. Where to get This is calculated during data transformation by finding the difference between the termination and hire event timestamps for a given employee. Examples 315360007776000015552000

Required Recommended Optional

Hire to Retire - Employee Lifecycle Activities

These are the key process steps and milestones to capture in your event log for accurate process discovery and optimization.

6 Recommended 8 Optional

	Activity	Description
	Employee Onboarded	This activity signifies the employee's official first day and their transition to an 'Active' employment status in the system. It is captured when the employee's designated hire date is reached and their status is updated accordingly.
Why it matters This is a critical milestone that marks the beginning of the employee's active tenure. It serves as the trigger for payroll, benefits, and other time-sensitive post-hire processes. Where to get Inferred from the employee's status field changing to 'Active'. This event aligns with the employee's official 'Hire Date' stored in their employment record. Capture Identify the timestamp when the 'Employment Status' field for an employee changes to 'Active'. Event type inferred
	Employee Record Terminated	The final activity in the lifecycle, where the employee's status officially changes to 'Terminated' on their last day. This event is captured when the effective date of the termination action is reached.
Why it matters This event serves as the definitive end of the employee's tenure. It is essential for calculating final employee lifecycle duration, analyzing turnover trends, and confirming the process conclusion. Where to get This is an inferred event based on the 'Effective Date' of the 'Termination' action in the employee's job history. The employee's status officially changes on this date. Capture Use the effective date of the final 'Termination' action in the employee's job data record. Event type inferred
	New Hire Record Created	This activity marks the creation of an employee profile in ADP Workforce, which typically occurs after a candidate accepts a job offer. The system captures this event when a new employee is formally entered, assigning them an Employee ID and setting a future hire date.
Why it matters As the definitive start of the employee lifecycle, this event is crucial for calculating the overall time-to-hire and analyzing the initial stages of the onboarding process. It establishes the baseline for all subsequent employee activities. Where to get This event is typically inferred from the creation date of the employee's primary profile or employment record in the core HR tables of ADP Workforce. It corresponds to the initial 'Hire' action log. Capture Use the creation timestamp or the earliest effective-dated 'Hire' action for the Employee ID. Event type inferred
	Performance Review Conducted	This activity marks the completion of a formal performance review cycle for an employee. It is typically captured when a manager or HR representative finalizes the review form in ADP's performance management module.
Why it matters Tracking performance reviews is essential for monitoring talent management processes, ensuring compliance with review cycle policies, and identifying correlations between performance and career progression or turnover. Where to get This is an explicit event captured in ADP's performance management module. Look for a 'Review Completed' status, a final approval date, or a submission timestamp on the performance review form. Capture Use the timestamp associated with the final status of a performance review form (e.g., 'Completed', 'Closed'). Event type explicit
	Promotion Approved	This activity signifies that an employee's promotion has been officially approved and recorded in the system. It is captured as a specific type of job data change with an associated effective date.
Why it matters Tracking promotions is fundamental to analyzing internal mobility, career pathing, and talent retention. It allows for the measurement of promotion velocity and helps identify bottlenecks in career progression. Where to get This is an effective-dated event in the employee's job history data. It is identified by a specific 'Action/Reason' code, such as 'PRO' for promotion, along with the effective date of the change. Capture Filter the employee's job history for records with an action code corresponding to 'Promotion'. Event type explicit
	Termination Initiated	This activity represents the formal initiation of the offboarding process for an employee. It is typically recorded when a termination action with a future effective date is entered into ADP by a manager or HR.
Why it matters This is a key milestone signaling the beginning of the end of the employee lifecycle. It triggers all subsequent offboarding activities and is the primary event for analyzing turnover rates and reasons. Where to get This is an effective-dated event in the employee's job history. It is captured by an action code for 'Termination' being entered, with the timestamp being when it was entered, not when it's effective. Capture Use the entry date of the future-dated 'Termination' action in the job history table. Event type explicit
	Background Check Initiated	Represents the point at which a background check is requested for a new hire. This is often managed through an integrated service within ADP or flagged manually as a required pre-employment step.
Why it matters Tracking the initiation and completion of background checks helps identify delays in the pre-boarding process. The duration of this activity is a key factor in the overall hiring cycle time. Where to get This information is likely available in ADP's recruiting or onboarding modules, or through integrations with third-party screening vendors. It may be a specific status or a timestamped event. Capture Look for a specific event or status change related to 'Background Screening' in the onboarding workflow. Event type explicit
	Benefits Enrollment Completed	Represents the successful completion of the employee's benefits selection process. This event is recorded when the employee finalizes their choices within the ADP benefits administration module, typically within a specific timeframe after their hire date.
Why it matters Analyzing the timeliness of benefits enrollment helps ensure employees are covered as expected and that the organization remains compliant. It highlights potential communication or system usability issues in the onboarding process. Where to get This event is typically logged explicitly within the ADP benefits module when an employee submits their elections. A timestamp or completion status for the enrollment event would be available. Capture Extract the submission timestamp of the benefits enrollment form or event. Event type explicit
	Compensation Change Approved	Represents a finalized change to an employee's salary, bonus structure, or other compensation elements. This event is captured when a compensation change action is approved and given an effective date in the system.
Why it matters Analyzing compensation changes helps in understanding salary trends, budget impacts, and the execution of pay-for-performance strategies. It is often linked to promotions and performance reviews. Where to get This is an effective-dated event in the employee's job or compensation history record. Each change is recorded as a new row with a specific action code (e.g., 'Pay Rate Change') and an effective date. Capture Extract events from the employee's compensation history table using the effective date as the timestamp. Event type explicit
	Job Data Change Processed	A general activity representing any significant change to an employee's job data that is not a promotion or termination. This includes lateral transfers, department changes, or manager updates, captured via effective-dated rows in job history.
Why it matters This activity provides visibility into all forms of internal movement, highlighting organizational restructuring and transfers. It helps understand process drivers that might otherwise be invisible if only promotions are tracked. Where to get Derived from the employee's job history table. Any new effective-dated row with an action code for transfer, data change, or position change constitutes this event. Capture Extract all effective-dated job history records not classified as hire, promotion, or termination. Event type explicit
	Leave Of Absence Started	Indicates the start of an employee's leave of absence (e.g., FMLA, personal, medical). This is captured when the employee's status is officially changed to a 'Leave' status in ADP on a specific effective date.
Why it matters Tracking leaves of absence is important for workforce planning, compliance monitoring, and understanding employee lifecycle interruptions. It helps analyze the impact of leave on an employee's tenure and career. Where to get This is an effective-dated status change in the employee's job data record. Look for a change in the 'Employment Status' field to a value like 'Leave of Absence' or 'LOA'. Capture Identify the timestamp when the 'Employment Status' field changes to a leave-related value. Event type inferred
	Offboarding Tasks Completed	Marks the completion of all required offboarding tasks, such as asset return, knowledge transfer, and final paperwork. This is often tracked via a checklist or workflow within ADP's HR modules.
Why it matters Ensuring all offboarding tasks are completed is critical for compliance, security, and mitigating legal risks. This activity provides a clear endpoint for the operational offboarding process. Where to get This may be an explicit event from an onboarding/offboarding module, captured when a workflow status is set to 'Completed'. If no module is used, this event may not be available. Capture Look for a completion timestamp on an offboarding checklist or workflow associated with the employee. Event type explicit
	Payroll Setup Completed	Indicates that all necessary information for payroll processing, such as tax forms and direct deposit details, has been entered and verified. This is a key task in the onboarding checklist within ADP.
Why it matters Timely payroll setup is critical for a positive new hire experience and ensures accurate first-time pay. Delays or rework in this activity can lead to employee dissatisfaction and administrative overhead. Where to get This is often captured as a completed task or a status change within ADP's onboarding or payroll modules. It may be inferred from the completion date of payroll-related forms. Capture Use the completion timestamp for the payroll section of an onboarding checklist or workflow. Event type inferred
	Return From Leave Processed	Marks the employee's return to active duty after a leave of absence. This event is captured when the employee's status is updated from a 'Leave' status back to 'Active' in the system.
Why it matters This event closes the loop on leaves of absence, allowing for accurate duration analysis. It ensures that payroll and benefits are reactivated correctly and that the employee is properly reintegrated. Where to get Inferred from an effective-dated status change in the employee's job record, where the 'Employment Status' moves from a 'Leave' value back to 'Active'. Capture Identify the timestamp when 'Employment Status' changes from a leave value to an active value. Event type inferred

Recommended Optional

Extraction Guides

How to get your data from Adp Workforce

Steps

Register an Application in ADP Marketplace: Before running any script, you must create a client application within the ADP Marketplace developer portal. This will be a 'private' application for your organization's use. During registration, you will define the application's name and specify the API scopes it requires. For this extraction, request scopes such as hr.worker.read, core.events.read, and potentially talent or compensation-specific scopes.
Obtain API Credentials: Once the application is registered and approved, ADP will provide a Client ID and a Client Secret. You will also need to generate a public/private key pair (X.509 certificate). Upload the public certificate (.pem or .crt) to your application's settings in the ADP developer portal. The private key file (.key) will be used by the Python script to sign authentication requests.
Set Up Python Environment: Ensure you have Python 3.6 or newer installed. Install the necessary libraries for interacting with the API and processing data by running the following command in your terminal: pip install requests PyJWT cryptography pandas.
Configure the Python Script: Open the provided Python script in an editor. Locate the configuration section at the top and replace the placeholder values with your actual ADP credentials. This includes the CLIENT_ID, CLIENT_SECRET, and the file paths to your SSL certificate (SSL_CERT_PATH) and private key (SSL_KEY_PATH).
Define Extraction Parameters: In the script's configuration section, set the START_DATE and END_DATE to define the time window for the data you wish to extract. This helps limit the amount of data processed and keeps API usage within reasonable limits. It is recommended to start with a smaller period, such as 3-6 months, for initial testing.
Execute the Script: Run the script from your terminal using python your_script_name.py. The script will first authenticate with ADP to get an access token. It will then make a series of API calls to fetch all worker profiles modified within your specified timeframe.
Data Processing and Event Generation: The script iterates through each worker's data, analyzing their history, status changes, compensation records, and other relevant fields. It translates these data points into a standardized list of activities, creating a separate record for each of the 14 defined events.
Review and Export the Event Log: After processing all workers, the script compiles the events into a pandas DataFrame. Finally, it saves this DataFrame to a CSV file named adp_hire_to_retire_log.csv in the same directory where the script is located. This file is now ready for upload to a process mining tool.

Configuration

API Application Scopes: Your registered ADP application must have the correct API permissions (scopes). At a minimum, hr.worker.read is required. To access all desired attributes, you may also need scopes related to talent management, compensation, and events.
Client Credentials: The script requires a valid Client ID, Client Secret, and a pair of SSL certificate files (.pem/.crt and .key). These must be securely stored and correctly referenced in the script's configuration section.
Date Range Filters: The START_DATE and END_DATE variables in the script are critical for controlling the volume of data. For a full lifecycle analysis, you may need a wide date range, but be aware this will significantly increase script execution time and API call volume. Start with a 6 to 12-month period for initial analysis.
Custom Field Mapping: Activities such as 'Background Check Initiated', 'Payroll Setup Completed', and 'Offboarding Tasks Completed' are often not standard API events. The script assumes these are tracked in custom fields. You must identify the names of these fields in your ADP instance (e.g., backgroundCheckStatusDate, payrollReadyDate) and update the corresponding placeholder variables in the script's process_worker_events function.
Pagination Handling: The script is designed to handle ADP API pagination using the $top parameter to fetch records in batches. The default page size is set to 50, which is generally efficient, but can be adjusted if you encounter timeout issues.
Prerequisites: You must have administrative access to your organization's ADP Marketplace developer account to register an application and manage credentials. The user account associated with the credentials should have sufficient permissions within ADP Workforce Now to view the required employee data.

a Sample Query python

import os
import requests
import json
import pandas as pd
from datetime import datetime, timezone
import jwt
import uuid

class=class="hl-string">"hl-comment"># --- CONFIGURATION SECTION --- #
class=class="hl-string">"hl-comment"># Replace with your ADP Application Credentials
CLIENT_ID = class="hl-string">'[Your_ADP_Client_ID]'
CLIENT_SECRET = class="hl-string">'[Your_ADP_Client_Secret]'

class=class="hl-string">"hl-comment"># Replace with the absolute paths to your certificate and key files
SSL_CERT_PATH = class="hl-string">'[Path_To_Your_SSL_Certificate.pem]'
SSL_KEY_PATH = class="hl-string">'[Path_To_Your_SSL_Private_Key.key]'

class=class="hl-string">"hl-comment"># ADP API Endpoints
ADP_TOKEN_URL = class="hl-string">'https://api.adp.com/auth/oauth/v2/token'
ADP_API_BASE_URL = class="hl-string">'https://api.adp.com'

class=class="hl-string">"hl-comment"># Data Extraction Parameters
START_DATE = class="hl-string">'2023-01-01T00:00:00Z' class=class="hl-string">"hl-comment"># Inclusive start date for changes
END_DATE = class="hl-string">'2023-12-31T23:59:59Z'   class=class="hl-string">"hl-comment"># Inclusive end date for changes

class=class="hl-string">"hl-comment"># --- END CONFIGURATION SECTION --- #

def get_adp_token():
    class="hl-string">"""Authenticates with ADP and returns an access token."""
    try:
        with open(SSL_KEY_PATH, class="hl-string">'r') as key_file:
            private_key = key_file.read()

        jwt_payload = {
            class="hl-string">'iss': CLIENT_ID,
            class="hl-string">'sub': CLIENT_ID,
            class="hl-string">'aud': ADP_TOKEN_URL,
            class="hl-string">'jti': str(uuid.uuid4()),
            class="hl-string">'exp': int(datetime.now(timezone.utc).timestamp()) + 3600
        }
        
        client_assertion = jwt.encode(jwt_payload, private_key, algorithm=class="hl-string">'RS256')

        token_payload = {
            class="hl-string">'grant_type': class="hl-string">'client_credentials',
            class="hl-string">'client_id': CLIENT_ID,
            class="hl-string">'client_assertion_type': class="hl-string">'urn:ietf:params:oauth:client-assertion-type:jwt-bearer',
            class="hl-string">'client_assertion': client_assertion
        }

        with open(SSL_CERT_PATH, class="hl-string">'rb') as cert_file:
            cert_data = cert_file.read()

        cert = (SSL_CERT_PATH, SSL_KEY_PATH)
        
        response = requests.post(ADP_TOKEN_URL, data=token_payload, cert=cert)
        response.raise_for_status()
        return response.json()[class="hl-string">'access_token']
    except Exception as e:
        print(fclass="hl-string">"Error obtaining ADP token: {e}")
        raise

def get_all_workers(token):
    class="hl-string">"""Fetches all worker records from ADP API, handling pagination."""
    workers = []
    page = 0
    page_size = 50
    
    headers = {
        class="hl-string">'Authorization': fclass="hl-string">'Bearer {token}',
        class="hl-string">'Accept': class="hl-string">'application/json'
    }
    
    class=class="hl-string">"hl-comment"># This filter is an example. Adjust as needed. It pulls workers updated in the time window.
    class=class="hl-string">"hl-comment"># For a full load, you might remove the filter and process all workers.
    api_filter = fclass="hl-string">"workers/workAssignments/actualStartDate ge '{START_DATE.split('T')[0]}' or workers/workAssignments/terminationDate ge '{START_DATE.split('T')[0]}'"
    
    while True:
        api_url = fclass="hl-string">"{ADP_API_BASE_URL}/hr/v2/workers?${'$'}top={page_size}&${'$'}skip={page * page_size}&${'$'}filter={api_filter}"
        print(fclass="hl-string">"Fetching workers from: {api_url}")
        try:
            response = requests.get(api_url, headers=headers)
            response.raise_for_status()
            data = response.json()
            current_workers = data.get(class="hl-string">'workers', [])
            if not current_workers:
                break
            workers.extend(current_workers)
            page += 1
        except requests.exceptions.HTTPError as e:
            print(fclass="hl-string">"HTTP Error fetching workers: {e.response.text}")
            break
        except Exception as e:
            print(fclass="hl-string">"An error occurred: {e}")
            break
            
    print(fclass="hl-string">"Total workers fetched: {len(workers)}")
    return workers

def parse_timestamp(ts_str):
    class="hl-string">"""Safely parse timestamp strings into datetime objects."""
    if not ts_str:
        return None
    class=class="hl-string">"hl-comment"># Handles formats like class="hl-string">'YYYY-MM-DD' and class="hl-string">'YYYY-MM-DDTHH:MM:SSZ'
    try:
        if class="hl-string">'T' in ts_str:
            return datetime.fromisoformat(ts_str.replace(class="hl-string">'Z', class="hl-string">'+00:00'))
        else:
            return datetime.strptime(ts_str, class="hl-string">'%Y-%m-%d')
    except (ValueError, TypeError):
        return None

def process_worker_events(worker):
    class="hl-string">"""Analyzes a single worker's data and generates a list of lifecycle events."""
    events = []
    employee_id = worker.get(class="hl-string">'associateOID')
    if not employee_id:
        return []
    
    class=class="hl-string">"hl-comment"># Basic attributes
    person = worker.get(class="hl-string">'person', {})
    work_assignment = worker.get(class="hl-string">'workAssignments', [{}])[0]
    user_name = person.get(class="hl-string">'legalName', {}).get(class="hl-string">'formattedName', class="hl-string">'System')
    department = work_assignment.get(class="hl-string">'assignedOrganizationalUnits', [{}])[0].get(class="hl-string">'nameCode', {}).get(class="hl-string">'shortName')
    job_title = work_assignment.get(class="hl-string">'jobTitle')
    rec_source = work_assignment.get(class="hl-string">'customFieldGroup', {}).get(class="hl-string">'stringFields', [{}])[0].get(class="hl-string">'stringValue') class=class="hl-string">"hl-comment"># Example custom field
    term_reason = work_assignment.get(class="hl-string">'terminationReason', {}).get(class="hl-string">'codeValue')

    def create_event(name, timestamp, completion_ts=None):
        event_ts = parse_timestamp(timestamp)
        if event_ts and START_DATE <= timestamp <= END_DATE:
            events.append({
                class="hl-string">'EmployeeId': employee_id,
                class="hl-string">'ActivityName': name,
                class="hl-string">'EventTimestamp': event_ts,
                class="hl-string">'EventCompletionTimestamp': parse_timestamp(completion_ts) if completion_ts else event_ts,
                class="hl-string">'UserName': user_name,
                class="hl-string">'DepartmentName': department,
                class="hl-string">'JobTitle': job_title,
                class="hl-string">'RecruitmentSource': rec_source,
                class="hl-string">'TerminationReason': term_reason if class="hl-string">'Terminat' in name else None
            })

    class=class="hl-string">"hl-comment"># 1. New Hire Record Created
    create_event(class="hl-string">'New Hire Record Created', worker.get(class="hl-string">'creationDateTime'))

    class=class="hl-string">"hl-comment"># 2. Background Check Initiated (assumes a custom date field)
    bg_check_date = next((f.get(class="hl-string">'dateValue') for f in worker.get(class="hl-string">'customFieldGroup', {}).get(class="hl-string">'dateFields', []) if f.get(class="hl-string">'fieldName') == class="hl-string">'[BackgroundCheckDate]'), None)
    create_event(class="hl-string">'Background Check Initiated', bg_check_date)

    class=class="hl-string">"hl-comment"># 3. Employee Onboarded
    create_event(class="hl-string">'Employee Onboarded', work_assignment.get(class="hl-string">'hireDate'))

    class=class="hl-string">"hl-comment"># 4. Payroll Setup Completed (assumes a custom date field)
    payroll_setup_date = next((f.get(class="hl-string">'dateValue') for f in worker.get(class="hl-string">'customFieldGroup', {}).get(class="hl-string">'dateFields', []) if f.get(class="hl-string">'fieldName') == class="hl-string">'[PayrollReadyDate]'), None)
    create_event(class="hl-string">'Payroll Setup Completed', payroll_setup_date)

    class=class="hl-string">"hl-comment"># 5. Benefits Enrollment Completed (assumes a custom date field)
    benefits_date = next((f.get(class="hl-string">'dateValue') for f in worker.get(class="hl-string">'customFieldGroup', {}).get(class="hl-string">'dateFields', []) if f.get(class="hl-string">'fieldName') == class="hl-string">'[BenefitsEnrollmentCompleteDate]'), None)
    create_event(class="hl-string">'Benefits Enrollment Completed', benefits_date)

    class=class="hl-string">"hl-comment"># 6. Performance Review Conducted (Placeholder - requires Talent API call)
    class=class="hl-string">"hl-comment"># This part is complex and often requires a separate API endpoint call per worker.
    class=class="hl-string">"hl-comment"># For this script, we'll assume a custom field for the last review date.
    last_review_date = next((f.get(class="hl-string">'dateValue') for f in worker.get(class="hl-string">'customFieldGroup', {}).get(class="hl-string">'dateFields', []) if f.get(class="hl-string">'fieldName') == class="hl-string">'[LastReviewDate]'), None)
    create_event(class="hl-string">'Performance Review Conducted', last_review_date)

    class=class="hl-string">"hl-comment"># Process work history for changes (simplified approach)
    class=class="hl-string">"hl-comment"># A true implementation would need to query an event or history endpoint.
    class=class="hl-string">"hl-comment"># Here we simulate from current work_assignment fields as an example.

    class=class="hl-string">"hl-comment"># 7. Compensation Change Approved
    comp_effective_date = work_assignment.get(class="hl-string">'compensation', {}).get(class="hl-string">'effectiveDate')
    create_event(class="hl-string">'Compensation Change Approved', comp_effective_date)

    class=class="hl-string">"hl-comment"># 8. Promotion Approved
    assignment_reason = work_assignment.get(class="hl-string">'assignmentReason', {}).get(class="hl-string">'codeValue')
    if assignment_reason == class="hl-string">'PRO': class=class="hl-string">"hl-comment"># class="hl-string">'PRO' is a common code for Promotion
        create_event(class="hl-string">'Promotion Approved', work_assignment.get(class="hl-string">'actualStartDate'))

    class=class="hl-string">"hl-comment"># 9. Job Data Change Processed
    if assignment_reason and assignment_reason not in [class="hl-string">'HIR', class="hl-string">'PRO', class="hl-string">'TER']:
        create_event(class="hl-string">'Job Data Change Processed', work_assignment.get(class="hl-string">'actualStartDate'))

    class=class="hl-string">"hl-comment"># 10. Leave Of Absence Started
    if work_assignment.get(class="hl-string">'assignmentStatus', {}).get(class="hl-string">'statusCode', {}).get(class="hl-string">'codeValue') == class="hl-string">'L': class=class="hl-string">"hl-comment"># Leave
        create_event(class="hl-string">'Leave Of Absence Started', work_assignment.get(class="hl-string">'statusReason', {}).get(class="hl-string">'effectiveDate'))

    class=class="hl-string">"hl-comment"># 11. Return From Leave Processed
    if work_assignment.get(class="hl-string">'assignmentStatus', {}).get(class="hl-string">'statusCode', {}).get(class="hl-string">'codeValue') == class="hl-string">'A' and assignment_reason == class="hl-string">'RFL': class=class="hl-string">"hl-comment"># Active, Return from Leave
        create_event(class="hl-string">'Return From Leave Processed', work_assignment.get(class="hl-string">'rehireDate'))

    class=class="hl-string">"hl-comment"># 12. Termination Initiated (simulated as date entry)
    term_date = work_assignment.get(class="hl-string">'terminationDate')
    if term_date and term_date > datetime.now().strftime(class="hl-string">'%Y-%m-%d'):
         create_event(class="hl-string">'Termination Initiated', work_assignment.get(class="hl-string">'lastWorkDate'))

    class=class="hl-string">"hl-comment"># 13. Offboarding Tasks Completed (assumes a custom date field)
    offboard_complete_date = next((f.get(class="hl-string">'dateValue') for f in worker.get(class="hl-string">'customFieldGroup', {}).get(class="hl-string">'dateFields', []) if f.get(class="hl-string">'fieldName') == class="hl-string">'[OffboardingCompleteDate]'), None)
    create_event(class="hl-string">'Offboarding Tasks Completed', offboard_complete_date)

    class=class="hl-string">"hl-comment"># 14. Employee Record Terminated
    if work_assignment.get(class="hl-string">'assignmentStatus', {}).get(class="hl-string">'statusCode', {}).get(class="hl-string">'codeValue') == class="hl-string">'T': class=class="hl-string">"hl-comment"># Terminated
        create_event(class="hl-string">'Employee Record Terminated', work_assignment.get(class="hl-string">'terminationDate'))

    return events


def main():
    class="hl-string">"""Main function to orchestrate the extraction and processing."""
    print(class="hl-string">"Starting ADP data extraction...")
    try:
        access_token = get_adp_token()
        print(class="hl-string">"Successfully obtained access token.")
        
        workers_data = get_all_workers(access_token)
        if not workers_data:
            print(class="hl-string">"No worker data found. Exiting.")
            return

        all_events = []
        print(fclass="hl-string">"Processing {len(workers_data)} workers for events...")
        for worker in workers_data:
            worker_events = process_worker_events(worker)
            all_events.extend(worker_events)
        
        if not all_events:
            print(class="hl-string">"No events generated from the worker data. Exiting.")
            return

        print(fclass="hl-string">"Generated a total of {len(all_events)} events.")
        
        class=class="hl-string">"hl-comment"># Create DataFrame and save to CSV
        df = pd.DataFrame(all_events)
        df = df.sort_values(by=[class="hl-string">'EmployeeId', class="hl-string">'EventTimestamp'])
        
        output_filename = class="hl-string">'adp_hire_to_retire_log.csv'
        df.to_csv(output_filename, index=False, date_format=class="hl-string">'%Y-%m-%dT%H:%M:%SZ')
        print(fclass="hl-string">"Event log successfully saved to {output_filename}")

    except Exception as e:
        print(fclass="hl-string">"A critical error occurred during the process: {e}")

if __name__ == class="hl-string">'__main__':
    main()