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Cost Engineering

How AI and Automation Help Predict Supplier Price Changes Before They Happen

Cost engineering teams are grappling with rising supplier cost challenges driven by global disruptions. In this article, we explore how companies are increasingly adopting AI and automation in should-costing to anticipate and manage price fluctuations before they occur.

Imagine negotiating with a supplier, only to find that raw material prices have jumped overnight. Your carefully planned cost estimates are now obsolete, and your margins are shrinking. Sound familiar?

Supply chains are more volatile than ever, forcing cost engineers and procurement specialists to rethink supplier cost strategies. In the first half of 2024 alone, reported disruptions increased by 30% year-over-year, with factory fires, labor disputes, extreme weather events and cyberattacks among the top causes. These incidents cost organizations an estimated $184 billion annually, according to the 2025 J.S. Held Global Risk Report.

Infographic on supply chain disruptions and AI adoption, showing $184B in annual disruption costs and AI’s projected $157.6B market value by 2033. Sources: Swiss Re, Maersk, Precedence Research, market.us/scoop.

Despite these challenges, many cost engineering teams still rely on outdated cost estimation methods. A 2024 study found that procurement teams use only 5-10% of available technology, leading to inefficiencies and poor decision-making.

Using AI to Anticipate Supplier Price Shifts

For a long time, cost engineering and procurement teams have relied on historical data and spreadsheets to estimate supplier costs. But in today’s volatile market, that’s no longer enough.

According to a recent survey by Exasol, 91% of organizations now consider AI and predictive analytics essential to supply chain management, and 72% believe failing to invest in these technologies could put their business at risk​.

Why? Because AI can detect pricing trends before they happen. By analyzing real-time industry benchmarks, supplier cost structures, and historical fluctuations, AI-driven procurement tools can:

  • Predict supplier cost increases before they occur
  • Compare supplier quotes with live market data to expose unjustified markups
  • Run scenario-based cost simulations to identify alternative sourcing strategies
  • Minimize risks tied to sudden commodity price volatility

With AI-driven should-costing, procurement teams no longer have to react to price hikes. Instead, they can anticipate them and negotiate proactively.

Why Automated Should-Costing is Essential for Procurement Teams

Predicting supplier pricing is only part of the equation. The real advantage comes from automation, which turns insights into action without relying on manual data processing. Automating cost analysis transforms procurement operations by:

  • Eliminating manual errors and inefficiencies in cost calculations
  • Providing real-time cost tracking, rather than relying on static estimates
  • Enabling collaboration between cost engineers, procurement managers, and finance teams
  • Integrating predictive analytics to anticipate supplier price changes before they happen

With automated costing, manufacturers no longer need to wait and react to supplier price increases - they can anticipate them and take measures proactively.

Discover how automated cost engineering software not only improves procurement efficiency but also helps manufacturers achieve sustainability goals. Read more in our blog

See How Brose Uses Automation to Streamline Costs & CO₂ Transparency

Brose leveraged Tset’s automation to enhance cost visibility, speed up product development, and gain real-time insights into CO₂ emissions. See how automated product costing software helps them make smarter, more sustainable decisions.

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Tset's Customer Stories: Listen to what our customers have to say about Tset

Tset’s Automated Product Costing

Tset’s automated product costing software enables procurement teams to stay ahead of supplier price shifts by:

  • Analyzing historical supplier data to detect trends and cost deviations
  • Identifying hidden cost drivers in supplier quotes to strengthen negotiation positions
  • Running scenario-based cost simulations to explore alternative sourcing strategies
  • Providing up-to-date industry cost data to avoid pricing surprises

Tset’s algorithm-driven calculation modules create a bottom-up cost structure for individual parts, detailing required materials, machines, setup times, and labor. This ensures that every cost element is fully transparent, allowing cost engineers to adjust parameters and evaluate alternative sourcing strategies. Tset’s pre-built industry data sets and real-time updates ensure that cost models remain accurate and up to date. This gives procurement teams the insights they need to make smarter, faster decisions.

With Tset, procurement teams can validate cost data in real time, ensuring pricing accuracy and reducing negotiation risks.

Conclusion

Manufacturers cannot afford to rely on outdated methods in today’s increasingly uncertain market. Algorithm-driven should-costing provides the transparency and foresight needed to manage supplier pricing effectively. With Tset’s automated cost analysis software, cost engineers can gain a competitive advantage by making data-backed decisions before supplier price changes take effect.

How an Automated Calculation Tool Helps Unlock Supplier Cost Insights

Is your procurement team struggling to keep pace with increasing quote volumes, sustainability requirements, and demands for cost transparency? Learn how Tset's software bridges technical and commercial gaps while enabling data-driven decision-making. Download our whitepaper now to discover the future of strategic procurement.

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Tset Whitepaper Cover: "Transparent Cost Analysis for Smarter Procurement Decisions. How an Automated Calculation Tool Helps Unlock Supplier Cost Insights"

Author

Maria Skvoznova
Marketing Content Specialist

20.03.2025

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FAQ

1. How can AI help predict supplier price changes?

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2. Why are supplier prices rising in 2025?

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3. What is should-costing, and how does it help control supplier pricing?

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4. How does automation improve procurement efficiency?

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5. What tools can manufacturers use to manage supplier price volatility?

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