Indus Motors: Inventory Management Custom Case Solution & Analysis

1. Evidence Brief (Case Researcher)

Financial Metrics

Annual Sales: 18,000 units (Exhibit 1).
Inventory Carrying Cost: 25% of unit cost per annum (Paragraph 4).
Average Unit Cost: $12,000 (Exhibit 2).
Stockout Cost: Estimated at $1,500 per unit in lost margin and customer goodwill (Paragraph 7).

Operational Facts

Current Lead Time: 4 weeks constant (Exhibit 3).
Demand Distribution: Normal distribution with mean of 346 units per week and standard deviation of 50 units (Exhibit 4).
Current Inventory Policy: Reorder point (ROP) of 1,500 units (Paragraph 5).
Warehouse Capacity: 5,000 units limit (Paragraph 9).

Stakeholder Positions

Operations Manager (Rajiv): Argues for reducing ROP to 1,200 to free up working capital.
Sales Director (Priya): Argues for increasing ROP to 2,000 to prevent recurring stockouts during peak seasons.

Information Gaps

Supplier reliability variance: Case assumes constant lead time; real-world data on lead time volatility is missing.
Seasonality: Monthly demand breakdown is absent, preventing precise seasonal adjustment.

2. Strategic Analysis (Strategic Analyst)

Core Strategic Question

How should Indus Motors optimize inventory levels to balance the $3,000 annual carrying cost per unit against the $1,500 stockout penalty, given the 5,000-unit warehouse constraint?

Structural Analysis

Service Level Optimization: Applying the Normal Distribution model to the current demand (mean 346, std dev 50), the current ROP of 1,500 units provides a service level significantly above 99%.
Cost Efficiency: The current policy is overly conservative, tying up $3.6M in capital (300 units excess safety stock).

Strategic Options

Option 1: Dynamic ROP Adjustment. Implement a two-tier ROP system (1,400 for off-peak, 1,700 for peak). Trade-off: Increased administrative complexity.
Option 2: Just-in-Time (JIT) Hybrid. Reduce ROP to 1,300 and negotiate 2-week lead times with the primary supplier. Trade-off: High dependency on single-source reliability.
Option 3: Economic Order Quantity (EOQ) Alignment. Recalibrate to a static ROP of 1,350 units. Trade-off: Lower capital intensity; moderate stockout risk during demand spikes.

Preliminary Recommendation

Adopt Option 3. A static ROP of 1,350 minimizes the total cost of ownership while maintaining a 95% service level, which aligns with industry standards.

3. Implementation Roadmap (Implementation Specialist)

Critical Path

Month 1: Data validation with logistics partners to confirm actual lead time variance.
Month 2: Pilot the 1,350 ROP threshold in the regional distribution center.
Month 3: Full system rollout and integration into the ERP procurement module.

Key Constraints

Supplier Latency: If lead time increases from 4 to 6 weeks, the ROP must scale to 2,200 immediately.
ERP Limitations: Current system lacks automated reorder triggers; manual intervention is required.

Risk-Adjusted Implementation

Maintain a 100-unit buffer above the 1,350 ROP for the first 90 days as a hedge against forecasting error.

4. Executive Review and BLUF (Executive Critic)

BLUF

Indus Motors is currently over-insured against stockouts at the direct expense of balance sheet efficiency. The recommendation to move to an ROP of 1,350 is correct, but the analysis ignores the primary danger: supplier lead time variance. If the supplier fails to meet the 4-week window, the entire model collapses. Management must shift focus from internal inventory levels to supplier contract penalties for late delivery. The current reliance on an average lead time is a flaw. Approved for implementation, provided the supplier contract is renegotiated to guarantee a 4-week lead time with financial penalties for exceedance.

Dangerous Assumption

The analysis assumes lead time is constant at 4 weeks. In industrial supply chains, lead time is rarely constant. A 1-week variance in lead time is mathematically more destructive than a 20% variance in demand.

Unaddressed Risks

Supplier Concentration: Reliance on one supplier for 100% of volume creates a single point of failure.
Demand Volatility: The model assumes a normal distribution, ignoring potential black-swan events or sudden market shifts.

Unconsidered Alternative

Vendor Managed Inventory (VMI). Shift the burden of inventory holding costs to the supplier by requiring them to manage stock levels within the warehouse. This removes the ROP calculation from internal management entirely.