Goal of the Day

Today, you will clean Titan’s inventory data, analyze stock health and trends, and prepare reports on inventory aging and fill rates.
You will begin linking inventory insights with sales fulfillment performance, setting up for integrated sales-inventory analysis.

Detailed Tasks with U2xAI Prompts and Interview Preparation Focus

1. Identify Inventory Data Errors and Cleaning Needs

  • What to Do:
    Scan the Inventory and Sales datasets for:
    • Missing SKU IDs
    • Negative or zero stock quantities
    • Discrepancies between available stock and sales orders
    • Misalignment between sales order dates and stock update dates
  • U2xAI Prompt:
    "What are the common inventory data quality issues and how would you systematically identify and clean them before analysis?"
  • How This Helps for Interviews:
    Readies you for questions like, “What cleaning checks are essential before inventory analysis?” or real-world case studies in logistics interviews.
  • Time Recommendation: 1 hour

2. Understand Fill Rate and Inventory Aging Concepts

  • What to Do:
    Learn two critical KPIs:Understand why low fill rates or old stock hurt customer service and working capital.
    • Fill Rate = (Orders Fulfilled Immediately / Total Orders) × 100
    • Inventory Aging = How long products stay unsold (group into 0-30 days, 31-60 days, etc.)
  • U2xAI Prompt:
    "Explain the importance of fill rate and inventory aging analysis in managing inventory efficiency and customer service performance."
  • How This Helps for Interviews:
    You’ll be ready to answer questions like, “How would you measure inventory efficiency?” or “What happens if aging inventory is high?”
  • Time Recommendation: 45 minutes
  • What to Do:Perform basic visualizations: bar charts for aging buckets, line plots for inventory trends over months.
    • Remove or fix rows with missing or invalid stock data.
    • Standardize date formats (e.g., stock entry/stock sold).
    • Calculate:
      • Fill rate per SKU
      • Average days in inventory for products
      • Stock aging buckets
  • U2xAI Prompt:
    "Show me how to clean inventory datasets and calculate fill rates and inventory aging metrics in Excel or Python (pandas)."
  • How This Helps for Interviews:
    Demonstrates real-world hands-on ability — exactly the kind of task you’ll perform in analyst or operations interviews.
  • Time Recommendation: 2 hours
  • What to Do:
    Based on findings:
    • Identify SKUs with low fill rates or high aging.
    • Suggest stock optimization strategies:
      • Improve forecasting
      • Increase safety stock for fast-movers
      • Liquidate or discount aging inventory
  • U2xAI Prompt:
    "How can fill rate analysis and inventory aging reports help optimize stock levels and improve supply chain efficiency?"
  • How This Helps for Interviews:
    You’ll be able to answer case study questions like, “How would you improve inventory turnover or fulfillment rates?”
  • Time Recommendation: 1 hour

5. Document Aging Reports and Fill Rate Findings

  • What to Do:
    Create simple, clear documentation:
    • Fill Rate by SKU Table
    • Inventory Aging Report (0-30, 31-60, 61-90, 90+ days)
    • Key insights (e.g., SKUs with highest aging stock)
  • U2xAI Prompt:
    "Suggest a clean format for documenting inventory fill rates, aging buckets, and key optimization recommendations."
  • How This Helps for Interviews:
    Prepares you for final project reporting and shows strong professional communication skills.
  • Time Recommendation: 45 minutes

6. Plan for Integrating Inventory and Sales Data Views Tomorrow

  • What to Do:
    Think about how:Write 3 questions you want to answer with integrated views tomorrow.
    • Inventory metrics (available stock, turnover)
    • Sales metrics (orders fulfilled, backorders)
      Can be merged for complete supply-demand analysis.
  • U2xAI Prompt:
    "Suggest 3 useful questions to answer when integrating inventory and sales data for supply chain performance analysis."
  • How This Helps for Interviews:
    Prepares you to answer questions like, “How would you integrate data across supply chain functions to find optimization opportunities?”
  • Time Recommendation: 15 minutes

Step-by-Step BUILDUP Application for Day 11

  • Breakdown:
    Identify inventory data issues and understand fill rate, aging KPIs.
  • Understand:
    Deepen understanding of why fill rates and aging analysis matter for operational performance.
  • Implement:
    Clean datasets, calculate fill rates, inventory aging, and create trend visualizations.
  • Link:
    Relate inventory performance to stock optimization strategies.
  • Document:
    Write clean reports covering fill rates, stock aging, and insights.
  • Upgrade Progress:
    Plan integrated sales-inventory performance views for tomorrow.

Deliverables for Today

  • Cleaned Inventory Dataset
  • Fill Rate Table by SKU
  • Inventory Aging Report (Grouped Buckets)
  • Stock Optimization Recommendation Sheet
  • Planning Notes for Inventory-Sales Integration

Practice Interview Questions for Day 11

  1. What steps would you take to clean an inventory dataset before analysis?
  2. How do you calculate and interpret fill rate in supply chain operations?
  3. What risks arise when inventory aging is high?
  4. How can inventory data analysis improve order fulfillment rates?
  5. How would you link poor inventory turnover to supply chain inefficiencies?

Bonus Practice:
Prepare a short 2-minute explanation answering:
“If Titan’s fill rate drops by 10% this quarter, how would you investigate and resolve the issue?”