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Generate board-ready workforce analytics and talent reports with GPT-4o

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Generate board-ready workforce analytics and talent reports with GPT-4o preview
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1. Workflow Overview

Intelligent workforce analytics and talent strategy report automation How It Works This workflow automates end to end workforce analytics and board level talent strategy reporting using a multi age...

Best for

  • HR automation workflows
  • AI RAG automation workflows
  • advanced n8n builders looking for reusable templates

Tools used

n8n-nodes-base.scheduletrigger, n8n-nodes-base.datatable, n8n-nodes-base.aggregate, n8n-nodes-base.code, @n8n/n8n-nodes-langchain.agent, @n8n/n8n-nodes-langchain.lmchatopenai, @n8n/n8n-nodes-langchain.outputparserstructured, @n8n/n8n-nodes-langchain.agenttool

Source and attribution

This workflow is cataloged by N8N Workflows and links back to its original n8n.io source page by Cheng Siong Chin.

Original n8n.io source

1.1 Workflow description

Title
Generate board-ready workforce analytics and talent reports with GPT-4o
Workflow name
Generate board-ready workforce analytics and talent reports with GPT-4o

Intelligent workforce analytics and talent strategy report automation

How It Works

This workflow automates end-to-end workforce analytics and board-level talent strategy reporting using a multi-agent AI orchestration system. Designed for HR leaders, people analytics teams, and CHROs, it eliminates manual effort in compiling workforce insights and translating them into executive-ready reports. The pipeline begins with a scheduled trigger that loads employee datasets and aggregates HR records. It then builds a skill similarity index and prepares a structured analytics dataset. A Main Orchestrator Agent coordinates two specialised sub-agents: a Workforce Analytics Agent (using SHAP value analysis and statistical tools) and a Talent Strategy Agent (leveraging skill similarity search). Results are parsed into a Board Report JSON schema, stored in a report repository, and optionally delivered via webhook. The system enables data-driven talent decisions at scale.

Setup Steps

  1. Add OpenAI or compatible LLM credentials for all Chat Model nodes.
  2. Configure employee dataset source (e.g., Google Sheets, database, or CSV node).
  3. Set the Schedule Trigger interval (daily/weekly) to match reporting cadence.
  4. Update the Prepare Report Storage node with your target storage path or bucket.
  5. Configure Optional Report Delivery webhook URL or email endpoint if needed.
  6. Verify the Board Report JSON Schema matches your organisation's reporting fields.

Prerequisites

  • OpenAI or compatible LLM API credentials
  • Employee dataset (CSV, Google Sheets, or DB)
  • Webhook endpoint or email (optional delivery)

Use Cases

  • Automated monthly board talent reports for CHROs

Customisation

  • Swap LLM models per agent for cost/performance balance

Benefits

  • Eliminates manual HR reporting effort

1.2 Logical Blocks

This catalog entry is organized from the workflow JSON. The node-level section below shows the executable blocks available for review before importing the template.

2. Block-by-Block Analysis

Block 1 - Schedule Workforce Analysis

Type / Role
n8n-nodes-base.scheduleTrigger - scheduleTrigger
Config choices
Version 1.3

Block 2 - Load Employee Dataset

Type / Role
n8n-nodes-base.dataTable - dataTable
Config choices
Version 1.1

Block 3 - Aggregate Employee Records

Type / Role
n8n-nodes-base.aggregate - aggregate
Config choices
Version 1

Block 4 - Prepare Analytics Dataset

Type / Role
n8n-nodes-base.code - code
Config choices
Version 2

Block 5 - Main Orchestrator Agent

Type / Role
@n8n/n8n-nodes-langchain.agent - agent
Config choices
Version 3.1

Block 6 - Orchestrator Chat Model

Type / Role
@n8n/n8n-nodes-langchain.lmChatOpenAi - lmChatOpenAi
Config choices
Version 1.3

Block 7 - Board Report JSON Schema

Type / Role
@n8n/n8n-nodes-langchain.outputParserStructured - outputParserStructured
Config choices
Version 1.3

Block 8 - Workforce Analytics Agent

Type / Role
@n8n/n8n-nodes-langchain.agentTool - agentTool
Config choices
Version 3

Block 9 - Analytics Agent Chat Model

Type / Role
@n8n/n8n-nodes-langchain.lmChatOpenAi - lmChatOpenAi
Config choices
Version 1.3

Block 10 - Talent Strategy Agent

Type / Role
@n8n/n8n-nodes-langchain.agentTool - agentTool
Config choices
Version 3

Block 11 - Strategy Agent Chat Model

Type / Role
@n8n/n8n-nodes-langchain.lmChatOpenAi - lmChatOpenAi
Config choices
Version 1.3

Block 12 - SHAP Value Calculator Tool

Type / Role
@n8n/n8n-nodes-langchain.toolCode - toolCode
Config choices
Version 1.3

Block 13 - Statistical Calculator Tool

Type / Role
@n8n/n8n-nodes-langchain.toolCalculator - toolCalculator
Config choices
Version 1

Block 14 - Prepare Report Storage

Type / Role
n8n-nodes-base.set - set
Config choices
Version 3.4

Block 15 - Store Workforce Report

Type / Role
n8n-nodes-base.dataTable - dataTable
Config choices
Version 1.1

Block 16 - Optional Report Delivery

Type / Role
n8n-nodes-base.httpRequest - httpRequest
Config choices
Version 4.4

Block 17 - Build Skill Similarity Index

Type / Role
n8n-nodes-base.code - code
Config choices
Version 2

Block 18 - Skill Similarity Search Tool1

Type / Role
@n8n/n8n-nodes-langchain.toolCode - toolCode
Config choices
Version 1.3

Block 19 - Sticky Note

Type / Role
n8n-nodes-base.stickyNote - stickyNote
Config choices
Version 1

Block 20 - Sticky Note1

Type / Role
n8n-nodes-base.stickyNote - stickyNote
Config choices
Version 1

Block 21 - Sticky Note2

Type / Role
n8n-nodes-base.stickyNote - stickyNote
Config choices
Version 1

Block 22 - Sticky Note3

Type / Role
n8n-nodes-base.stickyNote - stickyNote
Config choices
Version 1

Block 23 - Sticky Note4

Type / Role
n8n-nodes-base.stickyNote - stickyNote
Config choices
Version 1

Block 24 - Sticky Note5

Type / Role
n8n-nodes-base.stickyNote - stickyNote
Config choices
Version 1

Showing the first 24 of 25 workflow blocks. Download the JSON for the full node graph.

3. Summary Table

Workflow Generate board-ready workforce analytics and talent reports with GPT-4o
Complexity advanced
Nodes 25
Categories HR, AI RAG
Author Cheng Siong Chin
Published 05 Mar 2026

4. Reproducing the Workflow from Scratch

  1. 1. Download the workflow JSON

    Use the JSON export at /data/workflows/13898/13898.json as the source template for this automation.

  2. 2. Import the template into n8n

    Open n8n, import the downloaded JSON, and review each node before activating the workflow.

  3. 3. Configure credentials and variables

    Replace placeholder credentials, API keys, webhook URLs, account IDs, and environment-specific values with your own settings.

  4. 4. Test with sample data

    Run the workflow manually or in a staging workspace, inspect node output, and confirm downstream systems receive the expected data.

  5. 5. Activate and monitor

    Enable the workflow only after testing, then monitor executions, errors, and rate limits during the first production runs.

5. General Notes & Resources

Review imported nodes carefully before activation. This catalog entry is intended to help you inspect the workflow structure, understand required services, and find related templates faster.

Node names, credentials, schedules, webhook paths, and external service limits may need adjustment for your workspace.

Frequently asked questions

What does Generate board-ready workforce analytics and talent reports with GPT-4o do?

Intelligent workforce analytics and talent strategy report automation How It Works This workflow automates end to end workforce analytics and board level talent strategy reporting using a multi age...

What do I need before importing this workflow?

Review the workflow JSON, configure any required credentials in n8n, and test the automation in a safe workspace before using it in production.

Can I customize this workflow?

Yes. Use the block-by-block analysis and the downloadable JSON to inspect each node, then adjust credentials, prompts, schedules, filters, or destinations for your HR, AI RAG use case.