Nearshoring refers to relocating manufacturing or sourcing activities to a nearby country rather than a distant one. For European manufacturers, this often means shifting production from Asia to Eastern Europe, such as Hungary, Poland, or Romania. For U.S. companies, it typically involves moving operations from China to Mexico. This practice, also called regionalization or proximate sourcing, aims to reduce lead times, stabilize supply chains, and improve cost and CO₂ transparency.
Organizations across industries, including automotive, aerospace, apparel, and consumer goods, are embracing nearshoring to reduce dependency on fragile global supply chains and respond faster to market needs. As sourcing strategies evolve, manufacturers face one critical question: can their current costing tools support this shift?
Why Nearshoring Creates a New Set of Costing Challenges
Moving production closer to home brings more than just logistical changes. Each region comes with its own cost drivers: labor rates, material prices, freight costs, customs duties, tooling lead times, energy prices, and even manufacturing methods. Capturing these variations accurately and consistently is essential.
Unfortunately, most teams still rely on Excel for this task. And while spreadsheets may work for one-off comparisons, they fall short when cost structures become dynamic and scenario-based. What happens when you need to model ten variants, across five countries, with custom duty impacts and different energy assumptions? Without a structured system, this becomes a manual, error-prone process that slows down decisions.
Why You Should Stop Relying on Manual Spreadsheets
Manual calculations introduce risk. Each new scenario often means copying and pasting old models, modifying assumptions, and hoping formulas hold up. Key issues include:
- Inconsistent costing logic between users and projects
- No easy way to manage regional cost parameters
- Lack of transparency across teams
- Limited ability to reuse or standardize inputs
This slows down sourcing and can lead to misinformed decisions. As supply chains shift, the tools supporting them need to evolve too.