​​​​Problem we are trying to solve

Motion NEMA Motors lacks a unified view of the true end-to-end cost of the products and components we manufacture and source globally. Cost drivers are scattered across multiple systems and functions—including materials, labor, logistics, tariffs, routings, sourcing decisions, and supplier costs—making it difficult to accurately evaluate manufacturing alternatives or identify the most cost-effective supply chain strategy.

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This creates critical business challenges:

• Limited visibility into the total landed cost of products and components

• Make-versus-buy decisions are based on incomplete or disconnected cost data

• Manufacturing location decisions do not fully account for changing tariffs, logistics, and labor costs

• Supplier negotiations lack comprehensive should-cost insights

• Data integrity issues across routings, BOMs, sourcing, and standards reduce confidence in decision-making

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What solution do we seek?

Develop an AI-enabled solution that provides end-to-end product cost intelligence across ABB's global manufacturing and supply network. The solution should combine data from BOMs, routings, supplier pricing, labor rates, logistics, tariffs, and sourcing information to answer three key questions:

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1. What does a product actually cost today?

2. What should it cost? Future scope

3. Why does it cost what it costs? Future scope

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Future scope: The system should allow users to compare manufacturing and sourcing scenarios across locations, evaluate the impact of changing tariffs and supply chain conditions, identify key cost drivers, and support data-driven make/buy, sourcing, pricing, and production location decisions.

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Why now?

• Cost volatility is rising across tariffs, logistics, capacity, and regional manufacturing

• Cost data exists, but is split across ERP, sourcing, logistics, suppliers, tariffs, and spreadsheets

• AI can connect these sources, reveal cost drivers, and model sourcing or manufacturing scenarios​