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How do you choose between suppliers when every option feels like a black box? For global procurement teams and sourcing leaders evaluating alternate suppliers, or deciding whether to shift production entirely, is riddled with guesswork.
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You’re forced to make critical “make vs. make” decisions without truly understanding the cost or risk implications. And the stakes are high: a wrong move can mean higher costs, longer lead times, or supply chain disruptions.
Why It’s Happening:
Traditional methods of evaluating supplier trade-offs rely heavily on spreadsheets, outdated databases, and siloed market intelligence. They can’t model the full picture: material costs, labor rates, energy inputs, logistics, trade flows, and macroeconomic conditions. Even when data exists, it’s not product-specific enough to guide decisions confidently. This lack of visibility means sourcing strategies are often driven by inertia, not insight.
This problem is compounded in complex, high-mix manufacturing environments, where even a simple product can contain dozens of components, each with unique sourcing and cost dynamics. Without a comprehensive view, decisions are either delayed, or worse, made based on incomplete or misleading assumptions.
The Shift to Product Cost Intelligence:
Muir's Product Intelligence Platform transforms how sourcing and procurement teams evaluate supplier options. Rather than relying on static models or anecdotal vendor data, Muir’s platform uses AI and advanced analytics to simulate real-world cost structures across suppliers, geographies, and sourcing scenarios.
With Muir’s Product Intelligence platform, you’re no longer estimating, you’re calculating and taking action. You can assess alternate suppliers, simulate production shifts, and forecast total landed costs with precision. It’s a strategic advantage that replaces uncertainty with confidence.
How Muir Solves This:
1. Synthetic BoM Generation
Even with minimal input (like a product description), Muir builds a complete, synthetic bill of materials. It identifies raw materials, manufacturing processes, and cost drivers down to the component level—without needing full engineering drawings. This foundation enables supplier comparisons grounded in actual cost structure.
2. Trade Flow Prediction
Considering a supplier in India vs. Vietnam? Muir models likely trade flows, tariffs, transportation logistics, and sourcing routes based on your product’s origin and structure. You get a region-specific view of cost, risk, and time essential for weighing “make vs. make” decisions.
3. Scenario-Based Cost Modeling
Muir’s platform allows you to simulate alternative sourcing decisions across suppliers, geographies, or production strategies. Want to compare two suppliers based on labor costs, energy rates, and implementation difficulty? Muir’s Reduction Engine scores each scenario based on predicted savings and operational feasibility.
4. Granular Cost Forecasting
Muir breaks down every element of cost: material inputs, labor, energy, value-add processes, and overhead. This enables category managers and price analysts to compare total cost of ownership across suppliers, not just quoted prices. Now, you can answer: “What will it really cost to move from Supplier A to Supplier B?”
5. Portfolio-Level Optimization
Rather than analyzing supplier impact product by product, Muir identifies the most strategic opportunities across your entire portfolio. This helps sourcing teams prioritize which “make vs. make” decisions will deliver the greatest cost reductions or risk mitigation.
Actionable Takeaway:
If your team is still guessing when it comes to supplier trade-offs, you’re missing opportunities and exposing your supply chain to unnecessary risk. Muir's Product Intelligence Platform gives you the clarity to make bold, confident decisions faster.
See how much smarter your sourcing decisions can be. Discover what your products should cost not just what you’re paying today.
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