Finding Horsepower To Drive Productivity & Cost Savings
In the high-demand, Tier 1 automotive industry, this company was experiencing a 20% decrease in demand and felt it was time to analyze productivity and labor spend on one of its most innovative product lines.
Given that their continuous improvement team was already spread thin leading many initiatives and their corporate team was focused on growing capacity and talent, they felt that AMEND's expertise in operational excellence and analytics capabilities would provide the horsepower needed to navigate the (major) market challenge of reduced demand.
- Tier 1 Automotive
- $165 Million Business
Assessing the Landscape
- 8 production lines
- 550+ employees
- US & Mexico Plants
- 20% decrease in sales
- Undocumented processes and job assignments
- Limited granularity to cost data
- Limited technical resources on client team
Net Cost Reduction
Capacity Forecasting Model
We created a capacity model that converted the demand from the 6-month forecast into the amount of needed production labor. We leveraged the model to redesign the production shift schedule to align production labor perfectly with demand.
We eliminated unnecessary overtime, without needing to reduce the actual employee count, saving the organization up to $3.3 million annually.
Optimize Warehouse Management
We redesigned the inventory placement in the warehouse based on inventory value grading, making the materials that move the fastest the most easily accessible.
We streamlined the process to move inventory from the production lines to the docks.
The AMEND Process
Production Throughput Assessment
We walked the floor to understand production constraints and critical job functions.
Designed a Working Model
Built a rapid proof-of-concept model to calculate the labor needed to meet demand. Tested the assumptions over a multi-week period.
Redeployed Production Shift Schedule
Leveraging the scale-up model, AMEND deployed a six-month labor projection and staffing schedule to match production labor with current demand.