Wilkins, A Zurn Company: Materials Requirement Planning Custom Case Solution & Analysis
Evidence Brief: Wilkins, A Zurn Company
1. Financial Metrics
Annual Sales Growth: Consistent 20 percent year-over-year increase in the backflow preventer market.
Inventory Value: Total inventory reached 4.5 million dollars by the end of the fiscal year.
Inventory Turns: Current turns sit at 2.4, significantly below the industry benchmark of 4.0 for similar manufacturing profiles.
Product Range: Over 400 end-item stock keeping units (SKUs) with 2,500 active component parts.
Order Backlog: Late shipments currently represent 15 percent of total monthly order volume.
2. Operational Facts
System Infrastructure: Implementation of IBM MAPICS (Manufacturing Accounting and Production Information Control System).
Lead Times: Cumulative lead times for complex assemblies range from 8 to 12 weeks; fabrication lead times average 4 weeks.
Production Model: Transitioning from a manual card-based system to a computer-driven Materials Requirement Planning (MRP) logic.
Manufacturing Process: High-mix, low-volume production involving brass casting, machining, and final assembly.
Data Accuracy: Bill of Materials (BOM) accuracy is estimated at 85 percent; inventory record accuracy is approximately 70 percent.
3. Stakeholder Positions
Rick: Production Manager. Believes the MRP system logic is too rigid and does not account for shop floor realities or machine breakdowns.
Planners: Express frustration with the system generating hundreds of exception messages daily, leading to message fatigue.
Marketing Team: Demands high finished goods safety stock to maintain 98 percent service levels regardless of production constraints.
Zurn Corporate: Expects immediate reduction in working capital through lower inventory levels following the software investment.
4. Information Gaps
Capacity Constraints: The case lacks specific data on machine hours available versus machine hours required (Rough Cut Capacity Planning).
Setup Costs: Specific dollar costs for machine changeovers are not detailed.
Vendor Reliability: No formal metrics provided on supplier on-time delivery percentages.
Software Training: The total hours of employee training provided during the MAPICS rollout are unstated.
Strategic Analysis
1. Core Strategic Question
The primary dilemma is the failure to synchronize the rigid, time-phased logic of the MRP system with the inherent variability of the manufacturing floor and inaccurate underlying data.
Secondary issue: The conflict between the marketing goal of 98 percent service levels and the corporate mandate to reduce inventory value below 4 million dollars.
2. Structural Analysis
Inventory Management Lens: The bullwhip effect is being amplified by the MRP system. Because inventory records are only 70 percent accurate, the system triggers unnecessary replenishment orders, inflating work-in-process (WIP) and clogging the fabrication department.
Operations Strategy: Wilkins is attempting to run a sophisticated MRP system on a foundation of poor data discipline. The system assumes infinite capacity, which results in unrealistic production start dates that the shop floor ignores, reverting to informal prioritization.
3. Strategic Options
Option
Rationale
Trade-offs
Freeze and Clean
Stop the MRP expansion to fix BOM and inventory accuracy to 95 percent plus.
Short-term production slowdown for long-term system reliability.
Hybrid Push-Pull
Use MRP for long-lead raw materials and Kanban/Visual cues for assembly.
Reduces system complexity but requires higher shop floor discipline.
Capacity-Constrained Scheduling
Integrate finite capacity planning into the current MAPICS module.
High implementation cost and technical difficulty.
4. Preliminary Recommendation
Wilkins must adopt the Freeze and Clean approach immediately. The MRP system is currently a garbage-in, garbage-out engine. Until inventory accuracy exceeds 95 percent, the automated replenishment signals will continue to drive the wrong behaviors, increasing costs without improving service levels. Technical solutions cannot fix fundamental data failures.
Implementation Roadmap
1. Critical Path
Month 1: Data Integrity Audit. Conduct a full physical inventory count and freeze the BOM for the top 50 revenue-generating SKUs.
Month 2: Lead Time Recalibration. Update the MAPICS system with actual observed lead times rather than theoretical estimates.
Month 3: Pilot Run. Execute the MRP logic for a single product line while maintaining manual overrides for others to ensure service levels.
Month 4: Full Rollout. Expand to all SKUs only after achieving 95 percent cycle count accuracy for three consecutive weeks.
2. Key Constraints
Cultural Resistance: Shop floor supervisors prefer the old manual system and may bypass the computer-generated schedules.
Data Entry Latency: The time lag between a part moving on the floor and the record being updated in the system.
3. Risk-Adjusted Implementation Strategy
Success depends on shifting the planners from reactive fire-fighting to proactive data management. A contingency of 15 percent safety stock should be maintained on critical components during the 90-day transition to protect customer service levels. If inventory accuracy does not improve within 60 days, the rollout should be halted to prevent a total factory floor bottleneck.
Executive Review and BLUF
1. BLUF
Wilkins is currently mismanaging its 4.5 million dollar inventory because it has automated a broken process. The MRP implementation is failing not because of software limitations, but because inventory and BOM data are fundamentally unreliable. Management must immediately prioritize data integrity over system expansion. The recommendation is to halt full automation, achieve 95 percent data accuracy in a 90-day sprint, and move to a hybrid scheduling model. Failure to act will result in a continued 15 percent backlog and further erosion of margins due to excess WIP.
2. Dangerous Assumption
The most consequential unchallenged premise is that the MRP logic can function effectively with a 70 percent inventory accuracy rate. In a time-phased planning environment, a 30 percent error rate in stock levels renders every subsequent calculation for sub-assemblies and raw materials invalid, creating a self-perpetuating cycle of shortages and gluts.
3. Unaddressed Risks
Supplier Lead Time Variability: The analysis assumes suppliers will meet the new MRP-generated dates, yet no vendor performance program exists to enforce this. (Probability: High; Consequence: Production Stoppage).
Staff Competency Gap: There is a significant risk that the current planning staff lacks the analytical skills to interpret MAPICS exception messages, leading to continued manual workarounds. (Probability: Medium; Consequence: System Abandonment).
4. Unconsidered Alternative
The team should consider a pure Lean/Kanban system for the fabrication cell. Given the high mix and relatively stable demand for core components, a visual pull system would eliminate the need for complex MRP calculations for 60 percent of the parts, leaving the software to manage only the long-lead, high-value raw material imports.