Will AI replace a Supply Chain Business Analyst?
AI risk 72/100Opportunity 84/100Future demand 76/100
How AI is affecting this role
- ›Using n8n to connect a Gmail inbox containing transporter bills to a Google Sheet, where GPT-4 Vision extracts the Invoice Number and Amount, eliminating 2 hours of daily data entry.
- ›Leveraging ChatGPT to convert a warehouse manager's verbal brief into a complex SQL query for SAP HANA to retrieve slow-moving inventory in the Pune region.
- ›Using Excel Copilot to instantly identify outlier shipping costs in a dataset of 50,000 rows and asking it to 'highlight routes where costs increased by more than 15%'.
- ›Deploying a Python-based forecasting model (using Facebook Prophet) that automatically re-trains every weekend to predict SKUs demand for the next month, replacing manual spreadsheet extrapolation.
Ways to survive
- ›Automate the ETL (Extract, Transform, Load) process for your daily reports using no-code tools before someone else does.
- ›Master the art of debugging AI-generated code to ensure accuracy in financial and inventory reporting.
- ›Focus on exception management—use AI to handle normal flows and dedicate your time to investigating anomalies the AI flags.
Ways to get ahead with AI
- ›Build an internal 'Chat with your Data' bot using LangChain or RAG that lets sales managers ask natural language questions about stock availability.
- ›Learn to fine-tune simple classification models to automatically categorize warehouse damages from images.
- ›Design end-to-end automated workflows that integrate procurement data with finance systems to close the month faster.
How ONROL helps
ONROL will teach you to build the Python scripts and n8n workflows necessary to replace manual Excel dependency, transitioning you from a data reporter to a Supply Chain Systems Architect.
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