Benchmark procurement KPIs with Google Sheets, Gmail, and Google Gemini
Ready for 3.0What this workflow does
This AI workflow has 27 nodes and runs on a schedule (every month at 09:00). Along the way it connects Google Sheets, Gmail and Google Gemini Chat Model.
How it runs
Trigger: On a schedule (every month at 09:00).
- Load Benchmark Settings (Edit Fields (Set)): sets 14 fields: ready_status, processed_status, active_benchmark_value…
- Get Ready Procurement KPIs (Google Sheets): uses Google Sheets
- Get KPI Definition (Google Sheets): uses Google Sheets
- KPI Definition Found? (If): checks a condition and branches into true / false
- Get External Benchmark (Google Sheets): uses Google Sheets
- Handle Missing KPI Definition (Edit Fields (Set)): sets 6 fields: processing_status, error_type, error_message…
- External Benchmark Found? (If): checks a condition and branches into true / false
- Mark KPI as Review Required (Google Sheets): update
- Build Benchmark Comparison Context (Code): runs custom JavaScript code
- Handle Missing External Benchmark (Edit Fields (Set)): sets 6 fields: processing_status, error_type, error_message…
…plus 14 more steps. See the full node list below.
Services it uses
Before you upgrade to n8n 3.0
Nothing in this workflow is removed in n8n 3.0, so it should import and run after the upgrade.
Nodes used (9)
- Schedule Trigger
n8n-nodes-base.scheduleTrigger - Edit Fields (Set)
n8n-nodes-base.set - Google Sheets
n8n-nodes-base.googleSheets - Code
n8n-nodes-base.code - Basic LLM Chain
@n8n/n8n-nodes-langchain.chainLlm - If
n8n-nodes-base.if - Gmail
n8n-nodes-base.gmail - Google Gemini Chat Model
@n8n/n8n-nodes-langchain.lmChatGoogleGemini - Structured Output Parser
@n8n/n8n-nodes-langchain.outputParserStructured
From the author
Quick Overview This workflow runs monthly to benchmark procurement KPI results stored in Google Sheets against external peer benchmarks, calculates gap and severity, uses Google Gemini to generate management-ready analysis, writes results back to Google…