Optimizing Capacity Planning for a Manufacturing Giant

Situation

For three years, a Fortune 500 company’s manufacturing plant struggled to meet its order demand. This persistent shortfall resulted in a staggering $2M monthly loss.

The root cause?
A glaring communication gap between the Sales and Operations teams stemming from a lack of clear understanding of the plant’s actual production capacity. Product line allocations were being made on an ad hoc basis leading to inefficient production schedules and a growing backlog of orders.

ChallengeS

There was no clear picture of how different factors impacted production, and no prior analysis had been conducted to highlight and account for these complexities. Throughout the project, we identified multiple pain points:

• Lack of Capacity Awareness: The plant lacked a clear understanding of its production capacity, hindering effective planning and resource allocation.
• Throughput Bottleneck:Silicon molding was limiting the throughput of the plant.
• Product Profitability: Limited visibility and a lack of data-driven insights into product profitability.
• Product Concentration: Only 11% of all customer-facing numbers (CFNs) or offerings drove 80% of revenues, highlighting the need for better product prioritization.
• Tender Impact: Participating in tenders led to a nearly 50% reduction in the Quantity on Hand (QOH) for key customer-facing products, creating a supply deficit that took 3-6 months to recover.

Solution

To break this cycle, we designed a sophisticated Capacity Planning Tool that accounts for all business constraints while optimizing demand prioritization to minimize backorders. Key features:

1. User-Friendly Data Input:Allows users to input demand and inventory data, with the flexibility for manual adjustments to simulate real-life scenarios.
2. Brand Level Planning:Generates build plan at the month and brand level, enabling users to specify minimum demand percentages and save scenarios for informed decision-making.
3. Demand Drivers:Displays the variation of demand against available capacity for the next 12 months for each work center, facilitating proactive planning.

Outcome

Using the tool, the manufacturing plant gained a clear understanding of its capacity, bottlenecks, and the overall stress on the system. Optimized production outputs were achieved through consensus, and trade-off comparisons were made while prioritizing product lines based on desired objectives.

Impact

• $24M in new annual revenues
• 50% reduction in unused inventory:The negative impact of tenders was quantified, and steps were taken to prevent future inventory deficits.
• 3-6 months recovery time avoided: Improved order acceptance strategies prevented significant inventory deficits.