- Lacking visibility into design-stage cost drivers can negatively and irreparably impact the bottom line
- CNH Industrial leverages aPriori to make cost-conscious design decisions to drive profitability
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The world’s manufacturing powerhouses recognize the significance of early cost visibility and transparency during the crucial product design phase. Early cost insights enable teams to make more informed design and manufacturing decisions, resulting in better resource allocation, faster product launch schedules, and improved profit margins.
CNH Industrial (CNHI), an agricultural and construction machinery leader, provides world-class excavators, harvesting equipment, and more through twelve brands, including New Holland, Case IH, and STEYR. In fiscal year 2022, CNHI secured a leadership position in the construction & mining machinery and capital goods sectors, with $21.6 billion in revenue and a 15.32% total market share.
To remain competitive and profitable, CNHI leverages a digital manufacturing solution that provides valuable real-time insights into underlying product cost drivers. This capability empowers the organization to design customer-centric innovations from the outset and maintain its position at the forefront of the industry.
Challenges of Addressing Cost Drivers in a Time-Sensitive Product Design Cycle
The CNHI team previously relied on traditional product cost management tools, such as labor-intensive spreadsheets. However, these conventional spreadsheets failed to provide CNHI with real-time insights into the cost implications of various designs, raw materials, and production processes. Lacking early design-stage cost visibility often resulted in expensive end-stage engineering change orders (ECOs) and time-to-market (TTM) delays for the manufacturer.
CNHI sought a digital solution that automatically identifies cost drivers and manufacturability issues during the initial design phases. The technology would also align with CNHI’s tight launch timelines for new harvesting innovations and provide detailed cost structure analyses, reducing the risk of expensive redesigns.
“Being part of the harvesting team, the window for testing is often narrow,” said Tom LeFebvre, Product Cost Manager for CNHI. “When farmers are ready to harvest, the design needs to be in place. Engineers need to put their best foot forward the first time because they may not get a second chance.”
Reduce Early Cost Drivers, Fuel the Bottom Line With Digital Manufacturing Insights
CNHI determined that aPriori’s Manufacturing Insights Platform provided the right capabilities and has been leveraging the technology for five years. aPriori automates product cost analysis to identify early design-stage cost drivers and manufacturing issues quickly. The platform generates fast, actionable feedback to help minimize the potential effects of design and sourcing-related issues on profit margins.
“There were manual tools I used to evaluate the total cost of a product, but this was a time-consuming process that negatively impacted productivity,” said LeFebvre. “aPriori allows me to dramatically reduce the cycle time for making cost comparisons and gain early insights into critical drivers of cost.”
aPriori fosters collaboration among cross-functional teams and centralizes valuable cost data within a unified platform, empowering more informed decision-making and business activities. McKinsey suggests that digital manufacturing solutions like aPriori have the potential to increase team productivity by 30%, decrease TTM by 50%, and improve forecast accuracy by 85%.
Watch this video to learn more about how CNHI utilizes aPriori for strategic cost management.
How aPriori Enables Teams to Control Cost Drivers and Improve Supply Chain Decisions
aPriori automatically extracts geometric data from 3D CAD models in product lifecycle management (PLM) systems, providing scalable and accurate insights for the entire project team. This allows design, cost, and sourcing professionals to evaluate “what-if” scenarios, identify and eliminate cost outliers, and address manufacturability issues with high-return potential.
“Making sourcing comparisons within aPriori is easy,” said LeFebvre. “Should we source components from the U.S., India, or China? By opening a 3D model in aPriori, we can quickly explore various ‘what-if’ scenarios that we never had time for in the past. Our designers can also observe cost splits in design decisions while a cost engineer identifies the contributing cost drivers.”
The following aPriori features and capabilities enable companies, such as CNHI, to optimize cross-team collaboration and accelerate product costing methods:
- Intelligent End-to-End Digital Twins. aPriori leverages the digital thread to connect three digital twins: product, process, and factory, enabling the generation of actionable, real-time manufacturing insights. aPriori’s configurable digital factories can simulate production based on product design (geometry), manufacturing overhead costs, direct labor hours, machine hours, and more. These valuable insights are derived from aPriori’s real-world manufacturing process models and economic conditions for 87 regions across the globe.
- Centralized Reports and Automated Alerts. aPriori empowers cross-functional teams with granular, centralized reports on products, materials, and manufacturing, fostering data-driven decisions for rapid, cost-effective innovation. Further, aPriori delivers automatic notifications with feedback to address early-stage cost drivers, negative carbon impacts, and critical manufacturing problems. Product development teams can also set target costs and receive aPriori alerts when designs exceed cost thresholds. aPriori’s reporting capabilities make data easily digestible, allowing manufacturers to boost product development speed, enhance competitiveness, and preserve profit margins.
- Bulk-Cost Estimates for Should Cost Negotiations. Product teams can use aPriori to generate fast, detailed cost estimates for multiple and large batches of components simultaneously. They can quickly identify expensive outliers for cost-reduction opportunities and gain should cost insights to negotiate pricing with new or strategic suppliers. Teams can now collaborate on cost drivers without expert involvement, as aPriori’s bulk-costing module effectively incorporates real-world direct and indirect costs into its precise calculations. As a result, manufacturing companies gain the potential to drive down product costs by millions of dollars.
CNHI Quickly Identifies Millions in Estimated Savings With aPriori
In the first two months of implementing aPriori, the CNHI team successfully uncovered significant savings opportunities across multiple components. Below are some of CNHI’s initial project results and savings outcomes:
- Design alterations to a shank cultivator saved $143,820 in annual costs.
- An informed turnbuckle redesign and outsourcing process drove savings of $97,659.
- Wing roller, tine channel, and hub & spindle parts presented another $70,853 in savings.
By leveraging aPriori, CNHI’s team successfully identified potential annual savings of approximately $312,000 within a few months.
The company later performed a deep-dive cost analysis in aPriori for more than 100 components within a header reel assembly. During the analysis, a discrepancy of 8% was observed between the supplier’s quoted cost and aPriori’s precise should cost estimates.
Consequently, the company compared alternative digital factories within aPriori to make informed, cost-effective make-or-buy decisions. CNHI ultimately identified the best internal manufacturing location to enhance margins, leading to a $1,207 per assembly difference and $2.1 million in annual cost savings.
Integrate the Power of aPriori Into Your Cost-Reduction Strategy
Embracing automated digital manufacturing tools is crucial for companies looking to eliminate cost drivers early and maximize their bottom line. Manufacturers that leverage advanced technologies, such as aPriori, can streamline product development and make proactive decisions, resulting in significant cost savings and increased profitability.