Retail & Consumer Goods: Inventory and Demand Planning Cases

Inventory cases are where consulting interviews get quantitative fast. Based on our analysis of 800+ case interviews, inventory and demand planning questions appear in roughly 15% of retail-sector cases — and they disproportionately separate strong candidates from average ones because they require both structured thinking and comfort with unit economics.

Why Inventory Cases Are High-Signal for Interviewers

Inventory sits at the intersection of finance, operations, and strategy. A candidate who can navigate stockout costs versus carrying costs demonstrates the kind of trade-off thinking consultants use daily. In our experience working with retail clients, inventory decisions directly impact 20–30% of a retailer’s working capital, making this one of the highest-leverage operational levers available.

The Inventory Case Framework

Most inventory cases in consulting interviews follow one of three archetypes. Recognizing the archetype within the first 60 seconds lets you deploy the right analytical structure immediately.

flowchart TD
    A[Inventory Problem Identified] --> B{Primary Symptom?}
    B -->|Revenue Loss| C[Stockout Analysis]
    B -->|Margin Erosion| D[Overstock / Markdown Analysis]
    B -->|Cash Trapped| E[Working Capital Optimization]
    C --> F[Root Cause: Demand forecasting? Replenishment speed? Supplier reliability?]
    D --> G[Root Cause: Forecast bias? Promotional overbuying? Assortment bloat?]
    E --> H[Root Cause: Slow turns? Long tail SKUs? Payment terms?]
    F --> I[Quantify impact + Recommend]
    G --> I
    H --> I

Archetype 1: Stockout and Lost Sales

The client is losing revenue because shelves are empty. Your job is to quantify the revenue at risk and identify whether the root cause is demand-side (forecast accuracy) or supply-side (replenishment speed, supplier reliability).

Key metrics to request: stockout rate by category, days of supply, forecast accuracy (MAPE), supplier lead time variability.

Typical solution levers: safety stock recalibration, demand sensing with POS data, supplier diversification, cross-docking for fast-moving SKUs.

Archetype 2: Overstock and Markdowns

The client has excess inventory that erodes margins through markdowns, storage costs, or write-offs. Based on our work with CPG retailers, overstock cases often reveal that 30–40% of SKUs generate less than 5% of total revenue — the long tail is the real problem.

Key metrics to request: inventory turns by category, markdown rate, aging inventory (>90 days), SKU count growth versus revenue growth.

Typical solution levers: assortment rationalization, dynamic markdown pricing, vendor return agreements, demand-driven replenishment replacing push-based allocation.

Archetype 3: Working Capital Optimization

The client’s cash is locked in inventory. This archetype focuses on freeing capital without hurting service levels — a classic CFO-driven engagement.

Key metrics to request: cash conversion cycle, days inventory outstanding (DIO), inventory-to-sales ratio by category, payment terms with suppliers.

Typical solution levers: consignment models for slow movers, vendor-managed inventory (VMI), payment term renegotiation, postponement strategies.

Seasonal Demand: The Retail-Specific Complexity

Retail cases almost always involve seasonality. Interviewers expect you to recognize that annual averages hide the real story. In our experience, candidates who proactively ask “what does demand look like across the calendar year?” consistently score higher than those who analyze flat annual numbers.

Quantitative Shortcuts for Inventory Math

Interviewers love to test whether you can build quick estimates. Here are the formulas you should have ready:

Economic Order Quantity (simplified):

• EOQ ≈ √(2 × Annual Demand × Order Cost / Holding Cost per Unit)
• In interviews, round aggressively — the structure matters more than decimal precision

Safety Stock Rule of Thumb:

• Safety Stock ≈ Z-score × √(Lead Time) × Demand Variability
• For a 95% service level, Z ≈ 1.65; for 99%, Z ≈ 2.33

Inventory Turns:

• Turns = COGS / Average Inventory
• Healthy grocery: 14–20 turns/year; Fashion: 4–6 turns/year; Electronics: 8–12 turns/year

Common Mistakes in Inventory Cases

Based on our review of candidate performance data, these errors appear repeatedly:

1. Treating all SKUs equally — Always segment by velocity (A/B/C classification). The solution for fast-movers differs fundamentally from slow-movers.
2. Ignoring the service level trade-off — Going from 95% to 99% availability roughly doubles safety stock requirements. Acknowledge this cost explicitly.
3. Forgetting supplier constraints — Minimum order quantities, lead times, and container economics constrain theoretical optimal solutions. Ask about these early.
4. Solving for cost alone — Inventory decisions impact revenue (availability), margin (markdowns), and cash (working capital). The best answers triangulate all three.

Key Takeaways

• Inventory cases test trade-off reasoning: every decision involves balancing service level, cost, and capital efficiency
• Identify the archetype (stockout, overstock, or working capital) within 60 seconds to deploy the right framework
• Always segment by SKU velocity — Pareto logic applies universally in retail inventory
• Proactively address seasonality; annual averages are misleading in retail contexts
• Keep 3 formulas ready: inventory turns, safety stock, and EOQ — structure matters more than precision
• Connect inventory recommendations to P&L impact using concrete dollar estimates

Ready to test your inventory case skills? Explore retail industry cases in our case library for real practice scenarios, or sharpen your quantitative reasoning with AI Mock Interview sessions that simulate the pressure of live inventory case discussions. For broader operational frameworks, see our guide on supply chain and operations cases and the operations case framework.