Inventory Management Case Studies: Success Stories

Case Study 1: Reducing Waste with JIT at FreshWear

Problem: Overproduction leading to high inventory costs and waste.

Technique Applied: Just-In-Time (JIT) production.

Solution:

• Shifted from mass production to demand-based production.
• Production is triggered only by confirmed orders or real-time sales data.

Result and Analysis:

• Inventory decreased by 40%.
• Warehouse space was optimized.
• Waste was significantly reduced.

Key Learning: JIT minimizes holding costs, increases responsiveness, and reduces the risk of unsold stock.

Case Study 2: VES Analysis for AutoFix Garages

Problem: Stockouts of critical parts and overstock of low-priority items.

Technique Applied: VES (Vital–Essential–Supportive) analysis.

Solution:

• Vital: Engine parts are always kept in stock.
• Essential: Brake systems are closely monitored.
• Supportive: Accessories are ordered occasionally.

Result and Analysis:

• Emergency procurement decreased by 60%.
• Improved service efficiency.

Key Learning: VES helps prioritize inventory based on criticality, ensuring uninterrupted operations.

Case Study 3: ABC Analysis for MedPlus Pharma

Problem: Equal tracking of all SKUs leading to high costs and inefficiency.

Technique Applied: ABC Analysis (based on consumption value).

Solution:

• A items: (10% of items, 70% of value) receive strict control.
• B items: (20% of items, 20% of value) receive moderate focus.
• C items: (70% of items, 10% of value) are automated with less control.

Result and Analysis:

• Stockouts of high-value items were reduced.
• Inventory management costs decreased by 25%.

Key Learning: ABC ensures focus on high-value items, avoiding wasted effort on low-value stock.

Case Study 4: XYZ Analysis for BrightLite Electronics

Problem: Poor forecasting leading to overstock and understock issues.

Technique Applied: XYZ Analysis (based on demand predictability).

Solution:

• X items: (Stable demand) are auto-replenished.
• Y items: (Moderate fluctuations) are monitored monthly.
• Z items: (Irregular demand) are made-to-order.

Result and Analysis:

• Obsolete stock decreased by 40%.
• Service levels improved.

Key Learning: XYZ aligns inventory with demand patterns, improving accuracy in forecasting.

Case Study 5: ABC-XYZ Matrix for AgroPlus Seeds

Problem: Stock mismatch during seasonal demand periods.

Technique Applied: Combined ABC–XYZ Matrix.

Solution:

• AX: (High-value + stable demand) are tightly controlled.
• BZ: (Medium-value + erratic demand) are made-to-order.
• CY: (Low-value + moderate demand) receive quarterly reviews.

Result and Analysis:

• Surplus decreased by 30%.
• Better stock rotation.

Key Learning: Combining ABC and XYZ provides a comprehensive view of value and demand stability, ensuring balanced procurement and production.

Strategic Insights for Inventory Management

• JIT: Reduces overproduction and waste.
• VES: Ensures availability of critical components.
• ABC: Focuses resources on high-value items.
• XYZ: Manages uncertainty in demand.
• ABC–XYZ: Integrates both value and demand variability for optimal inventory planning.