---
title: "Hailey HR to PeopleStrong Migration: A Technical Guide"
slug: hailey-hr-to-peoplestrong-migration-a-technical-guide
date: 2026-08-20
author: Roopi
categories: [HRIS, Migration Guide]
excerpt: "A technical guide to migrating from Hailey HR to PeopleStrong — covering API extraction, data mapping, rate limits, GDPR compliance, and common failure modes."
tldr: "Treat Hailey HR to PeopleStrong as a master-data-first migration: build org hierarchies, map flat salaries to CTC structures, and validate payroll before cutover."
canonical: https://clonepartner.com/blog/hailey-hr-to-peoplestrong-migration-a-technical-guide/
---

# Hailey HR to PeopleStrong Migration: A Technical Guide


# Hailey HR to PeopleStrong Migration: A Technical Guide

Migrating from Hailey HR to PeopleStrong means moving from a Nordic-focused SME HRIS to an enterprise-grade HCM platform built primarily for India and Asia-Pacific. The two systems have fundamentally different data models, API architectures, and feature scopes. This is not a lift-and-shift.

Hailey HR optimizes for speed and simplicity — an employee profile is largely a flat document with a department, manager, and role. PeopleStrong operates on a deeply hierarchical architecture where an employee must be assigned to a specific **Position**, linked to a **Designation**, tied to a **Grade** under a **Band**, all within a defined **Legal Entity** and **Worksite**. If you attempt a direct export-import without a transformation layer, your PeopleStrong implementation will break at the foundation: payroll inputs, approval workflows, and reporting structures will all fail.

This guide covers extraction from Hailey, field mapping, API constraints on both sides, loading into PeopleStrong, compliance considerations for moving EU employee PII, and the testing protocols that separate a clean cutover from a multi-week cleanup.

## Why Teams Move from Hailey HR to PeopleStrong

Hailey HR handles employee lifecycle management, onboarding workflows, e-signatures, and GDPR compliance well for European SMEs with roughly 100–2,000 employees. But it is not a payroll system, not a benefits portal, and lacks deep coverage outside Northern Europe.

PeopleStrong is a different platform entirely — an enterprise HCM suite with modules spanning **Recruit, Core HR, Payroll, Leave & Attendance, Performance, Learning, Compensation, Analytics**, and more. It supports over 2 million users across 500+ enterprises and is especially strong in India, Southeast Asia, and the Middle East.

The typical trigger: a company with Nordic roots is expanding into APAC and needs native payroll processing, statutory compliance for local labor laws, and a platform that scales beyond the ceiling where Hailey starts to feel tight.

## Data Model Differences: Hailey HR vs. PeopleStrong

Understanding the structural gap between these two platforms is step one. Get this wrong, and every downstream step — scripting, validation, UAT — compounds the error.

### Hailey HR's Data Model

Hailey organizes data around the **employee profile** (the "digital employee file"). Each profile contains core identity fields, employment details, custom employee and employment fields, salary data, time-off records, education and certification records, documents organized in folders, and manager relationships. The company-level API endpoint returns arrays of custom fields, teams, locations, titles, legal entities, departments, business areas, and cost centers, each with unique identifiers. ([api.haileyhr.app](https://api.haileyhr.app/docs/v1/docs.json))

Hailey also officially supports **multiple employments**, future and past employments, casual employments, and a **priority** field when intervals overlap. This matters because PeopleStrong models employment differently, and you need explicit rules for what becomes the primary assignment, what becomes historical, and what gets archived.

### PeopleStrong's Data Model

PeopleStrong uses a hierarchical structure built around **Org Units, Worksites, and Entities**. Employee records are richer out of the box — PeopleStrong natively tracks everything from investment declarations and tax proof submissions to full-and-final settlements. The platform expects master data such as work sites, org units, bands, grades, designations, cost centers, employment types, and position data to exist and be configured centrally before employees are loaded. ([s2demo-admin.peoplestrong.com](https://s2demo-admin.peoplestrong.com/AltHelp/Content/Alt%20Admin%20Help/Learn%20by%20Module/HRIS/HRIS%20Master/Org%20Unit.htm))

PeopleStrong's own admin help uses examples like **Business Unit → Function → Department** for org units and **Zone → Region → Branch** for work sites. Its API exposes data with filters for Org Unit, Worksite, Entity, Employee Code, Employee Name, and Official Mail ID — more granular than Hailey's flat employee list.

### The Mapping Challenge

| Hailey HR Concept | PeopleStrong Equivalent | Migration Notes |
|---|---|---|
| Employee ID (UUID) | Employee Code | PeopleStrong uses alphanumeric codes; maintain a mapping table |
| Department / Business Area | Org Unit | PeopleStrong's hierarchy is deeper — departments nest under org units |
| Location | Worksite | May require geo-coordinates and compliance zone data |
| Legal Entity | Entity | PeopleStrong entities carry statutory and payroll configuration |
| Title | Designation (sometimes Job Role) | Not a 1:1 mapping in all cases |
| Custom Fields | Configurable Fields | Requires PeopleStrong admin to create matching fields before import |
| Time Off Reasons | Leave Types | PeopleStrong's leave module is policy-driven with accrual rules |
| Salary | Compensation / CTC Components | PeopleStrong breaks compensation into basic, HRA, allowances, reimbursements |
| Documents | Employee Documents | Different access control models; verify inbound upload path early |

> [!WARNING]
> **Custom fields are the biggest wildcard.** Teams often store compensation details, benefits info, equipment tracking, and probation status in Hailey custom fields because the platform doesn't natively support these modules. Audit every custom field before migration and decide whether it maps to a native PeopleStrong module, a configurable field, or is obsolete.

## Extracting Data from Hailey HR

You have two extraction paths: the REST API and manual CSV export.

### REST API (Recommended)

Hailey provides an open REST API (documented at api.haileyhr.app/docs/v1) with endpoints for all major data objects. Authentication uses personal access tokens, and the API is OpenAPI-specified. A third-party Node.js client (`hailey-api-client`) is available on GitHub, auto-generated from the OpenAPI schema.

Key endpoints for migration:

- **`GET /Employees`** — All employees with detailed information: ID, account status, contact details, employment details
- **`GET /Company`** — Custom fields, teams, locations, titles, legal entities, departments with unique IDs
- **`GET /Salaries`** — All salaries accessible to the authenticated user
- **`GET /TimeOffs`** — Time off for all employees, with optional `from`/`to` date filters
- **`GET /Educations`** — Education records
- **`GET /Certifications`** — Certification records
- **`GET /Employments`** — Employment history records, including future/past and casual employment records with the `priority` field for overlapping intervals

**Hailey webhook POST payload structure** (fired when company or employee data changes):
```json
{
  "event": "employee.updated",
  "companyId": "abc-123",
  "employeeId": "emp-uuid-456",
  "timestamp": "2024-03-15T14:22:00Z"
}
```
Webhooks deliver a `companyId` or `employeeId` — not a full diff. Your handler must re-query the relevant endpoint to capture current state. Enable these during phased migration to catch changes in the transition window.

**API output depends on the rights of the user behind the token.** Use a dedicated service account with the broadest legitimate access, or you risk exporting an incomplete view of employees, salaries, or documents without noticing until UAT.

```python
import requests
import json

BASE_URL = "https://api.haileyhr.app/api"
HEADERS = {
    "Authorization": "Bearer YOUR_ACCESS_TOKEN",
    "Content-Type": "application/json"
}

endpoints = [
    "Employees", "Salaries", "TimeOffs",
    "Educations", "Certifications", "Employments", "Company"
]

for endpoint in endpoints:
    response = requests.get(f"{BASE_URL}/{endpoint}", headers=HEADERS)
    with open(f"hailey_{endpoint.lower()}.json", "w") as f:
        json.dump(response.json(), f, indent=2)
```

Store the raw JSON responses — don't transform on the fly. You will want the original data for audit and reconciliation.

**Document extraction from Hailey:** The API returns document metadata (Document ID, Employee ID, Document Type, Creation Date, filename). Binary files are retrieved via a separate authenticated download endpoint that returns the file as a binary stream — not a base64 blob, not a redirect URL. Iterate metadata records and download each file individually using the same Bearer token. Store temporarily in a secure, AES-256 encrypted bucket before uploading to PeopleStrong.

### Manual CSV Export

Hailey supports exporting master data to an Excel-compatible file from the employee directory. This works as a validation cross-check against API extracts, but it is not practical as the primary extraction method for anything over ~200 employees — you lose relational IDs and nested data structures.

### What Hailey Does Not Expose

- **Workflow history** (onboarding tasks, e-signature completions) is not available via API. Request a manual export from Hailey support if you need it.
- **Manager notes** (confidential notes) are access-controlled and may not surface depending on your token's permissions.
- **Audit logs** — changes to employee records over time are not exposed as a dedicated endpoint.

> [!NOTE]
> Hailey retains data for 30 days after an agreement ends, then deletes everything using crypto shredding, which renders the data unreadable rather than physically overwriting it. **If a migration fails and Hailey has already initiated the deletion clock, you have a hard 30-day window to complete re-extraction.** If you are past day 25 and the migration has not succeeded, contact Hailey support immediately to discuss data retention extension options.

## The Mapping Decisions That Define Scope

### Org Structure

In Hailey, you think in departments, business areas, legal entities, teams, and locations. In PeopleStrong, **org unit types** are the named hierarchy levels and **work site types** are the named location levels. The platform expects hierarchies with unique source codes. ([s2demo-admin.peoplestrong.com](https://s2demo-admin.peoplestrong.com/AltHelp/Content/Alt%20Admin%20Help/Learn%20by%20Module/HRIS/HRIS%20Master/Org%20Unit.htm))

A practical mapping: Hailey departments and business areas become PeopleStrong org units. Hailey locations become worksites. Hailey cost centers map to PeopleStrong cost centers. Hailey employment types map to PeopleStrong employment types. Hailey titles often map to designation. Teams either become a lower-level org construct or stay as reporting metadata. Do not guess — PeopleStrong masters rely on codes and hierarchy.

### Compensation: Flat Salary to CTC Components

This is a trap. Hailey stores salary as a single figure with a salary type, pay period, currency, and history. PeopleStrong breaks compensation into a **CTC structure**: basic, HRA, special allowance, reimbursements, and more. A Hailey salary row is not enough to create a meaningful PeopleStrong payroll setup.

Two options:
1. **Define default CTC structures** in PeopleStrong and map Hailey gross salaries to components using agreed split ratios (e.g., Basic = 40% of CTC, HRA = 20% of Basic, Special Allowance = remainder). This requires upfront agreement with Finance on component breakdowns per grade or band.
2. **Import the gross figure** and let HR/Finance restructure compensation in PeopleStrong post-migration. Faster to execute, but the first payroll run will require manual intervention.

Option 1 is cleaner but requires upfront agreement on component breakdowns. Option 2 is faster but shifts work downstream and risks the first payroll run failing without manual correction.

### Leave and Attendance

Hailey tracks time off as requested and approved calendar entries. PeopleStrong tracks leave as **policy-driven accruals** with opening balances, credits, debits, holiday calendars, workflows, and reports. Flat time-off records do not map cleanly.

The standard approach:
1. **Freeze leave requests in Hailey** 48 hours before cutover.
2. Extract the final accrued balance for each leave type per employee.
3. Import these as **opening balances** in PeopleStrong — not raw historical records.
4. Configure PeopleStrong's accrual engine for future periods before importing any employee data.
5. Any leave requests for dates after cutover must be re-entered in PeopleStrong.

If you load leave history before PeopleStrong's leave policies are configured, the records may land but the behavior will not match what HR expects.

### Job History and Effective Dates

Hailey tracks job changes as a list of events. If you are bringing historical records into PeopleStrong, all date-bounded records must be contiguous — no overlapping dates, no gaps. If an employee had a salary increase and a manager change on the exact same day in Hailey, you must combine these into a single record or sequence them with distinct timestamps.

> [!CAUTION]
> **Same-day changes:** Separate records with identical effective dates will cause database constraint errors in PeopleStrong. Merge same-day events into a single record during transformation.

### Multi-Employment History

Hailey officially supports multiple employments, future/past employments, casual employments, and a priority field when intervals overlap. ([api.haileyhr.app](https://api.haileyhr.app/docs/v1/docs.json)) PeopleStrong can model rich employee structures, but you still need explicit rules for what becomes the primary assignment, what becomes historical data, and what gets archived. Skip this decision and reporting lines, location-based rules, and payroll inputs will drift out of sync.

## Loading Data into PeopleStrong

### API Architecture and Access

PeopleStrong exposes **Inbound APIs** (where your application pushes data in) and Outbound APIs. For migration, you will primarily use inbound endpoints. API access is provided on a **request-only basis** — coordinate with PeopleStrong's integrations team (Integrations@peoplestrong.com) to get access provisioned for your tenant.

Authentication uses an access token generated from your **tenant ID and secret key**. **Tokens expire after five minutes**, so build refresh logic into your pipeline before you write a single import script. ([api-docs.peoplestrong.com](https://api-docs.peoplestrong.com/))

> [!NOTE]
> **Sandbox vs. Production:** PeopleStrong's sandbox environment replicates the API surface but may have lower rate limits than production and may gate certain endpoints (particularly payroll-adjacent inbound APIs). Confirm with your PeopleStrong integrations contact which endpoints are fully available in sandbox before building your validation plan around them.

### Rate Limits and Constraints

This is where migrations hit unexpected walls. Confirm current tier-specific limits with PeopleStrong before building your pipeline — these figures represent documented platform behavior but are not published as fixed numbers for all tenants:

- **Rate limiting** is enforced on invocation count (per hour, per day, per month) and payload size. Exceeding invocation limits returns `429`; exceeding size limits returns `413`. Default limits vary by contract tier — request your tenant's specific thresholds from PeopleStrong before designing batch sizes.
- **Date range filters are capped at 15 days.** For historical data loads, batch requests into 15-day windows.
- **Pagination limits must be explicitly configured** — omitting them throws error code `EC6006`.
- **Data flow types** (Row-wise, Column-wise, Full load) must be specified or you get error code `EC6003`.
- The **`setMarkerDate`** parameter for recalling failed data cannot be older than one month. If your migration stalls, you have a 30-day window before the marker expires and failed records must be re-submitted from scratch.

### SFTP and Excel Bulk Upload

For large employee counts, PeopleStrong supports CSV import via SFTP. The expected SFTP format is UTF-8 encoded, comma-delimited CSV with headers in row 1. Required columns vary by data type (employee master, compensation, leave balance), and PeopleStrong provides template files for each through the admin UI — download these before building your transformation output. PeopleStrong also supports **Excel-based bulk upload** through its admin UI, with a **5 MB file size limit**. Data is first written to a temporary table, then processed into transactional tables, with upload transactions scheduled one by one. Large migrations need batching and queue awareness. ([s2demo-admin.peoplestrong.com](https://s2demo-admin.peoplestrong.com/AltHelp/Content/Alt%20Admin%20Help/Learn%20by%20Module/HRIS/Data%20Upload/Data%20Upload.htm))

The recommended approach:
1. **SFTP or Excel bulk upload for the initial load** (employee master data, org structure, historical compensation)
2. **Inbound API for incremental updates** during the transition period
3. **PeopleStrong webhooks** (which notify on data changes hourly) to validate imports landed correctly

### Required Load Sequence

Order matters due to relational dependencies. Load in this sequence:

1. **Foundation/Master Data:** Legal Entities, Worksites, Org Units, Departments, Bands, Grades, Designations, Employment Types, Cost Centers
2. **Employee Demographics:** Basic profiles (Name, Email, DOB, National IDs)
3. **Position and Employment Details:** Hire dates, current roles, position assignments
4. **Reporting Lines:** Manager-employee relationships (*after* all employees exist — manager IDs fail validation otherwise)
5. **Related Records:** Bank details, dependents, emergency contacts, ID documents, qualifications
6. **Compensation Data:** CTC structures, salary components
7. **Leave Balances:** Opening balances per leave type
8. **Historical Data:** Past roles, past compensation (if required)
9. **Documents:** Contracts, ID proofs, signed files

> [!WARNING]
> **The Foundation Rule:** You must build and populate PeopleStrong's organizational foundation before migrating a single employee record. If an employee's payload references a Grade ID or Org Unit that does not exist, the API will reject it with a referential integrity error — not a helpful validation message.

### Payload Example

Here is how a flat Hailey HR record translates into PeopleStrong's expected structure:

```json
{
  "employeeCode": "EMP-1042",
  "personalInfo": {
    "firstName": "Anders",
    "lastName": "Svensson",
    "dateOfBirth": "1988-04-15",
    "gender": "Male"
  },
  "jobInfo": {
    "legalEntityId": "LE_001",
    "locationId": "LOC_STOCKHOLM",
    "departmentId": "DEPT_ENG",
    "designationId": "DESIG_SNR_DEV",
    "bandId": "B4",
    "managerCode": "EMP-0998",
    "effectiveStartDate": "2023-01-01"
  }
}
```

You must maintain a mapping table in your transformation layer that translates Hailey HR's `"department": "Engineering"` into PeopleStrong's `"departmentId": "DEPT_ENG"`.

## Migrating Documents and E-Signatures

Hailey HR is often used to store employment contracts and e-signatures. Moving binary files requires a specific pipeline:

1. **Extract Metadata:** Pull document metadata via Hailey's API (Document ID, Employee ID, Document Type, Creation Date, filename).
2. **Download Binaries:** Use the authenticated binary download endpoint to retrieve each file as a binary stream. Store temporarily in a secure, AES-256 encrypted bucket.
3. **Map to PeopleStrong:** PeopleStrong requires documents categorized into specific folders. Map Hailey's document types to PeopleStrong's categories.
4. **Upload:** Use PeopleStrong's document endpoints, passing binary data as `multipart/form-data` and linking to the Employee ID.

> [!NOTE]
> **E-Signature Validity:** A downloaded PDF of a signed contract retains legal validity, but the cryptographic audit trail often lives in Hailey's e-signature provider. Request the separate audit trail documents (typically a JSON or PDF certificate of completion) from Hailey before offboarding and upload them alongside the contracts in PeopleStrong.

> [!WARNING]
> **Verify the document upload path early.** PeopleStrong's public documentation clearly covers outbound document download endpoints, but a fully documented inbound employee-document upload API was not clearly specified in the documentation reviewed for this guide. Confirm the actual load path — API endpoint, admin template upload, vendor-assisted import, or manual process — before committing to attachment parity in phase one scope. This is the one area where an assumption costs the most time at cutover.

## GDPR and Data Residency

Hailey HR is a Swedish company with EU data residency. It uses EU-owned providers with servers in Europe, encrypts personal data at rest using **AES-256**, secures communications via **TLS 1.2**, and uses **crypto shredding** to render deleted data unreadable. ([haileyhr.com](https://haileyhr.com/security-and-gdpr/))

PeopleStrong's infrastructure is primarily in India and Asia-Pacific, though it offers localized hosting options. If your PeopleStrong tenant is hosted outside the EU, transferring EU citizen data requires a lawful transfer mechanism under **GDPR Article 46** — most commonly **Standard Contractual Clauses (SCCs)** or a **Data Processing Agreement (DPA)**.

**Executing the cross-border transfer compliance process:**

1. **Initiate a DPA with PeopleStrong.** PeopleStrong maintains a standard DPA — request it from your account manager or via Integrations@peoplestrong.com before any data leaves Hailey's environment. Review it against your organization's DPA requirements and have Legal sign off.
2. **Confirm Hailey's data deletion process.** Once your Hailey agreement ends, Hailey initiates crypto shredding after 30 days. Request written confirmation from Hailey support of when deletion will occur and obtain a data deletion certificate if your DPO requires it.
3. **Determine EU hosting option availability.** If SCCs are insufficient for your legal context (e.g., sector-specific requirements), ask PeopleStrong whether an EU-region tenant is available. This affects implementation timeline.
4. **Document the transfer.** Your GDPR Article 30 Records of Processing Activities (RoPA) must be updated to reflect the new processor (PeopleStrong), data categories transferred, and transfer mechanism used.

> [!CAUTION]
> Do not begin migration until Legal has confirmed the lawful basis for transferring employee PII from an EU-hosted platform to a non-EU-hosted platform. GDPR fines can reach **4% of global annual revenue** or €20 million, whichever is higher. A failed DPA review discovered mid-migration is significantly more expensive than a two-week legal review before extraction begins.

During the migration itself:
- **Encrypt data at rest:** Any staging databases or CSV extracts must use AES-256 encryption.
- **Encrypt data in transit:** Force TLS 1.2 or higher for all API calls.
- **Restrict access:** Zero-trust access to the staging environment. Only the engineers executing the migration should have access. Audit all access logs.
- **Purge staging data:** Delete all intermediate files (raw JSON exports, transformation CSVs, staging buckets) within 72 hours of confirmed successful migration.

For more on handling sensitive HR data during migration, see our guide on [security and compliance for payroll data migration](https://clonepartner.com/blog/blog/payroll-data-migration-security-compliance/).

## Testing and Validation

Never execute a production cutover without at least two full mock migrations.

### Mock 1: Structure Test

Load a representative sample (10–15% of employees across different departments, countries, and employment types) into PeopleStrong's sandbox. Validate that:
- Org hierarchy renders correctly
- Reporting lines are accurate and managers see their direct reports
- Employee profiles display all expected fields
- Leave balances are accurate
- Document attachments are accessible

### Mock 2: Payroll Parallel Run

Load the full dataset into a sandbox. Run a payroll cycle using the migrated PeopleStrong data and compare gross-to-net outputs against your existing payroll system. Any discrepancies indicate a failure in CTC component mapping or date-bounded records.

### UAT Exit Criteria

Do not sign off on row counts alone. A serious UAT for this migration should prove that:

- Current, future-dated, terminated, contractor/casual, and multi-employment workers load correctly
- Org units, worksites, grades, designations, cost centers, managers, and employment types are correct
- Bank, ID, dependent, emergency contact, and qualification one-to-many data survived
- Leave balances and sample historical leave transactions behave correctly under live policies
- Payroll or CTC inputs match approved current compensation
- Employee documents, generated letters, and signed files are findable and open correctly
- Downstream integrations and ESS/mobile views show the correct primary employment record

If payroll, leave, or lifecycle workflows are in scope, **test behavior, not just stored data**.

## Common Failure Modes

**1. Custom field data loss.** Teams skip the custom field audit and discover post-migration that months of manually-entered data (equipment tracking, benefits notes, probation status) didn't make it into PeopleStrong. Fix: audit every Hailey custom field before transformation begins and map each to a destination or explicitly mark as deprecated.

**2. Leave balance errors.** Importing raw time-off records without configuring PeopleStrong's leave policies first leads to incorrect accrual calculations. Fix: set up leave policies in PeopleStrong, then import Hailey data as opening balances — never as raw historical records.

**3. Compensation structure mismatch.** Hailey stores a single salary number. PeopleStrong expects a structured CTC breakdown. If you import a flat gross salary without mapping to CTC components, the first payroll run will fail or produce incorrect outputs. Fix: agree on component split ratios with Finance before migration begins.

**4. API rate limit throttling.** Attempting to push all records through PeopleStrong's Inbound API in one batch will trigger `429` errors. Fix: use SFTP or Excel bulk upload for initial loads and reserve the Inbound API for incremental updates. Request your tenant's specific hourly/daily invocation limits from PeopleStrong before designing batch sizes.

**5. Multi-employment confusion.** Hailey supports overlapping employments with priority fields. Without explicit rules for primary vs. secondary assignments in PeopleStrong, reporting lines and payroll inputs drift. Fix: define assignment rules before extraction, encode them in your transformation scripts, and validate against multi-employment test cases specifically.

**6. Document upload path assumptions.** Assuming PeopleStrong's inbound document upload works the same as outbound without verifying early leads to a scramble at cutover. Fix: confirm the upload path in week one of the project, not week six.

**7. Same-day effective date conflicts.** Multiple Hailey events on the same calendar date (e.g., simultaneous salary change and manager change) cause database constraint errors in PeopleStrong. Fix: merge same-day events or assign sequential timestamps during transformation.

**8. Token expiry mid-batch.** PeopleStrong access tokens expire after five minutes. An unhandled expiry in a long-running import script produces silent failures — records stop loading but the script continues. Fix: implement token refresh logic before writing any import code.

## Cutover Plan

### The Weekend Sequence

1. **Friday 5:00 PM:** Lock Hailey HR. Revoke write access for all users. Extract the final delta (changes since the last sync).
2. **Saturday Morning:** Run the transformation pipeline. Push the final delta to PeopleStrong.
3. **Saturday Afternoon:** Run automated validation scripts comparing record counts and field-level checksums between source and target.
4. **Sunday:** HR and IT stakeholders perform UAT. Spot-check complex records — recent hires, terminated employees, multi-employment workers.
5. **Monday 8:00 AM:** Go-live on PeopleStrong.

> [!NOTE]
> **Best cutover window:** After payroll close, after the last approved leave import, and before the next workflow-heavy event like a day-one onboarding batch or performance cycle launch.

Build your delta strategy around PeopleStrong's constraints: token refresh logic (tokens expire after five minutes), batching for 15-day date range caps, retry handling for `429`/`413` errors, and the one-month `setMarkerDate` limit for recalling failed data.

### Rollback Decision Tree

A cutover without a rollback plan is a bet, not an engineering decision. Define rollback triggers before go-live.

**Rollback triggers — stop go-live and revert if:**
- More than 2% of employee records fail validation checks on Monday morning
- Payroll inputs for the current pay period are missing or incorrect for any employee
- Manager reporting lines are wrong for more than one business unit
- Leave balances are off by more than one day for more than 5% of employees
- Any employee cannot log in to PeopleStrong by 10:00 AM Monday

**Rollback procedure:**
1. **Declare rollback** — decision made jointly by HR Director and IT Lead; must happen before 10:00 AM Monday to keep Hailey accessible during business hours.
2. **Restore Hailey write access** — re-enable all user permissions in Hailey immediately.
3. **Communicate to employees** — template message: "We are continuing to use [Hailey HR] while we resolve a technical issue. No action is required from you."
4. **Preserve PeopleStrong state** — do not delete the failed migration in PeopleStrong; preserve it for root cause analysis.
5. **Identify root cause** — run validation scripts against the PeopleStrong sandbox export to identify which records failed and why.
6. **Schedule re-attempt** — minimum two weeks after rollback to allow for transformation fixes and a full mock migration.

**Critical constraint:** Hailey's 30-day data retention clock starts when your agreement ends. If you have terminated your Hailey subscription before go-live, a rollback may land you in a window where Hailey data is actively being deleted. **Do not terminate your Hailey subscription until PeopleStrong go-live is confirmed stable** — typically 5 business days post-cutover.

## When to Bring in Help

This migration is manageable in-house if you have fewer than 500 employees, minimal custom fields, no payroll restructuring, and engineering resources familiar with both APIs.

It gets complex fast with:
- 1,000+ employees with years of historical data
- Dozens of custom fields with inconsistent data quality
- Payroll restructuring from flat salaries to CTC components
- Multi-country operations requiring different PeopleStrong entity configurations
- Document migration with access-control requirements
- Active Hailey e-signature workflows that need audit trail preservation

**Effort benchmarks** based on observed migrations:

| Scope | Estimated Duration |
|---|---|
| Under 500 employees, no payroll restructuring, minimal custom fields | 1–2 weeks |
| 500–1,000 employees, CTC restructuring, moderate custom fields | 3–4 weeks |
| 1,000+ employees, payroll restructuring, multi-entity, document migration | 4–8 weeks |
| 1,000+ employees + parallel payroll run + GDPR cross-border compliance | 8–12 weeks |

These estimates assume dedicated engineering time, an accessible PeopleStrong sandbox, and completed master data decisions before scripting begins. Add 30–50% for teams where master data (grades, bands, org structure) has not yet been configured in PeopleStrong.

## Migration Decision Summary

| Scenario | Recommended Approach |
|---|---|
| Under 200 employees, no payroll | Excel bulk upload; manual validation |
| 200–1,000 employees, no payroll | SFTP initial load + Inbound API delta |
| Any size, payroll in scope | Parallel payroll run required before cutover |
| EU employees to non-EU PeopleStrong tenant | DPA + SCCs before extraction begins |
| Multi-employment workers present | Explicit primary/secondary assignment rules before scripting |
| Hailey subscription already terminated | Verify data retention window immediately; 30-day deletion clock is active |

## What the Audit Trail Must Show

A migration from Hailey HR to PeopleStrong involves EU employee PII. Your post-migration audit trail should demonstrate:

- **Source extraction:** Timestamped raw JSON from Hailey API, stored for 12 months minimum
- **Transformation log:** Record-by-record transformation decisions, including fields merged, deprecated, or remapped
- **Load confirmation:** PeopleStrong API response codes and transaction IDs for every record submitted
- **Validation report:** Field-level checksum comparison between source and target, signed off by HR and IT
- **Access log:** Who accessed the staging environment and when
- **Data deletion confirmation:** Proof that staging files were purged within 72 hours of confirmed successful migration
- **GDPR transfer documentation:** Executed DPA, SCC reference, and RoPA update

If you are audited under GDPR or asked to demonstrate compliance by a client or regulator, these records are the answer.

## Making the Cutover Boring

A good Hailey HR to PeopleStrong migration should feel uneventful on go-live day. The hard work happens earlier: stable master data, clear code strategy, explicit rules for multi-employment and salary history, validated leave and payroll behavior, and a delta plan that accounts for token expiry, rate limits, and attachment ambiguity.

The table below summarizes what goes wrong and which section of this guide prevents it:

| Common Failure | Root Cause | Prevention |
|---|---|---|
| Custom field data loss | No pre-migration audit | Audit every custom field before transformation |
| Leave balance errors | Policies not configured before data load | Set up leave policies first; import as opening balances |
| Payroll run fails | Flat salary not mapped to CTC components | Agree on component splits with Finance before scripting |
| 429 throttling | All records pushed via API at once | Use SFTP/bulk upload for initial load |
| Multi-employment drift | No primary/secondary assignment rules | Define assignment rules before extraction |
| Token expiry failures | No refresh logic in import scripts | Implement token refresh before writing import code |
| Same-day constraint errors | Multiple events on same effective date | Merge or sequence same-day events in transformation |
| Rollback with no Hailey access | Subscription terminated pre-go-live | Keep Hailey active until 5 days post-go-live confirmed |

If your scope includes payroll continuity, complex org hierarchies, or signed document migration, this is where a specialist migration team earns its keep. Our [HRIS data migration checklist](https://clonepartner.com/blog/blog/hris-data-migration-checklist/) covers the full planning framework, and if you are still evaluating whether to leave Hailey, start with [Hailey HR Alternatives (2026)](https://clonepartner.com/blog/blog/hailey-hr-alternatives-2026-tco-features-migration-paths/).

> Migrating from Hailey HR to PeopleStrong and want to get it right on the first run? Talk to our engineers. We'll scope the work, map the data model, and handle the technical execution — so your HR team can focus on the rollout, not the plumbing.
>
> [Talk to us](https://cal.com/clonepartner/meet?duration=30)

## Frequently asked questions

### Can you migrate data directly from Hailey HR to PeopleStrong?

No direct pipe works. Hailey HR uses a flat data model while PeopleStrong requires a deeply hierarchical structure with Org Units, Grades, Bands, and Designations. You need a transformation layer — a staging database or ETL pipeline — to map Hailey text fields to PeopleStrong's relational IDs. In practice, most teams use a hybrid of APIs and Excel-based admin uploads.

### What data is hardest to map between Hailey HR and PeopleStrong?

Org hierarchy, multi-employment history, salary-to-CTC mapping, leave balances, and documents are the hardest because the two platforms do not share a one-to-one data model. Custom fields are also a wildcard — teams often store compensation, benefits, and equipment data in Hailey custom fields that need to be mapped to native PeopleStrong modules.

### What are PeopleStrong's API rate limits?

PeopleStrong enforces rate limits on invocation count (per hour, day, and month) and payload size. Exceeding invocation limits returns HTTP 429; exceeding size limits returns HTTP 413. Date range filters are capped at 15 days per request. Tokens expire after five minutes. Exact limits depend on your tenant configuration.

### What are the biggest risks in a Hailey HR to PeopleStrong migration?

The top risks are: (1) custom field data loss if you skip the field audit, (2) leave balance errors from importing time-off records without configuring PeopleStrong's leave policies first, (3) payroll failures from importing flat salary figures instead of structured CTC components, (4) GDPR non-compliance if transferring PII from EU-hosted Hailey to a non-EU PeopleStrong tenant, and (5) document upload path uncertainty if you don't verify inbound upload capabilities early.

### How long does a Hailey HR to PeopleStrong migration take?

For a straightforward migration under 500 employees with minimal custom fields, expect 1–2 weeks. For 1,000+ employees with payroll restructuring, multi-entity configuration, and document migration, plan for 4–8 weeks including sandbox validation and parallel payroll runs.