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Your Payroll Processing Data Template

ADP Workforce Now

Payroll Processing Attributes (18) Payroll Processing Activities (15) Extraction Guides (3)

Your Payroll Processing Data Template

This template provides a comprehensive framework for mapping your payroll cycles within ADP Workforce Now. It outlines the essential attributes and activities required to build a robust event log, allowing you to identify bottlenecks and ensure compliance across your entire organization. By following these guidelines, you can transform raw system data into a clear visualization of your actual business operations.

Recommended attributes for detailed analysis
Critical process steps and milestones
ADP Workforce Now extraction best practices

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

Download Template

Payroll Processing Attributes

These recommended data fields provide the necessary context for your event log to support a deep dive into your payroll cycles.

5 Required 7 Recommended 6 Optional

	Name	Description
	Activity ActivityName	The name of the process step or event performed.
Description This attribute captures the specific action taken within the payroll workflow, such as 'Time Sheet Submitted', 'Gross Pay Calculated', or 'Bank Transfer File Generated'. It is fundamental to the process map, defining the nodes in the graph and allowing the visualization of the workflow sequence. Variations in activity sequences highlight rework loops and deviations from the standard operating procedure. Why it matters It defines the 'what' of the process, enabling the visualization of process flows and variants. Where to get Audit trails or transaction history logs in ADP Workforce Now. Examples Time Sheet SubmittedPayroll Record ApprovedData Correction Performed
	Event Timestamp EventDateTime	The specific date and time when the activity occurred.
Description This attribute records the exact moment an activity was logged in the system. It is used to sequence events chronologically and calculate durations between steps. Precise timestamps are critical for identifying bottlenecks, measuring lead times (e.g., time to approval), and ensuring that service level agreements for payroll processing are met. Why it matters It provides the temporal dimension required for all cycle time and performance analysis. Where to get System timestamps associated with transaction logs. Examples 2023-10-01T08:30:00Z2023-10-01T14:45:12Z2023-10-02T09:15:00Z
	Payroll Record PayrollRecordId	Unique identifier for the specific employee and pay period combination.
Description The Payroll Record acts as the central case identifier for the process. It represents a single instance of an employee being paid for a specific cycle (e.g., Pay Period 12 for Employee X). In analysis, this attribute groups all disparate events—from the initial timesheet submission to the final tax filing—into a cohesive end-to-end journey. It allows analysts to track the velocity and accuracy of payment for each individual record. Why it matters It is the mandatory case key that binds all event data together to enable process reconstruction. Where to get Consult ADP Workforce Now documentation Examples PR-2023-10-A-00123PR-2023-10-A-00456PR-2023-10-B-00789
	Last Data Update LastDataUpdate	Timestamp indicating when the record was last modified in the source.
Description Reflects the most recent modification time of the data record in ADP Workforce Now. This is used to determine data freshness and manage incremental data loads. It ensures that the process analysis reflects the current state of the payroll records. Why it matters Critical for incremental data extraction and ensuring analysis is based on current data. Where to get Consult ADP Workforce Now documentation Examples 2023-10-05T17:00:00Z2023-10-06T08:00:00Z
	Source System SourceSystem	The system of record where the event originated.
Description Identifies the software environment from which the data was extracted, in this case, 'ADP Workforce Now'. In complex landscapes where data might be blended with other HRIS or Banking systems, this field ensures data lineage and helps isolate system-specific integration issues. Why it matters It ensures traceability and context, especially in multi-system process mining environments. Where to get Hardcoded during the ETL process. Examples ADP Workforce NowADP WFNADP_PROD
	Department DepartmentCode	The department or cost center associated with the employee.
Description Represents the organizational unit of the employee being paid. In ADP, this is often the 'Home Department'. This attribute is essential for the 'Departmental Process Variance' analysis, allowing the organization to compare approval times and error rates across different business units. Why it matters Key for benchmarking performance across different organizational units. Where to get Employee Master Data or Cost Center fields. Examples Sales-101IT-Dev-200HR-Admin-001
	Gross Pay Amount GrossPayAmount	The calculated gross pay for the record before deductions.
Description The total compensation amount calculated for the employee for the specific pay period. While not always used for process flow analysis, it provides context for 'ActivityAmount' and helps prioritize high-value records when analyzing audit exceptions or retrospective adjustments. Why it matters Provides financial context and magnitude for the payroll record. Where to get Payroll Result tables. Examples 2500.005430.501200.00
	Is Manual Intervention IsManualIntervention	Flag indicating if the activity involved manual data entry or correction.
Description A boolean attribute derived from the activity name or transaction source (e.g., true if activity is 'Data Correction Performed'). This drives the 'Manual Correction Rate' KPI, helping management identify where automation is failing and where human effort is heavily concentrated. Why it matters Directly supports analysis of automation rates and process efficiency. Where to get Derived from ActivityName or specific transaction codes. Examples truefalse
	Is Retrospective IsRetrospective	Flag indicating if this payroll record is an adjustment for a past period.
Description Identifies if the processing is for a current period or a correction to a previously closed period (retro-pay). This supports the 'Retrospective Adjustment Volume' dashboard, highlighting the stability of the payroll process and the frequency of post-publication errors. Why it matters Distinguishes between standard processing and rework/correction cycles. Where to get Derived from Pay Run Type or comparison of Pay Period vs Current Date. Examples truefalse
	Pay Group PayGroupCode	Identifies the specific payroll cycle or group (e.g., Bi-Weekly US).
Description Segments employees into processing groups based on pay frequency and type (e.g., Weekly, Bi-Weekly, Executive). Used to filter analysis for specific cycles and is critical for the 'Manual Data Correction Frequency' dashboard to see if certain groups are more prone to errors than others. Why it matters Allows segmentation of the process by pay frequency and employee type. Where to get Pay Group configuration or Payroll Header tables. Examples US_BiWeeklyCA_MonthlyUS_Executive
	Payroll Specialist PayrollSpecialistName	The user or system agent responsible for performing the activity.
Description Identifies the individual (e.g., Payroll Specialist, Manager) or automated system account that executed the activity. This attribute enables the 'Specialist Throughput Performance' dashboard, helping to balance workloads and identify training needs or bottlenecks caused by resource constraints. Why it matters It enables resource analysis, workload balancing, and segregation of duties auditing. Where to get User ID or Actor fields in audit logs. Examples Jane DoeSystem AdminJohn Smith
	Tax Jurisdiction TaxJurisdictionCode	The specific region or state code for tax filing purposes.
Description Indicates the primary tax authority or region (e.g., CA, NY, Federal) relevant to the payroll record. Required for the 'Tax Filing Completion Benchmarks' dashboard to identify which regions are experiencing delays in statutory filing and to ensure compliance with local regulations. Why it matters Essential for compliance monitoring and regional performance analysis. Where to get Tax profile or Payroll Tax tables. Examples US-CAUS-NYUS-TX
	Audit Exception Type AuditExceptionType	Categorization of the compliance or data warning flagged.
Description Specifics the type of issue found during validation (e.g., 'Negative Net Pay', 'Missing Tax ID'). Used in the 'Audit Exception Resolution Monitor' to analyze which types of errors are causing the longest delays and to guide root cause analysis for upstream data quality improvements. Why it matters Provides detail on why the process was halted or flagged. Where to get Consult ADP Workforce Now documentation Examples Missing SSNNegative Net PayBenefit Mismatch
	Bank File ID BankTransferFileId	Identifier for the generated payment file sent to the bank.
Description The unique reference number for the ACH or wire file generated during the 'Bank Transfer File Generated' activity. This helps link individual payroll records to the bulk payment execution step, enabling the 'Disbursement and Publication Velocity' analysis. Why it matters Links individual cases to batch processing events. Where to get Consult ADP Workforce Now documentation Examples ACH-20231005-01ACH-20231005-02
	Cost Center CostCenterId	The financial cost center code charged for the payroll.
Description Indicates the specific GL unit or cost center associated with the payroll expense. This attribute provides a financial view of the process, allowing the organization to correlate processing inefficiencies (like rework costs) with specific business units. Why it matters Aligns process analysis with financial reporting structures. Where to get Labor Distribution fields. Examples CC-500CC-900CC-120
	Cycle Time (Days) CycleTimeDays	The total duration of the case from start to finish.
Description A calculated metric representing the number of days from the first event (e.g., Time Sheet Submitted) to the last (e.g., Payment Executed). It serves as a high-level performance indicator for the 'End to End Payroll Cycle Trends' dashboard, allowing for the monitoring of overall process speed and efficiency. Why it matters High-level metric for overall process speed. Where to get Calculated during data transformation. Examples 3.55.02.1
	Employee ID EmployeeId	Unique identifier of the employee being paid.
Description The specific ID of the employee associated with the payroll record. While the CaseId tracks the record, the Employee ID allows for longitudinal analysis of specific employees who may chronically submit late timesheets or require frequent manual corrections. Why it matters Enables analysis of behavior patterns at the employee level. Where to get AssociateOID or File Number in ADP. Examples A102030000123456
	Pay Period End Date PayPeriodEndDate	The closing date of the pay cycle.
Description Marks the end of the period for which the employee is being compensated. Used in conjunction with event timestamps to determine if processing is happening on schedule relative to the close of the pay period. Why it matters Reference point for calculating schedule adherence and lateness. Where to get Pay Cycle configuration. Examples 2023-10-152023-10-31

Required Recommended Optional

Payroll Processing Activities

These essential process steps and milestones capture the lifecycle of a payroll run from initial time entry to final payment.

9 Recommended 6 Optional

	Activity	Description
	Audit Exception Flagged	Indicates the system detected a violation of validation rules (e.g., negative net pay, missing tax jurisdiction) during calculation. Captured from the generation of error messages in the calculation output.
Why it matters Driver for the 'Audit Exception Resolution Monitor'. High volumes indicate upstream data quality issues. Where to get Payroll Processing Error Log or 'Verify Payroll' output report. Capture Logged when system generates validation error Event type explicit
	Bank Transfer File Generated	The technical creation of the NACHA/ACH file for direct deposits. Usually triggered immediately after the 'Finalize' step completes.
Why it matters Monitors the 'Time to Bank Transfer File Generation' to ensure technical handoffs don't delay payments. Where to get Output/Reports Log; Timestamp of 'ACH File' or 'Direct Deposit File' generation. Capture Logged when output file created Event type explicit
	Gross Pay Calculated	The system executes the logic to multiply hours by rates and add supplemental earnings. This is inferred from the completion timestamp of the 'Calculate Payroll' batch process.
Why it matters Core processing step. Multiple occurrences indicate rework loops typically visualized in the 'Payroll Preview Loop Analysis'. Where to get Payroll Audit Trail; completion time of 'Calculate' action on the specific Pay Group Batch. Capture Derive from completion timestamp of calculation job Event type inferred
	Pay Slip Published	The availability of the digital pay statement to the employee via the self-service portal (iPay). Usually scheduled relative to the Payment Date.
Why it matters Supports 'Pay Slip Publication Lead Time' and employee satisfaction analysis. Where to get Inferred from System Settings (Pay Statement Availability Rule) applied to the Check Date. Capture Derive from comparing field Check Date to Publication Rule Event type inferred
	Payment Executed	The effective date funds are released to employees. This is often a calculated event based on the Check Date defined in the payroll batch.
Why it matters The primary outcome of the process. Essential for calculating 'Tax Filing Compliance Lead Time'. Where to get Payroll History; 'Check Date' field. Capture Derive from comparing field Check Date to System Date Event type calculated
	Payroll Record Approved	The formal acceptance of the payroll batch, locking it against further changes and authorizing money movement. This is the 'Finalize' step in ADP WFN.
Why it matters The definitive milestone ending the processing phase and starting the disbursement phase. Where to get Payroll Process Workflow; Status change of Batch to 'Finalized' or 'Committed'. Capture Logged when transaction 'Finalize Payroll' executed Event type explicit
	Payroll Record Initialized	Occurs when the payroll batch is created or opened for the cycle, effectively instantiating the payroll case for the employee. Inferred from the creation timestamp of the Paydata record in the active batch.
Why it matters Establish the start of the specific payroll calculation window. Measures the 'Incentive Data Integration Lag' when compared to data import timestamps. Where to get Payroll Module; Paydata Batch Header creation timestamp or first entry in Paydata Grid. Capture Compare status field before/after batch creation Event type inferred
	Time Sheet Approved	Represents the manager's approval of the timecard, authorizing the hours for payroll processing. This is a critical gatekeeping step that moves data from T&A to the Payroll module.
Why it matters Essential for the 'Timesheet Approval Cycle Times' dashboard. Identifies managerial bottlenecks that jeopardize the processing timeline. Where to get ADP Time & Attendance Audit Trail; filter for 'Status Change' to 'Approved'. Capture Logged when transaction 'Approve Timecard' executed Event type explicit
	Time Sheet Submitted	Marks the moment an employee or manager submits time and attendance data for the pay period. Captured explicitly from the Time & Attendance module audit logs within ADP Workforce Now.
Why it matters Starts the payroll cycle lead time clock. Delays here ripple downstream, reducing the time available for payroll specialists to validate data. Where to get ADP Time & Attendance Audit Trail; filter for 'Status Change' to 'Submitted' on Timecard objects. Capture Logged when transaction 'Submit Timecard' executed Event type explicit
	Benefits Deductions Applied	The application of benefit rules (medical, 401k) to the gross pay. Usually occurs simultaneously with calculation but is logically distinct for audit purposes.
Why it matters Correlates with 'Audit Exception Flagged' to determine if benefit logic is triggering compliance errors. Where to get Inferred from the creation or update of deduction line items in the Paydata Grid following a calculation event. Capture Compare deduction fields before/after calculation Event type inferred
	Data Correction Performed	A manual modification to the Paydata Grid executed by a payroll specialist to resolve errors or adjust amounts. Captured via the field-level audit trail.
Why it matters Key metric for 'Manual Data Correction Frequency'. High correction rates suggest automation failures. Where to get Paydata Grid Audit Trail; User 'Update' actions on pay lines. Capture Logged when transaction 'Update Paydata' executed Event type explicit
	Incentive Data Imported	Records the ingestion of external pay data such as commissions or bonuses via the ADP Import utility. This event tracks when secondary income sources are attached to the payroll record.
Why it matters Crucial for identifying integration delays. Late imports often force recalculations and rework loops. Where to get ADP Integration/Import Logs; success timestamp for 'Paydata Import' job. Capture Logged when transaction 'Import Paydata' executed Event type explicit
	Payroll Result Previewed	The generation of the 'Preview Payroll' register or reports for human verification. This step validates the calculation results before finalizing.
Why it matters Used in 'Payroll Preview Loop Analysis'. Excessive previews imply a lack of confidence in the data. Where to get System Logs; timestamp of 'Preview Payroll' report generation. Capture Logged when transaction 'Generate Preview' executed Event type explicit
	Retrospective Adjustment Posted	Occurs when a historical correction is applied to a closed payroll record, typically affecting the next cycle. This identifies errors found after the process officially ended.
Why it matters Critical for 'Retrospective Adjustment Volume' analysis, indicating failed upstream quality checks. Where to get Payroll History; New transactions posted with an 'Effective Date' in the past. Capture Logged when transaction 'Post Adjustment' executed Event type explicit
	Tax Filing Completed	Marks the completion of statutory tax filings for the pay period. For ADP Tax Service clients, this is when ADP confirms the filing package is closed.
Why it matters Tracks compliance risk. Delays here can result in penalties. Where to get Tax Module; Quarter-End or Period-End filing status update. Capture Requires system analysis Event type inferred

Recommended Optional

Extraction Guides

How to get your data from ADP Workforce Now

Steps

Log in to ADP Workforce Now with Administrator or Payroll Practitioner access rights.
Navigate to Reports & Analytics and select Custom Reports from the dashboard menu.
Click New Custom Report and select the Payroll data domain. Depending on your version, this may be labeled as Pay Data or Payroll Register.
In the Field Selection step, locate and add the unique identifier for the case. Select File Number or Associate ID combined with Pay Frequency and Pay Period Number to construct the PayrollRecordId.
Select all relevant date fields required to map the activities. You must include Pay Period Start Date, Pay Period End Date, Check Date, Period End Date, and Calculation Date. Note that some audit fields like Timecard Approval Date may need to be joined from the Time & Attendance module if not present in the primary view.
Add financial and dimension fields including Gross Pay, Net Pay, Department, Cost Center, and Tax Jurisdiction.
Add the Audit Trail or Field Changes block to the report layout if available. This is crucial for capturing manual events like Data Correction Performed. If this is not joinable in one report, you must create a separate Audit Report and join by Employee ID and Pay Period externally.
Configure filters to exclude voided checks and restrict the date range to the desired analysis window (e.g., Last 12 Months).
Navigate to the Sort & Total step and sort by Pay Period Start Date and then by Associate ID to ensure data is ordered logically.
Proceed to the Run/Schedule step. Choose Run Now to test, then set up a recurring Schedule to export the file as a CSV or Excel format.
Once the raw wide-format report is generated, use an ETL tool or script to transform the data. You must unpivot the date columns so that each date field becomes a separate row in the event log (Activity).
Verify the final CSV contains the required columns: PayrollRecordId, ActivityName, EventDateTime, and SourceSystem before uploading to ProcessMind.

Configuration

Report Type: Standard Custom Report
Data Domain: Payroll / Pay Data Dictionary
Output Format: Comma Separated Values (CSV)
Recommended Date Range: Rolling 12 to 24 months for trend analysis
Key Filters: Pay Group Code (select relevant groups), Company Code (if multi-entity), Status is Active or Leave
Granularity: One row per Associate per Pay Period (Raw), transformed to multiple rows per Associate (Final)
Permissions Required: View Payroll Data, View Audit Trails, Create Custom Reports
Localization: Ensure date formats are set to ISO 8601 (YYYY-MM-DD HH:MM:SS) in user preferences to avoid ambiguity

a Sample Query config

/* 
ADP Workforce Now does not accept SQL queries from end-users. 
The following configuration block represents the Transformation Logic required to convert the ADP Custom Report export (Wide Format) into the Process Mining Event Log (Long Format).

Input Source: ADP_Custom_Payroll_Export.csv
Logic Language: Pseudo-ETL/Config
*/

TRANSFORMATION_CONFIG {

  GLOBAL_SETTINGS {
    SOURCE_SYSTEM: "ADP Workforce Now"
    CASE_ID_FORMULA: CONCATENATE(Field_AssociateID, "-", Field_PayPeriodNumber, "-", Field_Year)
    LAST_DATA_UPDATE: SYSTEM_TIMESTAMP()
  }

  ACTIVITY_MAPPING_RULES {

    /* 1. Time Sheet Submitted */
    RULE "Time Sheet Submitted" {
      IF Field_Timecard_Submit_Date IS NOT NULL THEN
        CREATE_EVENT(
          ACTIVITY: "Time Sheet Submitted",
          TIMESTAMP: Field_Timecard_Submit_Date,
          ATTRIBUTES: [PayrollSpecialistName: Field_Timecard_User, IsManualIntervention: "False"]
        )
    }

    /* 2. Time Sheet Approved */
    RULE "Time Sheet Approved" {
      IF Field_Timecard_Approval_Date IS NOT NULL THEN
        CREATE_EVENT(
          ACTIVITY: "Time Sheet Approved",
          TIMESTAMP: Field_Timecard_Approval_Date,
          ATTRIBUTES: [PayrollSpecialistName: Field_Manager_Name, IsManualIntervention: "True"]
        )
    }

    /* 3. Payroll Record Initialized */
    RULE "Payroll Record Initialized" {
      IF Field_Pay_Period_Start_Date IS NOT NULL THEN
        CREATE_EVENT(
          ACTIVITY: "Payroll Record Initialized",
          TIMESTAMP: Field_Pay_Period_Start_Date,
          ATTRIBUTES: [PayGroupCode: Field_PayGroup, IsRetrospective: "False"]
        )
    }

    /* 4. Incentive Data Imported */
    RULE "Incentive Data Imported" {
      IF Field_Import_Batch_Date IS NOT NULL AND Field_Batch_Type == "Import" THEN
        CREATE_EVENT(
          ACTIVITY: "Incentive Data Imported",
          TIMESTAMP: Field_Import_Batch_Date,
          ATTRIBUTES: [IsManualIntervention: "False"]
        )
    }

    /* 5. Gross Pay Calculated */
    RULE "Gross Pay Calculated" {
      IF Field_Calc_DateTime IS NOT NULL THEN
        CREATE_EVENT(
          ACTIVITY: "Gross Pay Calculated",
          TIMESTAMP: Field_Calc_DateTime,
          ATTRIBUTES: [GrossPayAmount: Field_Gross_Pay, DepartmentCode: Field_Home_Dept]
        )
    }

    /* 6. Benefits Deductions Applied */
    RULE "Benefits Deductions Applied" {
      /* Often occurs simultaneous to Calc, adding 1 second for logical sort */
      IF Field_Calc_DateTime IS NOT NULL AND Field_Total_Deductions > 0 THEN
        CREATE_EVENT(
          ACTIVITY: "Benefits Deductions Applied",
          TIMESTAMP: DATE_ADD(Field_Calc_DateTime, 1, "SECOND"),
          ATTRIBUTES: [GrossPayAmount: Field_Gross_Pay]
        )
    }

    /* 7. Audit Exception Flagged */
    RULE "Audit Exception Flagged" {
      IF Field_Error_Message_Timestamp IS NOT NULL THEN
        CREATE_EVENT(
          ACTIVITY: "Audit Exception Flagged",
          TIMESTAMP: Field_Error_Message_Timestamp,
          ATTRIBUTES: [IsManualIntervention: "False"]
        )
    }

    /* 8. Data Correction Performed */
    RULE "Data Correction Performed" {
      IF Field_Audit_Change_Date IS NOT NULL THEN
        CREATE_EVENT(
          ACTIVITY: "Data Correction Performed",
          TIMESTAMP: Field_Audit_Change_Date,
          ATTRIBUTES: [PayrollSpecialistName: Field_Audit_User, IsManualIntervention: "True"]
        )
    }

    /* 9. Payroll Result Previewed */
    RULE "Payroll Result Previewed" {
      IF Field_Preview_Run_DateTime IS NOT NULL THEN
        CREATE_EVENT(
          ACTIVITY: "Payroll Result Previewed",
          TIMESTAMP: Field_Preview_Run_DateTime,
          ATTRIBUTES: [IsManualIntervention: "True"]
        )
    }

    /* 10. Payroll Record Approved */
    RULE "Payroll Record Approved" {
      IF Field_Finalize_DateTime IS NOT NULL THEN
        CREATE_EVENT(
          ACTIVITY: "Payroll Record Approved",
          TIMESTAMP: Field_Finalize_DateTime,
          ATTRIBUTES: [PayrollSpecialistName: Field_Finalizer_User, IsManualIntervention: "True"]
        )
    }

    /* 11. Bank Transfer File Generated */
    RULE "Bank Transfer File Generated" {
      /* Logic: Usually occurs 2 hours after Finalize or at specific cutoff */
      IF Field_ACH_File_Date IS NOT NULL THEN
        CREATE_EVENT(
          ACTIVITY: "Bank Transfer File Generated",
          TIMESTAMP: Field_ACH_File_Date,
          ATTRIBUTES: [IsManualIntervention: "False"]
        )
    }

    /* 12. Payment Executed */
    RULE "Payment Executed" {
      IF Field_Check_Date IS NOT NULL THEN
        CREATE_EVENT(
          ACTIVITY: "Payment Executed",
          TIMESTAMP: Field_Check_Date,
          ATTRIBUTES: [GrossPayAmount: Field_Gross_Pay, IsRetrospective: "False"]
        )
    }

    /* 13. Pay Slip Published */
    RULE "Pay Slip Published" {
      IF Field_Advice_Available_Date IS NOT NULL THEN
        CREATE_EVENT(
          ACTIVITY: "Pay Slip Published",
          TIMESTAMP: Field_Advice_Available_Date,
          ATTRIBUTES: [IsManualIntervention: "False"]
        )
    }

    /* 14. Tax Filing Completed */
    RULE "Tax Filing Completed" {
      IF Field_Tax_Filing_Confirmation_Date IS NOT NULL THEN
        CREATE_EVENT(
          ACTIVITY: "Tax Filing Completed",
          TIMESTAMP: Field_Tax_Filing_Confirmation_Date,
          ATTRIBUTES: [TaxJurisdictionCode: Field_Tax_State, IsManualIntervention: "False"]
        )
    }

    /* 15. Retrospective Adjustment Posted */
    RULE "Retrospective Adjustment Posted" {
      IF Field_Adjustment_Run_Date IS NOT NULL AND Field_Run_Type == "Adjustment" THEN
        CREATE_EVENT(
          ACTIVITY: "Retrospective Adjustment Posted",
          TIMESTAMP: Field_Adjustment_Run_Date,
          ATTRIBUTES: [IsRetrospective: "True", IsManualIntervention: "True"]
        )
    }
  }
}

Steps

Obtain ADP Marketplace API credentials including Client ID, Client Secret, and the SSL Client Certificate (PEM and Key files) associated with your application.
Verify your application has the necessary scope permissions enabled: Payroll (read), Worker (read), and Time (read).
Install the required Python libraries using pip: requests, pandas, and pyOpenSSL (often required for mutual TLS handling).
Configure the Python script provided below with your specific ADP API endpoints and credential file paths.
The script initializes a secure session using mutual TLS to authenticate against the ADP Token Endpoint.
It first queries the Time and Labor Management API to retrieve time card status changes for the target period.
Next, it queries the Payroll Output API (payroll-v1) to fetch the detailed Pay Statement JSON for each employee.
The script iterates through the complex nested JSON structure to identify timestamps for specific events like calculation, approval, and file generation.
It applies conditional logic to infer activities such as Audit Exception Flagged by checking the notification/warning arrays in the response.
Data from Time and Payroll sources are merged based on the AssociateOID (a unique employee identifier in ADP).
The final list of events is converted into a Pandas DataFrame and formatted to match the ProcessMind event log schema.
Run the script to generate the output CSV file and verify the column headers match the requirements before uploading to ProcessMind.

Configuration

Client ID and Secret: Obtain these from the ADP Developer Portal for your specific application.
SSL Certificates: Path to your client.pem and client.key files. ADP requires mutual TLS (mTLS) for API communication.
API Base URL: Typically https://api.adp.com, but may vary for specific environments (e.g., wfn-api.adp.com).
Date Range: Recommended extraction window is 3 to 6 months per run to adhere to API pagination and timeout limits.
Page Size: Set the $top parameter (limit) to 50 or 100 records per request to optimize throughput without hitting timeouts.
Company Code: Filter by Organization Unit or Company Code if your ADP instance hosts multiple legal entities.
AssociateOID: This is the primary key for joining Time and Payroll data, distinct from the visible Employee ID.

a Sample Query python

import requests
import pandas as pd
import json
from datetime import datetime
import uuid

class=class="hl-string">"hl-comment"># === CONFIGURATION ===
class=class="hl-string">"hl-comment"># Replace these placeholders with your actual ADP credentials and paths
ADP_CLIENT_ID = class="hl-string">"[Your ADP Client ID]"
ADP_CLIENT_SECRET = class="hl-string">"[Your ADP Client Secret]"
CERT_PATH = class="hl-string">"path/to/your/client_certificate.pem"
KEY_PATH = class="hl-string">"path/to/your/client_private_key.key"
TOKEN_URL = class="hl-string">"https://api.adp.com/auth/oauth/v2/token"
PAYROLL_API_URL = class="hl-string">"https://api.adp.com/payroll/v1/payroll-output"
TIME_API_URL = class="hl-string">"https://api.adp.com/time/v1/time-cards"

class=class="hl-string">"hl-comment"># Output File
OUTPUT_FILENAME = class="hl-string">"ADP_Payroll_Event_Log.csv"

class=class="hl-string">"hl-comment"># === AUTHENTICATION ===
def get_access_token():
    class=class="hl-string">"hl-comment"># ADP requires mutual TLS (mTLS) for authentication
    payload = {
        class="hl-string">'client_id': ADP_CLIENT_ID,
        class="hl-string">'client_secret': ADP_CLIENT_SECRET,
        class="hl-string">'grant_type': class="hl-string">'client_credentials'
    }
    try:
        response = requests.post(
            TOKEN_URL,
            data=payload,
            cert=(CERT_PATH, KEY_PATH),
            verify=True
        )
        response.raise_for_status()
        return response.json()[class="hl-string">'access_token']
    except Exception as e:
        print(fclass="hl-string">"Authentication failed: {str(e)}")
        return None

class=class="hl-string">"hl-comment"># === DATA EXTRACTION ===
def fetch_adp_data(url, token, params=None):
    headers = {
        class="hl-string">'Authorization': fclass="hl-string">'Bearer {token}',
        class="hl-string">'Accept': class="hl-string">'application/json'
    }
    all_records = []
    
    class=class="hl-string">"hl-comment"># Simple pagination loop (ADP uses class="hl-string">'skip' and class="hl-string">'top' or class="hl-string">'next' links)
    class=class="hl-string">"hl-comment"># This is a simplified implementation assuming standard offset pagination
    skip = 0
    limit = 50
    fetching = True
    
    while fetching:
        current_params = params.copy() if params else {}
        current_params[class="hl-string">'$skip'] = skip
        current_params[class="hl-string">'$top'] = limit
        
        try:
            response = requests.get(
                url, 
                headers=headers, 
                params=current_params, 
                cert=(CERT_PATH, KEY_PATH)
            )
            if response.status_code != 200:
                break
                
            data = response.json()
            class=class="hl-string">"hl-comment"># Adjust key based on actual API response structure (e.g., class="hl-string">'payrollOutputs', class="hl-string">'timeCards')
            class=class="hl-string">"hl-comment"># Using generic list detection for the script
            key = next((k for k in data.keys() if isinstance(data[k], list)), None)
            
            if not key or len(data[key]) == 0:
                fetching = False
            else:
                all_records.extend(data[key])
                skip += limit
                
        except Exception:
            fetching = False
            
    return all_records

class=class="hl-string">"hl-comment"># === EVENT LOG GENERATION ===
def generate_event_log(payroll_data, time_data):
    event_log = []
    
    class=class="hl-string">"hl-comment"># Index time data by AssociateOID for quick lookup
    time_map = {item.get(class="hl-string">'associateOID'): item for item in time_data}

    for pay_record in payroll_data:
        class=class="hl-string">"hl-comment"># Basic Attributes
        associate_id = pay_record.get(class="hl-string">'associateOID', class="hl-string">'Unknown')
        pay_period_start = pay_record.get(class="hl-string">'payPeriodStartDate', class="hl-string">'')
        class=class="hl-string">"hl-comment"># Create a unique Case ID using AssociateID and Pay Period
        case_id = fclass="hl-string">"{associate_id}-{pay_period_start}"
        
        dept_code = pay_record.get(class="hl-string">'worker', {}).get(class="hl-string">'homeOrganizationalUnits', [{}])[0].get(class="hl-string">'nameCode', {}).get(class="hl-string">'code', class="hl-string">'Unknown')
        pay_group = pay_record.get(class="hl-string">'payrollGroupCode', class="hl-string">'Main')
        gross_pay = pay_record.get(class="hl-string">'grossPayAmount', 0.0)
        tax_jur = pay_record.get(class="hl-string">'taxJurisdiction', {}).get(class="hl-string">'code', class="hl-string">'US')
        last_update = datetime.now().isoformat() class=class="hl-string">"hl-comment"># Using extraction time as fallback if record update time missing

        class=class="hl-string">"hl-comment"># Helper to append event
        def add_event(activity, timestamp, specialist=None, manual=False, retro=False):
            if timestamp:
                event_log.append({
                    class="hl-string">'PayrollRecordId': case_id,
                    class="hl-string">'ActivityName': activity,
                    class="hl-string">'EventDateTime': timestamp,
                    class="hl-string">'SourceSystem': class="hl-string">'ADP Workforce Now',
                    class="hl-string">'LastDataUpdate': last_update,
                    class="hl-string">'PayrollSpecialistName': specialist if specialist else class="hl-string">'System Agent',
                    class="hl-string">'DepartmentCode': dept_code,
                    class="hl-string">'PayGroupCode': pay_group,
                    class="hl-string">'GrossPayAmount': gross_pay,
                    class="hl-string">'TaxJurisdictionCode': tax_jur,
                    class="hl-string">'IsManualIntervention': manual,
                    class="hl-string">'IsRetrospective': retro
                })

        class=class="hl-string">"hl-comment"># --- ACTIVITY 1: Time Sheet Submitted ---
        class=class="hl-string">"hl-comment"># Derived from Time API
        t_card = time_map.get(associate_id)
        if t_card and t_card.get(class="hl-string">'submissionDateTime'):
            add_event(class="hl-string">"Time Sheet Submitted", t_card[class="hl-string">'submissionDateTime'], specialist=t_card.get(class="hl-string">'submittedBy'))

        class=class="hl-string">"hl-comment"># --- ACTIVITY 2: Time Sheet Approved ---
        class=class="hl-string">"hl-comment"># Derived from Time API
        if t_card and t_card.get(class="hl-string">'approvalDateTime'):
            add_event(class="hl-string">"Time Sheet Approved", t_card[class="hl-string">'approvalDateTime'], specialist=t_card.get(class="hl-string">'approvedBy'))

        class=class="hl-string">"hl-comment"># --- ACTIVITY 3: Payroll Record Initialized ---
        class=class="hl-string">"hl-comment"># Creation of the pay data record
        create_time = pay_record.get(class="hl-string">'creationDateTime')
        add_event(class="hl-string">"Payroll Record Initialized", create_time)

        class=class="hl-string">"hl-comment"># --- ACTIVITY 4: Incentive Data Imported ---
        class=class="hl-string">"hl-comment"># Check for specific earnings codes related to incentives
        earnings = pay_record.get(class="hl-string">'earnings', [])
        for earn in earnings:
            if earn.get(class="hl-string">'typeCode') in [class="hl-string">'BONUS', class="hl-string">'COMMISSION']:
                class=class="hl-string">"hl-comment"># Use entry time of the specific line item
                add_event(class="hl-string">"Incentive Data Imported", earn.get(class="hl-string">'entryDateTime', create_time))
                break class=class="hl-string">"hl-comment"># Capture once per case to avoid duplicates or refine logic for multiple

        class=class="hl-string">"hl-comment"># --- ACTIVITY 5: Gross Pay Calculated ---
        class=class="hl-string">"hl-comment"># When the calculation engine finished
        calc_time = pay_record.get(class="hl-string">'calculationDateTime')
        add_event(class="hl-string">"Gross Pay Calculated", calc_time)

        class=class="hl-string">"hl-comment"># --- ACTIVITY 6: Benefits Deductions Applied ---
        class=class="hl-string">"hl-comment"># Usually happens same time as calc, but logically distinct
        class=class="hl-string">"hl-comment"># We look for deduction processing timestamp
        deductions = pay_record.get(class="hl-string">'deductions', [])
        if deductions and calc_time:
             add_event(class="hl-string">"Benefits Deductions Applied", calc_time)

        class=class="hl-string">"hl-comment"># --- ACTIVITY 7: Audit Exception Flagged ---
        class=class="hl-string">"hl-comment"># Check notification messages
        msgs = pay_record.get(class="hl-string">'notificationMessages', [])
        if msgs:
            class=class="hl-string">"hl-comment"># Take the timestamp of the first warning
            add_event(class="hl-string">"Audit Exception Flagged", msgs[0].get(class="hl-string">'generationDateTime', calc_time))

        class=class="hl-string">"hl-comment"># --- ACTIVITY 8: Data Correction Performed ---
        class=class="hl-string">"hl-comment"># Compare modification time vs creation time. If significantly different, assume correction.
        mod_time = pay_record.get(class="hl-string">'modificationDateTime')
        if mod_time and create_time and mod_time > create_time:
            add_event(class="hl-string">"Data Correction Performed", mod_time, manual=True)

        class=class="hl-string">"hl-comment"># --- ACTIVITY 9: Payroll Result Previewed ---
        class=class="hl-string">"hl-comment"># Report generation time
        report_time = pay_record.get(class="hl-string">'reportGenerationDateTime')
        add_event(class="hl-string">"Payroll Result Previewed", report_time)

        class=class="hl-string">"hl-comment"># --- ACTIVITY 10: Payroll Record Approved ---
        class=class="hl-string">"hl-comment"># Final approval timestamp
        approve_time = pay_record.get(class="hl-string">'approvalDateTime')
        add_event(class="hl-string">"Payroll Record Approved", approve_time, specialist=class="hl-string">"Payroll Manager")

        class=class="hl-string">"hl-comment"># --- ACTIVITY 11: Bank Transfer File Generated ---
        class=class="hl-string">"hl-comment"># Distribution file generation
        dist_time = pay_record.get(class="hl-string">'distribution', {}).get(class="hl-string">'fileGenerationDateTime')
        add_event(class="hl-string">"Bank Transfer File Generated", dist_time)

        class=class="hl-string">"hl-comment"># --- ACTIVITY 12: Payment Executed ---
        class=class="hl-string">"hl-comment"># The actual check date or payment date
        pay_date = pay_record.get(class="hl-string">'paymentDate')
        class=class="hl-string">"hl-comment"># Convert date-only string to datetime (assuming 9 AM local)
        if pay_date:
            pay_dt_time = fclass="hl-string">"{pay_date}T09:00:00"
            add_event(class="hl-string">"Payment Executed", pay_dt_time)

        class=class="hl-string">"hl-comment"># --- ACTIVITY 13: Pay Slip Published ---
        class=class="hl-string">"hl-comment"># Usually available on Check Date
        class=class="hl-string">"hl-comment"># Or specific class="hl-string">'publicationDate' if available
        pub_date = pay_record.get(class="hl-string">'payStatementAvailableDateTime')
        if not pub_date and pay_date:
             pub_date = fclass="hl-string">"{pay_date}T08:00:00"
        add_event(class="hl-string">"Pay Slip Published", pub_date)

        class=class="hl-string">"hl-comment"># --- ACTIVITY 14: Tax Filing Completed ---
        class=class="hl-string">"hl-comment"># Tax filing status date
        tax_file_time = pay_record.get(class="hl-string">'taxFiling', {}).get(class="hl-string">'completionDateTime')
        add_event(class="hl-string">"Tax Filing Completed", tax_file_time)

        class=class="hl-string">"hl-comment"># --- ACTIVITY 15: Retrospective Adjustment Posted ---
        class=class="hl-string">"hl-comment"># Check if this record is marked as a retro adjustment
        is_retro = pay_record.get(class="hl-string">'isRetroactive', False)
        if is_retro:
            retro_time = pay_record.get(class="hl-string">'postingDateTime', calc_time)
            add_event(class="hl-string">"Retrospective Adjustment Posted", retro_time, retro=True)

    return pd.DataFrame(event_log)

class=class="hl-string">"hl-comment"># === EXECUTION ===
if __name__ == class="hl-string">"__main__":
    class=class="hl-string">"hl-comment"># 1. Authenticate
    token = get_access_token()
    
    if token:
        class=class="hl-string">"hl-comment"># 2. Fetch Data
        print(class="hl-string">"Fetching Payroll Data...")
        class=class="hl-string">"hl-comment"># Filter for last 90 days - example
        payroll_raw = fetch_adp_data(PAYROLL_API_URL, token)
        
        print(class="hl-string">"Fetching Time Data...")
        time_raw = fetch_adp_data(TIME_API_URL, token)
        
        class=class="hl-string">"hl-comment"># 3. Transform
        print(class="hl-string">"Generating Event Log...")
        df_events = generate_event_log(payroll_raw, time_raw)
        
        class=class="hl-string">"hl-comment"># 4. Export
        if not df_events.empty:
            class=class="hl-string">"hl-comment"># Ensure timestamp format
            df_events[class="hl-string">'EventDateTime'] = pd.to_datetime(df_events[class="hl-string">'EventDateTime']).dt.strftime(class="hl-string">'%Y-%m-%d %H:%M:%S')
            df_events.to_csv(OUTPUT_FILENAME, index=False)
            print(fclass="hl-string">"Success! Event log written to {OUTPUT_FILENAME} with {len(df_events)} rows.")
        else:
            print(class="hl-string">"No events generated.")

Steps

Log in to ADP Workforce Now with Administrator or Payroll Practitioner access rights.
Navigate to Reports & Analytics and select Custom Reports from the dashboard menu.
Click New Custom Report and select the Payroll data domain. Depending on your version, this may be labeled as Pay Data or Payroll Register.
In the Field Selection step, locate and add the unique identifier for the case. Select File Number or Associate ID combined with Pay Frequency and Pay Period Number to construct the PayrollRecordId.
Select all relevant date fields required to map the activities. You must include Pay Period Start Date, Pay Period End Date, Check Date, Period End Date, and Calculation Date. Note that some audit fields like Timecard Approval Date may need to be joined from the Time & Attendance module if not present in the primary view.
Add financial and dimension fields including Gross Pay, Net Pay, Department, Cost Center, and Tax Jurisdiction.
Add the Audit Trail or Field Changes block to the report layout if available. This is crucial for capturing manual events like Data Correction Performed. If this is not joinable in one report, you must create a separate Audit Report and join by Employee ID and Pay Period externally.
Configure filters to exclude voided checks and restrict the date range to the desired analysis window (e.g., Last 12 Months).
Navigate to the Sort & Total step and sort by Pay Period Start Date and then by Associate ID to ensure data is ordered logically.
Proceed to the Run/Schedule step. Choose Run Now to test, then set up a recurring Schedule to export the file as a CSV or Excel format.
Once the raw wide-format report is generated, use an ETL tool or script to transform the data. You must unpivot the date columns so that each date field becomes a separate row in the event log (Activity).
Verify the final CSV contains the required columns: PayrollRecordId, ActivityName, EventDateTime, and SourceSystem before uploading to ProcessMind.

Configuration

Report Type: Standard Custom Report
Data Domain: Payroll / Pay Data Dictionary
Output Format: Comma Separated Values (CSV)
Recommended Date Range: Rolling 12 to 24 months for trend analysis
Key Filters: Pay Group Code (select relevant groups), Company Code (if multi-entity), Status is Active or Leave
Granularity: One row per Associate per Pay Period (Raw), transformed to multiple rows per Associate (Final)
Permissions Required: View Payroll Data, View Audit Trails, Create Custom Reports
Localization: Ensure date formats are set to ISO 8601 (YYYY-MM-DD HH:MM:SS) in user preferences to avoid ambiguity

a Sample Query config

/* 
ADP Workforce Now does not accept SQL queries from end-users. 
The following configuration block represents the Transformation Logic required to convert the ADP Custom Report export (Wide Format) into the Process Mining Event Log (Long Format).

Input Source: ADP_Custom_Payroll_Export.csv
Logic Language: Pseudo-ETL/Config
*/

TRANSFORMATION_CONFIG {

  GLOBAL_SETTINGS {
    SOURCE_SYSTEM: "ADP Workforce Now"
    CASE_ID_FORMULA: CONCATENATE(Field_AssociateID, "-", Field_PayPeriodNumber, "-", Field_Year)
    LAST_DATA_UPDATE: SYSTEM_TIMESTAMP()
  }

  ACTIVITY_MAPPING_RULES {

    /* 1. Time Sheet Submitted */
    RULE "Time Sheet Submitted" {
      IF Field_Timecard_Submit_Date IS NOT NULL THEN
        CREATE_EVENT(
          ACTIVITY: "Time Sheet Submitted",
          TIMESTAMP: Field_Timecard_Submit_Date,
          ATTRIBUTES: [PayrollSpecialistName: Field_Timecard_User, IsManualIntervention: "False"]
        )
    }

    /* 2. Time Sheet Approved */
    RULE "Time Sheet Approved" {
      IF Field_Timecard_Approval_Date IS NOT NULL THEN
        CREATE_EVENT(
          ACTIVITY: "Time Sheet Approved",
          TIMESTAMP: Field_Timecard_Approval_Date,
          ATTRIBUTES: [PayrollSpecialistName: Field_Manager_Name, IsManualIntervention: "True"]
        )
    }

    /* 3. Payroll Record Initialized */
    RULE "Payroll Record Initialized" {
      IF Field_Pay_Period_Start_Date IS NOT NULL THEN
        CREATE_EVENT(
          ACTIVITY: "Payroll Record Initialized",
          TIMESTAMP: Field_Pay_Period_Start_Date,
          ATTRIBUTES: [PayGroupCode: Field_PayGroup, IsRetrospective: "False"]
        )
    }

    /* 4. Incentive Data Imported */
    RULE "Incentive Data Imported" {
      IF Field_Import_Batch_Date IS NOT NULL AND Field_Batch_Type == "Import" THEN
        CREATE_EVENT(
          ACTIVITY: "Incentive Data Imported",
          TIMESTAMP: Field_Import_Batch_Date,
          ATTRIBUTES: [IsManualIntervention: "False"]
        )
    }

    /* 5. Gross Pay Calculated */
    RULE "Gross Pay Calculated" {
      IF Field_Calc_DateTime IS NOT NULL THEN
        CREATE_EVENT(
          ACTIVITY: "Gross Pay Calculated",
          TIMESTAMP: Field_Calc_DateTime,
          ATTRIBUTES: [GrossPayAmount: Field_Gross_Pay, DepartmentCode: Field_Home_Dept]
        )
    }

    /* 6. Benefits Deductions Applied */
    RULE "Benefits Deductions Applied" {
      /* Often occurs simultaneous to Calc, adding 1 second for logical sort */
      IF Field_Calc_DateTime IS NOT NULL AND Field_Total_Deductions > 0 THEN
        CREATE_EVENT(
          ACTIVITY: "Benefits Deductions Applied",
          TIMESTAMP: DATE_ADD(Field_Calc_DateTime, 1, "SECOND"),
          ATTRIBUTES: [GrossPayAmount: Field_Gross_Pay]
        )
    }

    /* 7. Audit Exception Flagged */
    RULE "Audit Exception Flagged" {
      IF Field_Error_Message_Timestamp IS NOT NULL THEN
        CREATE_EVENT(
          ACTIVITY: "Audit Exception Flagged",
          TIMESTAMP: Field_Error_Message_Timestamp,
          ATTRIBUTES: [IsManualIntervention: "False"]
        )
    }

    /* 8. Data Correction Performed */
    RULE "Data Correction Performed" {
      IF Field_Audit_Change_Date IS NOT NULL THEN
        CREATE_EVENT(
          ACTIVITY: "Data Correction Performed",
          TIMESTAMP: Field_Audit_Change_Date,
          ATTRIBUTES: [PayrollSpecialistName: Field_Audit_User, IsManualIntervention: "True"]
        )
    }

    /* 9. Payroll Result Previewed */
    RULE "Payroll Result Previewed" {
      IF Field_Preview_Run_DateTime IS NOT NULL THEN
        CREATE_EVENT(
          ACTIVITY: "Payroll Result Previewed",
          TIMESTAMP: Field_Preview_Run_DateTime,
          ATTRIBUTES: [IsManualIntervention: "True"]
        )
    }

    /* 10. Payroll Record Approved */
    RULE "Payroll Record Approved" {
      IF Field_Finalize_DateTime IS NOT NULL THEN
        CREATE_EVENT(
          ACTIVITY: "Payroll Record Approved",
          TIMESTAMP: Field_Finalize_DateTime,
          ATTRIBUTES: [PayrollSpecialistName: Field_Finalizer_User, IsManualIntervention: "True"]
        )
    }

    /* 11. Bank Transfer File Generated */
    RULE "Bank Transfer File Generated" {
      /* Logic: Usually occurs 2 hours after Finalize or at specific cutoff */
      IF Field_ACH_File_Date IS NOT NULL THEN
        CREATE_EVENT(
          ACTIVITY: "Bank Transfer File Generated",
          TIMESTAMP: Field_ACH_File_Date,
          ATTRIBUTES: [IsManualIntervention: "False"]
        )
    }

    /* 12. Payment Executed */
    RULE "Payment Executed" {
      IF Field_Check_Date IS NOT NULL THEN
        CREATE_EVENT(
          ACTIVITY: "Payment Executed",
          TIMESTAMP: Field_Check_Date,
          ATTRIBUTES: [GrossPayAmount: Field_Gross_Pay, IsRetrospective: "False"]
        )
    }

    /* 13. Pay Slip Published */
    RULE "Pay Slip Published" {
      IF Field_Advice_Available_Date IS NOT NULL THEN
        CREATE_EVENT(
          ACTIVITY: "Pay Slip Published",
          TIMESTAMP: Field_Advice_Available_Date,
          ATTRIBUTES: [IsManualIntervention: "False"]
        )
    }

    /* 14. Tax Filing Completed */
    RULE "Tax Filing Completed" {
      IF Field_Tax_Filing_Confirmation_Date IS NOT NULL THEN
        CREATE_EVENT(
          ACTIVITY: "Tax Filing Completed",
          TIMESTAMP: Field_Tax_Filing_Confirmation_Date,
          ATTRIBUTES: [TaxJurisdictionCode: Field_Tax_State, IsManualIntervention: "False"]
        )
    }

    /* 15. Retrospective Adjustment Posted */
    RULE "Retrospective Adjustment Posted" {
      IF Field_Adjustment_Run_Date IS NOT NULL AND Field_Run_Type == "Adjustment" THEN
        CREATE_EVENT(
          ACTIVITY: "Retrospective Adjustment Posted",
          TIMESTAMP: Field_Adjustment_Run_Date,
          ATTRIBUTES: [IsRetrospective: "True", IsManualIntervention: "True"]
        )
    }
  }
}

Your Payroll Processing Data Template

Your Payroll Processing Data Template

Payroll Processing Attributes

Payroll Processing Activities

Extraction Guides

ADP Workforce Now Custom Reporting Export

Steps

Configuration

a Sample Query config

ADP Workforce Now Payroll API Python Script

Steps

Configuration

a Sample Query python

General Ledger Interface File Extraction

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Configuration

a Sample Query config

Ready to Get Started?

Fix Payroll Processing Delays in ADP Workforce Now Today

Your Payroll Processing Data Template

Your Payroll Processing Data Template

Payroll Processing Attributes

Payroll Processing Activities

Extraction Guides

ADP Workforce Now Custom Reporting Export

Steps

Configuration

a Sample Query config

ADP Workforce Now Payroll API Python Script

Steps

Configuration

a Sample Query python

General Ledger Interface File Extraction

Steps

Configuration

a Sample Query config

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Ready to Get Started?

Fix Payroll Processing Delays in ADP Workforce Now Today