AI Analytics for Supply Chains

Data-Driven Supply Chain Management

🔄 Quick Recall: In the previous lesson, we identified cost optimization opportunities across the supply chain. Now we build the systems that monitor performance continuously—so you catch problems early, measure improvements, and make data-driven decisions instead of relying on gut feelings.

Flying blind is the default state for most small supply chains. Orders go out, inventory depletes, suppliers deliver (usually), and everyone hopes nothing goes wrong. Analytics replaces hope with knowledge.

By the end of this lesson, you’ll be able to:

• Identify the essential supply chain KPIs for your business
• Build a simple supply chain dashboard
• Use AI to analyze data, generate reports, and flag anomalies

The Essential Supply Chain KPIs

Not every metric is worth tracking. Focus on KPIs that drive decisions:

Order Fulfillment KPIs

Inventory KPIs

Supplier KPIs

✅ Quick Check: Which of these KPIs could you start tracking today with data you already have?

How AI Helps

“I run an e-commerce business selling [product type]. I ship about [X] orders per month from [Y] suppliers. Which 5-7 KPIs should I prioritize tracking? For each, explain how to calculate it, where to get the data, and what a red flag looks like.”

Building a Simple Dashboard

You don’t need expensive software. A simple spreadsheet dashboard provides 80% of the value:

Dashboard Layout

┌────────────────────────────────────────────┐
│           SUPPLY CHAIN DASHBOARD           │
│            Week of Feb 3, 2026             │
├──────────────┬──────────────┬──────────────┤
│ Orders       │ Inventory    │ Suppliers    │
│ Accuracy: 99%│ Turnover: 6x │ On-time: 92% │
│ On-time: 96% │ Stockouts: 1 │ Defects: 0.5%│
│ Cycle: 3.2d  │ DOS: 18 days │ Lead var: +1d│
├──────────────┴──────────────┴──────────────┤
│ ALERTS: Supplier B on-time rate dropped    │
│ below 90% for second consecutive week      │
├────────────────────────────────────────────┤
│ TRENDS: Inventory turnover improving       │
│ (5.2x → 6.0x over last quarter)           │
└────────────────────────────────────────────┘

Tools for Dashboards

How AI Helps

“Create a Google Sheets template for a weekly supply chain dashboard. I track [X] products from [Y] suppliers with [Z] monthly orders. Include: KPI cells with conditional formatting (green/yellow/red), a weekly trends section, and an alerts section. Provide the spreadsheet structure with column headers and sample formulas.”

AI-Powered Analysis Techniques

1. Natural Language Data Analysis

Feed your supply chain data to AI and ask questions in plain English:

“Here’s my order data for the last 3 months: [paste or describe]. Answer these questions:

1. What’s my average order cycle time, and is it improving?
2. Which products have the highest stockout rate?
3. Are there any seasonal patterns in order volume?
4. Which day of the week has the most orders?”

2. Anomaly Detection

AI spots patterns humans miss:

“Here are my daily order volumes for the past 60 days: [list]. Identify any anomalies—days that were significantly higher or lower than expected. For each anomaly, suggest a possible cause.”

3. Automated Reporting

Instead of manually writing weekly reports:

“Based on this week’s supply chain KPIs: [paste data], write a 5-sentence executive summary highlighting: overall performance, biggest improvement, biggest concern, and recommended action for next week.”

4. Predictive Alerts

“Based on my supplier performance over the last 6 months: [paste data], which suppliers show a declining trend? Predict which supplier is most likely to miss a delivery in the next 30 days and recommend preventive action.”

From Dashboard to Decisions

Data without action is just noise. Build a weekly decision process:

The Weekly Supply Chain Review (30 Minutes)

1. Check the dashboard (5 min): Any red alerts? Any KPIs moving in the wrong direction?
2. Investigate anomalies (10 min): Why did Supplier B’s on-time rate drop? Why did stockouts increase?
3. Decision and action (10 min): Assign tasks. Contact suppliers. Adjust reorder points.
4. Update forecast (5 min): Any new information that changes your demand outlook?

How AI Helps

“Here are my supply chain KPIs for the past 4 weeks: [paste]. Run a weekly review analysis: identify trends, flag deteriorating metrics, investigate likely causes, and recommend 3 specific actions I should take this week.”

Try It Yourself

Build your analytics system:

“Help me set up a supply chain analytics system for my business: [describe business, products, suppliers, volume].

1. Recommend the 6 most important KPIs to track
2. Design a weekly dashboard layout
3. Create a data collection template (what data, where to get it, how often)
4. Write a weekly analysis prompt I can reuse with AI
5. Suggest 3 automated alerts I should set up”

Key Takeaways

• KPIs (order accuracy, on-time delivery, inventory turnover, supplier performance) measure supply chain health
• A simple dashboard consolidates metrics and reveals relationships between them
• AI adds natural language analysis, anomaly detection, and automated reporting to your analytics
• Weekly reviews (30 minutes) turn dashboard data into specific improvement actions
• Start simple with spreadsheets—upgrade tools only when complexity demands it

Up Next

In Lesson 8: Capstone — Optimize a Supply Chain, you’ll bring everything together. You’ll analyze a complete supply chain scenario, identify improvements, and build an optimization plan using every tool you’ve learned.